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
Part 3 of 4
Sharing some of the UI screens that I had envisaged for the Zen Clinicals system. The core premise of the system is to be data driven and workflow driven and NOT BE a transactional system wherein a sequential set of activities or tasks are carried out.
Zen Clinicals ensures there are actionable insights that are presented to the right care providers at the right time.
Welcome you to review the first two parts of this blog:
Part 1: https://blog.hcitexpert.com/2015/12/zen-clinicals-1of3.html
Part 2: https://blog.hcitexpert.com/2018/07/zen-clinicals-patient-care-pathways-by-manish-sharma.html
A Clinical Care Pathways Workflow & Activity Orchestration
Clinical Data Repository
Care Pathways Designer
Clayton Christensen coined the phrase disruptive innovation two decades ago as a way of embracing the deconstruction that is necessary when a new technology displaces an old one.
…
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.
AI has the potential to have a broad-based disruptive impact on society, creating a variety of economic benefits. While some of these benefits can be measured, others, such as consumer convenience and time savings, are far more intangible in nature. Our analysis focuses on measuring the GVA impact of AI.
Read the press release here >>
https://newsroom.accenture.com/news/artificial-intelligence-could-add-957-billion-to-indian-economy-according-to-new-research-by-accenture.htm
Read the complete report here >>
https://www.accenture.com/in-en/insight-ai-economic-growth-india
Team HCITExperts
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[21]. 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
You can also review the various articles on Blockchain on the HCITExpert Blog.
[1]: Blockchain Articles by David Houlding:
https://www.linkedin.com/in/davidhoulding/detail/recent-activity/posts/
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From cybersecurity operations into strategic Digital Risk Management
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Team HCITExperts
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%.
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.” [1]
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. [3]
| Top Wearable Devices by Product, Volume, Market Share, and CAGR [1] | |||||
| Product | Shipment Volume 2017 | Market Share 2017 | Shipment Volume 2021* | Market Share 2021* | CAGR (2017-2021)* |
| Watches | 71.4 | 56.9% | 161.0 | 67.0% | 26.5% |
| Wristbands | 47.6 | 37.9% | 52.2 | 21.7% | 1.2% |
| Clothing | 3.3 | 2.6% | 21.6 | 9.0% | 76.1% |
| Earwear | 1.6 | 1.3% | 4.0 | 1.7% | 39.7% |
| Others | 1.6 | 1.3% | 1.4 | 0.6% | -16.0% |
| Total | 125.5 | 100.0% | 240.1 | 100.0% | 18.2% |
| Source: IDC Worldwide Quarterly Wearables Device Tracker, June 21, 2017 | |||||
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| 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 [2]
“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) [2] | |||||
| Vendor | 4Q16 Unit Shipments | 4Q16 Market Share | 4Q15 Unit Shipments | 4Q15 Market Share | Year-Over-Year Growth |
| 1. Fitbit* | 6.5 | 19.2% | 8.4 | 29.0% | -22.7% |
| 2. Xiaomi | 5.2 | 15.2% | 2.6 | 9.1% | 96.2% |
| 3. Apple | 4.6 | 13.6% | 4.1 | 14.1% | 13.0% |
| 4. Garmin | 2.1 | 6.2% | 2.2 | 7.6% | -4.0% |
| 5. Samsung | 1.9 | 5.6% | 1.4 | 4.7% | 37.9% |
| Others | 13.6 | 40.1% | 10.3 | 35.5% | 32.1% |
| Total | 33.9 | 100.0% | 29.0 | 100.0% | 16.9% |
| Source: IDC Worldwide Quarterly Wearable Device Tracker, March 2, 2017 | |||||
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| Image Source: https://www.accenture.com/us-en/insight-accenture-2017-internet-health-things-survey |
The Internet of Health Things (IoHT) is already delivering tangible cost savings, but continuous investment is essential
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.[1] Within the next five years the healthcare sector is projected to be #1 in the top 10 industries for Internet of Things app development.[2]
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
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| Source: Accenture Report |
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| Source: Accenture Report |
The report lists four major takeaways for the payors and providers:
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.
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.
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.”
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.
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| Source: Accenture Report, [2] |
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
Team HCITExperts
July 7, 5PM CET/11AM ET: Join #PhilipsChat and let’s discuss how connected care is transforming healthcare pic.twitter.com/lKNO5RCVjB— Philips Healthcare (@PhilipsHealth) 4 July 2017
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
An always connected channel of communication of care between the patient and provider, from “touch time” to “face time”
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)
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.
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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 BMD, consists of the following aspects that every venture, startup or intraventure can evaluate themselves on.
The the BMD Model’s founding premise is
“You dont need to understand the Technology to ask the basic business questions”
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
The 12 Dimensions of the Bell Mason Diagnostic are:
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| 12 Dimensions of the Bell – Mason Diagnostic (BMD) |
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:
There is a more updated definition of the Startup Stages that can be found here >> http://www.bellmasongroup.com/approach/
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| BELL MASON DIAGNOSTIC – STAGES |
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.
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.
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| [2]: Source: How Bell Mason Diagnostic measures the companies – https://www.finsia.com/docs/default-source/jassa-new/jassa-1996/warning-bells-or-sound-of-success-.pdf?sfvrsn=2 |
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. [2]
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
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| Source: http://www.bellmasongroup.com/approach/ |
Here is an Update, got an interesting update from Mr. Raj Grover, shared by him on the Fundraising for Indian Startups on what aspects should be covered in a startup pitch
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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?
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.” [2]
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.
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.
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)
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 [3] 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) [1]. They define the critical policy and technical components required as
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 the Unintended 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.
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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
Benefits of Implementing an HIE
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 on issues, 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,
https://www.linkedin.com/pulse/india-aims-global-leader-digital-health-rajendra-pratap-gupta
Manish Sharma
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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: [1]
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 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.
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.
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: [4]
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.
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 [9]. 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
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.
Some of the other areas where AI is being implemented in Healthcare. Microsoft, Apple, IBM and other major players are all looking to AI help in curing people. And they are forming a group that creates the standard of ethics for the development of AI.
[15]: Doctor’s 35-hr shift on 8 bananas, a toilet in nearby cafe
http://indianexpress.com/article/india/india-others/doctors-35-hr-shift-on-8-bananas-a-toilet-in-nearby-cafe/
[16]: Gigerenzer’s simple rules by NS Ramnath on Founding Fuel
http://www.foundingfuel.com/article/gigerenzers-simple-rules/
[17]: A.I. VERSUS M.D: What happens when diagnosis is automated? By Siddhartha Mukherjee
http://www.newyorker.com/magazine/2017/04/03/ai-versus-md
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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
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 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
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.
For instance, Live 3D imaging is one of the hottest topics in optics today, transforming medical imaging capabilities and delivering the immersive experience behind augmented and virtual reality.
Tim Cook in a recent interview indicated Augmented Reality to be a bigger market than virtual reality.
With VR technology projections reaching $3.8Billion by 2020, there will be an increase in the use of VR technologies in Healthcare
Virtual reality has an increasing number of implementation opportunities in Healthcare for education, training and patient treatment.
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.
VR tech is currently being used to
4 Blockchain
Interoperability in Healthcare is a big topic for debate and a sore unsolved puzzle. With the US HHS and ONC seeking research on Blockchain for Healthcare, there seems to be growing interest in the technology.
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
Blockchain technology is being researched to be the super secure healthcare data aggregator of EHR data and IoT devices data
Blockchain technology is supposed to benefit healthcare
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.
“By 2025, AI systems could be involved in everything from population health management, to digital avatars capable of answering specific patient queries.” — Harpreet Singh Buttar, analyst at Frost & Sullivan.
In a recently published report, AI adoption by enterprises is imminent. 38% of respondents are already using AI, another 28% will adopt it by 2018.
The AI ecosystem is projected to be worth $5.5Billion by 2020
Artificial Intelligence ecosystem consists of:
Artificial Intelligence has already started making its way into healthcare, with 90+ AI startups getting funding to deliver solutions like;
Some of the other areas where AI is being implemented in Healthcare. Microsoft, Apple, IBM and other major players are all looking to AI help in curing people. And they are forming a group that creates the standard of ethics for the development of AI.
Finally have a look at the AI in healthcare: Category Heatmap
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| Source: CBINSIGHTS |
“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:
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.
The overall world market for robotics in healthcare will reach $3,058m in 2015, and expand further to 2025.
The global robotics industry will expand from $34.1 billion in 2016 to $226.2 billion by 2021, representing a compound annual growth rate (CAGR) of 46%.
Other areas robots are being used in healthcare in addition to the above scenarios are:
#Emerging #trends & #technology @Gartner ~ @CBInsights #VirtualReality #VR #AugmentedReality #blockchain #pinksocks #telemedicine #mHealth❤️ pic.twitter.com/VJGZBOeeWL— Brian Ahier (@ahier) October 28, 2016
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| Forrester’s Top Emerging Technologies To Watch: 2017-2021 http://bit.ly/2dmVRkZ via @GilPress |
And there you go, we look forward to you sharing your experiences and thoughts regarding these Future Technologies and share them with our community of readers.
We appreciate you considering sharing your knowledge via The HCITExpert Blog
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Meet The Internet’s Best Productivity Tool: If This Then That https://t.co/746vhP8F8S via https://t.co/0oUrB2wIQO: WSJD #HITMC #HITsmIND— HealthcareIT Experts (@HCITExpert) June 2, 2016
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.
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.
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
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
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“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
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.
We are using the following interactive Word Cloud to understand the conversations our readers are having around Digital Health topics
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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?”
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.
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.
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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 [4] 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 [6]:
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 [2] to help the hospital administration in optimising the time of their most important resources: Physicians, nurses and medical assistants.
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| Handbook of Healthcare System Scheduling – Reference [7] |
Additional Scenarios where the AI based resource scheduling systems in Healthcare [7] can be deployed are:
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.
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Data | Medical Devices | Connectivity
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:
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
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
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| The Tower of Babel (Pieter Bruegel the Elder, c. 1563), a metaphor for the challenges existing in medical device semantic interoperability today |
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| 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
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 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:
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:
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
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
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
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
I am looking for partnerships, sponsors to develop this solution. If interested kindly get in touch via email: manish.sharma@hcitexpert.com
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Concise message from the #Leaders conference @Arab_Health #ArabHealth @gulf_news pic.twitter.com/p4Mh0coMvw
— Homero Rivas (@mHealthSurgeon) January 29, 2016
Manish Sharma
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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 jitendra.arora@gov.in on or before 20th April 2016.
Workflow Optimisation
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.
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.
For instance,
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.
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
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06.Feb.2016, Bangalore, India
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