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February 17, 2019 February 26, 2020 / CONFERENCES / 9 minutes of reading
Impact of Frugal Innovations, AI, Remote Health Services, Vertically Integrated Technology Platforms and Care Delivery Platforms supported by technology, Blockchain based HealthTech solutions, Personal Digital Avatars, Diffusion of Digital HealthTech
July 18, 2018 March 28, 2020 / WORKFLOW / 1 minute of reading
Part 2 of 4
Now that we have defined the various actors and the activities that they could be performing. It becomes to important to define the guidance as to how these activities will be delivered to their respective audiences.
July 18, 2018 March 8, 2020 / WORKFLOW / 6 minutes of reading
A Clinical Care Pathways Workflow & Activity Orchestration
Clinical pathways are structured multidisciplinary care plans which address specific clinical scenarios and help to standardize and coordination of care.
The patient care pathways solutions have become an important clinical guidelines implementation tools in hospital settings. They have the ability to provide, not only a standardised care to the patients’ presenting same/ similar diagnosis, but also provide the ability to handle the variance from the defined care pathways for various specialties and diagnosis.
The care pathways also provides the ability to coordinate care of a patient across various user groups and user roles, like the group of nurses across shifts and across roles like doctors, nurses and administrative staff.
The Care Pathways aim to optimize the efficiency and quality of care
The care pathways solution that we propose to develop have the following features.
Clinical Data Repository
At the heart of our Patient Care Pathways solution is a clinical data repository that maintains a longitudinal patient care record. The Patient CDR is a data warehouse of the Patient’s clinical data that has been stored in the clinical data repository to enable data analysis across the patient episodes and visits.
The Clinical Data Repository provides the ability to organically analyse data from ‘similar’ patients across same or similar set of data points like diagnosis, test results and clinical studies.
The clinical data repository converts all the data captured in various connected systems to a analysable data point for the care pathways solution. The data captured in the external system
The clinical data repository is a the heart of the care pathways solution that contains information that has been stored in standardised format using the standard healthcare coding systems like ICD10, SNOMED CT, ICD10 PCS and others as applicable in the clinical scenario.
In-built into the Clinical Data Repository are latest big data analytics capabilities that are required to generate the statistical analysis of the adherence to the quality and efficincy of the Care Pathway.
The clinical data repository has the ability to generate, out of the box, all the analytical reports and predictive modelling required for todays’ clinicians to make the right decisions at the right time.
The Clinical Data Repository allows for the following features and functionalities that are relevant to the Care Pathways solution
Allows for analysing historical outcomes from clinically similar patients, e.g. patients like me type of scenario matching
Display the variance and outcomes for the patient specific pathway and across various patients
Care Pathways Designer
The Care Pathways designer is a visual tool that allows the user to define the workflow of activities based on a start condition. The Start Up condition for a Care Pathway could be a Code Red alarm for quarantine or it could be a set of questions that a care provider answers to based on the patient they are treating for, for instance, chest pain.
The Care pathways designer has at its core the following:
Care Pathways Designer Features:
The care pathways designer is a tool that allows the care pathways design team to define the standardised care templates of activities that should be scheduled for a patient presenting a chief complaint or being treated for a chronic condition.
The care pathways designer has a set of pre-defined activity categories. For example, Appointment Scheduling, Laboratory Orders, Radiology Orders, Pharmacy Orders and many more. Each of the activity categories are defined based on the corresponding activity that needs to be instantiated at the host system, such as an EHR or a HIMS Solution. The Patient Care Pathways solution allows the users to define these activity categories depending on the host system.
The Care Pathways Designer tool allows the users to define the workflow for the care pathways. The tool allows the user to define rules and the activities (or activity groups) that will be instantiated depending on the condition of the rule.
The Care Pathways designer tool also has the ability to define various outcomes and the activities that need to be performed to achieve those outcomes.
The clinical pathways designer will have a rules designer that allows the users to select the various activities and activities groups to be the outcome and action targets for a clinical rule.
For instance, if the doctor selects a certain type of schedule H drugs to be ordered for a patient and the doctor does not have the authorization to order schedule H drugs, the order will be sent to the next level of authorization within the patient care team.
The rules can be included into the care pathways designer as workflow activities and decision criteria.
User & User Group based Task Lists
The system will have a user specific task list that will inform the user on the various activities that a user (nurse, doctor, admissions and billing users) needs to perform vis-a-vis a patient. The Task list will help the user to complete the tasks that have been generated based on the various active care pathways for the various patients.
The system also has the ability to share the generated tasks between a group of care providers. This allows for the nurses taking care of the patients across the various shifts to review the tasks that have been completed or not completed during an earlier shift.
Care Pathway Dashboard
The system will have a comprehensive Care Pathway Dashboard. The dashboard will display the following:
The Care Pathway adherence Index displays the variance or conformance of a care pathway when applied to multiple patients.
The Care Pathway patient adherence Index, this displays the effectiveness of a care plan when applied to a specific patient.
In both the above scenarios, the care plan adherence Index will display the deviations, the variances and adherence levels to the defined care plan. It will also list out the activities that were done in addition or in variance of a defined care plan.
In addition to the variance and conformance metrics the Care Pathway Dashboards will display to the users the following:
The Patient Specific Care Pathway Activity Scheduler: Displays the day by day list of all the activities that have been defined (scheduled) in a care plan. It also has the ability to showcase the activities by a shift.
Care Pathway timeline: Displays the care plan timeline and recorded variance and non-conformance detection
Outcomes Recording: The Care Pathway solution also allows the users to record the outcomes for each of the planned activities and the Outcomes defined for the Care Pathway.
Care Pathway Push Notifications & Alerts Center
The Care Pathway Push Notifications and Alerts center is an important part of our solution. The Care Pathway push notification system identifies the most important and high priority tasks that need to be performed for each of the patients. The users are alerted about these high priority tasks on their associated mobile devices.
The Care Pathway Push Notifications have been designed to be non-obstrusive and presented in a way the user has configured these to be delivered to them. This is done to ensure there is no alert-fatigue generated based on our notifications and alerts center.
In addition to the Push Notification for tasks to be performed on a high priority, the Care Pathways solution also has the ability to provide alerts of outstanding or upcoming, completed or activities in variance of the defined Care Pathway to relevant team members.
Each alert and push notification will be configured with a level of priority (that can be assigned to the alert type or determined by the system) and depending on the Level of Priority of that alert and notification, the system will present the alert to the user.
Additional Resources & Standards Definitions:
The care pathway models in the tool are based on the following industry standards:
OMG Case Management Model and Notation (CMMN), and
December 22, 2017 March 8, 2020 / AI/ML/DL / 3 minutes of reading
In a recently published report by Accenture, they have highlighted the need for india to invest in AI, we bring you the excerpts of the report. (The following content is sourced from the Accenture report).
Artificial intelligence (AI) has reached a tipping point. The combination of the technology, data and talent that make intelligent systems possible has reached critical mass, driving extraordinary growth in AI investment. Across the world, G20 countries have been building up their AI capabilities. The power of AI starts with people and intelligent technologies working together within and across company boundaries to create better outcomes for customers and society. But India is not fully prepared to seize the enormous opportunities that AI presents. Even with a tech-savvy talent pool, renowned universities, healthy levels of entrepreneurship and strong corporations, the country lags on key indicators of AI development. Much work remains.
The report, ‘Rewire for Growth,’ estimates that AI has the potential to increase India’s annual growth rate of gross value added (GVA) by 1.3 percentage points, lifting the country’s income by 15 percent in 2035. To avoid missing out on this opportunity, policy makers and business leaders must prepare for, and work toward, the AI revolution.
The era of AI has arrived. Established companies are moving far beyond experimentation. Money is flowing into AI technologies and applications at large companies. The number of patents filed on AI technologies in G20 countries has increased at a more than 26 percent compound annual growth rate since 2010.Funding for AI startups has been growing at a compound annual growth rate of almost 60 percent. AI is a new factor of production that can augment labor productivity and innovation while driving growth in at least three important ways: Mobilize Intelligent Automation Automate complex, physicalworld tasks that require adaptability and agility. Empower Existing Workforces Complement and enhance the skills and abilities of workforces. Drive Innovations Let AI be a catalyst for broad structural transformation of the economy. Do things differently, do different things.
The report points out AI is expected to raise India’s annual growth rate by 1.3 percentage points—in a scenario of intelligent machines and humans working together to solve the country’s most difficult problems in 2035 AI TENDING TO INDIA’S HEALTH India’s healthcare providers have embraced artificial intelligence, recognizing its significant value in better diagnostics with data intelligence and in improving patient experience with AI-powered solutions. Take Manipal Hospitals, headquartered in Bengaluru, which is using IBM Watson for Oncology, a cognitive-computing platform, to help physicians identify personalized cancer care options across the country. In cardiac care, Columbia Asia Hospitals in Bengaluru is using startup Cardiotrack’s AI algorithms to predict and diagnose cardiac diseases, disorders, and ailments. And in eye care, Aravind Eye Hospital is working with Google to use AI in ophthalmology for diabetic retinopathy screening. Also, the government of Telangana is planning to use Microsoft Intelligent Network for Eyecare (MINE), an AI platform, to reduce avoidable blindness, which would make it the first state in India to deploy AI for eye care screening as part of the Rashtriya Bal Swasthya Karyakram program under the National Health Mission. Accenture, for its part, has developed an AI-powered smartphone solution to help the visually impaired improve the way they experience the world around them and enhance their productivity in the workplace. The solution, called Drishti, was initially developed and tested through a collaboration with the National Association for the Blind in India.
October 16, 2017 March 8, 2020 / BLOCKCHAIN / 15 minutes of reading
Every once in a while a new technology finds its way in the Gartner Hype Cycle for Technologies (in Healthcare) and its effectiveness and usability is applied to the management and interoperability of Healthcare Records. For instance, access to the Healthcare records by various stakeholders in the care continuum: care providers and patients.
Gartner in their recent report defines Blockchain as a Digital Platform. And healthcare industry has been perennially on the lookout for a Digital Platform that will allow for an efficient and secure way to share patient data. Providing access to the healthcare data involves providing access to the patient data to relevant stakeholders at the right time and to the right person, not only ensuring the privacy but also providing the patient control of their data. Another problem that remains evasive in healthcare is driven by privacy of the patient data, and has been at times been seen to be impeding the flow of patient data between disparate systems, (i.e., Interoperability). We now have the Blockchain Technology and various companies are working to apply the technology to help solve not only the interoperability problem but also applying the same technology to solve various usecases in the Care Continuum, to save costs, improve efficiency, ensure privacy. So what are the problems Blockchain is being applied to in the Healthcare context? What are the benefits one would accrue by applying Blockchain to Healthcare and what are the pitfalls. The past august, ONC in the US setout a Blockchain challenge with the objective,
“The goal of this Ideation Challenge is to solicit White Papers that investigate the relationship between Blockchain technology and its use in Health IT and/or health-related research. The paper should discuss the cryptography and underlying fundamentals of Blockchain technology, examine how the use of Blockchain can advance industry interoperability needs expressed in the Office of the National Coordinator for Health Information Technology’s (ONC) Shared Nationwide Interoperability Roadmap, as well as for Patient Centered Outcomes Research (PCOR), the Precision Medicine Initiative (PMI), delivery system reform, and other healthcare delivery needs, as well as provide recommendations for Blockchain’s implementation. In addition to a monetary award, winners may also have the opportunity to present their White Papers at an industry-wide “Blockchain & Healthcare Workshop” co- hosted by ONC and NIST.”
As part of the Ideation Challenge, the following papers were the declared winners: 1. Blockchain and Health IT: Algorithms, Privacy, and Data: This papers discusses the need to create a peer-to- peer network that enables parties to jointly store and analyze data with complete privacy, based on highly optimized version of multi-party computation with a secret-sharing. An auditable, tamper-proof distributed ledger (a permissioned blockchain) records and controls access through smart contracts and digital identities. We conclude with an initial use case of OPAL/Enigma that could empower precision medicine clinical trials and research. Authors: Ackerman Shrier A, Chang A, Diakun-thibalt N, Forni L, Landa F, Mayo J, van Riezen R, Hardjono, T. Organization: Project PharmOrchard of MIT’s Experimental Learning “MIT FinTech: Future Commerce.” 2. Blockchain: Securing a New Health Interoperability Experience: Blockchain technologies solutions can support many existing health care business processes, improve data integrity and enable at-scale interoperability for information exchange, patient tracking, identity assurance, and validation. This paper suggests these processes can be supported by three most important applications: Creating secured and trusted care records, linking identities and recording patient consent decisions and patient directives within the secured patient record. Authors: Brodersen C, Kalis B, Mitchell E, Pupo E, Triscott A. Organization: Accenture LLP 3. Blockchain Technologies: A Whitepaper Discussing how Claims Process can be Improved: Smart contracts, Blockchain, and other technologies can be combined into a platform that enables drastic improvements to the claims process and improves the health care experience for all stakeholders. The healthcare industry suffers from an inability to clearly communicate costs in a timely and easy-to-understand format. This problem is a symptom of interoperability issues and complex agreements between providers, patients, health plans/payers and government regulators. These agreements are encoded in legal language with the intent of being defensible in court. However, the focus on legal enforceability, instead of understandability, creates problems resulting in hundreds of billions of dollars spent annually to administer an inefficient, outdated and complex process for adjudicating and paying health plan claims. The process results in errors and often leaves the patient unclear on how much they need to pay. If these agreements were instead translated into computer code (smart contracts) leveraging Blockchain technologies, the claim process would not only be interoperable, but also drive standardization, research and innovation. Transparency and trust can be injected into the process when both the logic and the data driving these decisions is stored permanently and made available to all stakeholders through a peer-to- peer distributed database like blockchain. The result will be a paradigm shift toward interoperability and transparency, enhancing the speed and accuracy of cost reporting to patients. This paper discusses how smart contracts, blockchain and other technologies can be combined into a platform that enables drastic improvements to the healthcare experience for all stakeholders. Author: Culver K. 4. Blockchain: A new model for Health Information Exchanges: Presentation of an implementation framework and business case for using Blockchain as part of health information exchange to satisfy national health care objectives.
Authors: Krawiec RJ, Barr D, Killmeyer K, Filipova M, Nesbit A, Israel A, Quarre F, Fedosva K, Tsai L. Organization: Deloitte Consulting LLP 5. A Case Study for Blockchain in Healthcare: “MedRec” Prototype for Electronic Health Records and Medical Research Data: A long-standing focus on compliance has traditionally constrained development of fundamental design changes for Electronic Health Records (EHRs). We now face a critical need for such innovation, as personalization and data science prompt patients to engage in the details of their healthcare and restore agency over their medical data. In this paper, the authors propose MedRec: a novel, decentralized record management system to handle EHRs, using blockchain technology. The system gives patients a comprehensive, immutable log and easy access to their medical information across providers and treatment sites. Leveraging unique blockchain properties, MedRec manages authentication, confidentiality, accountability and data sharing—crucial considerations when handling sensitive information. A modular design integrates with providers’ existing, local data storage solutions, facilitating interoperability and making our system convenient and adaptable. MedRec incentivize medical stakeholders (researchers, public health authorities, etc.) to participate in the network as blockchain “miners”. This provides them with access to aggregate, anonymized data as mining rewards, in return for sustaining and securing the network via Proof of Work. MedRec thus enables the emergence of data economics, supplying big data to empower researchers while engaging patients and providers in the choice to release metadata. The purpose of this paper is to expose, in preparation for field tests, a working prototype through which we analyze and discuss our approach and the potential for blockchain in health IT and research. Authors: Ekblaw A, Azaria A, Halamka J, Lippman A. Organizations: MIT Media Lab, Beth Israel Deaconess Medical Center 6. The Use of a Blockchain to Foster the Development of Patient-Reported Outcome Measures (PROMs): This paper suggests the use of Cognitive Behaviour Therapy as a modality to treat Mental Health disorders. This the author suggests is achieved by the use of various applications that allow the patient to record information using SMS or applications. These applications keep track of any emergencies, provides patient coaching and guidance, recording of daily progress and medication adherence. While many patients feel ashamed of their mental state and feel a stigma associated with conditions such as depression and anxiety, the anonymous nature of these applications may make it more likely for them to seek help. These types of use cases are the first step in implementing blockchain technology as they help identify the system requirements and looks at the interactions between users and systems. In this case, the focus would be on personal health information that is highly sensitive and coming from mobile applications that require direct interaction between the patient and providers, as well as those involved in the care of the patient. Each scenario that involves a transaction, or data being transferred from the application to those who have “signed” the transaction would be documented so the information flow and usage is understood. In this manner, the appropriate permissions would be granted and provenance could readily be established. Use of the Internet of Things in combination with Blockchain technology for Patient Reported Outcome Measures (PROMs). Author: Goldwater JC. Organization: National Quality Forum 7. Powering the Physician Patient Relationship with ‘HIE of One’ Blockchain Health IT: ‘HIE of One’ links patient protected health information (PHI) to Blockchain identities and Blockchain identities to verified credential provider institutions to lower transaction costs and improves security for all participants. HIE of One, (Health Information Exchange of One) shifts the trusted intermediary role away from the hospital and into the blockchain. The blockchain can also provide the link between physician credentials and patient identity. Author: Gropper A. 8. Blockchain: The Chain of Trust and its Potential to Transform Healthcare – Our Point of View: This paper talks about Potential uses of Blockchain technology in health care including a detailed look at health care pre-authorization payment infrastructure, counterfeit drug prevention and detection and clinical trial results use cases. The paper also highlights what Blockchain is not. Some of the additional usecases as presented in the paper are listed below:
Organization: IBM Global Business Service Public Sector 9. Moving Toward a Blockchain-based Method for the Secure Storage of Patient Records: Use of Blockchain as a novel approach to secure health data storage, implementation obstacles, and a plan for transitioning incrementally from current technology to a Blockchain solution. The author suggests a practical first step towards moving towards a blockchain enabled world, here is a suggested workflow by the author, from the submission:
Author: Ivan D. 10. ModelChain: Decentralized Privacy-Preserving Health Care Predictive Modeling Framework on Private Blockchain Networks: ModelChain, to adapt Blockchain technology for privacy-preserving machine learning. Each participating site contributes to model parameter estimation without revealing any patient health information (i.e., only model data, no observation-level data, are exchanged across institutions). We integrate privacy- preserving online machine learning with a private Blockchain network, apply transaction metadata to disseminate partial models, and design a new proof-of-information algorithm to determine the order of the online learning process. We also discuss the benefits and potential issues of applying Blockchain technology to solve the privacy-preserving healthcare predictive modeling task and to increase interoperability between institutions, to support the Nationwide Interoperability Roadmap and national healthcare delivery priorities such as Patient-Centered Outcomes Research (PCOR). Authors: Kuo T, Hsu C, Ohno-Machado L. Organizations: Health System Department of Biomedical Informatics, University of California San Diego, La Jolla, CA Division of Health Services Research & Development, VA San Diego Healthcare System. 11. Blockchain for Health Data and Its Potential Use in Health IT and Health Care Related Research: A look at Blockchain based access-control manager to health records that advances the industry interoperability challenges expressed in ONC’s Shared Nationwide Interoperability Roadmap. In this usecase the authors discuss the use of blockchain technology with a data lake for scalability. All medical data would be stored off blockchain in a data repository called a data lake. Data lakes are highly scalable and can store a wide variety of data, from images to documents to key- value stores. When a health care provider creates a medical record (prescription, lab test, pathology result, MRI) a digital signature would be created to verify authenticity of the document or image. The health data would be encrypted and sent to the data lake for storage. Every time information is saved to the data lake a pointer to the health record is registered in the blockchain along with the user’s unique identifier. The patient is notified that health data was added to his blockchain. In the same fashion a patient would be able to add health data with digital signatures and encryption from mobile applications and wearable sensors.
Authors: Linn L, Koo M. 12. A Blockchain-Based Approach to Health Information Exchange Networks: Sharing healthcare data between institutions is challenging. Heterogeneous data structures may preclude compatibility, while disparate use of healthcare terminology limits data comprehension. Even if structure and semantics could be agreed upon, both security and data consistency concerns abound. Centralized data stores and authority providers are attractive targets for cyber attack, and establishing a consistent view of the patient record across a data sharing network is problematic. In this work we present a Blockchain-based approach to sharing patient data. This approach trades a single centralized source of trust in favor of network consensus, and predicates consensus on proof of structural and semantic interoperability. The authors describe the Healthcare Blockchain as:
Because a blockchain is a general-purpose data structure, it is possible to apply it to domains other than digital currency. Healthcare, we believe, is one such domain. The challenges of a patient record are not unlike those of a distributed ledger. For example, a patient may receive care at multiple institutions. From the patient’s point of view, their record is a single series of sequential care events, regardless of where these events were performed. This notion of shared state across entities, inherent to the blockchain model, is congruent with patient expectations. Also, it is reasonable to assume that each patient care event was influenced by one or more events before it. For example, a prescription may be issued only after a positive lab test was received. The notion of historical care influencing present decisions fits well into the blockchain model, where the identity of a present event is dependent on all past events.
Much like the Bitcoin approach, our block is a Merkle Tree-based structure. The leaf nodes of this tree represent patient record transactions, and describe the addition of a resource to the official patient record. Transactions, however, do not include the actual record document. Instead, they reference FHIR Resources via Uniform Resource Locators (URLs). This allows institutions to retain operational control of their data, but more importantly, keeps sensitive patient data out of the blockchain. FHIR was chosen as a exchange format not only because it is an emerging standard, but also because it contains inherent support for provenance and audit trails, making it a suitable symbiotic foundation for blockchain ledger entries. FHIR in conjunction with the blockchain can serve to preserve the integrity and associated context of data transactions.
A Blockchain-based approach to sharing patient data that trades a single centralized source of trust in favor of network consensus, and predicates consensus on proof of structural and semantic interoperability. Authors: Peterson K, Deedvanu R, Kanjamala P, Boles K. Organization: Mayo Clinic 13. Adoption of Blockchain to enable the Scalability and Adoption of Accountable Care: A new digital health care delivery model that uses Blockchain as a foundation to enable peer-to-peer authorization and authentication.
The recent trends in Accountable Care based payment models have necessitated the adoption of new process for care delivery that requires the co-ordination of a “network” of care providers who can engage in shared risk contracts. In addition, the need for sharing in the savings generated equitably is key to encourage the network providers to invest in improved care paradigms.
Current approaches to digitize healthcare focus on improvement of operational efficiency, like electronic records as well as care collaboration software. However, these approaches are still based on the classical centralized authorization model, that results in significant expense in implementation. These approaches are fundamentally limited in their ability to fully capitalize on the peer-to-peer digital work- flow revolution that is sweeping other segments of industry like media, e-retail etc.
In this paper the author formulates a new digital health care delivery model that uses block chain as the foundation to enable peer-to-peer authorization and authentication. The author will also discuss how this foundation would transform the scalability of the care delivery network as well as enable payment process via smart contracts, resulting in significant reduction in operational cost and improvement in care delivery.
In addition, this block-chain based framework can be applied to enable a new class of accountable tele-monitoring and tele-medication devices that would dramatically improve patient care adherence and wellness. Finally, the adoption of block chain based digital-health would enable the creation of varifiable “personalized longitudinal care” record that can form the basis of personalized medicine.
Author: Prakash R.
14. A Blockchain Profile for Medicaid Applicants and Recipients: A solution to the problem churning in the Medicaid program that illustrates how health IT and health research could leverage Blockchain-based innovations and emerging artificial intelligence systems to develop new models of health care delivery. The solution envisions a Smart Health Profile by thinking of the blockchain profile simply as a broker that can answer questions about you as the need arises, your identity remains distributed. No one can ever see everything about you at once, including yourself.
What makes the profile smart is that the services it provides can be quite intelligent. It can make sophisticated queries and actually trigger an action when certain conditions are met. For example, suppose you had a smart drug dispenser that recorded every dose you take as a transaction on the blockchain. A profile service might check everyday to see if you’ve taken your pill and automatically order a refill when you’ve used up all the pills. Over time, however, an AI service might become much more sophisticated to use a combination of information about your vital statistics from your wearable device and population studies of people using the various medications for your condition and either recommend a different regimen to your physician or simply cut out the middleman and direct your pharmacist to deliver you a new prescription.
The solution goes on to discuss the use of Blockchain in a medicaid scenario and a much more comprehensive solution as a distributed infrastructure for health. Authors: Vian K, Voto A, Haynes-Sanstead K. Organization: Blockchain Futures Lab – Institute for the Future 15. Blockchain & Alternate Payment Models: Blockchain technology has the potential to assist organizations using alternative payment models in developing IT platforms that would help link quality and value. Author: Yip K. References The content provided in the examples above have been collated from the various submissions to the ONC’s Blockchain Ideation Challenge. You can write to me or connect with me, in case you are interested in receiving the copy of the documents. In my previous article on Blockchain I shared whats Blockchain and types of Blockchain. I also discussed some of the usecases companies and startups have focussed on developing Blockchain based solutions. In this article I will share some of the usecases based on Blockchain technology, in healthcare. Alternatively, you could follow the links here
October 9, 2017 March 8, 2020 / CYBERSECURITY / 7 minutes of reading
Cybersecurity is in the news almost daily and Investment in cybersecurity, by established corporations or venture capital is rising. The stature and business significance of cybersecurity operations within organisations continues its rise to a strategic management issue in every organisation. A dearth of skills shortage continues to impede the progress of a successful cyber defense strategy that can be put in place, this is driving most organizations to increasingly look for outside help be entering into consulting and managed security services contracts.
Rapid Increase in the Investment in Cybersecurity
According to Gartner, worldwide spending on cybersecurity increased by 7% as compared to last year and will reach $86.4 billion in 2017.
Spending on both cybersecurity services and products is expected to keep growing into 2018, reaching $93 billion by the end of the year.
An Enterprise Strategy Group (ESG) survey found that for 39% of organizations, improving cybersecurity is the most important business initiative driving IT spending in 2017 and that 69% of organizations are increasing their cybersecurity budgets in this year alone.
81% of cybersecurity professionals agree that improving security analytics and operations is a high priority at their organizations.
Cybersecurity startup funding hit an all-time quarterly high in terms of number of deals in the first quarter of 2017, up 26% from the previous quarterly high. The trend held through the second quarter, which saw just one fewer deal (145 total) compared to the previous quarter.
The amount of disclosed equity funding to cybersecurity companies has also recently broken records, reaching an all-time quarterly high of $1.6 billion in the second quarter of 2017, according to CB Insights.
From cybersecurity operations into strategic Digital Risk Management
Organizations today generally think of cyber-risk as internal network penetration and defense. But there is now a shift towards developing a more comprehensive risk management strategy that includes all the digital assests such as – websites, social networks, partner exposure, branding and reputation management and compliance.
Says ESG: “Comprehensive Risk Management Strategy is a more holistic digital risk strategy designed to analyze threat intelligence, monitor deep web activities, track the posting of sensitive data, and overseeing third parties and partners.”
With the transformation of cybersecurity into comprehensive risk management, Gartner predicts that by 2020, 100% of large enterprises will be asked to report to their board of directors on cybersecurity and technology risk at least annually, which is an increase from today’s 40%.
The key in presenting to the board, says Gartner, is to connect the cybersecurity program goals to business risks. An example would be a discussion of implementing a process for managing third-party risk to support a business’s cloud strategy.
Cybersecurity skills shortage, a problem needing attention
There are currently more than 348,000 open security positions, according to CyberSeek. By 2022, there will be 1.8 million unfilled positions, according to the Center for Cyber Safety and Education. And The industry needs and will continue to need new kinds of skills as cybersecurity evolves in areas such as data classes and data governance, says Gartner.
According to the ESG Survey, Things aren’t improving at all, some survey results:
In 2016, 46% of organizations reported a problematic shortage of cybersecurity skills. In 2017, the research is statistically the same as last year; 45% of organizations say they have a problematic shortage of cybersecurity skills.
According to 2016 research conducted by ESG and the Information Systems Security Association (ISSA), 33% of respondents said that their biggest shortage of cybersecurity skills was in security analysis and investigations. Security analysis and investigations represented the highest shortage of all security skill sets.
Recent ESG research reveals that 54% of survey respondents believe that their cybersecurity analytics and operations skill levels are inappropriate, while 57% of survey respondents believe that their cybersecurity analytics and operations staff size is inappropriate.
The ramifications of skills and staff deficiencies are also apparent in the research. Cybersecurity operations staffs are particularly weak at things like threat hunting, assessing and prioritizing security alerts, computer forensics, and tracking the lifecycle of security incidents.
CISOs propose an easy fix: companies must work towards hiring more cybersecurity staff to bridge the knowledge and staffing gaps. In fact, 81% of the cybersecurity professionals surveyed say that their organization plan to add cybersecurity headcount this year.
However, its not that simple to do. According to the ESG research, 18% of organizations find it extremely difficult to recruit and hire additional staff for cybersecurity analytics and operations jobs while another 63% find it somewhat difficult to recruit and hire additional staff for cybersecurity analytics and operations.
Gartner recommends focusing the cybersecurity team on the most important tasks and automating the manual ones, such as log reviews. It tells CISOs to review their job listings to see if they are hiring for positions that can be outsourced.
Managed Security Services, SaaS and ITO route to managing security
All organizations need cybersecurity help, says ESG. When companies buy security tools, the product contracts include a professional services component that allow the companies to manage and ensure optimal usage of their security portfolio. CISOs can leverage the MSSPs and SaaS providers to outsource the relevant areas of their security portfolio.
According to Gartner, 40% of all managed security service (MSS) contracts in 2020 will be bundled with other security services and broader IT outsourcing (ITO) projects, up from 20% today.
To deal with the complexity of designing, building and operating a mature security program in a short space of time, says Gartner, many large organizations are looking to security consulting and ITO providers that offer customizable delivery components that are sold with the MSS.
As ITO providers and security consulting firms improve the maturity of the MSS they offer, customers will have a much broader range of bundling and service packaging options through which to consume MSS offerings. The large contract sizes associated with ITO and security outsourcing deals will drive significant growth for the MSS market through 2020.
IDC estimates that services will be the largest area of security-related spending over the next five years, led by three of the five largest technology categories: managed security services, integration services, and consulting services.
Together, companies will spend nearly $31.2 billion, more than 38% of the worldwide total, on these three categories in 2017.
Increased confidence in cloud cybersecurity
Just about 5 years ago, concerns about adequate security were cited as one of the top reasons for not moving IT operations and assets to the cloud. This thinking has recently changed, accompanied by rapid cloud adoption by many large corporations. A recent survey by analyst firm ESG has found “improved security” reported as a benefit that has been realized by 42% of organizations that already leverage cloud-based data protection services.
Gartner explains the potential key benefit of cybersecurity in the cloud: Today’s data centers support workloads that typically run in several different places—physical machines, virtual machines, containers, and private and public cloud. Cloud workload protection platforms provide a single management console and a single way to express security policy, regardless of where the workload runs.
While there are known benefits of moving the security services to the cloud, Gartner warns that as the cloud environment reaches maturity, it’s becoming an increasing security target. As with most services, possibility of the cloud based security services being targeted and the rendering the service unstable and insecure. Organisations therefore should work on developing security guidelines as to how they use private and public cloud and prepare a cloud risks model.
AI and machine learning (ML) driven Cloud Security
ML algorithms have the ability and potential to help with employee productivity & security analytics, but the technology is in its infancy and not well understood, says ESG. A survey of 412 cybersecurity professionals asked them to assess and characterize their knowledge of machine learning/artificial intelligence as it relates to cybersecurity analytics and operations technologies. Of the total survey population, only 30% of respondents claim to be very knowledgeable in this area. In other words, 70% of cybersecurity professionals really don’t understand where machine learning and AI fit their security portfolio.
Additionally, cybersecurity pros were asked about the status of deploying or are planning to deploy machine learning/AI technologies for cybersecurity analytics and operations in their respective organisations.
Only 12% say that their organization has done so extensively and 6% of respondents have no plans to deploy machine learning/AI technologies for cybersecurity analytics and operations. In the long run, most of the cybersecurity professionals did see the potential of AI and machine learning to help with automating manual tasks and ensure the management of skill shortage in the area.
Its is important that organisations take the effort to gain knowledge about AI and ML and how it will impact Cybersecurity Services and Products. This way they will be able to be more proactive to understanding the adversarial capabilities of hackers. Many companies employ ethical hackers to find out the loop holes in their security portfolios and protocols.
Your partner in Digital Health Transformation using innovative and insightful ideas
September 24, 2017 March 8, 2020 / #WEARABLES / 7 minutes of reading
IDC: Smartwatches accelerate in the second quarter, Device shipments grew 10.3% year over year to hit 26.3 million units during the second quarter of 2017; smartwatches grew 60.9%.
We are seeing the transformation of the wearables market with the total shipment volumes expected to maintain their forward momentum. According to the International Data Corporation’s (IDC) Worldwide Quarterly Wearable Device Tracker, vendors will ship a total of 125.5 million wearable devices this year, marking a 20.4% increase from the 104.3 million units shipped in 2016. From there, the wearables market will nearly double before reaching a total of 240.1 million units shipped in 2021, resulting in a five-year CAGR of 18.2%. 
The wearables market is entering a new phase
In the first phase of the market development, it was about getting the product out, to generate awareness and interest and getting the customers accustomed to the idea. This opportunity remains to be explored by the traditional and fashion brands as the scale of consumer electronics market evolves. Now, the wearables market is entering a new phase, opines IDC’s Ramon T. Llamas.
Now it’s about getting the experience right – from the way the hardware looks and feels to how software collects, analyzes, and presents insightful data. What this means for users is that in the years ahead, they will be treated to second- and third-generation devices that will make the today’s devices seem quaint. Expect digital assistants, cellular connectivity, and connections to larger systems, both at home and at work. At the same time, expect to see a proliferation in the diversity of devices brought to market, and a decline in prices that will make these more affordable to a larger crowd.” 
The phase 2 of the wearables development appears to be about taking the user data and provide analytics around the data to provide insights to the user, like step counts translate into a healthier heart. In this phase its about getting the customer to see the devices that actually augment the abilities to make lives easier, healthier and more productive, rather than another screen for the user. 
Top Wearable Products 
Watches: account for the majority of all wearable devices shipped during the forecast period. The report however shows that the basic watches (devices that do not run third party applications, including hybrid watches, fitness/GPS watches, and most kid watches) will continue out-ship smart watches (devices capable of running third party applications, like Apple Watch, Samsung Gear, and all Android Wear devices), as numerous traditional watch makers shift more resources to building hybrid watches, creating a greater TAM each year. The report suggests that the Smart watches, however, will see a boost in volumes in 2019 as cellular connectivity on the watches becomes more prevalent on the market. Wrist Bands: The report indicates a slow down in the market for the wristbands from 2016 onwards, but the market will be propped up with low-cost devices with good enough features for the mass market. However, the trend seems to focus on the users transitioning to watches for additional utility and multi-purpose use. Earwear: (this excludes the bluetooth headsets) are not counting. Instead, the report focusses on those devices that bring additional functionality, and sends information back and forth to a smartphone application. Examples include Bragi’s Dash and Samsung Gear Icon X. The report, also suggests the increase in the uptake of smarter earwear that centers on collecting fitness data about the user, real-time audio filtering or language translation. Clothing: The smart clothing market took a strong step forward driven by the chines vendors providing connected apparel. The growth in this segment is seen to be driven by the adoption of the connected clothing by the professional athletes and organizations have warmed to their usage to improve player performance. For instance, the upcoming release of Google and Levi’s Project Jacquared-enabled jacket. Others: include lesser known products like clip-on devices, non-AR/VR eyewear, and others into this category. It will include vendors catering to niche audiences with creative new devices and uses.
Top Wearable Devices by Product, Volume, Market Share, and CAGR 
Shipment Volume 2017
Market Share 2017
Shipment Volume 2021*
Market Share 2021*
Source: IDC Worldwide Quarterly Wearables Device Tracker, June 21, 2017
Global wearables market to grow 17% in 2017, 310M devices sold, $30.5BN revenue: Gartner | TechCrunch http://ow.ly/YFVu30eWQHL
Like any technology market, the wearables market is changing  “Like any technology market, the wearables market is changing,” noted Ramon Llamas, research manager for IDC’s Wearables team. “Basic wearables started out as single-purpose devices tracking footsteps and are morphing into multi-purpose wearable devices, fusing together multiple health and fitness capabilities and smartphone notifications. It’s enough to blur the lines against most smart wearables, to the point where first generation smartwatches are no better than most fitness trackers, he says. Beyond the top 5 vendors of the wearables market, new entrants like fashion icons Fossil along with their sub-brands and emerging companies like BBK and Li-Ning, are tapping into niche segments of the wearables market. Fossil, is coming up with a luxury/fashion device, BBK focuses on child-monitoring devices and Li-Ning on step-counting shoes. “With the entrance of multiple new vendors with strengths in different industries, the wearables market is expected to maintain a positive outlook, though much of this growth is coming from vendor push rather than consumer demand,” said Jitesh Ubrani senior research analyst for IDC Mobile Device Trackers. “As the technology disappears into the background, hybrid watches and other fashion accessories with fitness tracking are starting to gain traction. This presents an opportunity to sell multiple wearables to a single consumer under the guise of ‘fashion.’ But more importantly, it helps build an ecosystem and helps vendors provide consumers with actionable insights thanks to the large amounts of data collected behind the scenes.”
Top Five Wearable Device Vendors, Shipments, Market Share and Year-Over-Year Growth, 4Q 2016 (Units in Millions) 
4Q16 Unit Shipments
4Q16 Market Share
4Q15 Unit Shipments
4Q15 Market Share
Source: IDC Worldwide Quarterly Wearable Device Tracker, March 2, 2017
Implications of Wearables in Healthcare
Llamas, IDC. “Health and fitness remains a major focus, but once these devices become connected to a cellular network, expect unique applications and communications capabilities to become available. This will also solve another key issue: freeing the device from the smartphone, creating a standalone experience.”
Its important to note here the scalability of wearables in a clinical setting requires Intention, Education and collaboration. Some of the usecases highlighted for wearables in healthcare:
Managing Chronic Conditions of patients who might develop a secondary or tertiary complication because of a pre-existing condition (diabetic undergoing hip replacement surgery)
Tracking vital signs
Manage patients recovery at home (defensive medicine) instead of the recovery in a general ward, with help of remote monitoring
Detecting Alzheimer’s, most common form of dementia
Monitoring patients with chronic diseases and after hospitalization or the start of new medications for a decline in daily activity may help detect medical complications before rehospitalization becomes necessary
Clinical Trials: Monitoring of recruits
Smart Stethoscope for patients with cardiovascular disease
Ear device to track body temperature fluctuations
Temporary tattoo that senses vital signs
Smart Glasses with AR enabled patient records and physician information system
Finally, here is an interesting Infographic on Wearable Technology.
The Internet of Health Things (IoHT) is already delivering tangible cost savings, but continuous investment is essential
In a recently published report by Accenture , based on a survey of 77 Healthcare payers and 77 Healthcare providers in the US, the reports findings indicate that healthcare leaders are at risk of missing out on substantial cost savings, if they don’t take the full advantage of Internet of Health Things (IoHT).
The report indicated that by introducing more connectivity, remote monitoring, and information gathering IoHT can encourage more informed decisions, better use of resources and empowering healthcare users.
According to estimates, the value of IoHT will top US$163 billion by 2020, with a Compound Annual Growth Rate (CAGR) of 38.1 percent between 2015 and 2020. Within the next five years the healthcare sector is projected to be #1 in the top 10 industries for Internet of Things app development.
What is Internet of Health Things?
Internet of Health Things (IoHT) is the integration of the physical and digital worlds through objects with network connectivity in the healthcare industry. IoHT transforms raw data in simple, actionable information and communicates with other objects, machines or people. IoHT can be leveraged to improve access to health, quality of care, consumer experience and operational efficiency
Source: Accenture Report
Source: Accenture Report
The report lists four major takeaways for the payors and providers:
The Time is Now
Despite challenges with security and privacy, inaction is not an option. There are players outside of traditional healthcare organizations looking at these same industry challenges and considering ways to capture the opportunity. If providers and payers do not invest in demonstrating IoHT value now, they risk losing out to non-traditional players. Going forward, providers and payers must identify parts of the business where IoHT solutions may be applied to do things differently—and do different things to grow in the long-term.
Measure and Build on Successes
Providers and payers have already demonstrated value through IoHT—but they need to continue investments to better understand where programs are successful to prepare for future scaling. They need to measure effectiveness beyond the technology and then build on those areas of effectiveness quickly to offer value across the business. By demonstrating the benefits and best practices, providers and payers can strengthen business cases, encourage adoption and drive interoperability.
Put consumers First
Providers and payers must continue to incorporate IoHT solutions that drive better experiences and healthier patient outcomes, along with key medical and administrative cost savings initiatives. IoHT solutions offer the seamless collection of patient-generated health data, enabling providers and payers to provide more convenient, personalized and effective care. They must train their workforces to make IoHT a part of the “new normal.”
Form Nimble Partnerships
Technology and innovation partners can help payers and providers quickly test and learn how IoHT can drive business value to inform future scaling requirements. Strategy and change management partners can help to integrate these new technologies into their workflow, culture and training.
Key Findings of the Survey
73% consider IoHT to be a major change, and consider IoHT to be a major disruptor in three years.
however, 49% say the leadership at these organisations are yet to understand the potential of IoHT.
As IT investments are going up so are the IoHT investments seeing to become a major budget line item.
Healthcare providers and payors are investing in IoHT in three areas of their businesses – RPM, wellness and operations. And these organisations are reporting real benefits from the initial programs.
While 57 percent of healthcare organizations surveyed say that their IT departments lead the IoHT charge, 26 percent say their research and development (R&D) divisions are leading their IoHT efforts and one in ten organizations even have dedicated IoHT subsidiaries or business units.
RPM Based IoHT: 33% of PROVIDERS report extensive operational cost savings from their RPM IoHT programs. 42% of PAYERS report extensive medical cost savings from their RPM IoHT programs.
The majority of both providers’ (76%) and payers’(75%) RPM IoHT investments are focused on cardiac conditions. Interestingly, in the past, behavioral health has not received investment at similar levels to traditional high-cost areas such as cardiac, but the spotlight appears to now be shining on this area. Mental health, including behavioral health, is a relatively high priority for both providers (48 percent) and payers (55 percent)
Whenever a TweetChat is held, the moderator puts out an agenda for the discussion. Once its time, the participants share their point of view by Tweeting out their responses to the questions, tweeted by the moderator. The Connected Care #PhilipsChat questions follow and I Look forward to You sharing your thoughts and point of view on the role of Connected Care in Healthcare: 1. How would you explain connected care in one line? 2. Is the healthcare industry ready to embrace connected care? 3. How are your organization using connected care? Since when? 4. Based on your experience, what are the elements to enable connected care further? 5. How are you involving policy makers to embrace connected care? If we take these questions with an india context, how connected care can enable the affordability and accessibility to healthcare in India. These are the most often mentioned aspects of Healthcare, that needs to be addressed by not only the government, but also the Startup community willing to disrupt the Health Tech / Digital Health industry. I have attempted to share my thoughts on Connected Care questions put forward during the tweetchat and I hope you will consider sharing your insights by filling in the form below
1. How would you explain connected care in one tweet?
An always connected channel of communication of care between the patient and provider, from “touch time” to “face time”
2. Is the healthcare industry ready to embrace connected care?
In India, with the major push for digital services by the govt and private healthcare facilities, and with 350+MN internet users connected care is the only way to solve the accessibility to healthcare problem (1:3200 doctor to patient ratio)
4. Based on your experience, what are the elements to enable connected care further?
The connected care needs to bring about change in thought of how to use a connected care framework for the patient as well as the doctor. For the patient, connected care is about – experience that enables an ease of access to care – Ability to build their own healthcare record’s completeness – Have a better set of processes and #workflows to manage their health and care – Have the ability to find “patients like me” and be part of the community For the Doctor, I believe it will be about – how to glean new insights from the data stream – How to collaborate with a patient via an always connected model? What signifies the end of a consultation? – To build constantly evolving care plans for their patients, based on realtime, near-realtime, time-delay, or frequency per day/week month updates – To evolve more treatment plans based on the insights that can be drawn from the raw patient data feed (an e.g.) – How to build a community and be part of a community of specialists to keep themselves up-to-date on the current research and practices.
I am including the Questions as a Google Form, do consider sharing your insights into what is Connected Care? And how do you see it being enabled for the benefit of the patients and clinicians.
June 26, 2017 June 26, 2017 / OTHERS / 5 minutes of reading
Please note the above slides have been extracted from the Mary Meeker, Internet report 2017 purely for the purposes of this article. The statistics mentioned in this Blog have been taken from the Mary Meeker Internet Report 2017, relevant for DigitalHealth. For more details please view the complete report here While reviewing the Mary Meeker, Internet Report 2017 I found came across the statement “DigitalHealth at an Inflection point”. So in this article (as also the slide deck above) I have tried to review the Digital Health specific updates and provide a correlation to them by linking it up with the India Internet section that has also been highlighted in the report.
We are seeing a great many startups bringing the healthcare services by deploying Digital platforms, I think it will be an interesting exercise by the incumbents as well as new innovators, to view these two sections of the Mary Meeker report while preparing to expand their digital footprint or while trying to bring in new services to the market. Do we see a new category of Digital Health startups that can leverage the customer segmentation and growth in the customers with access to mobiles and internet penetration. We start with the India Internet growth story, and proceed to the Digital Health story.
The India Internet Story
There are some interesting insights related to the India Internet Story. These are:
With 355 MM users, India is second to china in the number of Internet Users. A 40% Y/Y growth and 29% penetration. This presents a large customer base for the Digital Health Startups providing services online
India is number 1 in terms of the number of Android apps downloaded, greater than the US. So an obvious first choice of platform on mobiles
India has been recording a steady growth in the smartphone shipments, at 15% Y/Y
There has been a reduction in the cost of 1GB of data from $3.15/ 1GB to about $2/ 1GB. Including Jio, the cost comes down to $0.33/ 1GB
There has been a push from the Government towards “Digital” services as can be seen from the following initiatives: Jan Dhan, Digital India, Skill India, Startup India. Government’s Policies rolled out with speed and scope
India identity via Aadhar + eKYC, Digital authentication of 1B+ people, 82% of the population have aadhar, has the potential to enable services with speed, scale and scope (e.g., SIM card activation from 1-3 days to 15 minutes)
46% of Internet users primarily consume local language content. 6 Languages spoken by > 50MM users (excluding english)
Young India: 64 % of the population, 72% of the Internet users less than 35 years of age
27% increase in the Consumption Class (income levels at which consumers start to have the ability to spend beyond basic necessities).
India consumption is focused on basics, i.e. 54% of personal consumption expenditure
The India Healthcare Story
India Healthcare has a high and rising out of pocket spend, <20% insurance penetration (a potential area for disruption?)
India Healthcare reimagined: Increasingly accessible via mobile and affordable via online aggregation and price transparency. Savings on Services like Online pharmacy (20-30%), lab tests ordering (40-50%).
The Digital Health at an Inflection Point
There are some interesting insights related to the Digital Health being at an Inflection point. These are:
100 years ago: human touch; 25 years ago: machine assisted/ analog; Today: technology enabled/ digital
4 trends highlight the current Digitisation of Healthcare and the Virtuous Cycle of Innovation: Data Inputs, Data Accumulation, Data Insights, Translation. Together these trends are helping measure Outcomes and rapidly iterate to enable compression of Innovation Cycle times.
The earlier analog medical technology is increasingly being replaced with Digital Technology, and is (continuously being) connected
Diagnostics Technology: increase in the number of measured / monitored data attributes
Increasing adoption in the use of wearables, for health and wellness. For health, heart rate and temperature
Leading technology brands are well positioned to participate in the Digital Health wave, with the customers stating in a Rock Health survey they will be most willing to share healthcare data with the likes of Google, Microsoft, Samsung, Apple, Amazon, Facebook and IBM (in that order)
Data Accumulation enabling the proliferation of Digitally native healthcare related datasets
Proliferation of health apps, with a 5% Y/Y growth in the US and 15% Y/Y growth in rest of the world
EHR adoption is leading to a broad and centralised accumulation of data with various types of patient data elements in a native digital dataset , e.g., clinical results, scanned images, vital signs, problems, medications, allergies, etc
In the US there has been an increase in the number of hospitals allowing for the patients digital access to the healthcare information
There has been an increasing digitisation of inputs fueling a 48% Y/Y growth in healthcare data
Data Accumulation: a typical 500-bed hospital generates 50 petabytes of data (1 petabyte = 1 mm gigabytes).
Rise in inputs + increase in digital healthcare data = medical research and knowledge is doubling every 3.5 years
Now that you have these data points available to you, what are the Digital Health business categories can you think of? Digitisation = Democratisation. How can we make use of the various natively digital datasets available to deliver better and improved healthcare services to the customers. How can the hospitals adopt Digitisation to improve service delivery. More so what is the shape of a Digitally enabled hospital? Your thoughts? Stay tuned to our list of Startup Categories that you can consider for your next startup.
June 9, 2017 June 9, 2017 / OTHERS / 11 minutes of reading
#Startup, is a favourite word we hear these days from AiM to PM. At times it has connotations of a journey to fulfil, a dream to Startup is to Just go for it, and at times it brings about the memories of your struggles and wins, from that journey. But to startup is to also understand the basics of the entire process of establishing a business and running it.
You can proceed on two paths, just get started and learn by doing or you could get started and follow a process that allows you to ask yourself some questions each step of the way. I worked in a company that had a “Board” room named as Kaizen. I remember spending a great many hours in that room discussing what would be the new path our product would take and also showcasing the future releases of the product to existing and prospective customers. That was a room that also helped the team to see first hand the reactions of these very customers to our solution and not a meeting went by when the team came out of that room thinking what other “WOW” moment we can create for our customers. From the Kaizen room, the teams always came out wanting to do better and wanting to be the best. And I feel and see the same enthusiasm from the Digital Health Startups I have been following for quite sometime now. Guess we had built in a continuous feedback loop that allowed us to get updates from our various customers and what they were saying about us and also having the ability to constantly innovate and continuously improve. Well I digress, I was here to tell you about how you need to think like a VC or Angel and the reason I mention the story is to state the point, that in the rush and din of starting up, funding, customer acqusitions, round two, series a, b, c… etc, we tend to stop thinking about the basics. The Business Plan Evaluation Aids, that I list in this blog post, will help you define a schedule that will help you continuously improve, track, change and pivot your business plan to meet the needs of the customers you are serving or want to serve. And the best part is that the BPEAs are driven by fundamental questions that are generally asked during a due-diligence process of funding, IPO, exits or business evaluations by third party auditors. The BPEAs help you build a “Continuous Feedback Loop” to continuously evaluate yourself with metrics that will help you determine where you are, where you want to go and what you must do to reach your goal.
Why is there a need for this process, in a startup? Arent’ startups supposed to Hack-It, Jugaad-a-thon it, Frugally Innovate, be Agile? And at the same time we also hear the statement, “9 out of 10 Startups will fail”. Or of late, have been hearing about stats such as why do most Indian Startups close within 5 years. Lets try to turn that tide and improve the odds. Lets build to last !! (taken from a famous strategy book, i always like referring to and like the title because its not about exits, its about building something tangible and long term. Thats my personal take on starting up) Lets try, by adding some semblance of method to the Startup madness and agility, by considering the Bell Mason Diagnostic as a Business Plan Evaluation Aid (BPEA) for your startup. The Bell Mason has been used by the Authors of the Model, to evaluate Technology Startups since the late 90’s (and has been used around the world to evaluate about a 2000+ ventures). I came across an interesting statistic from a study, “Venture capitalists reported devoting 8 to 12 minutes on average to evaluate a business plan (Sandberg 1986). Much of the evaluation is purely intuitive, despite the existence of several decision aids, which might be expected to aid both efficiency and consistency in the decision-making process.” So if you are able to prepare yourself to provide the VC or Angel with the best information about your startup and a story line that is compelling, you might just get funded. And perhaps that is what differentiates that one startup that makes it? Another interesting story from the recently concluded Google IO, 2017. I remember one of the top executives from Google making the presentation and talked about how they had been “preparing” for this presentation from a long time. Well its Google, they dont need to do it, they can Just Do It too? Right? Same is the case, with Apple, when we have heard, read and seen the great presentations made by Steve Jobs for every single presentation for a new product launch, like the iPhone Launch. Let there be planning and evaluation at each stage of your journey, after all you might either have the time in the Elevator to Pitch or have 8 to 12 minutes, make them count. The Bell – Mason Diagnostic (BMD) – A Startup Evaluation Model
The Bell – Mason Diagnostic  involves answering questions about your Startup. The authors where involved in evaluating Technology Investments. The model can be used by startups to evaluate their current stage, or can be used by corporates, planning on investing in new technologies and ventures (Intraventures).
What is the Bell – Mason Diagnostic Evaluation Model?
The BMD, consists of the following aspects that every venture, startup or intraventure can evaluate themselves on.
1 The Founding Premise
The the BMD Model’s founding premise is
“You dont need to understand the Technology to ask the basic business questions”
2 The Four Diagnostics
The BMD model is built on the following 4 Diagnostics that each company/ project needs to do, depending on the current Stage of their startup/ venture or intraventure
Space: 12 standard dimensions of any venture
Time: 4 Stages of company development
Quantification: Questions under each dimension to evaluate the company
Visualisation: The graph showing the current status of the company based on the stage of company development
There are 12 Standard Dimensions of Analysis of a venture. These highlight the various aspects of a startup.
The 12 Dimensions of the Bell Mason Diagnostic are:
12 Dimensions of the Bell – Mason Diagnostic (BMD)
Service Delivery/ Manufacturing
Board of Directors
The twelve dimensions are organized in four groups, each containing three dimensions:
Product: Technology/engineering, manufacturing and product
Market: Business plan and marketing and sales
People: CEO, top-level team, and board of directors
Finance/ Control: Cash, financeability, and operations/control
2. Time: The 4 Stages of Growth The 4 Stages of Growth for every Startup or Venture or Intraventure according to the Bell Mason Diagnostic are:
Concept (0 to 12 months) – Discovery
Seed (3 to 12 months) – Definition
Product Development (12 to 48 months) – Development
You can also review the 5D Delivery Process that I have written about here:http://blog.hcitexpert.com/p/5d-service-delivery-framework.html 3. Quantification: The quantification process involves asking a series of questions to oneself for your own company or to the startup being evaluated. Each of these questions are based on the 4 Stages, the 12 Dimensions. Each of the questions has a simple rating 1, 2, or 3. Each of these ratings can be attributed with a weighted score to arrive at the efficacy of a company or an idea. This is the way the startups can codify their work using a best practices approach to starting up. 4. Visualisation: Once the Founding Team has answered and presented their idea within the purview of these stages and dimensions, the results are plotted onto the radar chart. Each of the sections of the radar chart, corresponds to a dimension of the BMD and depending upon the outcome of the questions under each of the dimensions, helps the person evaluating the proposal to identify the steps ahead.
So how does the Bell – Mason Diagnostic Evaluation Model, work?
Identify the Stage of your startup: Based on the Stage your startup is at, The Bell Mason Diagnostic presents the various dimensions that you need to focus on. These dimensions are relevant for that stage of your company (venture or intraventure). Each of these dimensions comes with a series of questions that need to be reviewed and answered by the startup team (project, venture, intraventure). The focus areas for each startup stage are defined by the following radar chart.
You can event do a quick run through each of the dimensions relevant for the current state of your startup and rate each of the dimensions with a score of 1 to 5. That will help you identify if you are able to move your startup from one stage to the next. It also helps the startup to evaluate what are the tasks they need to perform to move from one stage to the next. For instance, at the concept stage the BMD shows that the Startup needs to evaluate the following dimensions: technology, business plan, CEO, cash and financeability.  Another important aspect of the Bell Mason Diagnostic, is to help the startup identify the equity they can give out at that stage of the startup. Using this method the founders can understand the finance they would need, the type of finance they can go for and the amount of equity they should be able to give away at each of the stages
How to, Build to Last
As startups we need to beat the odds i shared earlier, 9 out of 10 startups fail? Why startup if you accept the fact that you are going to be keeping the batting average at the above number. The average is not acceptable as a rapidly evolving startup nation. We need to focus on how we can build organisations that are “Built to Last“ and while we can still remain agile in our delivery process, but at each stage of your startup, we need to evaluate the current state by answering these in-depth questions which can pile up quite fast and under the radar. The BMD helps the startups run an iterative and a continuously improving and evolving analysis of their company that in turn generates a list of activities, to-do lists, product backlogs, etc that will help the company to move to the next stage of their startup journey. While I am not proposing that you keep doing the same thing again and again, you can surely use the BMD to also identify if you need to pivot, exit, re-strategize and work at other aspects of your business plan to improve what you are building/ developing. There are many other models of Startup (or venture, intraventure) Evaluation. In this blog post I have tried to present the Bell Mason Diagnostic to help you get started on a task of evaluating the current state of your startup. Be it due-diligence, or preparing for presentation to new board members or members of the executive team, use this model to help you identify the next steps to be taken. Just remember building a product requires getting your fundamentals right, the BMD framework can help you do that. While you are working on evaluating your startup using the Bell-Mason Diagnostic (BMD), you might also consider reviewing the following Business Plan Evaluation Aids (BPEAs). “A BPEA is a highly specialised subset of human decision aids used for the specific purpose of screening entrepreneurial business plans. Any decision aid is used to provide assistance and structure to improve the accuracy and consistency of human judgment.”  1) the FVRI System (Fiet, Gupta, et al. ) and 2) the New Venture Template(Mitchell ) 3) The Venture Opportunity Screening Guide(Timmons ) 4) ProGrid Venture (Bowman ) I have put together an excel sheet that will help you arrive at the “Go – No-Go” for each of the Startup Stages. Let me know and I can share the same with you. Drop me an email at manish.sharma [at] hcitexpert [dot] com. In the followup Blogs I will present some of the other BPEA tools listed above and share the various categories of healthcare startups. If you are a Digital Health Startup, I would like to hear and share your story, what is the solution you are developing, more importantly why? Here is an interesting write up by Shailesh Gogate (@sgogate), on 5 lessons learned while assisting Healthcare #startups
May 29, 2017 May 29, 2017 / OTHERS / 6 minutes of reading
In my previous article I discussed about the benefits and barriers to the use of an Integrated Health Information Platform. In healthcare the need for presenting the Information to the Right Person at the Right Time has been proven to improve outcomes in patient treatment.
Will HIE 2.0 benefit from the use of Blockchain in presenting the information to the Right Person at the Right Time?
What is Blockchain?
Various definitions of Blockchain have been put across based on the context of the use. Some of these definitions are: A digital ledger in which transactions made in bitcoin or another cryptocurrency are recorded chronologically and publicly. “The blockchain is an incorruptible digital ledger of economic transactions that can be programmed to record not just financial transactions but virtually everything of value.” Don & Alex Tapscott, authors Blockchain Revolution (2016) The Blockchain is a decentralized ledger of all transactions across a peer-to-peer network. Using this technology, participants can confirm transactions without the need for a central certifying authority. Potential applications include, fund transfers, settling trades, voting etc. Blockchain is a distributed system for recording and storing transaction records. More specifically, blockchain is a shared, immutable record of peer-to-peer transactions built from linked transaction blocks and stored in a digital ledger.  A Blockchain is a data structure that can be timed-stamped and signed using a private key to prevent tampering. There are generally three types of Blockchain: public, private and consortium. 
How is Blockchain different?
Traditional databases are proprietary to the entity that maintains them and owns them. And the information stored within these databases are accessed only by providing access via an application or shared by the entity in some form of a distributed architecture. On the other hand, “blockchain is enabling a database to be directly shared across boundaries of trust, without requiring a central administrator. This is possible because blockchain transactions contain their own proof of validity and their own proof of authorization, instead of requiring some centralized application logic to enforce those constraints. Transactions can therefore be verified and processed independently by multiple “nodes”, with the blockchain acting as a consensus mechanism to ensure those nodes stay in sync.”  A quite often stated example for explaining Blockchain is the Google Doc example. Earlier, collaborating on a document involved a serial approach to making changes to a document. Only once the author has completed the document, can it be forwarded to the next person to edit and provide feedback. But consider the Google Doc (or any of the other collaboration tools), once you have created a google doc, you can start creating the document and also share the same document with other collaborators who can also make changes to the document at the same time allowing for reconciliation of changes to be incorporated within the document to finalise it. The author takes the comments from the collaborators and generates the finalised document.
Blockchain: How it Works?
A transaction is requested. The transaction is broadcasted to the peer-to-peer network consisting of computer nodes. The network validates the transaction and the initiating entity’s status using relevant algorithms. The transaction record is then considered to be verified. On verification, the transaction record is added with other transactions to create a new block of data for the decentralized ledger of all transactions across a peer-to-peer network. The new Block is added to the existing ledger of all transactions, i.e., the Blockchain. The transaction is now complete.
Types of Blockchains
Permissionless or Unpermissioned Blockchain allows anyone to join the network and participate in the block verification. For instance, a permissionless blockchain example is the Bitcoin.
Permissioned Blockchains restricts the nodes in the network who can contribute to the consensus of the system. Only permissioned nodes have the rights to validate the block transactions.
For instance, most enterprise Blockchains are permissioned blockchain and allow for privacy, scalability and fine-grained access control.  There are more types of Blockchains.
Interoperability in Healthcare
The context of discussing Blockchains in healthcare is Interoperability. There are various use cases that come to mind, when we talk about interoperability in Healthcare. (most are N:N interactions)
HIMS to Lab Equipment
HIMS to PACS
HIMS to HIMS
HIMS to Apps
HIMS to Portals (Patient, Physician, etc)
Portal to Portal
Stakeholders to HIE
Hospitals to Insurance
You can consider the number of stakeholders in the Interoperability ecosystem and continue to add them to the above list of use cases. And that allows one to understand the current fragmented nature of the Patient’s Healthcare Information. Each of the above stakeholders, generate the patient care record and have the need at one time or another to share this information with others in the ecosystem. We have already seen the benefits and barriers to information exchange. For the purpose of this blog, lets consider the Healthcare Information exchange use case. HIEs’ share the patient information in a network that is accessed by participating entities. The Patient information available on the HIE can be accessed as and when required by the patients’ treating doctor. The availability of a patient information, at the right place and at the right time was (one of) the intended purpose of a Health Information Exchange. HIE frameworks relied on a centralised or federated or hybrid architectures  to make the information available to the participants in the exchange. The exchange is maintained by an entity. In the nationwide Interoperability roadmap defined by the ONC (US) . They define the critical policy and technical components required as
Ubiquitous, secure network infrastructure
Verifiable identity and authentication of all participants
Consistent representation of authorization to access electronic health information, and several other requirements
Additionally, the ONC challenge stated Potential uses to include:
Digitally sign information
Computable enforcement of policies and contracts (smart contracts)
Management of Internet of Things (IoT) devices
Distributed encrypted storage
In India, anIntegrated Health Information Platform (IHIP)is being setup by the Ministry of Health and Family Welfare (MoHFW). The primary objective of IHIP is to enable the creation of standards compliant Electronic Health Records (EHRs) of the citizens on a pan-India basis along with the integration and interoperability of the EHRs through a comprehensive Health Information Exchange (HIE) as part of this centralized accessible platform.
IHIP is envisaged to enable
Better continuity of care,
secure and confidential health data/records management,
better diagnosis of diseases,
reduction in patient re-visits and even prevention of medical errors,
optimal information exchange to support better health outcomes
With the understanding of What is Blockchain, What is Interoperability in Healthcare and What are the use cases for Interoperability in healthcare, do you think Blockchain Technology can be used in Healthcare? Do share your thoughts and use cases. And while you share your usecases, do read up on the very interesting two part series from Dr. Senthil N, on theUnintended Consequences of new Technologies in Healthcare, Thoughts on Blockchain In the next part of the blog, I will explore some of these use cases in healthcare and for the purpose of defining how Blockchain can help interoperability of Patient Transactions across healthcare facilities.
We have seen the benefits of Aadhar and how a public data repository can be used for public good. Population Health based clinical data repositories too can play a similar pivotal role in providing potentially great benefits
The use of Healthcare IT in the Indian context is picking up with most of the corporate hospitals going for the #EHRs and HIMS solutions. And these are present mostly in the Tier I cities and urban areas. There is a move now to get these solutions to the Tier 2 and Tier 3 centers as well. I would be looking to review reports that highlight percentage of IT enablement in Healthcare facilities, as part of follow up articles to this one.
The Center for Healthcare Informatics has rolled out an RFI detailing the requirements of an Integrated Healthcare Information Platform (IHIP). You can also visit the dedicated website to review the details of the IHIP RFI:
In this article I would like to highlight the benefits that will accrue from implementing such a solution in India. With no historic data of past implementations of such a system in India, I have reviewed the information available in journals and public domain regarding similar implementations across the world and what are the benefits and barriers in implementing an Healthcare Information Highway of patient healthcare data.
Benefits of Implementing an HIE
Benefits of Implementing HIEs:
HIEs that have been implemented in the US have conclusively shown emergency departments gaining efficiency in patient visits with the use of HIE based solutions.
HIEs have shown to reduce the length of patient stay, readmission risk, and number of doctors involved in patient visits .
One of the examples of benefits of an HIE, is the ability to generate alerts 24-hour to 48-hour prior to the patient’s’ discharge to Transportation services, Pharmacies at the patient’s location and alerts to help patient identify long term care and home care facilities. 
Transfer of Radiology Images:
Currently the process of exchanging patient radiology images either does not exist or at best is time consuming with problems faced by the patients and providers treating the patients.
The ability to access and view radiology images is important for an accurate and timely patient diagnosis and treatment. Historically, the process of image exchange has happened via CDs with an understanding the receiving and reviewing physician will have the ability to view the PACS images leading to high costs and long time to diagnosis.
Enabling a Transfer to PACS capability helped in cutting these lacunae in the image sharing workflow, enabling providers to quickly share images with each other. 
Vaccination and Immunisation details:
HIEs are now moving towards incorporating the exchange of patient immunisation details. Thereby enabling patient centered technology implementations.
Disease Surveillance and Immunisation Records
IHIP will provide increased view of disease outbreaks and allow the governments at the state and national levels to deploy resources effectively and efficiently. IHIP based identification and surveillance of disasters and outbreaks is a big benefit of implementing a platform such as IHIP. And additional areas that provide a fillip to the IHIP-initiative needs to be identified and those aspects of the IHIP needs to be implemented in the initial stages.
Medication Information Sharing via HIEs:
The ability for the patient to build and maintain an electronic Drug Profile is important for the continued care for the patient. Presence of a Comprehensive Patient Drug profile has direct correlation to improved patient safety. Improved medication information processing has a direct correlation to the benefits of an HIE like the IHIP since it will be able to provide a more complete clinical picture of the patient. 
Telemedicine service enabled by HIEs:
Telemonitors will be able to provide patients a way to measure and record their vital signs daily from home using a touchscreen tablet/ mobile/ PC. The information will be then wirelessly transmitted to nurses monitoring the information for changes, giving patients with, complex disease states such as heart and respiratory conditions, a sense of empowerment around their health. Telehealth has far reaching benefits for specialists providing their services to patients in the rural, underserved and non-tier I cities. With the presence of digital payment gateways and transactions, Telemedicine is fast becoming a viable business model for certain types of visits(e.g., follow-ups, referrals). 
New Use Cases for an HIE:
When HIEs have been implemented, new use cases can emerge that extend the usefulness of HIEs. For example, HIEs have been able to send hospitals alerts and reminders when patient transitions occur, device to device data transport, sending and receiving of claims attachments, and exchanges of documents for referrals 
Security of Patient Information (PHI):
The greatest benefit of an IHIP-like solution is the Implementations of Security protocols for transport and transfer of patient information between healthcare facilities and between patients and hospitals. This ensures creation of “Trust” centers of patient data.
Improves the Trust in sources of information
One of the reasons a physician would order for a repeat test for a patient in case of a referral, would be “Trust” on the presence of a similar/ same test result available for the patient in an earlier visit. Enabling information sharing via IHIP in a standardised and secure format will enable “Trust” between healthcare facilities as trusted sources of information. 
Strategies to avoid Information Blocking:
Information Blocking has been known to be a major cause of hindrance to the benefits brought out by an HIE. Information Blocking is healthcare facilities not sharing patient healthcare record information causing holes in the episodes of care of a patient’s longitudinal record. To avoid this from happening, “Increasing transparency of EHR vendor business practices and product performance, stronger financial incentives for providers to share information, and making information blocking illegal were perceived as the most effective policy remedies,” wrote researchers. 
Paradigm Shift in HIE from 1.0 to 2.0:
HIE 1.0 was characterized by a focus on “the noun,” that is trying to address perceived market failures by solving a wide variety of rich use cases through comprehensive interoperability.
By contrast, HIE 2.0 focuses on the verb that is trying to meet market needs most pressing to participating providers; HIE 2.0 has fewer legal challenges because it is trying to tackle less complex use cases and in many instances has the ability to marshal financial, technical and organizational resources. Tripathi also pointed out that HIE 2.0 comes in many shapes and sizes including point-to-patient; point-to-point; vendor-specific; transaction-specific national level; enterprise-level HIE organizations; State-level and regional collaborative HIE organizations and National level collaborative HIE organizations.
Three areas identified to spur innovation and move towards HIE2.0 were: Lab data transmission, Lightweight directed query of patient information, eCPOE and measures.
Problems Implementing HIE: A review of Global HIE Experiences
Unspecified Interoperability Standards:
Barriers to HIE relate to incomplete and unspecific interoperability standards and the cost of interfacing the EHR with the HIE. The lack of mature, agreed standards around interfaces, patient consent and patient identification are significant barriers to success.
Accurate patient identification is not only a data management and data quality issue, it’s also a patient safety issue
Clinical Information Generator and Vendor relations
In the India context, healthcare facilities like hospitals, laboratories, pharmacies deploy systems that are proprietary in nature and not necessarily standards based. In the event of strained relations between healthcare facilities and respective vendors, there is a need to consider addressing the need to have the patient related information to be relayed to the patient in a HIE readeable format. This information can then be uploaded by the patient thereby ensuring the continuity of care records are maintained in the IHIP, specific to the patient.
In this scenario, there could be a loss of updates to the public health based registries and the hospital based registries and it should be incumbant on the hospital to ensure the data is transmitted before the changeover of systems happens.
Identifying ROI for various Stakeholders
A study needs to be enabled by the government at the national and state levels that will study the benefits of implementing interfaces that will share information between the Healthcare facilities and the IHIP. Potential savings can be quantified based on cost and projected savings in improved efficiencies enabled by the implementation IHIP towards patient safety and care coordination for the stakeholders.
Additionally, its important to quantify the cost of implementing HIE-based interfaces by the various healthcare entities (like Hospitals, Laboratories, Diagnostic centers, pharmacies, etc). It will be important to identify the Revenue Streams to sustain IHIP data sharing, and how can it be sustained by the stakeholders.
Breach of Security of Data contained in IHIP or connected interfaces
We have seen various types of hacks that have breached the security of patient records stored in hospital systems. Enabling security at various levels needs to be ensured before any of the Stakeholders connect with the IHIP. Security guidelines will have to be defined and adhered to and reported on a regular basis as a regulatory requirement.
Security is also necessary at the IHIP level which has been defined as a main requirement for developing the IHIP infrastructure.
In the US Architecturally, RHIOs employ either the CHMIS approach of a centralized database, the CHIN model of federated independent databases, or some combination of the two, hybrid model.
Usability & Access to Information Ok, so the data about a patient has been stored in the Data Repository for all to access and review at the time of emergencies, for enabling a continuity of care record for the patient and for generating population health management analysis. But, what if the data is not easily accessible, the functionality to access the care information of the patient, requires multiple access requests and clicks and permissions. What if, the data has now been stored in the public data repository, who can access it? Who can view it? Can there be an unauthorised data access by persons not connected to the health care of the patient? 
For-profit EHR vendors have a natural vested interest in increasing revenue by limiting the flow of data.
“The specific forms of and perceived motivations for information blocking were harder to predict a priori,” Adler-Milstein & Pfeifer explain. “What we found in relation to specific forms is that EHR vendors appear to most often engage in information-blocking behaviors that directly maximize short-term revenue. Our respondents reported that EHR vendors deploy products with limited interoperability and charge providers high fees unrelated to the actual cost to deliver those capabilities or refuse to support information exchange with specific EHRs and HIEs.”
Hospitals and health systems likewise utilize information blocking as a means to prevent clients from seeking services elsewhere to keep from losing out to the competition.
“In our results, the most commonly reported forms of information blocking among hospitals and health systems point to their interest in strengthening their competitive position in the market by controlling patient flow, which has been reported in other studies,” they wrote.
Interoperability in Healthcare: Some thoughts to share
Having followed the implementations in India for sometime now, I always wonder why interoperability is not a top priority or not implemented in most systems. They are HL7 compliant, but are they really interoperable? And I dont mean the part from HIMS to Lab or Rad equipment, that part is fairly well defined and documented. – But from the Patient to Hospital to Patient – Patient to Insurance to Patient – Patient to app to hospital to Patient Take for instance most systems are able to share the discharge summaries as emails to patients, and a print out, even today. But on discharge can the patient “share” her discharge summary from an app or application to another practitioner who takes care of the patient rehab? Are for instance, the systems involved in the above use case, interoperable? Another point, how many Healthcare Apps (the production versions) have any data sharing via standards? They can however email PDFs of the recorded data. So what can be done to enable out-of-the-box interoperability in the Healthcare Apps? With the growing number of mHealth Apps, we will soon find ourselves in another new set of “Data-Silos” being created on a daily basis. Recently we moved from Cash to Cashless to Less Cash scenarios … so is it right to say, in healthcare context, we are working from a Paper to Paperless to Less Paper scenario in Healthcare before going totally paperless? And if so: 1. What will be the business case for interoperability and for sharing the discharge summary/ medications in a format that is easily exchangeable? 2. Can a Healthcare IT think tank, work on defining the standards of “workflow” of the data being generated in healthcare today? Starting from the Patient through the healthcare ecosystem and back to the Patient?
3. Can the Healthcare IT vendors form a group of HIMS, LIMS, Pharma Apps, HomeCare solutions that enable a “Patient Data Workflow” exchange group (a mini-IHIP) that actually enables the “Interoperability” of patient data as a great showcase. It could perhaps be tied to the IHIP effort or NDHA. It adds onto the work that is being planned in the Phase 1 of the IHIP project, by being able to provide feedback onissues, solutions, recommendations, pain points etc. Its important to note, that a system like IHIP has a potential to solve the accessibility of patient care problem in India. My view is that there is a need to see interoperability from a Patient’s point of view rather than from the point of view of “Systems”. There is a need to map the flow of data from the Patient and back to the Patient, and this can help in enabling a radically different approach to interoperability in Indian Healthcare. With Aadhar based solutions allowing for the consumer information to be securely transmitted and verified, it only behoves well if we were to adopt an “HIE of Patient” approach to IHIP wherein the Information is exchanged between various stakeholders in the Patient’s Care Continuum and that information finally rests with the Patient’s Electronic Health Record (PEHR). With the EHR standards mandating the Healthcare Information belongs to the patient, it will be extending that mandate to IHIP. And here is a review by Mr. Rajendra Pratap Gupta, Policy Maker, Researcher, Author, TED Speaker, Economic & Political Strategies, Innovation, Healthcare) on how “India aims to be a Global Leader in Digital Health,
April 4, 2017 April 4, 2017 / OTHERS / 14 minutes of reading
is The ability to adapt one’s behavior to fit new circumstances.
In Psychology, human intelligence is not regarded as a single ability or cognitive process but rather as an “array” of separate components. Research in building AI systems has focused on the following components of intelligence: 
These components of human intelligence are also utilized during diagnosing a patient and defining the treatment plan and protocol for the patient.
The process of Medical Diagnosis
The process of how a Doctor goes about her diagnoses of a patient, is the ability of a Doctor to adapt to varying presenting illnesses of her patients.
Identify the Chief complaint of a patient
Gather information about the history of present illness
List the possible diagnosis & record the differential diagnosis for a patient
And then perform relevant diagnostic tests to determine the most likely causes for the presenting complaints
The Doctor initiates the process of identifying the most likely cause of the patient’s presenting illness and then based on the results of the diagnostic tests, proceeds to confirm a diagnosis and then proceed towards defining a treatment plan for enabling the patient to recover from the disease.
In the above simple process defined for a medical diagnosis, the Doctor (based on her training) makes use of all the “components of intelligence” to arrive at the most likely treatment plan for a patient. The process obviously gets more involved and complex depending on the type and nature of diagnosis.
Medical Diagnosis or Medical Algorithms?
From the above “very simple example” it’s clear that the doctor uses her learning and reasoning to proceed towards the best possible treatment pathway for the patient. And this can be treated as a series of Questions that help the doctor arrive at the “confirmed diagnosis” for the patient.
The process of Medical Diagnosis can then be treated as an Algorithm that helps the doctor arrive at a conclusion based on the presented facts.
Dictionary defines an “Algorithm” as, a process or set of rules to be followed in calculations or other problem-solving operations
The doctor in the above scenario has being processing via a set of rules and calculations and problem-solving operations to arrive at the confirmed diagnosis.
The doctor goes through a perception analysis to determine what specifically is presented based on the patient’s illness and then determines based on, not only the diagnostic test results, but also based on other parameters of a patient’s active and confirmed diagnosis.
Medical Diagnosis work in clinical practice generally has four models: 
Pattern Recognition, wherein the doctor recognizes the current patient’s problem based on her past experiences with other patients, e.g., Down’s syndrome.
Hypothetico-deductive, wherein the doctor performs a certain battery of tests to test a hypothesis, a tentative diagnosis
the Algorithm Strategy: the algorithm strategy has been used in Healthcare and has been represented using Medical Logic Modules , Arden Syntax for Medical Logic Systems  and Clinical Pathways  and finally the
Complete History Strategy has been defined to be the identification of Diagnosis by possibility. Evidence based medicine is then used to come to a conclusion of the final diagnosis. 
The training process to arrive at a Medical Diagnosis has been used in the past to the development of expert systems or Clinical Decision Support Systems (CDSS). Early medical AI systems have tried to replicate the clinical training of a doctor into meaningful implementations of AI in healthcare.
Usecase for Artificial Intelligence in Healthcare
Understanding the process and workflow in healthcare is going to be important in implementing solutions that are “aware” and intelligent. And the systems that need to be developed for Healthcare need to be able to assist the clinicians with systems that are more close to the clinicians natural daily workflow. Consider the current scenario of a physician meeting with a patient in a clinic setting, with the current systems in place the “Patient Visit” workflow generally involves the doctor having to divide her time between talking to the patient, examining the patient and recording the findings on an EHR (electronic health records) system. Most such visits can last from 5 minutes to an hour depending on the specialty (for instance, general medicine to mental health). Additional complexity is added to the workflow based on the patient diagnosis.
There have been many studies that have recorded the doctor’s reasons for resistance to enter the visit data into a system . A time and motion study of a patient – doctor interaction can be revealing in an EHR vs a non-EHR setting. While EHRs have shown their ability to reduce potential errors (as has been well documented in the report, to err is human) the additional steps of transcribing the visit data into an EHR is generally seen by the doctors as being a disruption in their natural visit or encounter workflow.
On the other hand, take into consideration a study of the workflow of a pathology department such as biochemistry or hematology, where the technology implementation is relatively easily accomplished. The pathology departments main “Entity”(from a systems perspective) to be processed is the patient sample and the level of automation required to process the various tests that need to be performed on the sample is quite well defined by its degrees of freedom, the test ordered by the doctor. Similarly the entity in a radiology department is the image that is the outcome of a radiology exam.
In radiology department for instance, an AI-based solution can enable operations at scale for enabling reading of radiology images from rural areas, where in the images get uploaded by the medical assistant or radiographer at the remote location. The AI systems now have the ability to read and report the images with increasing accuracy, but we still have some way to go before we achieve a greater deal of accuracy.
On the other hand, the “Entity” in a patient doctor interaction in a visit, the patient, has many more touch points within the patient care continuum and the level of complexity of this interaction needs to be dealt with in a completely different approach. While the processing in a pathology or radiology department is based on the sample or an exam, which is a snapshot at particular point in time, the treatment of a patient constantly needs to be monitored and presents more data points on an ongoing basis.
An AI-based solution to help a physician therefore needs to be applying for instance, the four models of medical diagnosis to a patient visit before we can call a patient visit as an intelligent or aware encounter.
If a doctor divides her time between listening to the patient regarding her present illness, and simultaneously recording the information on a computer system, there has been a disruption in the doctor’s natural workflow of focusing on the patient, of listening to her present illness, asking questions about onset, etc. and reviewing the results of the investigations and radiology reports. The doctor is trained to handle all these data points and process the information from the perspective of the four aspects of the medical diagnosis training of the physicians.
Here is an interesting story you would like to review showcasing a doctors 35-hr shift in Delhi, India. By the way the story lends itself to creating some really interesting “Intelligent Digital Assistants” for the doctors. It also presents to experts developing AI based solutions for Healthcare, a fantastic time and motion study of a Doctors’ shift and the touch points to where the technology can be integrated into the Doctors “workflow” Current systems do not allow that, they tend to focus on implementing a strategy of recording by exception, by recording only the exceptions and all the other aspects being marked as normal, for instance. While such aspects have been proposed and devised by working with the physicians, still they are workarounds to do what the technology of today allows or allowed in the past.
These are re-creations of paper based systems that have been translated to an electronic health recording system.
The Patient – Physician interaction needs to be revamped, in the current information technology systems by enabling the various components of human intelligence we have highlighted earlier:
Ideal scenario for a Patient – Physician interaction would be the implementation of a solution that “records” all of the conversation during a visit and automatically creates the Visit note, by understanding the Chief complaint, presenting illness, history of the patient, procedures ordered, medications prescribed, follow-ups or referrals ordered, et al. Purely based on the conversations between the doctor and the patient.
Such a scenario requires the implementation and collaboration between various components of the Artificial Intelligent ecosystem. And that will be the true and useful implementation of AI for the Patient and Physician interaction, enabled by Artificial General Intelligence capabilities.
The change needs to be implemented by not only incorporating the changes to the core algorithms, but it also involves incorporating changes to the UI and UX design changes. AI based solutions will force a change in the way current systems have been designed.
Its important to explain the way the physician thinks while interacting with the patient. It’s been of late seen technology solutions to be hindering the doctor patient visit process. And hence it my endeavor to try to present the case that AI while hyped to be replacing doctors, is not yet ready for the prime time. There are areas of immense potential, radiology image processing for instance but then that’s from a process improvement perspective. And not doctor patient interaction perspective. For years now, technology in healthcare has been trying to take the paperless approach and has tried to “replace” paper while forgetting that there is a more important component of enabling workflow in the Patient Care Continuum. And it’s because of this reason, I argue that whilst it’s great for the technology hype cycle to see AI as the deliverer, we need to remind ourselves once again, that it’s not about going paperless, but ensuring the 15 min that a patient gets of the doctor’s time, are well spent with the conversation being patient focused and the technology receding to the background and generating the relevant care records. In other areas of healthcare too it is about process improvement. And add to that the fact that in most implementations in healthcare, clinical documentation is either cumbersome or non existent, the hype cycle of AI needs to consider these issues. From my understanding since the underlying data is fragmented, not standardized and not interoperable in majority of the instances; I took a shorter term view of the AI implementation in the systems in this article. Current Status of Artificial Intelligence in Healthcare
There has been data explosion in Healthcare not only from the perspective of the patient care continuum, but also from the point of view of the resource management and scheduling, inventory and purchase management, insurance, financial management, etc.
While most of the current focus has been on building AI-based solutions that are in the patient care continuum, there are definitely many more areas within a healthcare organization that will benefit from the implementation of intelligent systems.
Just the other day, I attended a conference around AI and the panelists were mentioning the following uses of AI
learning for students based on concepts in school
AI based treatments plans for cancer patients
intelligent assistants, chatbots
Teaching computers to see; etc.
And while they all highlighted areas of advancement in AI tech, they are yet to reach the ability to currently create a system that converts a doctor patient conversation to actionable events that can spawn workflows that needs to be instantiated based on the ever changing patient condition. In the near-term, I see there will be specialized implementations of AI that will enable the brute power of technology to present the best case scenario for a particular patient condition, but an AI Physician is still a work in progress. This has been shown to be a success with the advent of cancer care solutions using IBM Watson.
The AI systems are being implemented in various scenarios in healthcare and you could consider them to being “trained” and being presented with a great amount of data and studies. As more data is presented to these AI systems, their level of accuracy will only improve and provide benefits in-terms of scale and reach thereby reducing the time to diagnosis and time to treatment for patients having affordability and accessibility issues in healthcare.
Artificial Intelligence has already started making its way into healthcare, with 90+AI startups getting funding to deliver solutions like;
helping the oncologist define the besttreatment plan specific to each patient
a virtual nursing assistants, to follow-up with patients post discharge
drug discovery platforms, for new therapies
Medical Imaging and diagnostics
The use of AI in diagnosing diseases, patient education and reducing hospital costs
AI in healthcare also has a potential to be leveraged to be implemented in the following aspects of Healthcare Industry:
Billing and Insurance Workflow, Insurance reconciliations and provider workflows can be enhanced by enabling total automation of the processes by enabling handling of the insurance claims by AI based Insurance agents. The exceptions and outliers can be escalated for manual interventions and closures.
Improving customer experience in healthcare by providing a 360 degree engagement, the SMAC based solutions will use the power of integrating the data streams from multiple sources to help deliver a better service to the patients.
Inventory and Supply chain processes can benefit from AI driven optimization by incorporating e-commerce driven innovations that allow for a democratization of product to vendor mix by searching and delivering the best cost options to the procurement department. Thereby bringing the costs down. Logistics improvements delivered in other industries need to come to healthcare to allow for the reduction in the cost of procurement of drugs, devices and durables. AI will help organizations in identifying variable costs and help them understand how to handle scenarios that will present themselves in an ongoing basis.
AI enabled resource management and scheduling will allow for identifying areas that need to be staffed with more resources and when additional resources need to be hired to meet with the increasing demands or provide elastic resource management based on ever changing operational demands. Booking appointments with doctors, will become a job taken up by Bots or AI assistants, enabling the nursing and administrative staff to focus more on delivering care and enhanced service experience for the patients.
AI-based people management systems will help hospitals in recruitment, retention and performance management of their employees. By presenting an analytics driven approach to people management, systems will be able to help employees to be trained to take up newer roles and responsibilities.
So by when will AI really take over Doctors?
It’s clear from the image above, that estimates of how much processing power is needed to emulate a human brain at various levels (from Ray Kurzweil, andAnders Sandberg andNick Bostrom), “along with the fastest supercomputer fromTOP500 mapped by year. Note the logarithmic scale and exponential trendline, which assumes the computational capacity doubles every 1.1 years” . Kurzweil believes that mind uploading will be possible at neural simulation, while the Sandberg, Bostrom report is less certain about whereconsciousness arises
Based on the above point of view, an interesting question to ask today:
If a Doctor goes through 7+ years of training to become a specialist, how many days will it take for an AI based Physician?
The answer perhaps lies in the following statements
Chief scientist and AI guru Andrew Ng of Chinese search giant Baidu Inc. once put it, “worrying about takeover by some kind of intelligent, autonomous, evil AI is about as rational as worrying about overpopulation on Mars.” , .
What is it that makes us human? It’s not something that you can program. You can’t put it into a chip. It’s’ the strength of the human heart. The difference between us and machines.
September 19, 2016 March 8, 2020 / #DIGITALHEALTH / 10 minutes of reading
It’s mid-2016, and here is a look at the current status of 8 Future Technologies that might be having a significant impact on Healthcare
Most if not all these technologies will make an impact on Healthcare, and hence it is important to understand the various scenarios and the stories detailing how the experts from across the world are incorporating these technologies in healthcare
1 Internet of Things
By 2020, there are expected to be 50B IoT devices with a total economic impact of $3.9Trillion – $11.0Trillion across all the industries, out of which $1.6 trillion impact in the “Human” segment.
Experts have identified the various areas in Healthcare, where IoT-based solutions can be implemented in healthcare.
IoT refers to any physical object embedded with technology capable of exchanging data and is pegged to create a more efficient healthcare system in terms of time, energy and cost.
Dr. Vikram in his article on how IoT can transform healthcare opined the benefits of remote patient monitoring in emergency cases
Dr. Pankaj Gupta, noted in his article for IoT-based solutions to be aggregators of healthcare data from primary, secondary and supporting care market will begin to be aggregated. It will be in the interest of Insurance, Pharma and Govt to support IoT driven Healthcare Market Aggregation
IoT platforms need to be created to ensure the utilization of data being generated by the IoT devices deployed in healthcare. Absence of platforms to aggregate IoT device data will result in loss of meaningful and contextual insights being drawn for the patients’ conditions. Here is an Infographic, by Team HCITExperts, IoT in Healthcare, Types of Opportunities
2 Augmented Reality
Pokemon Go happened and augmented reality has triggered the imaginations of the innovators to work on bringing the technology to Healthcare
By 2020, an IDC report states AR – VR revenue will hit $162Billion by offering major applications for healthcare and product design.
In a recently concluded Intel developer conference, Microsoft’s Windows chief Terry Myerson announced a partnership with the chip maker that will make all future Windows 10 PCs able to support mixed reality applications.
While the cost of using VR in healthcare is still something that needs to be dealt with, partnerships like the one with Intel and Microsoft only bodes well for bringing the technology mainstream and be cost effective.
For instance, “By combining the blockchain with the peer-to-peer business model, this creates the potential for a near-autonomous self-regulated insurance business model for managing policy and claims. No single entity would control the network. Policyholders could “equally” control the network on a pro-rata basis” – Cyrus Maaghul in Why out of hospital Blockchains matter
Merck has already announced its exploring the use of Blockchain technology for clinical trials. For instance, if a patient is enrolled for multiple clinical trials, a single blood test common to all the clinical trials needs to be done only once and can be shared across the clinical trial studies the patient has enrolled for.
5 Artificial Intelligence Artificial Intelligence has been a topic of research all these years, but with the advent of the Data Age, Artificial Intelligence is fast moving mainstream and presents a viable business opportunity.
6 3D Printing 3D Printing in Healthcare is making fast inroads in many disruptive ways. The projected market size for 3D Printing in Healthcare as suggested in the IDC report:
“Global revenues for the 3D printing market are expected to reach $US35.4 Billion by 2020, more than double the %US15.9 Billion in revenues forecast for 2016.
This represents a compound annual growth rate (CAGR) of 24.1 percent over the 2015-2020 forecast period, IDC research reports that while 3D printers and materials will represent nearly half the total worldwide revenues throughout the forecast, software and related services will also experience significant growth”
Gartner expanded the number of profiles from 16 in 2014, to 37 technology and service profiles in their latest Hype Cycle for 3D Printing
3D Printing in Healthcare is being used in the following ways:
3D Printing and Surgery. All surgical and interventional procedures with complex pathology, extensive resection and/or extensive reconstructions could benefit from this technology: Orthopedics, Cardiovascular, Otorhinolaryngology, Abdominal, Oncology and Neurosurgery.
A bespoke 3D Printed model of the patient’s forearm changed the standard course of a 4 hour surgery to a 30 min less evasive soft tissue procedure
Researchers are also exploring the use of 3D Printing which could come mainstream in the future such as Printing prescription drugs at home, Synthetic skin, 3D Printing and replacing body parts.
Last year in a conference a researcher proposed the use of Drones for delivering healthcare in much the same way Katniss receives medicine in the Hunger Games movie or for that matter in the movie Bourne Legacy, UAVs are shown to retrieve the blood samples of Jeremy Renner.
The worldwide market for drones is $6.8 billion anticipated to reach $36.9 billion by 2022
Similarly, there is an active interest in the use of drones to be monitoring traffic, to delivering pizza and products ordered online. In context of Healthcare, UAVs are being field tested for transporting samples and blood supplies, medical drone manufacturer Vayu is using UAVs to deliver cutting edge medical technology in Madagascar. In Rwanda, estimated 325 pregnant women per 100,000 die each year, often from postpartum hemorrhage. Many of these deaths are preventable if they receive transfusion via drone delivery in a timely manner. In India, Fortis hospital plans on using drones during Heart Transplants, to cut the travel time and save lives. An estimated 500, 000 are in need for organ transplants in a year in India. Drones & UAVs are also being tested for delivering emergency medical supplies during accidents and natural disasters.
Robotics in healthcare has been used for sometime now, for instance the Da Vinci surgery system is being used for a myriad of surgeries. Just the other day i came across an article on robots being used for some of the tasks at the reception of the hospital.
“Cloud robotics can be viewed as a convergence of information, learned processes, and intelligent motion or activities with the help of the cloud,” the report explains. “It allows to move the locus of ‘intelligence’ from onboard to a remote service.” – Frost and Sullivan report on Cloud Robotics.
Naturally, I tried thinking of usecases to apply the technology in a Healthcare setting.
About IFTTT IFTTT works with a series of simple recipes using channels.
IFTTT stands for IF this then that
Channels are “connected” apps, like Gmail, Google Calendar, Google Contacts, Twitter and many others supported by IFTTT. You can download IFTTT for android or iOS and start connecting channels to your account. Recipes IFTTT allows you cook up your own recipes. Recipes are composed of this and that. Once you have connected the apps to your IFTTT account, you can start creating recipes.
“this”in the recipe stands for a Trigger Condition or criteria, much like the IF condition you would create in an excel sheet, or in code.
“that”is the action that would be performed when the Trigger condition is met. Based on this condition being TRUE, IFTTT will execute that Trigger Action.
Lets take an example now, assume you are attending a conference and you would like to keep a list of tweets that you liked, and you want to retweet these out later or incorporate these in a blog. Given this scenario, you could do the following steps in IFTTT
Download the App on your phone and create an account
In the IFTTT app enable the Twitter & Google Drive “channels” by connecting to your Twitter and Google Drive credentials
Once you have connected the channels, lets head over to Create a recipe
Click Create recipe and it will ask you for a Trigger Channel, select Twitter
Next, select the Trigger Conditions from the list of possible options provided by IFTTT based on the channel selected
For our usecase we will select “New Liked Tweet by you” as the Trigger Condition
Next we want IFTTT to save the “Liked” tweet in an excel file, for that we will select the trigger Action channel as Google Drive
And we will select the Trigger Action as “Add row to spreadsheet”
IFTTT will keep adding all the tweets you liked to the spreadsheet that you have selected
IFTTT you consider Healthcare Use cases OK, so we now have some understanding and agreement in terms how we are able to very simply, and with no coding, able to create a logic statement and get some work done. In fact you have just “Integrated” two apps and got them to “interoperate”
Lets now assume, IFTTT you could use in Healthcare use cases, What would you do?
What IFTTT offers is a set of features that allows for the end-user to create some of the rules based on their day-to-day circumstances. Lets say a nurse wanted the EHR system to Alert a doctor based on a certain specific parameter, but incorporating that logic would require a “code-change” to be done by the EHR vendor. The process is long-drawn to bring in such changes.
Instead IFTTT the EHR system can incorporate the ability for the nurse to create her own recipe by providing Channels corresponding to various modules in the EHR system, and also provide the end users Trigger Actions and Trigger Conditions (pre-defined by the EHR vendor).
Lets consider some of the usecases that can be enabled for an IFTTT type functionality in Healthcare
appointment reminders for doctors based on urgency of care
reminders to the nurse to change patient medication dosage based on doctors suggestion of lab results
pharmacy requisitions based on quantity on hand value defined
checking and validating medical actions for medical errors
patient discharge process alerts to all departments
IFTTT app allows for the end user to create her own “recipes” and “share” these within the community. And considering every patient’s treatment circumstances are different, clinical teams can setup trigger and action criteria that are active for a particular patient and can be continuously changed based on patient condition. Additionally, it also provides the end-user the ability to make enhancements to the system’s in-built logic by enabling customisation at the user end and instantaneously.
Once the patient gets discharged the clinical staff can have the ability to save all the tasks related to similar disease “patients like” scenario, to be templated for future IFTTT you could Connect Healthcare Devices Thinking a bit ahead to the future, one could control certain medical devices based on trigger based activities. So imagine, the nurse comes along with the doctor for the ward rounds and she is able to adjust the IV flow based on a doctor’s recommendations IFTTT patients’ could Patients too can be allowed to use IFTTT-like functionality by allowing them to create a folder in her google drive that contains all her electronic records emailed to her or her doctor
Patients can also setup reminders for their appointments since their hospital app enables the IFTTT-like functionality.
Patients can be sent alert notifications on their wearables or phones, about daily Medication reminders using IoT-based devices that dispense their medications
The power of IFTTT is in the simplicity and custom trigger and action criteria it provides it’s users
While writing the above article I recalled the time I was working in a Healthcare IT Product development company in Bangalore and we were looking to incorporate an Alerts & rules engine into our HIMS product. While defining the requirements for the solution, we had discussions with our end users in terms of how they would like the notifications from the system to be delivered. They all reported “Alert Fatigue” to be a factor in terms of how they went about using the system. They wanted to be able to control what alerts they saw and how they would like to view these alerts. An IFTTT-esque functionality incorporated within EHR systems will go long way in helping the end-users “customise” the solution based on their current requirements. They would be able to create focussed alerts based on their daily work.
Afterall, the workflows in the hospital undergo a constant change and an EHR should be able to allow the end-users to incorporate customised workflow and rules
“Taken together, the Social Technographic groups make up the ecosystem that forms the groundswell. By examing how they are represented in any subgroup, strategists can determine which sorts of strategies make sense to reach their customers.” – Forrester
As part of a successful social media campaign, its important to know the audience with whom we are sharing the content and creating the content for.
I came across this insightful categorization from Forrester, that provides a categorisation of your Social Media users, using the Social Technographics ladder on the basis of their level of activity on your Social Media Channels
To enable an engaging social media strategy, it will be important to guide your followers across the various steps in the ladders, leading them from being Inactives to being Creators of thought leadership content.
By examining each sub-group, social media strategists can determine which sorts of strategies make sense to reach their target customers. Companies that can understand the typography of their end customers can therefore better target their audience with topics and articles of relevance.
Based on the Forrester Social Technographic ladder of engagement, the people participating and engaging with your content has been categorized by Forrester with the percentage for each type of person.
In India we have 204.1 million smartphone users in 2016 [ http://www.statista.com/statistics/467163/forecast-of-smartphone-users-in-india/ ], it’s only natural to find startups using the mobile as the way to acquire customers by providing mobile Health based products and services. While it is a great way to provide accessibility and affordability of healthcare services via mobile health solutions, it is also important to understand the need to ensure interoperability of the healthcare data being captured in these apps.
Today we have apps for Diabetes Management, Appointments Scheduling, Continuous Monitoring, Remote monitoring, Activity monitoring linked with wearables, women and child health, cardiology, telemedicine, secure messaging apps, etc. The list in the past couple of years has really grown exponentially. And that is great, since the mobile phone has become the centerpiece device for most people. One aspect seems to be missing in the Go-to-Market rush, >> INTEROPERABILITY !! It reminds me of the scenario in healthcare regarding medical devices, which traditionally were never developed for the purpose of sharing data with other systems or outside the location they were placed. It just sufficed that they were connected to the patients and displayed the readings the doctor viewed during her rounds. And I find the same happening with the DigitalHealth Apps.
I have been following some of the DigitalHealth Startups that have developed apps that cater to one specialty or another, and I have come across most of these mHealth apps to be trying to build in the feature-set, i.e., to be a patient’s one stop shop for healthcare related data. In doing this they are duplicating the patient health record and there is a speciality-specific personal health record in each mHealth App (just like the medical device).
Since, each of the mHealth apps’ provides a feature for the patient to upload and store their records, soon we will have more “silos of information” than ever before. Multiply that with the number of apps a single user might have on her phone for capturing one or the other healthcare related parameter, the problem compounds.
The problem of solving the interoperability of patient information will continue to be an area of concern.
Its therefore very important for the startups developing mHealth apps, to start the app development process by incorporating the Interoperability Standards in healthcare. I think this should be the first step in the app development process and in fact patients and the healthcare VCs, investors should demand the app to have the ability to generate interoperable medical records out-of-the-box. The question that one should ask before downloading and using an app should be, “Will I be able to share my medical data between apps, in a Standard and interoperable form?”
Quality & Interoperability
Just as there is no compromise on quality, there should be no compromise on interoperability Take for instance the medical devices, no one insisted on interoperability, or the cost of enabling interoperability was perhaps higher than the cost of the machine, that no one went for it. It was perhaps thought, its OK, anyways the doctor goes on her rounds she will see the information
Similarly, today if we take a ‘share-it via app way’ out to interoperability, we will not have demanded for the “right way” of doing things, we would simply have been taking the same approach as before.
Interoperability should be a plug’n’play option and not a separate service that the vendor chooses to provide, if paid for. It should not be a “Optional”, or paid add-on.
Last i checked there were 100,000+ “medical apps” on the various app stores. How many of these are interoperable? If earlier we had to contend with medical devices that were not plug’n’play interoperable, today we have siloed data being created by mHealth apps.
Solutions to the Problem
The EHRs should have the ability to “add” apps data to the patient EHR allowing for incorporating the mHealth App Data into the patient’s longitudinal record.
The app developers should consult doctors and capture “contextual” healthcare data of the patient. The app should have the ability to share this data via the HL7 certified, interoperable document.
Additionally, when a mobile user deletes a mHealth app from her device, any data stored for the patient should automatically be sent to the patient’s registered email as a HL7 enabled document. Providing a summary and detailed medical record information of the patient. These should be downloadable into any EHR or another app.
And there you go, its fairly simple and we look forward to you sharing your experiences with our community of readers. We appreciate you considering sharing your knowledge via The HCITExpert Blog
July 14, 2016 March 8, 2020 / AI/ML/DL / 5 minutes of reading
One of the areas where AI can be implemented in the Hospital with high volume of transactions, is the Appointments Scheduling of Patients. On any given day, there are a finite number of slots available for a doctor, e.g. 10 min or 30 min slots, depending on whether its a first visit or a follow up visit. In most hospitals, Routine patients are scheduled in advance and some patients are scheduled based on an urgency, to the physician schedule. [Denton et al – 8] A typical workflow for booking an appointment can go like this:
1. Patient calls (or visits) the hospital, and speaks to the person at the reception, at a specific department 2. The person looks up the available time slots, that a doctor is free and available in the clinic 3. Consults with the Patient on the best time possible for her appointment and then schedules the appointment
Now this three step process can either happen on a call, at the hospital reception or via a website provided by the hospital. But in real life, the appointment booking process for a patient might not be so straight forward. Here are some of the different scenarios that might occur:
1. Doctor is not available, asks her medical assistant to cancel all her appointments. Existing appointments need to be shifted to other doctors or rescheduled based on patient priority. 2. Patient calls at the last moment and asks for her appointments to be re-scheduled or cancelled 3. Patient does not show up for the appointment, and asks for a new appointment 4. During a clinic day, multiple new and urgent cases need to be seen by the physician, which delay the subsequent appointments 5. Scheduling of renal therapy patients or cancer therapy patients also needs supervised scheduling that is closely related to the patients’ care protocols and care plans 6. Scheduling based on urgency and emergency situations also changes the “scheduled” visits of a doctor Considering these challenges in the daily working environment of a hospital, an AI-based scheduling solution can help the hospitals in providing an optimal use of resources. For instance a research from Indiana University  found using Artificial Intelligence in patient care can be cost effective and improve patient outcomes.
Consider for instance the following statistics of a Government Hospital in Rajasthan, India :
Nearly 1.27 crore patients were registered at OPD in medical centres affiliated to medical colleges and
9.27 crore in state medical institutions in the year 2014-2015
in the year 2015 around 35,000 patients per day were registered at the OPD at medical college-affiliated centres
The High number of patients (the 35,000 per day patients registered at the OPD at medical college-affiliated centres) and the resource scheduling scenarios, presents an apt usecase to implement an AI based Appointment Scheduling system.
While it not only present a challenge to manage the care of all the visiting patients, it also allows for the administration to ask; How many doctors, nurses and medical assistants should be scheduled to manage the care planning & scheduling requirements of each of these patients, visiting one or many departments of the hospital.
In addition to Patient Scheduling, AI based algorithms can be deployed in such settings  to help the hospital administration in optimising the time of their most important resources: Physicians, nurses and medical assistants.
Handbook of Healthcare System Scheduling – Reference 
Additional Scenarios where the AI based resource scheduling systems in Healthcare  can be deployed are:
Operating Theatre + Operating Team Scheduling
Renal Dialysis Centers
Radiology Diagnostic Facilities
Medication Reminders Apps
Acuity-based nurse assignment and patient scheduling in oncology clinics
Care Plans based activity & event scheduling
Health Checkups Packages
Once an AI based solution has been implemented, the scheduling, rescheduling, planning, allocating and many other scenarios are handled by an AI based Scheduling Agent allowing for hospital administrators and physician scheduling managers to focus on treating the patients.
And Scheduling a patient appointment becomes an autonomous process: A. Jane emails Dr. John to schedule an appointment for a followup visit. Jane receives a confirmation email regarding the appointment with Dr. John from his assistant Amy. A reminder is set in her calendar.
B. Jane, on the day of the appointment is unable to make it to the hospital and sends an email requesting for rescheduling her appointment to the next wednesday. Amy reviews, Dr. Johns schedule and responds to Jane with a confirmation of her re-scheduled appointment.
In the above example Amy is an AI assistant to the Physician, nurse or medical health professional. Or in fact it could be an assistant (Siri, cortana, or amy from x.ai etc) to the Patient.
What do you think, do share your thoughts?
Sundar Pichai, CEO, Google says we are moving from a mobile first world to an AI first world, quite fast.
TRIVENI, a remote patient monitoring solution that is a confluence of three aspects of patient information:
Data | Medical Devices | Connectivity
Just the other day we heard the SpaceX rocket zoom off to the space to deliver a satellite to the geospatial orbit, Rosberg won the 2016 russian grand prix & Mars rover continuously transmitted the images and vital parameters from millions of miles away in the space
The above three scenarios present the ability to stream data in realtime to a base station providing the ability to remotely monitor the performance of a space-craft, a formula 1 car and a remote autonomous vehicle.
Similarly consider the following use cases in relation to a patient in a Healthcare setting:
patient information in a Hospital
patient in an ambulance or
patient under homecare
presents use cases that require remote monitoring of patient information.
The existing technological paradigms such as IoT, data streaming analytics, connectivity & interoperability allow for a framework to allow for remote patient monitoring in each of the three Healthcare use cases
I would like to propose TRIVENI, a remote patient monitoring solution that is a confluence of three aspects of patient information
Triveni proposes to implement a plug-n-play framework that will allow for easy connectivity between healthcare information sources. The etymology of the word TRIVENI in Sanskrit means “where three rivers meet”. Similarly, the three aspects of Patient Information need to be integrated to meet the requirements of a remote patient monitoring solution
Focus areas of TRIVENI
Initially to showcase the Proof-Of-Concept for the solution, the above three focus areas will be considered to present as the use cases. Each of the three focus areas present the ability to test the confluence of three aspects of Patient Information defined above
Need for TRIVENI
The Tower of Babel (Pieter Bruegel the Elder, c. 1563), a metaphor for the challenges existing in medical device semantic interoperability today
Piecemeal integration creating information silos; leading to difficulty in sharing patient information
Silos unable to deliver real-time patient data reliably; leading to lack of data synchronization to ensure latest time-aligned data
Vendor Dependent solutions; leading to internal battlegrounds
Lack of semantic interoperability between systems; leading to a tower of babel situation in medical device semantic interoperability
Captive investments by healthcare facilities in existing medical devices leading to a long time before the medical devices can be replaced with newer systems with easier connectivity features
The Remote Patient Monitoring Process Flow
Typical Remote Patient Monitoring process (adapted from Center for Technology and Aging)
The Center for Technology and Aging indicates a 5 – Step process for Remote Patient Monitoring. The 5 steps are essential to deliver a continuous flow of patient related information to the remote base station monitoring a patient(s) in any of the use cases or the focus areas presented earlier
The Remote Patient Monitoring Process Flow Mapped with TRIVENI Framework Components
It becomes imperative for the solution to incorporate these founding principles of a remote monitoring process into any framework/ product of such a nature. The process steps get implemented in the TRIVENI framework, allowing for the continuous monitoring of patient information from the various connected systems.
The processes allow for a modular approach to the Product Definition of the TRIVENI framework, with the ability for each component of the platform to evolve as dictated by its internal technology and thus enables each component to incorporate newer technology paradigms as and when they present themselves
The TRIVENI Components are
TRIVENI Connect ®
A programmable Connector that allows the transmission of data from the connected medical device
Supports BLE, Wireless technologies
TRIVENI Hub ®
A Medical Device Data Aggregator that has the ability to receive data from the TRIVENI Connect and transmit the patient vital data streams to the TRIVENI Exchange
Supports 2G, 3G, Wifi, 4G networks
TRIVENI Exchange ®
TRIVENI Exchange is a secure, reliable patient vital data store that can seamlessly transmit data received from TRIVENI Hub to TRIVENI Apps
SSL Security, supports interoperability, Data Delivery to TRIVENI Apps or Connected EHR Systems (via HL7)
TRIVENI Apps ®
TRIVENI Apps have the ability to securely receive identified patient’s Medical Data from the TRIVENI Exchange
TRIVENI Apps are delivered on Android, iOS, Web-based platforms
The TRIVENI Connect is a device that acts as a converter that allows any medical device to connect to the TRIVENI system. The Connect device for instance will be connected to a Patient Monitor via the RJ45, RS232-to-USB converter. Once connected, the TRIVENI Connect will automatically download the relevant driver from the TRIVENI HUB, that allows for the Patient Data Stream from the Monitor to be streamed. Additional features of the TRIVENI Connect are:
Has the ability to Fetch Data from the connected Device
No. of Manufacturers
No. of Devices
One TRIVENI Connect per Device
Convert Data from Device by encoding Device Data with Following information
Device ID, Manufacturer ID
Ambulance ID/ Hospital ID
The TRIVENI Device Should be configurable with the above data. Additional capabilities of the TRIVENI Connect are:
Allow for Access Point Configuration
Via PC/ Via mobile device
Configure the TRIVENI Exchange IP
Send Data to TRIVENI Exchange
Over the Air
Linux Based, WiFi USB Dongle with a RS232 – USB Converter
The TRIVENI HUB is a device that acts as a data aggregator device at the remote location. All the Patient Data streams from various connect devices are routed to the HUB. The HUB can be configured via a mobile app. Using the mobile app the users will be able to configure various aspects of the TRIVENI HUB like the internet connectivity, TRIVENI Connect linked to the HUB, Username and password configuration of the HUB & Connect devices, Store and forward configuration to name a few.
The HUB device has the following features:
Is a WiFi Router + Cellular Modem
Has the functionality to work as a patient data stream aggregator with a store and forward feature
Has multiple SIM slots or Multiple USB ports for Broadband Connectivity
Will Work as a WiFi Router Access Point for the TRIVENI Connect
Will work as a Cellular Modem for Transmitting the data to the TRIVENI Exchange
Will work as a WiFi Router Access Point for the TRIVENI Connect
Will connect with the Hospital LAN to connect to the Internet
Has the ability to store and forward patient data
Data streams will be prioritized based on the QoS of network connection
Ability to send data packets over multiple networks to reduce packet loss
Data aggregation from multiple types of sources other than TRIVENI Connects
Maintains the security of the data-on-move over wire and when data-stationary when within the TRIVENI Hub by enabling security protocols (SSL) and encryption of data
The TRIVENI EXCHANGE is a Medical Data+Media Server that can be configured as a Virtual / Physical Server. The EXCHANGE has RTP/ RTSP/ RTCP Capabilities for Live Streaming of the Patient Data Streams from each of the HUBs connected to the EXCHANGE.
The features of the TRIVENI Exchange are
Site Configuration: Allows the Creation of an Identity for a Client (Ambulance Services/ Hospital Provider)
Identification/ Allocation of IP Address (Destination IP for Medical Data Streams) for the TRIVENI Exchange
Allows the configuration of the TRIVENI Connect’s to stream data to the Identified IP Address
Has the ability to update the TRIVENI Connect / TRIVENI Exchange Firmware OTA
Has the ability to receive Voice and Data Streams
Has the ability to enable Live Streaming of Data, Video and Voice to TRIVENI Apps
Can be Configured for each client in a multi-tenant server configuration.
Has a Medical Data Controller module to identify the source and destination of the medical data streams
Ability to allow store and forward data on demand
Allows data push or pull configurations for the TRIVENI Components
Maintains the “device” drivers for various types of patient sources
The TRIVENI APP is an android or iOS based app. There are two APPs that come with the TRIVENI framework. One APP is for configuring the remote configuration for the connect and the hub devices at the location for the client
Another APP is for configuring the Exchange and for viewing the data being streamed from the various devices connected to the patients in the remote locations
Enables Care Anywhere
Web-based, Android or iOS based apps
Allows for a two way communication between devices
Free to download app on the App Store
Allows the user to authenticate her credentials
Allows two way communication between the Apps between two users
Ensures the reliability of the data
Security enabled to ensure patient data authenticity
TRIVENI Apps will be developed as web-based and subsequently as native apps
TRIVENI apps will incorporate the usability guidelines for the healthcare based apps
TRIVENI apps can be configured for data push or pull options
TRIVENI apps enabled with security and data encryption profiles
There are two types of TRIVENI Apps: TRIVENI HUB & TRIVENI EXCHANGE apps to configure remote and base components
Interoperability Considerations for Medical Peripherals
If one was to trace the progression of delivery of printer drivers, it presents an interesting case study regarding how hardware-software interoperability has progressed over the years in the IT industry. And studying these aspects help us to, hopefully in the future define the way Interoperability in the Healthcare Industry should be handled.
Printers have been essential hardware devices that are connected to the software platform (OS) via various types of connectivity platforms, and service the productivity needs of the organisation.
Lets consider the various Printer installation processes we have seen in the past
CD with OS compatible drivers: Printers started out as peripherals that required a specific driver to be installed on the system (PC/ Laptop/ Server) that was going to be connected to the printer, via a printer cable
OS with Pre-installed Printer Drivers: Then we progressed to the OS itself having a list of compatible drivers that enabled the OS to auto-detect the type of printer or peripheral that was connected to the system. This also allowed for network printers to be installed in the network and allowed for the print server to have all the relevant drivers installed just on that server. PCs in the network wanting to use the printer resource, just needed to send the document to the print server.
Cloud Printers: Now a days, it is possible to connect the printer to the cloud via HP-ePrint or google printer services and access the printer from anywhere in the world.
Device & Software Interoperability
Taking learning from the way peripherals interoperability has been handled in the IT industry, Healthcare Interoperability should be a de-facto feature that should be present in most systems
Interoperability needs to be made as a plug-n-play feature in the Healthcare Services and Solutions. What are the various “Peripherals” that need to be connected in the Healthcare Industry?
Healthcare Information Management Systems
Additional Thoughts on Interoperability
Now the idea for defining the progression of a hardware connectivity w.r.t. The Printer device, is to try and define how medical device connectivity & interoperability should be enabled in the future
Currently, Interoperability is a “Service” that is offered as part of the implementation process by the system integrator or the vendor of the healthcare software. The point is, why should the customer bear the cost of “connecting” the hardware and software OR two software’s within an organisation
In Healthcare we are working towards providing such seamless and plug-n-play connectivity between EMRs, medical devices and now a days, additionally the mobile health applications.
Was in a tweetchat sometime ago on the Need for Time Management for Practitioners (physicians, nurses, allied health professionals) in Healthcare, by the HealthXPh communities Weekly Tweetchat, Every Saturday.
During the conversation it was really interesting to hear from the practicing doctors regarding how they have to manage their time and work towards scheduling themselves around their HealthIT systems and their patient care activities.
It was really interesting because, aren’t the Healthcare IT solutions supposed to ease the workload of the users? Arent the solutions supposed to be developed around providing the Time Management activities of the healthcare practitioner?
Which again brings me back to my earlier question, arent the Healthcare IT solutions help the Healthcare Practitioner Manage their time? After all we have taken the paper records and replaced them with the feature rich and innovative healthcare IT solutions.
But then why do we hear the doctors say that they are losing direct face time with the patients?
Why are the nurses unable to find time to keep up with the IT and non-IT related work they are supposed to be doing daily?
In the multiple product development lifecycles that I have been through (and the experience of the reader might be the same or vary) I have found during the requirements phase there are two types of users, the first category are the ones who have perhaps not used a system earlier but would like to implement a healthcare solution. The second category are the ones who have had prior experience working on a solution and would provide their requirements that incorporates the enhancements or the lacunae that the earlier solution had.
I think the EHR systems are in this conundrum right now, wherein they need to fit into these two categories of users and fast. Building products is a capital intensive enterprise and the ‘project management’ practices are always focussed on gathering requirements and completing the project.
But during this ‘Delivery’ process are the requirements of the two categories of users been analysed in a way to deliver solutions that will take into account the needs of the users and come up with a solution paradigm that helps each of these users to ‘Manage’ their time.
Should the solution make a Healthcare Professional work their way around the solution, or should it be the other way.
I think it is this need for the solution to now work around every Healthcare Professional to help them manage their time better that will bring about the version 3.0 of the EHR solutioning.
In the version 3.0 of EHR solutioning multi-disciplinary teams will come together to develop the solutions that work around each users life-at-work and helps them to Manage their tasks in their workplaces.
As indicated in the recently concluded ArabHealth a message went out indicating that “One size does not fit all”
Extending the analogy to an EHR solution: If there is a uniqueness in treating each patient, it is obvious that the activities that a Doctor or a healthcare professional would do would be unique. At this point I do agree, that the process would perhaps stay same for the 80% of the time, but the datapoints to be presented or captured would perhaps be different from patient to patient.
I therefore think that the next generation of EHRs should be able to incorporate these variations as part of workflows that allows the solutions to be adoptive to the end-user requirements across specialities.
Some feature considerations for the next gen EHRs.
Incorporate Task and Workflow oriented frameworks. The workflow in the hospital is not stationary, it evolves as often as a patient’s condition
Incorporate the Healthcare Practitioner’s daily activities in the workflow, help them manage their time a, and not they working around what the system has to offer.
OK, so we converted all the paper forms into electronic formats and now have the ability to analyse them. Its now time to bring in cognitive platforms that present to a doctor generated pages that are relevant to a patient. 80% of the forms are not filled in 80% of the patient visits. Then why should all this data be ‘presented’ to be filled for each patient?
At the design time consider the time and motion analysis for each category of user, develop solutions to incorporate their activities.
EHRs should adopt a multi-form factor delivery approach. Now its clear, the desktops and PCs are here to stay. Go back to the drawing board and develop ‘for-each’ form-factor. A one size fits all or a responsive approach perhaps will not work in the case of the healthcare multi-form factor solutions approach. After all you cannot expect a 5 page form to be answered on a mobile device, just because we can make it responsive.
Make EHRs with the analytics first approach. Since the first systems, its always been the need to capture the infomation on systems so that we can analyse the data later. Today there should be the need to revise the data structures to meet the demands of analytic and cognitive computing.
Am sure there are more that can be collated, but will keep that for the Zen Clinicals series that I have been working on to define what a next generation EHR should have as core feature set and that is different from what it is today.
Founder HCITExpert.com, Digital Health Entrepreneur.
─ The Ministry of Health and Family Affairs in India recently published a Concept note on the National eHealth Authority and called for comments and feedback on the formation of NEHA, India. All comments and suggestions can be emailed to firstname.lastname@example.org on or before 20th April 2016.
NEHA is envisioned to be, to quote from the concept note, “a promotional, regulatory and standards setting organisation to guide and support India’s journey in eHealth and consequent realisation of benefits of ICT intervention in Health Sector in an orderly way”
While considering the implementation of DigitalHealth Solutions in India, its is very important to understand the “Workflow” of the patients and understand the Information requirements within the Identified workflows.
Since Healthcare has always been considered to be the “last bastion” to be Digitised for many years, the approach to Digitize Healthcare Workflows has always taken the “Traditional” approach, i.e., Go to the hospital, Study their workflows, gather all the current paper being generated and Digitize IT. And hence we came up with the “Paperless Hospital” approach.
But the flaw in the paperless approach, in my opinion is the approach that caused the creation of Information silos. We Digitised the Paper, and not the workflow.
Take for instance the workflow of a Doctor in a hospital. She is inundated with information which her training is able to Streamline as a workflow, but give the doctor a system, she is faced with a daunting task of having to “feed” the system with the information, because the system is not designed to help her streamline her workflow in her specialty.
The problem in the usecase of the doctor is that we have Digitised the feeding the information part, but not the workflow of the doctor-patient relationship and by that extention the care provider-doctor-patient relationships.
There have been many recorded and unrecorded cases of HIT implementations wherein the Clinical workflows are the last to be IT-enabled and at times not even enabled, due to this very reason.
World over the learnings of other National eHealth Implementations are definitely pointing towards the absence of patient and healthcare professional workflows being digitised, leading to dissatisfaction with the current Digital Health solutions.
NEHA should consider “Workflow Digitisation” in a Healthcare Facility as the driving force instead of Data Generation or Data Capture. It is important to identify and define the workflows across the healthcare organisation considering each care providers role and responsibilities. And to endeavour incorporating these workflows into the HIMS of the future.
Major and Minor workflows need to be identified and incorporated within the ambit of the pragmatic workflow optimisation, to ensure the relationship model between the care providers and the patients are well documented.
The Interoperability Red-herring
Most often than not, the main premise of setting up a National Level eHealth Authority in most countries has been to provide for “Interoperability” of information between the “Silos of Information” within and outside of the hospital.
As the report points out, Lack of Interoperability leads to “Ineffective Results”.
In the discussion about Interoperability, I would like to for the need of discussion define “Exchange of Information” to be subcategorised as two specific areas:
–INTRA-operability: between Digital Health systems within the Hospital. Most vendors are contracted with the hospital and hence there is more control for the hospital management in this particular aspect, from a solutioning point of view.
–INTER-operability:between Digital Health systems within the Hospital and “External” Digital Health systems that could be government bodies, patients, Digital Health Apps, etc.
The above sub-categorisation can help in identifying areas of information flow and help the NEHA define the standards for each of the presenting usecases.
Consider the various Digital Health solutions within a Healthcare Organisation and you will realise the presence of “Standards” that each are specific to the type of Digital Health solution.
a Laboratory equipment exchanges information via the RS232 port or RJ45 port in a ASTM format.
A Radiology imaging platform deals with DICOM standards.
The Patient Monitoring system in the hospital is a fortress of information, “Designed” to “Lock-in” the information that is “Proprietary” to the vendor that has supplied the system.
Just take the above three scenarios, and try and get a quote from a vendor to build you a system that “Integrates” all these three data streams (or information silos) into a patient’s EHR. It will be considerable. I would guesstimate 10-20% of the cost of ownership of a enterprise Digital Health solution.
Now, lets say you have been able to take up the implementation of such an “integrated” system, it took you a good year to stabilise your system with “INTERoperable” solution. And after the year of stability, you need to start sharing all this Information with the new app that has become famous with the patients.
Lets assume, that the new app is built on a standard that is different version (or perhaps proprietary) from the one that you have implemented during the past year. The entire process begins again to now “INTERoperate” with the new app.
I would suggest that the NeHA identify Digital Health information sources and fix the VERSION of messaging formats for each of these Digital Health Information sources for a period of 7 years so that all the sources of Digital Health Information are talking the same language without the need to constantly keep changing the standards of information exchange.
There should be a clear roadmap for version upgrades within the NEHA framework to allow for newer usecases but avoid changing the messaging format altogether year on year.
Streamline and standardise the INTERoperability and INTRAoperability standards for Digital Health Information sources.
As an additional step, it is important to mandate the implementation of common Digital Health Standards in all the Medical Devices that is OPEN and can be easily extracted from existing and new Medical Device implementations.
Ideally, solutions, EHR products, medical devices and any other patient information generation device or software solution should adhere to a fixed set of standards, that allow for easy exchange of information.
Finally, NEHA can provide an Infrastructure to provide “Open and Secure Digital Health Exchange Services/ APIs”. This will definitely remove the cost barrier to interoperability of Digital Health information.
I would suggest the use of “a Pragmatic approach to Interoperability” that helps NeHA identify and enable Interoperability of Digital Health information that provides the context in patient care. Physicians, Specialists and Chronic and palliative care experts should be consulted to define the usecases for patients need of Digital Health information. Questions to consider for Patient Information Inter / Intra Operability :
Does the Doctor really need the “Womb to Tomb” record of a patient?
What percent of patients need a “Womb to Tomb” record?
Is it really possible to have such a record available, if one version of the HIMS is different than the other?
What percent of Patient’s benefit from Digital Health Interoperability?
To remove the boundaries between information silos in a Hospital workflow are the key aspects that should be identified and addressed in a pragmatic interoperability approach for an optimised workflow approach rather than a paperless or less paper approach
Founder HCITExpert.com, Digital Health Entrepreneur.
The post discusses how a Health ID can be linked to Aadhar Number
Unique Identifiers, Health ID & Aadhar Number
A unique identifier from a database technology standpoint, is the ability to create a primary key and link all the data in the database using a primary key (parent record) & foreign key (child records) concept.
Keeping this concept in mind using Aadhar Number as a Health ID offers a very compelling opportunity to uniquely identify a patient across multiple episodes and visits, in a single facility or across multiple facilities (that may be located in same geographical location or multiple geographic locations)
In most Health Information systems, the records of a patient are tied to a Unique Patient Identifier, a Patient ID or a UHID.
Let’s consider what are the various use cases of the Aadhar Number and a Patient ID.
The Aadhar Number has been planned to be used by the government for various welfare and direct benefit transfer schemes. There have been many instances that the Information that has been recorded in the Aadhar ID may or may not have the latest information of the person carrying the Aadhar Card. The purpose for which the Aadhar Card has been created is to identify a person for various government schemes and also has been deemed to be used to be provided at the time of opening of a bank account. Hence there are quite many financial transactions that might be linked to the Aadhar Card.
Patient ID or UHID Number
The Patient ID in various Healthcare information systems, is generally used to uniquely identify a patient so as to deliver various services for the patient at the right place and the right time and to the right person. And also link all the healthcare information about the patient to this unique identifier.
Keeping in mind the need to uniquely identify a patient and to avoid duplicates becomes a very important factor in the Hospital Information Systems.
In a specific system ( and these obviously vary from one HIMS to the other) the Patient ID is utilised to keep track of various types of patient related information or healthcare events. In addition to the Patient ID, there is the Episode ID and the Visit ID information that is used to store specific visit related and diagnosis based information in the Health Information System. In these systems, the Episode ID and the Visit ID are used as the child records of the Patient ID.
Most Health IT systems employ an algorithm to identify patient duplicates based on various data points creating a complex key.
Using Aadhar as a Health ID
In various countries around the world, the use of a single identifier as a universal identifier has never been successful due to the complexity & security concerns of the various use cases.
Take for example the case of the SSN (Social Security Number) in the US. The SSN is recorded for the patients in the Healthcare Information Systems but is never utilised to uniquely identify a patient due to the issues of Security and Identity theft. There are a lot of instances in which the SSN has been stolen and leads to the person suffering from stolen identity.
Healthcare Information systems have been hacking targets and currently the losses estimated in every hacking incident runs into millions of dollars.
Now take the example of Aadhar ID as a Health ID. We might land up having similar issues of the healthcare information system at a hospital/ clinic being hacked into and the Aadhar information being misused by the hackers.
Obviously, the security levels of an IT infrastructure at a hospital or clinic will not be as superior as the competent authorities security and IT infrastructure.
The government agency will be able to ensure the security of the Aadhar number, by providing robust and secure systems, but the same may or may not be expected of the Hospital Information System vendor or the hospital or a clinic that has implemented the solution or for that matter a Health Information Exchange authority.
Use Aadhar to validate the Identity of the Patient, Only
The Aadhar number must be used only and only to validate and authenticate the Identity of the person who has come to the hospital. Aadhar Authority could provide a service that could be called to authenticate a person.
Use Health ID to be the Primary Key, Patient IDs to be the Secondary Key
In the absence of standards as to how the Patient information is to be stored within a Healthcare Information Management System or EHRs, it is more advisable to maintain the Health ID as a Primary Key, the ownership remains with the Health Authority. However, each visit that a patient makes into any healthcare facility, the HIMS/EHR/EMR vendor generates a care summary record (using Patient ID) as a “Secondary Key” information for the patient.
This is akin to how each bank might have different banking information systems, but the PAN number is a unifying information to understand how many bank accounts a tax payer might have (since PAN number is mandatory for every transaction done).
In this bank scenario, the PAN is the Primary Key, and every transaction done against the PAN card is the secondary key.
The authentication of the PAN is done by the competent authority who develops robust systems to safeguard the PAN card information of the PAN Card holder.
Patient ID/ Health ID should be maintained by the Health Authority (e.g., the National Health Portal)
We propose the Health ID should be maintained by the Health Ministry in the government and the various aspects of Health Information should be defined by this authority. Since the Health Information of the patient needs to interoperate between the Hospitals/ clinics (which comes under the Health Ministry) and the Insurance Companies (which is another government department), maintaining a separate Health ID with its own security and interoperability guidelines is an appropriate approach.
The interoperability between the various government departments is more easier than any other third party vendor implementing such a interoperability system. The government therefore becomes an enabler of interoperability between various consumers of the healthcare information (in this case, the insurance companies and the Hospitals)
For instance, the Health ID could have a one-to-one relationship with the Aadhar Number. But the contents of the Health ID related information can be dictated by the Health Ministry or the National Health Portal Authority.
Health ID should be used to maintain a persons’ Health Record across the care continuum.
Health ID can derive the Demographic information from the Aadhar ID and use the Aadhar ID for Identity matching, duplicate check and person authentication services.
There should be a one-to-one relationship between Health ID and Aadhar ID.
Each time a patient makes a visit to a healthcare facility, the Health ID information regarding the patient will be updated. Mechanism to be worked out if the current and latest information gathered from the patient regarding the demograhics should be updated back to the Aadhar Information.
For Healthcare Related information, Healthcare Information Exchange purposes, Health Insurance purposes; the Health ID should be the unique and Primary Key.
The Patient ID or UHID captured in each of the system should be treated as the Secondary key or the child records that will help put together the patient visit related information.
We can now move to a National Level Health Information Exchange to store health data for the Patient’s clinical events across healthcare facilities, against a Health ID