Continue reading “Top 8 Healthcare Predictions for 2019 by Reenita Das, @ReenitaDas – @FS_healthcare”
What can you look forward to in healthcare in 2019? The debate expects to get hotter between AI vs. Physicians, Consumer vs. Clinical, Human empathy vs. Machine Intelligence as many new players enter the ecosystem
As patients become more digital savvy, caregivers are increasingly implementing technology solutions that enable both parties to perform several activities online such as accessing personal medical information to online scheduling of appointments. Today, healthcare industry is looking at those technologies or combinations of technologies that can optimize their front, middle and back-office operations so that care givers get adequate time to spend on priority tasks.
Robotic Process Automation (RPA) is one of the key technologies that has gone mainstream in many industries including healthcare. Why health IT leaders should continue to turn their pivot towards RPA? We’re exploring the reasons through this post.
RPA in Healthcare: Common Applications and Benefits
Robotic Process Automation or RPA automates processes that are repetitive and transactional, primarily by imitating human behavior for rule-based tasks. RPA enables caregivers to focus on high-value activities by enhancing overall administration of healthcare processes. It executes routine tasks at a fraction of time than that’s taken by a human, eliminating the risk of human errors. The scope of RPA in the administrative and clinical functions of healthcare is very vast.
Technologies such as cloud computing and data virtualization have enabled scalable deployment of RPA software across various units and geographic locations of a healthcare organization. So far, healthcare administrators have leveraged RPA in several areas of their back, middle and front-office operations; few of which are mentioned in the table below:
Areas of RPA implementation
Benefits to healthcare providers
(relatively untapped by RPA)
Most of the present day healthcare organizations are using RPA for automating rules-driven and repetitive back office work. The potential RPA can offer healthcare in unison with advanced technologies such as machine learning (ML) and artificial intelligence (AI) is tremendous. It’s no surprise if we consider Robotic Process Automation a stepping stone to integrating these sophisticated cognitive technologies into healthcare.
What needs to be automated in healthcare?
1 Connecting and automating disparate health monitoring devices: The case of neonatal ICU:
2 Compliance monitoring and analysis:
3 IoT analytics to empower process automation
Leveraging RPA with exponential technologies
The future healthcare environment could look very different from what we see today. Technologies like Robotic Process Automation will have a greater say on employee productivity. Automating routine tasks such as collecting blood samples could help the job of a nurse, reduce task time and eliminate manual errors, while improving the patient experience. As organizations progress from depending on manual tasks to applying RPA and cognitive computing, the workforce also shifts from being “doers” to “reviewers.” Health IT leaders and providers, hence should focus on developing proactive, winning strategies to attain long-term financial sustainability and improved patient experience.
NITI Aayog’s “National Health Stack – Strategy and Approach” document published in July ’18 is a good starting point in the direction of digitizing India’s healthcare management for meeting the challenge of healthcare of India’s masses. It’s a clear reflection of the realization that India’s Healthcare needs a digital infrastructure. The National Health Stack (NHS) is outlined as a “visionary digital framework” with four key components — electronic health registries of health service providers and beneficiaries, a coverage and claims platform, a federated personal health records framework and a national health analytics platform.
However at the same time there are some gaps and untouched aspects which must be taken care sooner than later to ensure initiatives across the nation start on robust and comprehensive foundations. Ironically, while the document as well clearly recognizes that Ayushman Bharat has a 2 pronged strategy — setting up of 1.5 lakh Wellness Centers in Primary Healthcare and increasing the financial protection for secondary and tertiary care – the Wellness Centers are not at all touched upon in the proposed Digital framework. There can be no two thoughts about the high criticality of the Primary Healthcare system in India’s healthcare. NHS implementations designed with primary focus on insurance claims and coverage will be a lopsided strategy for the scale of efforts involved. In fact, extending this further beyond the Wellness Centers, the NHS must plan to give adequate provisioning for Anganwadi and other grassroots level Health-workers who are working most closely with the masses and form the lowest layer of healthcare services hierarchy which is extremely critical for preventive and primary healthcare. Any digitization initiative leaving these grassroots workers out of purview would be stunted and ineffective. Options must also be explored to address all existing gaps in this is extremely critical layer.
Coming to the technical aspects of the NHS stack it is important to understand that in our highly democratic and federal setup it may be justified for NITI Aayog to restrict their guidelines only till technical stack level. However leaving the next line of details totally to various public and private stakeholders will likely lead to anarchic and incompatible solution outcomes across the country. It is imperative that NITI Ayog comes up with next level of guidelines and pushes the states and all stakeholders to align to those guidelines. Without going into the modalities of the way it will be done, the rest of this article will focus on some of the key design considerations which must be included by various implementers for ensuring there is basic hygiene and consistency in this National registry of this scale.
Envisioning National Health Electronic Registry as a national one, as “a single source of truth for and manage master health data of the nation” sounds very ambitious. Rather than letting this happen at the “democratic” pace, this needs to be executed with greater authority, careful planning and a best-in-breed technology platform. At the same time we must also look at the returns on investment for this grand registry or repository – do we really see a significant proportion of patients moving across states for health treatments?
Instead of trying to build a mammoth data repository a more practical and effective approach may be to maintain the repositories at state-level for now, provisioning the central registry to have only meta-data for querying and pulling information from the state health repositories.
For unique identification of patients across various systems and networks a standard and uniform mechanism will have to be ensured while giving due regard to all the various Government approved Identity mechanisms and not just Aadhar. This is to ensure that the treatment are not delayed or denied for lack of Aadhar or any other identity mechanism. This needs to be balanced carefully with the need to provide robust mechanism for avoiding any Data duplication or Data redundancy.
Another extremely important aspect to be looked into is data privacy and data security. Vision of having a centralized registry of health data for 130 billion people entails a huge challenge in terms of ensuring the data is secure, only authorised and appropriate data is accessible to stakeholders and the data cannot be misused by technical or non-technical individuals, agencies, organizations or negative forces. This requires very strong and explicit guidelines to be provided to all the implementers at different levels because any gaps and nuisances with respect to data security and data privacy can have cascading effect and has tremendous detrimental potentials on this mega initiative.
The envisioned health registry will be the central registry for all Health establishments, professionals, patients, health workers, medical personnel and other stakeholders. And it will be closely integrated with the Health data repository which should have all the data or meta-data for all patients, their visits to all different health-establishments, diagnosis, scans, test-reports and treatments. Considering the scales, volumes and complexities it is obvious that a digital platform connecting all these cannot afford to be based on any manual data updates without any data-duplication. All the different applications will have to be integrated in a seamless manner and in real-time basis using open APIs. Hence all participating applications need to be mandated to expose APIs in a standard way. API formats and protocols need to be laid out clearly rather than leaving it to participating organizations and stakeholders.
NITI Aayog deserves a pat on the back for envisioning the National Health Stack which will push the digitization initiative in India’s Healthcare in a big way, paving the way for numerous healthcare benefits to the masses including the financial protection and also other benefits including policy making, governance, research and so on. In doing this NITI Aayog have set the bar high for themselves. However it will be extremely important to translate this framework into large scale adoption and follow it up with detailed IT architecture guidelines for National or State Health IT Platforms, or possibly even the solution architecture itself, incorporating the inputs highlighted here among all other considerations. They must also apply the crucial lessons learnt from the India stack adoption. Only then we can be assured that this Digitization initiative goes beyond a cliche and fetches results in the range of expectations!
Indian health care is at an inflection point. Today governments’ spending on healthcare needs is one of the lowest amongst the Developing countries . India spends about 5% of the total expenditure on Health which is around 1.7% of the GDP. Public healthcare growth has slowed down over years. In 1998 about 43% of population was served by Public Hospitals and today only 30% use the Public health care system.  That means almost 70% of the health care needs are serviced by Private players, trust hospitals and non-profit institutions. This has led to the rapid growth of Private players who are growing at the rate of CAGR 16.5% year on year . The costs of procedures or hospitalization has increased anywhere from 83% to 263% in 10 yrs. i.e. 2004 to 2014. There is also a wide variation of the cost for the same procedure in different hospitals . It is also noted that 86% of rural Indian patients and 82% of urban Indian patients do not have access to any form of employer-provided or state-funded insurance.
Government of India is cognizant of this gap and is taking a 360-approach to help people of India get affordable, accessible, quality healthcare. They have capped prices for certain lifesaving drugs, stents and implants. They have created a common entrance examination throughout India. The Medical council of India is being replaced by National Medical Commission which has more representation across different states. Ayushman Bharath is world’s biggest and ambitious project to cover 10 lakh family appropriately 50 crore people based on socio economic status defined by the Socio- Economic caste census 2010.
Some of the states are also proactively implementing systems to monitor delivery of the healthcare services through State medical establishment acts.
Being an integral part of the healthcare delivery system, we are not only responsible for treating patients but also understand our role and responsibility in the way care is delivered. We are the primary drivers, who can steer the system in the most cost-effective way, with good clinical outcomes or remain oblivious of costs! In order to help the patient and the hospital, it is important we understand what goes in to the revenue and costs of running a hospital and how each factor plays a role in escalating and deescalating the costs. In a study done by IMS (Intercontinental marketing company- Parent IQVIA) institute on avoidable costs in healthcare they attributed avoidable costs into six major buckets: They are:
– Medication Non compliance
– Non/Delayed adherence to Evidence based medicine
– Antibiotic misuse
– Medication errors
– Suboptimal use of generics
– Mismanaged polypharmacy in elderly
If the above mentioned are the six major causes in the delivery of care, the following are the major factors in inappropriate utilization of services i.e. inappropriate admissions, overuse of outpatient services, misuse and abuse of prescriptions and unindicated ER visits.
Medication non adherence:
Medication non adherence alone contributes to $68billion to $148billion dollars in costs. Patients usually are non-adherent to prescriptions due to costs, lack of information on the long term effects of noncompliance, cultural beliefs, side effects and lack of social support. It is noted that only 75% of patient fill their prescription when written first time. And 32% -40% do not fill up their prescriptions on subsequent follow up. Government initiatives in capping the prices and fixing the selling price do help in improving compliance. But as Doctors we can play our role by educating patients, prescribing low cost, quality product so that we do not burden our patients.
Nonadherence or delayed adherence to Evidence Based Medicine protocols:
Avoidable costs due to delayed or non-adherence to evidence based medicine costs anywhere from $19 billion to $64billion. Not able to timely diagnose, start treatment and lack of follow up are the major contributing factions. Guideline adherence is seen only on 61.9% in Diabetes and 20% in Hepatitis C patients. The importance of keeping ourselves updated with recent changes in the standards and protocol and use them appropriately in order to avoid such wastage cannot be stressed enough. Educating patients on long term complications and help patients understand that prevention always costs less than the actual treatment, goes a long way.
Antibiotic misuse, the cost opportunity for the antibiotic misuse ranges from $27 billion to $42 billion. Prescriptions for viral infections and usage of broad spectrum antibiotics tops the list of Antibiotic misuse. The common reasons are pressure from patients, defensive medicine. Being more responsible, while prescribing antibiotics, understanding the communities’ microbial nature and their sensitivity pattern helps to decide on the antibiotic needs.
Similarly medication errors, suboptimal use of generics and mismanaged polypharmacy in elderly also contribute to approximately $50billion in costs.
Apart from patient and clinical factors, administrative factors adds on to $126 to $315 billion in cost for delivering health care. The cost are majorly coming from ineffective claims process, staff turnover, ineffective IT systems and paper prescriptions.
There are tools available to calculate the healthcare wasteful spending in USA. These tools assess spending at the micro level, helps to develop specific targets and to assess the results of specific Interventions.
Another trend that is catching up is on payments based on value of care given rather than quantity. Value based payment models are slowly, but surely catching up across many developed countries and in India it is in its nascent stage enforced by few Insurance companies.
While we are grappling with inadequate funding, inefficient systems, lack of standardization, there is whole new wave that is going to make its presence felt sooner than later which is on “Information technology” in health care. There is already quite a bit of information technology solutions used in public sectors such as national health portal, online registration system, Central drug standard control organization so on and so forth. In private sectors the use of technology is far advanced in the form of electronic medical records, apps, call center, point of care devices, internet of things etc… The growth of this sector in health care will continue to see upswing as they try to help us find out solutions for each of the problem case in Health care.
The hospitals of the future will move from hospitals to home, utilize mobile technologies to stay connected with patients, care pathways to help standardize delivery of the care. The hospital beds probably will get restricted to use for post-operative care, intensive care and such other high end work. Public insurance will gradually increase the spectrum of population they cover and public private partnership has to happen in order to deliver care for such huge population base. Becoming cost effective is the need of the hour.
 Rising income level, ageing population, growing health awareness and changing attitude towards preventive healthcare is expected to boost healthcare services demand in future, but in a different areas, than what it is today. We need to understand these trends and prepare ourselves better so that we are not caught unaware.
The article was first published in American college of Physician-India chapter in their 3rd annual conference, Lucknow and has been republished here with the author’s permission.
1. World health organization and world health statistics 2017
2. National sample survey office(NSSO)
3. Frost and Sullivan LSI financial services, Deloitte
4. BMJ Open. 2013; 3(6): e002844.Published online 2013 Jun 11. doi: 10.1136/bmjopen-2013-002844 PMCID: PMC3686227 PMID: 23794591 Costs of surgical procedures in Indian hospitals Susmita Chatterjee and Ramanan Laxminaraya
5. IMS Institute for healthcare informative: Avoidable costs in Healthcare.
6. Analysis by PricewaterhouseCoopers’ Health Research Institute: the price of excess.
7. American health policy institute: using data driven disruption to reduce wasteful spending in health care.
8. NAT health PWC funding Indian healthcare, catalyzing the next wave of growth.
9. An HFMA value Project report: Strategies for restructuring costs structure.
10. India brand equity foundation
After hearing about India’s New Health Insurance Program, I thought it is good idea to share about Health Economics, so here I am
|Alan William Plumbing Diagram about Health Economics|
(A) Health and its values,
(B) Influencers to health,
(C) Demand for healthcare,
(D) Supply of healthcare and
(E) Market equilibrium factors are the analytical of health economics.
The remaining three (F) Microeconomic evaluations, (G) Planning, budgeting and monitoring and (H) Evaluation of system are main area of
The article was first published on Dr. Karan Sharma’s LinkedIn pulse page here, its been re-published here with the Author’s permission.
There is recognition for the need of holistic longitudinal individual electronic health records for citizens, rather than just collated population-based data, for which one of the key components in the NHS Stack is going to be the Federated Personal Health Record. But is this requirement of an individual’s record to ensure continuity of care or mainly to avoid fraud and bring greater trust into the claim handling process? If it is for the stated objective of fulfilling the National Health Policy 2017 that states
“The attainment of the highest possible level of health and wellbeing for all at all ages, through a preventive and promotive health care orientation in all developmental policies, and universal access to good quality health care services without anyone having to face financial hardship as a consequence… “
Then, in this write up I focus on two issues of immediate concern.
1. No requirement explicitly stated for compliance to Healthcare Information Technology (HIT)/EHR standards as recommended by MOHFW and published on December 2016
2. Different applications being developed at various levels of care, both in the public and private healthcare domain, which are not proven to “talk” to each other i.e. exchange healthcare data (interoperability)
Going into greater details about each of these issues:
1. No requirement explicitly stated for compliance to Healthcare Information Technology (HIT)/EHR standards as recommended by MOHFW and published in December 2016, except for patient/beneficiary identification.
It is understandable that when the program starts – the focus is going to be on assembling the registries of beneficiaries, providers, empanelled hospitals etc and the claims or payment for healthcare services rendered by providers. For validating the claims there is going to be proof of services rendered to be provided by filling forms and uploading supporting documents, such as test results, into the claims component of the stack by the hospitals/providers. However, instead of just having a checklist format of proof of service, if the data input is coded compliant to recommended standards (such as SNOMED CT for Diagnosis or LOINC for lab results) instead of just free text or proprietary codes –– then the healthcare data being collated is of much more immense value for clinical study and analytics. More importantly, this would bring about the perception that the information being asked for and checked on, has value in providing in-sights to providing better healthcare, instead of being perceived as an overseeing billing validation into the services provided by the clinicians, and so will facilitate onboarding clinicians to digitization.
For continuity of care and to facilitate quality clinical care, the assumption that having an open API based paradigm for fetching the records of a citizen from across different points of care, without the need for being standard compliant, maybe misplaced. Ok, so touch points will bring across data from corresponding associated fields when different healthcare systems exchange data, for example diagnosis from the exporting system into the importing system. However here lies the problem if not standard compliant, when attempting to consolidate the diagnosis section of a patient in a repository or into a consolidated longitudinal record: – say a patient has Pulmonary Tuberculosis and over time, goes to 3 different doctors in a few years. It is very possible that the first doctor may record the diagnosis as “Pulmonary Tuberculosis”, the next doctor may have logged in this diagnosis as “Tuberculosis of the Lung” and yet a third doctor may have put in the diagnosis as “Pulmonary TB”. So, when the data is being collated – the computer will not understand that all these three different terminologies represent the same concept and site of the disease, and may record them as separate problems. However, if the diagnosis was standard compliant and coded with the recommended SNOMED CT code (Concept ID 154283005), then the compilation and consolidation of this individual’s diagnosis list will be correct, since this standard code consolidates all three terminologies as the same disease and site. Similarly, lab tests results may have various terminologies, for example Fasting Blood Sugar aka Fasting Blood Glucose aka FBS, but if the recommended LOINC code (1558-6) is tagged, then during consolidation of a patient’s test results, the correct interpretation that these are results of the same test will occur and so will be trended accurately. This will come into play even at the claims phase. Healthcare is knowledge intensive, with whole lot of concepts, terminologies, semantics and nuances involved, which needs a framework of standards to convey the correct meaning and interpretation, when exchanging information between different HIT systems.
Another trend is that in those states that already have such universal health coverage programs deployed, there is a tendency to come up with proprietary codes for procedures in each of these different schemes, to suit the billing/claims end users. For example, Andhra Pradesh’s NTRVS program has got procedure codes like S5 for orthopaedics procedures, drilling down to S5.1 for fracture correction in orthopaedics procedures, further drilling down to S5.1.4 for reduction of compound fracture and external fixation. The same procedures have a different proprietary coding system in the program run by Tamil Nadu. So, what happens when you try to compare outcomes from the same procedures between these two states? If the recommended SNOMED coding system for procedures was applied in both the states – then carrying out such comparative studies become much more feasible and meaningful. Instead of reinventing the wheel with proprietary or local codes, if the recommended international standards that have been developed over the years by domain experts are put into place, then not only can we carry out such studies between our states but also between India and other countries, leading to adoption of the most efficient, cost effective, least invasive interventions with best outcomes.
It is of utmost importance that these recommended standards, including clinical standards, be introduced at the foundational phase of the framework for the National Health Stack. With about 20% more effort upfront, it is possible to plug in the look up databases for these standards into their respective fields- such as Diagnosis, Labs, Procedures, Medications etc. Even better, that these standards be deployed and utilized (where relevant) even for claims (as explained above), while place holders be put into place for those standards (mainly clinical) that may come into play only when the Federated PHR phase is activated. Importantly, to enable exchange of data between HIT systems, it is highly advisable to be compliant to HIT messaging standards such as HL7/FHIR. That will be the only way that the National Health Stack will have the robustness and flexibility to handle billing, claims and clinical healthcare functionalities optimally. If this is not done at the foundational phase and if the NHS framework is mainly set up for billing and claims, this will straitjacket the framework to effectively introduce these standards later and lead to fitting a square peg into a round hole situation. Also, an even bigger problem that proprietary codes could lead to, is if down the line wisdom prevails, and a decision is made to mandate recommended HIT standards, then the big headache issue of retrospective mapping of these proprietary codes to standard codes comes up for existing patients with past visits/admissions. It should not be billing and claims requirements that be the primary driving force for the National Health Stack, but ideally should be patient care and provider requirements in conjunction with billing/claims requirements that should be the driving force.
2. Different applications being developed at various levels of care, both in the public and private healthcare domain, which are not proven to “talk” to each other i.e. exchange healthcare data (interoperability)
The NHS document states that the National Health Stack a. Is designed to bring a holistic view across multiple health verticals and enable rapid creation of diverse solutions in health b. To enable patients to effectively become a Healthcare Information Exchange (HIE) of one: as meaningful data accumulates in a patient controlled repository, a complete picture of the patient emerges, resulting in improved quality of care across a range of providers.
For the above stated objectives to be attained, it requires at least these two conditions to be fulfilled: –
a. The diverse HIT systems that are involved in healthcare of the beneficiaries should ” talk to each other ” with ability to exchange data appropriately and without loss of meaning and interpretation in the exchange i.e. Interoperability. That is how accurate meaningful data of a patient should be accumulated. Considering that 70% of healthcare in India is provided by the private sector, this accumulation of a patient’s data will require visits/admissions to private hospitals to be brought in. For this, there is the most important requirement and need to publish the open APIs specifically being used in the NHS, so that these private healthcare organizations’ systems can integrate and exchange healthcare data with the NHS.
For example, if I am an authorized doctor for a patient – what is the API to be used to fetch this patient’s healthcare longitudinal record from the National Health Stack? Again, if the recommended standard like HL7’s FHIR (which is API based) was adhered to for data exchange, it would have made this deployment, hooking up and integration with NHS much easier and effectively feasible.
b. For the data to be meaningful, classified and categorised correctly with terms implying the same concept put into the same category and not into different ones, need the variations in terminology (especially clinical terminologies) to map back to the correct concept as that intended by the provider – which requires the recommended HIT standards to be mandated. Only then can the healthcare data be meaningfully analysed, trends and patterns including outcomes be detected (by deploying statistical methodologies including machine learning and AI) and standard protocols with best outcomes for the various respective Indian ethnicities be formulated, thus achieving the stated goals and objectives of the NHS
If the National Health Stack does provide the latest and greatest in this platform- with the recommended standards, then with our large numbers, English speaking brilliant human resources, internationally renowned prowess in Information Technology and Healthcare ; this assimilation of a treasure trove of Healthcare Information, along with the well-known Indian ingenuity, presents a huge opportunity for the country to leap frog healthcare to the next level and bring about betterment for humanity.
There is undoubtedly a clear argument for Universal healthcare. The question still looming large is “How do we get there”
Today, the National Health Protection Scheme (NHPS) has been credited as the world’s largest health insurance plan. The plan aims to provide a health insurance cover of up to Rs 5 Lakh annually to 10 crore families, which would in turn cover 40 percent of country’s population. RSBY, the earlier predecessor of Ayushman Bharat was able to reach 3.6 Crore families over a 10-year timeframe against a targeted coverage of 6 Cr families, let’s say 60% success rate in 10 years. Undoubtedly, the scheme is very well intentioned and fundamentally ambitious which is the need of the hour. The scheme, however, currently seems to address only one of the three pillars – Affordability for healthcare services; two other pillars access and quality remain unanswered!
Do we have the infrastructure access?
India has around 1.6 million hospital beds and around 55,000 hospitals (excluding community health centres and primary health centres). The infrastructure is woefully inadequate to cater to the healthcare needs of the country. In addition, there is a large variation across states. While states like Karnataka and Tamil Nadu have ~1000 people served by one government hospital, states like Bihar and Assam have more than 5000 people being served by a government hospital. Given this, how do we deliver care to the population remains a question. The gaps are even more pronounced across Tier-1/2/3/4 towns. However, the opportunity also presents solutions;
The government needs to smartly build capacity as utilization increases and also increase capacity utilization of existing Primary Health Centres (PHCs) and Community Health Centres (CHCs). However, there is a lot of ground to be covered; the current efforts are still geared towards building a registry of hospitals in Rohini (Registry of Hospitals in Network of Insurance) which finally claims to have ~33,000 unique hospitals.
Good primary care is an essential precondition for a healthy nation. And rightly so, Ayushman Bharat also proposes setting up of 1.5 lakh health and wellness centres across the country. These centres would provide comprehensive healthcare, maternal and child care, disease screening, free drugs and diagnostics to the poor. A meticulous implementation and robust healthcare delivery in these centres could reduce the need for secondary and tertiary care. Addressing problems associated with supply logistics and spurious medication is another challenge. There could be an opportunity to tie up with players involved in last mile logistics to tackle some of these challenges.
Finally, a large question that looms over is the participation from private sector. Can the government assure enough incentives to the private sector which already faces problems of receivable and collection from other government insurance schemes? Given that government hospitals have 0.5 beds per 1000 people, non-participation or even limited participation from private sector could adversely impact implementation.
Do we have skilled personnel?
Our country has around 1 million doctors. While states like Karnataka and Tamil Nadu have 1.5 doctors per 1000 population, states like Bihar and Assam have less than 0.5 doctors per 1000 population. Apart from Physicians, contractual staff accounts for more than half of skilled workforce in the country.
There are also sporadic examples and learnings from other countries. For instance, Costa Rica established integrated primary healthcare teams each looking after 5000 people. The team included paramedics to visit patients, an executive who maintains records, a nurse, pharmacist and finally a doctor. Ethiopia has a concept of health extension workers who are rural high school graduates undergoing one-year training before they are sent back to their native areas. These health extension workers have played a key role in reducing the child and maternal mortality by 32% and 38% respectively. In a review of studies conducted across some countries in Africa, it was found that clinical officers with three years of training performed Caesarean Sections as safely as doctors. In Thailand, there are incentives in place for doctors who work in rural areas. Inculcating some of these best practices should bring in much more efficiencies in the current system.
Do we care about quality?
In India, the average length of doctor consultation is little more than 2 minutes and features a single question – “What’s wrong with you?”. Not surprisingly, research done by World Bank has shown that only 30% of the consultations have resulted in correct diagnosis. Citing another example, in India, around half a million children die of diarrhoeal diseases every year. In this context, a research done by the World bank around Diarrhoea in Delhi showed that only 25% of the providers ask parents whether there was blood or mucous in the child’s stool, which is the definitive symptom of the disease. Some of these are fundamental corrections needed in the healthcare quality today.
Hospitals), compliance is altogether a different subject. In addition, less than one percent of hospitals have NABH accreditation.
Sometime back, Ministry of Health and Family Welfare launched an initiative Mera Aspataal (My Hospital) an app-based platform to enable patients share real time feedback on hospitals. The app has seen a meagre 5000 downloads and numerous complaints of inability to share feedback or non-actioned feedback. In addition, the website has numerous challenges right from accepting a mobile number for registration.
A large-scale quality and patient experience audit followed by implementation of drastic interventions is required to drive overall quality. There must be a commitment to deliver quality healthcare and not just on paper. Quality needs to be defined on multiple parameters and incentives need to be created around these quality standards. India would need standardized survey instrument and data collection methodologies to measure patients’ perspectives of hospital care. Hospitals providing quality as reflected in standardized patient scores need to be both recognized and incentivized appropriately. Practices such as HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) in the United States need to be studied and some best practises need to be suitably adapted to the Indian Context.
Is there a need to educate the consumer?
In order to drive healthcare consumption and changes in health seeking behaviour of the population, there is a need to educate the consumer. More importantly, the government needs to take a lead in facilitating patient education around insurance. This would also include educating them on seeking healthcare from the right set of institutions. The move would be much easier than educating informal physicians on right diagnosis and treatment. The government should take the lead in facilitating public health; focusing on awareness and education. Pulse polio campaign which witnessed a resounding success in India, needs to be created for Non-Communicable diseases in the country.
The way forward
The concept of Universal healthcare is not something new and has been embraced by quite a few countries across the globe while being a work in progress for others. In addition, it has helped them achieve desired results. Look at Rwanda, a small African country as an example, its GDP per person is only $750 but its healthcare scheme covers 90% of the population and infant mortality has halved in a decade.
however what the program needs is a clear thinking and internally designed implementation roadmap.
Ayushman Bharat, undoubtedly, could be a game changer in the Indian context if planned meticulously and implemented well. Amitabh Kant, Niti Aayog CEO, expects around 50% of the families to receive coverage in the first year. As per him. “the challenge is not resources for the scheme, but challenge is its implementation”. The goal of Universal Healthcare is certainly achievable and affordable by the government; it needs a thinking on how to optimally use scarce resources!
The healthcare SIG is planning a panel discussion and networking event at Equinox on this theme. Please reach firstname.lastname@example.org if you wish to collaborate for the same.
1. On Death and Money – History, Facts and Explanations – Angus Deaton
2. Census of India – Annual Health Survey Bulletins
3. Government of India Ministry of Finance – Ayushman Bharat for a New India -2022
4. Medium Healthcare Consulting Analytics
Register for the 6th Annual Conference by Medium Consulting, Sep 28th 2018, at Hyderabad:
Here is the catching observation from the report:
The article was first published on the Author’s Linkedin Pulse Blogs, its republished here with the Author’s permission.
Let us talk about Healthcare now. Illusions occur when brain tries to make sense out of conflicting information based on his/her experience. Many of you would have heard about Conformational bias.
User-Driven Healthcare: Concepts, Methodologies, Tools, and Applications: Concepts, Methodologies, Tools, and Applications:
Communication Skills for the Health Care Professional: Concepts, Practice, and Evidence:
NEW DATA PROTECTION LAW PROPOSED IN INDIA! FLAVORS OF GDPR
The much-awaited Personal Data Protection Bill, 2018 (“Draft Bill”) was released by the Committee of Experts entrusted with creating a Data Protection Framework for India (“Committee”) on Friday evening.
The Committee, chaired by retired Supreme Court judge, Justice Srikrishna, was constituted in August 2017 by the Ministry of Electronics & Information Technology, Government of India (“MeitY”) to come up with a draft of a data protection law. After over a year of deliberations and a series of a public consultations followed by release of a white paper with preliminary views, the Committee has released a Draft Bill. The Draft Bill is accompanied by its report titled “A Free and Fair Digital Economy Protecting Privacy, Empowering Indians” (“Report”) which provides context to the deliberations of the Committee.
MeitY as the nodal ministry may accept, reject or alter such Draft Bill. Thereafter, the Draft Bill would need to be approved by the Union Cabinet before it is introduced in the Parliament for deliberations.
Some of the key highlights of the Draft Bill are:
Extra-territorial application i.e. the Draft Bill is to apply to foreign data processors in so far as they have a business connection to India or carry on activities involving profiling of individuals in India.
- Differential obligations imposed based on criticality of data, i.e. differing obligations for Personal Data and Sensitive Personal Data;
- Obligations of the Data Processor : Notice (that is clear, concise and comprehensible), Purpose Limitation and Collection Limitation, maintaining data quality, storage limitation;
- Grounds for processing in addition to consent include use for employment purposes as well as emergencies.
- Intended to be made applicable to the State as well as private parties.
- Child Rights: Child is defined as someone who is less than 18 years of age. Profiling, tracking or behavioral monitoring of or targeted advertising towards children is not permitted.
- Rights of the Data Subject: Include Data Portability, Right to be forgotten as well as the right to correction of the data etc.
- Concept of Privacy by design and a data breach notification have also been introduced;
- High Risk Data Processors – A mandatory registration requirement has been imposed on data processors who conduct high risk processing. Such processors are required to implement: Trust Scores, Data Audits as well as a Data Protection Impact Assessment
- Data Localisation: A copy of all Personal Data must be stored in India; additionally the Government may notify certain types of personal data that should be mandatorily be processed only in India. The Government has retained with itself the power to exempt storage of copies of Sensitive Personal Data, in some cases.
- Cross Border Data Flows: In addition to consent cross border transfers would also require the use of (a) model clauses; and (b) possible adequacy requirements, i.e. transfer to jurisdictions approved by the Government;
- The Data Protection Authority of India (“Authority”) appointed under the Act will provide or endorse Codes of Practices.
- GDPR Style Penalties: Upto 4% of global turnover in some cases;
- Criminal penalties also introduced for limited cases;
- Phased manner of implementation once the law is implemented.
To summarize, whilst we believe that the Draft Bill does have its share of positives, in several places the Draft Bill is either ambiguous / not clear or imposes excessive obligations on Data Fiduciaries and prescribes disproportionate punishments. Several factors are left to be determined through Codes of Practices or to be determined by the Government at a later stage. Therefore, at this stage the full impact of the proposed law cannot be comprehended in entirety.
In several respects, we note the Draft Bill appears to have borrowed heavily from the recently notified E.U. General Data Protection Regulation (“GDPR”). Given the infancy at which the GDPR is at this stage, it would be imperative that law makers provide for enough flexibility for the law to be altered on the basis of global experiences. Further, we find that even the current basic law under the Information Technology (Reasonable Security Practices and Procedures and Sensitive Personal Data or Information) Rules, 2011 (“2011 Rules”) has yet not been implemented fully even after 7 years. Therefore, implementation will be key to this fairly detailed and somewhat cumbersome law.
We hope that the law is made more balanced by diluting some of the draconian provisions as well as by issuing clarifications on the points that are not clear, after public consultation. Therefore, ideally, once the MeitY finalizes the draft, it should place such law in the public domain and provide stakeholders an opportunity to provide further inputs, before the law is placed before parliament.
We have set out in our detailed analysis below the possible implications that it may have on businesses, including offshore companies doing business in India. As we continue to read, debate and delve deeper into the wording of the law, our views on several of these issues may evolve.
To summarize, while the Draft Bill does have its share of positives, in several places the Draft Bill is either ambiguous / not clear or imposes excessive obligations on Data Fiduciaries and prescribes disproportionate punishments. It also seems to have certain unintended consequences for start ups/non digital businesses in terms of imposing exposing them to excessive compliances.
Our detailed analysis of the Draft Bill is available here.
Please do join us this Tuesday (31Jul 2018) and / or Wednesday (01 Aug 2018) at our Webinar where we discuss the impact that the Draft Bill may have. The registration link for the same is available here.
Email the Technology & Privacy Law Team and You can direct your queries or comments to the authors
The article was first published here, its been republished on the HCITExperts Blog with the authors permission.
1. Regulatory Essentials for eHealth in India by Dr. Milind Antani, Nishith Desai Associates:
There were 4 Components:
a. Decentralisation and integration of surveillance activities through establishment of surveillance units at district, state and central levels
b. Human Resource Development with training of State Surveillance Officers, District Surveillance Officers, Rapid Response Teams and other relevant staff
c. Use of information technology for collection, compilation, analysis and dissemination of data and
d. Enhancement of Public Health Laboratories.
The following Objectives were to be met
1. Cover limited number of diseases of public health importance which needed public health response
2. Implement multiple methods of surveillance
3. Be a proactive program with timely response at all levels i.e. Be an Early Warning and Response (EWAR) program
4. Use Information Technology to facilitate information gathering, collation, analysis and dissemination
5. Decentralise and have states take ownership and
6. Centre be responsible for coordination, quality control, policy formulation, finance management and technical assistance.
It was realised that though the healthcare infrastructure in India had grown over the years, disease surveillance had not got the required attention in the past, resulting in late detection of disease outbreaks with related morbidity and mortality. One of the main reasons for this shortcoming was the time-consuming and labour-intensive manual methods of data collection, transmission, analysis and feedback for response with paper.
Hence a countrywide Information and Communication Technology (ICT) network was established under IDSP with the help of National Informatics Centre (NIC) and Indian Space Research Organisation (ISRO). This IDSP network connects the District Surveillance Offices to the State Surveillance Offices which then connects to the Central Surveillance Office at the National Centre for Disease Control (NCDC).
The network is also presently being deployed to CHC and even PHC levels in some states. The network is used for data entry, compilation, analysis and feedback from data coming in from the sub centre level and above. It has video conferencing ability to help in meetings and training sessions. Furthermore, there is an IDSP portal ( www.idsp.nic.in ), which is a one-stop portal for data entry, reports, outbreak reporting, data analysis and training modules related to disease surveillance.
The IDSP program has three methods of surveillance
1. Indicator Based Surveillance
2. Event Based Surveillance and
3. Media Surveillance.
Briefly describing each of these: –
Indicator Based Surveillance
There are three levels where these indicators are collected: –
S form – this form is filled by the sub-center health worker and collects collated details on conditions such as Fever, Cough, Loose watery stools, Jaundice and Acute Flaccid Paralysis (AFP). These forms are submitted to the supervising primary care centre once a week and fed into the IDSP system via the District Surveillance Unit (DSU).
P form – this form is filled by the primary care providers and collects collated data on about 20 different conditions including the above plus additional conditions such as Pertussis, Diphtheria, Leptospirosis etc. This is also submitted on a weekly basis and uploaded into the IDSP system weekly via the DSU.
L form – this is the form collected from public health (and private) Labs for positive test results for specific diseases such as Dengue, Japanese encephalitis , Cholera etc. The difference in these forms are that for each positive result, further details such as the patient name, age, address, test done and lab confirmation diagnosis is also recorded. These forms also go into the IDSP network via the DSU on a weekly basis.
For more details about information on each of these forms please visit the following link
From the DSU the information gets instantaneously transmitted to the State Surveillance Unit (SSU) and then the Central Surveillance Unit (CSU) via the IDSP network. This network has been effectively working since 2010. The result is that the CSU based in the National Centre for Disease Control (NCDC), has been publishing nationwide outbreaks of these specific diseases on a week by week basis about a month later (On June 20th could see the outbreaks that occurred in the week of May 14th to May 20th) – here is the link
Event Based Surveillance
In summary it is a combination of all the above three methods that bring about the Early Warning mechanism for outbreaks and potential epidemics in India. While there is much room for improvement- the IDSP program has proven the effectiveness of a nationwide IT network and in-fact can potentially be upgraded to be the Healthcare IT highway for the country.
“Dedicated to the IDSP program and public health staff of India – who do so much with so little. Often criticized, seldom appreciated, a big heartfelt thank you” – Dr. Pramod Jacob
Napier Healthcare is a global company headquartered in Singapore, where it manages the development of technologies to world-class standards. My other point of reference is the US. So whenever I consider the industry in India, I am invariably piqued by its difference from the industry in Singapore and the US. Especially the US, since it is a democracy like India and has similar health problems on a large scale.
The most obvious difference I see between India and the US is in their standards and certification environments. We do business in the US and have to be certain that our solutions meet that market’s most stringent regulatory and certification requirements. They include HIPAA and a few others, but more significantly in the case of hospital information systems, the Meaningful Use Stage 2 (MU2) compliance certification. These certifications create significant entry barriers for non-serious players, and make certain that healthcare IT (HIT) quality is maintained in the market.
Compared to a global average of 2-2.5 percent of investments by hospitals, or 6-15 percent by other sectors in India itself, hospitals are far behind their global peers in recognizing the value of good software. The impulse is always to invest for the quick ROI. For example, instead of investment in IT, many CEOs traditionally have wanted to invest in CT Scan or other equipment, which can generate revenue from the following morning itself.
Finally, Insurance is coming
Increasingly top hospitals are becoming aware that the Insurance reimbursements are a significant portion of their revenue and rising every year. DRG classifications and reporting are going to become commonplace as Insurer’s seek to reduce their cost by paying for “packages” rather than individual services. This means that Hospitals that won’t or can’t respond to the Insurer’s will be left to address private-pay market that will shrink slowly but surely. If one studies the evolution of the US system you will find a strong parallel to the trends in the Indian healthcare system. This will be an existential question for providers.
The Article was first published on Mr. Tirupathi Karthik’s LinkedIn Pulse blog, here, and has been republished with the author’s permission.
Here’s my tuppence on DISHA (Draft Digital Information Security in Health Care Act)
The article was first published on Inder Davalur’s LinkedIn Pulse page here, its been republished here with the Authors’ permission.
State of Health in India
Maternal Mortality Rate (year 2015): defined as number of women who die during pregnancy and childbirth, per 100,000 live births. India has a rate of 174 maternal deaths per 100,000 live births, which is worse than Bhutan (148 / 100,000) or Sri Lanka (30 / 100,000 ). China which also has a large population is much better (27 / 100,000)
Infant Mortality Rate (year 2017): defined as number of children who die less than one year of age per 1000 live births. In India the figure is 39 per 1000 live births, behind Bangladesh ( 32 / 1000 ) and Nepal ( 28 / 1000 ). China is 12 / 1000.
State of healthcare information collection for events like epidemics in India
Before 2010, it would take about six months for the health information to be collected, collated and analysed to prove that a given region in India had an epidemic as the entire process was paper based. By that time the disease (with most being self-limiting) would have struck, had its toll of morbidity and mortality and run its course. With most data collection being paper based this delay costs India loss of lives and productivity with high morbidity, especially in rural areas ( in urban areas- private hospitals and clinics have a process of notifying the public health authorities for notifiable diseases, hence epidemics are identified earlier in urban areas) .
To top it all there is general disbelief in the official published health statistics in India. For example, official data claimed that Malarial deaths in India was only 1,023 in 2010, however a Lancet published study showed the figure to be actually 46,800. Following the Lancet article, the official data agreed that they had their figures off by twenty to thirty times. Even for a common disease like Cholera, which strikes every monsoon in endemic areas along the Ganges and Brahmaputra, the official estimate for India is 3,631 cases per year, while research has shown this to be about 22,200 per year.
While the immediate reaction is to blame the public health authorities and Government in India, one must understand the limitations in a paper world to collect health information of 1.3 billion people across 3,200,000 square kilometres. Compare that to collection of information electronically – an electron can travel around the world in about 19 seconds.
The solution – Healthcare Information Technology (HIT)
The solution is to produce healthcare information in a timely manner with accuracy and reliability. To achieve speed, it is best to do so with Information Technology – hence HIT. To achieve accuracy and reliability, it is best if the patient’s data is put into the HIT system by the providers of healthcare such as doctors, nurses, pharmacist etc at the point of care. This patient level data can then be collated and processed to get timely, accurate and reliable population-based healthcare information.
In addition, HIT systems provides the power of IT to healthcare such as giving alerts for drug-drug interactions, duplication in lab tests and bringing about efficiency in processes and workflows in a healthcare setting, producing reports quickly which will help in planning and deployment of healthcare. It is estimated that healthcare doubles in knowledge every few months and it is difficult for doctors to keep up. With HIT it will be possible to keep up with the latest and deploy best practice evidence-based medicine applicable for India.
The proof of HIT bringing exponential improvement in speed and access to important healthcare information like epidemics even in Indian public health, is best exemplified by the IDSP program. The IDSP program has gone digital from district level upwards to state and then to the National Centre for Disease Control (NCDC), Delhi. As a result, the NCDC now publishes data on epidemics and events on a month to month basis and will soon be publishing it on a weekly basis. Will cover the details of this program in a future write up.
This article has been republished here with the author’s permission. The article was first published here.
The 2 part paper: Discusses the key role of evidence-adaptive clinical decision support systems (CDSS) in the healthcare system of the future. Weighs the pros and cons that hospitals should considered when deciding to buy or build such decision support tools
Care that is important is often not delivered. Care that is delivered is often not important1.
The importance of clinical care grounded in a reliable evidence base cannot be over-emphasised. Evidence-based care processes, supported by automated clinical information and decision support systems, offer the greatest promise of achieving the best outcomes2. Proprietary Clinical Decision Support Systems (CDSS) built on evidence-adaptive platforms incorporating clinical knowledge that continually reflects current EBM gleaned from both the research literature and sources of practice expertise will soon outgrow self-synthesised (home-grown) solutions. This paper explores this process.
Clinical practice is full of contradictions, not only where individual professional experiences conflict, but even where “evidence” partially or completely disagrees. The primary reason for these inconsistencies is that evidence is dynamic and emergent, never constant.
The Fallibility of Evidence
Evidence can often be incomplete, with varying levels of quality and strength of recommendations3. Keeping up with latest evidence and eliminating its inconsistencies is quite an arduous task and carries the inherent risk of practicing outdated medicine (with occasional catastrophic consequences).
Consider the following scenario:
A 2 month-old infant comes to your office suffering from heart failure. She has a prescription for two drugs that reduce excess fluids from the body (diuretics), prescribed by a cardiologist based on evidence demonstrating the effectiveness of the two medications when administered together. One of the drugs reduces the body’s level of potassium (an important electrolyte) while the other conserves potassium. You are doubtful that two drugs are required for the treatment of such a young patient. Given the amount of time it will take to find evidence to address your skepticism, you call the cardiologist. Unfortunately, the prescribing cardiologist is unavailable, so you then call another renowned cardiologist. He tells you to stop the second drug based on professional experience that it causes growth problems in infants as well as his belief that potassium loss is of little concern in infants. You are now left wondering what is best for your tiny patient, having moved from a stage of having no information to a stage of conflicting “information noise.”
Given such realities of evidence-based medicine, one must consider: is the business of extrapolating evidence something providers and healthcare organisations are willing to do on their own?
THE EVIDENCE DELUGE
It has been estimated that greater than two million articles are published in the biomedical literature each year4. If a physician were to attempt to keep up with this literary explosion by reading two articles each day, at the end of one year, that physician would be more than sixty centuries behind! If physicians were to read everything of possible clinical relevance, they would need to read around 6,000 articles a day!
Compounding this problem is the conundrum of diffusion. “Diffusion” is the spread of best (research) evidence on managing diseases and symptoms to the patient bedside5. According to conventional wisdom, it takes an average of 17 years for validated clinical research findings to make their way into routine clinical practice6. In an age where global public health emergencies (like the recent Zika virus outbreak) require “knowledge hyper-loops” for rapid diffusion of knowledge into general practice, the 17-year latency needs to be radically shortened to 17 hours or even less.
A SOLUTION TO ACCELERATE LEARNING HEALTH SYSTEMS
Clinical Decision Support Systems (CDSS) have been described as the Computerised Patient Record (CPR) System’s Crown Jewel7. According to Gartner’s CPR generations (Fig 1), CPRs or Electronic Health Records (EHRs) have had an increasingly positive impact over the last few decades in reducing medical errors. With the inclusion of CDSS, the EHR evolves from being a provider “colleague” to a “mentor,” with the power to cover the entire care continuum in guiding clinicians at all points of care.
We are now seeing the evolution of the Sixth Generation EHR – “The Seer,” that has computable, standardised clinical data able to invoke clinical decision support from evidence-adaptive CDSS platforms. Although at present evidence-adaptive platforms require human intervention, we are now beginning to see the inclusion of artificial neural networks (deep learning), Bayesian networks, reinforcement learning, and other artificial intelligence techniques for synthesising evidence relevant to patient data in real-time, with potentially unprecedented insights for clinicians. Intelligence Augmentation (IA), where technology amplifies the decision-making capabilities of humans, has linked healthcare providers to vast amounts of patient data with relevant clinical knowledge, in real-time, at the point-of-care. We are likely to soon witness wide-scale proliferation of IA in Sixth Generation EHRs that incorporate evidence-adaptive CDSS.
This kind of evidence-adaptive CDSS is at the heart of a Learning Health System (LHS)1, wherein evidence influences practice and the practice, in turn, generates evidence, creating self-propagating, virtuous cycles that bring about better, safer clinical care at optimal costs.
There are six critical success factors (Table 1) for a CDSS, based on the ACUDIR model (Latin for “Come to the Rescue”), that can form the foundation of such a rapid LHS.
CDSS solutions like Order Sets, Care Plans, and Clinical Pathways are a combination of evidence-based content and advanced technology platforms. The dilemma which healthcare organisations face today is whether they can “build” such advanced CDSS on their own or if they should “buy” proprietary CDSS products.
Read the Part 2 of this blog post by Dr. Ujjwal Rao, here