Month: September 2018

Simplifying Health Economics by Dr. Karan Sharma

After hearing about India’s New Health Insurance Program, I thought it is good idea to share about Health Economics, so here I am


Health economics is a branch of economics concerned with issues related to efficiency, effectiveness, value and behavior in the production and consumption of health and healthcare. 


Alan William Plumbing Diagram about Health Economics
I am using Alan Williams “Plumbing Diagram” to comprehensively understand Healthcare Economics. He has divided scope of healthcare economics into eight distinct topics (explained in the documents) which are:
·        What is health and what is its value?
·        What influences health? (other than healthcare)
·        The demand for healthcare
·        The supply of healthcare
·        Micro-economic evaluation at treatment level
·        Market equilibrium
·        Evaluation at whole system level
·        Planning, budgeting and monitoring mechanisms.
There are interlinkages between each topic, which make it possible to see Health Economics as an integrated whole – more than an Ad-hoc assemblage of topics. According to understanding – The first five boxes
(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 “Engine” of health economics.

The remaining three (F) Microeconomic evaluations, (G) Planning, budgeting and monitoring and (H) Evaluation of system are main area of Applied Economics. 

Let us understand each topic and its relationships:
CORE ENGINE
A.    Health 
Health can be defined as physical, mental, and social wellbeing, and as a resource for living a full life. It refers not only to the absence of disease, but the ability to recover and bounce back from illness and other problems.
Health generally evaluated through its value and perceived attributes, which are like:
1.     Productivity of individual healthy days
2.     Value of life
3.     Expenses caused by diseases and etc.
Health can be treated both as consumption and an investment good, Consumption: health makes people feel better, Investment: it increases the number of healthy days to work and to earn income.
Health does have characteristics that more conventional goods have; it can be manufactured; it is wanted and people are willing to pay for improvements in it; and it is scarce relative to people’s wants for it. It is less tangible than most other goods, cannot be traded and cannot be passed from one person to another, although obviously some diseases can.
B.     Influencers
According to WHO, many factors combine together to affect the health of individuals and communities. The few factors which affect health include:
1.     Income and social status – higher income and social status are linked to better health. The greater the gap between the richest and poorest people, the greater the differences in health.
2.     Education – low education levels are linked with poor health, more stress and lower self-confidence.
3.     Physical environment – safe water and clean air, healthy workplaces, safe houses, communities and roads all contribute to good health. Employment and working conditions – people in employment are healthier, particularly those who have more control over their working conditions
4.   Social support networks – greater support from families, friends and communities is linked to better health. Culture – customs and traditions, and the beliefs of the family and community all affect health.
5.     Genetics – inheritance plays a part in determining lifespan, healthiness and the likelihood of developing certain illnesses. Personal behavior and coping skills – balanced eating, keeping active, smoking, drinking, and how we deal with life’s stresses and challenges all affect health.
6.     Health services – access and use of services that prevent and treat disease influences health
7.     Gender – men and women suffer from different types of diseases at different ages.
There are evidences available of other examples which has been documented which are like: Transport, Food and Agriculture, Housing, Waste, Energy, Industry, Urbanization, Water, Radiation, Nutrition etc.
C.     Demand
Health demand is to achieve larger stock of Health Capital (healthy days). It is not passively purchased from market; it is produce in combining time with purchased medical inputs. Both value of Health and its influencers affect the demand. 
The demand for health is unlike most other goods because individuals allocate resources in order to both consume and produce health. There are four roles of person in health economics:
1.    Contributors
2.    Citizens
3.    Provider
4.    Consumers
 In the context of ordinary goods and services, economics distinguishes between a want, which is the desire to consume something, and effective demand, which is a want backed up by the willingness and ability to pay for it. It is effective demand that is the determinant of resource allocation in a market, rather than wants. But in the context of health care, the issue is more complicated than this, because many people believe that what matters in health care is neither wants nor demands, but needs. Health economists generally interpret a health care need as the capacity to benefit from it, thereby relating needs for health care to a need for health improvements. 
Not all wants are needs and vice versa. For example, a person may want nutrition supplements, even though these will not produce any health improvements for them; or they may not want a visit to the dentist even if it would improve their oral health.
Healthcare has its peculiarity that may mean, it is not considered as any good or service where demand can be analyzed, however that the usual assumptions about the resource allocation effects of markets do not hold meaning for healthcare. Moreover, it may well be that people wish resource allocation to be based on the demand for health or the need for health care, neither of which can be provided in a conventional market. 
D.    Supply
Supply is to achieve and fulfill the demand of health. The supply side of the market is analyzed in economics in two separate but related ways. One is related to the Resource input and Goods output model, looking at how resource use, costs and outputs are related to each other within a system.
Important influencing factors to supply are as follows:
1.     Cost of production of service
2.     Alternatives of services
3.     Substitutes of inputs
4.     Remuneration and incentives
5.     Medical equipment and pharmaceutical markets
Other way in which supply is analyzed is Market structure – how many firms are there supplying to a market and how do they behave with respect to setting prices and output and making profits. These generally managed through market equilibrium
E.     Market equilibrium 
State where economic forces like demand and supply balanced. For healthcare many believes, it is imperfectly competitive market (Nash Equilibrium) where there is strategic interdependence between two firms. The Nash equilibrium occurs when both firms are producing the outputs which maximize their own profit given the output of the other firm. The other side believes it is competitive market. Market equilibrium factors are as follows:
1.     Money (payer), investment etc.
2.     Price mechanism
3.     Time price factors
4.     Waiting list
APPLIED ECONOMICS
F.      Micro-economics evaluation
In simple words it is decision making related to allocation of resources. Major goal of microeconomics is to analyze the market mechanisms that establish relative prices among goods and services and allocate limited resources among alternative uses. It also analyzes market failure, where markets fail to produce efficient results. Few topics which would play important role in micro economics evaluation are:
1.     Cost effectiveness and cost benefit analysis of alternative treatment
2.     Cost utility analysis
3.     Opportunity costing
4.     Allocation based on phases of disease (Detection, diagnosing, treatment and after care)
5.     Market structure
Healthcare market typically which are analyzed are:
1.     Healthcare financing market
2.     Physician and Nurse services market
3.     Institutional service market
4.     Input factors market
5.     Professional education market
G.    Planning, Budgeting and Monitoring
Optimizing the system through effective instruments and tools, few are as follow:
1.     Budgeting
2.     Manpower allocation
3.     Regulation and norms
4.     Incentives structure
H.    Evaluation of system
It is to bring efficiency and equity to the system to bear on (E) Market equilibrium and (F) Micro economic factors through inter regional comparison, international comparison and benchmarking.
Efficiency – the allocation of scarce resources that maximizes the achievement of aims by Knapp.
Equity is always an important criterion for allocation of resources. However, it is observable that people attach more importance to equity in health and health care than they do to many other goods and services. It is important to distinguish equity from equality. Equity means fairness; in the health care context this means a fair distribution of health and health care between people and fairness in the burden of financing health care. Equality means an equal distribution, but it may not always be fair to be equal. 
Health economics has number of methodological limitations but it can offer us useful concepts and principles which help us think more clearly about the implications of resource decisions. An understanding of some basic economic principles is essential for all practitioners not only to understand the useful concepts the discipline can offer but to appreciate its limitations and shortcomings.
Wish to hear more from my connections on this…

The article was first published on Dr. Karan Sharma’s LinkedIn pulse page here, its been re-published here with the Author’s permission. 

Author
Karan Sharma

Healthcare Strategy and Customer Experience Manager, Technology Enthusiast, Innovator and Healthcare Business Leader.

Highly experienced and focused senior Executive with strong background in Healthcare strategies and business problem solving. Have managed multiple projects in different disciplines and geographies with strong track record of building great teams with exceptional results. Provide and Execute vision, strategies or idea.

He is a clinician and healthcare management professional, worked in India, Middle East and Maldives.

Some perceived shortfalls in the proposed Indian National Health Stack by Dr. Pramod Jacob

There is ongoing work in India for a Nationwide Information Technology platform, that will support and facilitate the deployment of the Ayushman Bharat program, which is called the “National Health Stack”, the objective of which is to help achieve Continuum of Care across Primary, Secondary and Tertiary care for each of its citizens and facilitate payment for the care.

A draft of the National Health Stack (NHS) strategy and approach was put out in July 2018 for feedback and comments till July 31, following which no final draft has been published in the public domain. Hence the shortfalls brought out in this write up are based on the July 2018 draft and so these are perceived shortfalls, because the final version may have addressed these concerns. If so, request that the final document be published in the public domain. http://niti.gov.in/writereaddata/files/document_publication/NHS-Strategy-and-Approach-Document-for-consultation.pdf  


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. 
https://www.nhp.gov.in/categories-for-adoption-of-standards_mtl

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. 

Author

Dr Pramod D. Jacob (MBBS, MS- Medical Informatics)

After completing his medical degree from CMC Vellore and doing his Master of Science in Medical Informatics from Oregon Health Sciences University (OHSU) in the US, Dr Pramod worked in the EMR division of Epic Systems, USA and was the Clinical Systems Project Manager in Multnomah
County, Portland, Oregon. He went to do Healthcare IT consultancy work for states and counties in the US and India.

At present he is a Director and Chief Medical Officer of dWise Healthcare IT solutions. He was also a consultant for WHO India in the IDSP project and for PHFI for a Non Communicable Diseases Decision Support Application.

Universal Healthcare: How do we get there? by Ritesh Dogra @ritesh_medium

There is undoubtedly a clear argument for Universal healthcare. The question still looming large is “How do we get there”


Angus Deaton, a well renowned economist, explains that while there is a correlation between higher income and better life expectancy, this is not the only factor. There are means to ensure great health at less cost and equally spending large sum with no purpose, America being one case in point. While earlier any spending on healthcare was dubbed as social overhead, it is no longer so – there is enough evidence to prove that spending on healthcare speeds growth of the nation.

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.

Manpower optimization practices; creation of skilled manpower including nurses, technicians and other support staff through short term training courses could increase resource efficiency for doctors. Healthcare Sector Skill Council (HSSC) had already taken this initiative. However, it requires participation from some private players to jointly build the ecosystem. Certain practices such as midwifery which have been quite successful as isolated examples, need planning and mass implementation.


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.

We have seldom talked about quality standards in existing public or private hospitals. A glance in the corridor of some of the best public hospitals across the country could send shivers down the spine. Is quality the least concern? While we have quality standards drafted by bodies such as NABH (National Accreditation Board for


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.

Increased penetration of both feature phones and smart phones could be another opportunity. In Kenya, for example, M-Tiba is a dedicated health account on cell phone that allows anyone to send, save and spend funds for medical treatment. In addition, it uses internationally recognized ‘safe care’ standards to monitor quality of care at approved facilities.

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.

The fulcrum of change is Niti Aayog and almost everyone in healthcare industry is keen to associate themselves with the program execution along with Niti Aayog; right from medical device and pharma firms, health tech platforms and consulting firms,


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 ritesh_dogra2009@pgp.isb.edu if you wish to collaborate for the same.

References

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

This article has been written by Ritesh Dogra, alumnus from PGP Co ’09, Moderator of the Alumni Healthcare Special Interest Group(SIG) & Managing Partner, Medium Healthcare Consulting. The article was first published here, and has been re-published on the blog with the author’s permission. The images in the article body have been sourced from the original article.

Healthcare Conference
Register for the 6th Annual Conference by Medium Consulting, Sep 28th 2018,  at Hyderabad: 
http://www.amchamindia.com/healthcareconference2018/
Author
Ritesh Dogra

Ritesh has been a member of the Founding Team at Medium Healthcare Consulting. He has led a number of engagements in areas as diverse as market expansion strategy for a Fortune 500 medical equipment manufacturer to planning and commissioning of novel healthcare concepts to performance transformation of a leading hospital chains in South and East India. He has received numerous accolades from clients for his rare insights and extraordinary commitment.

Timeline: The History of the EMR/EHR by David Rice @bigdatadavid13


Much of the conversation around healthcare technology is centered on where new developments are taking us. But as the age old adage goes, you can’t know where you’re going until you know where you’ve been.
And when it comes to health IT, few innovations have been more significant or played more of a central role in innovation, than the digitization of medical information in the form of the electronic medical record (EMR) and later, the electronic health record (EHR). To better illustrate the history behind this technology, we’ve created the following timeline to provide you with some context behind the evolution of this technology.


The article was first published here. The article has been republished here with the authors’ permission. 
Author
David Rice

David Rice is the editor of USF Health Online. He covers a wide range of health IT related topics for the University of South Florida’s online informatics and healthcare analytics programs.

A PhD Researcher’s QnA on #BigDataAnalytics (BDA) with a Healthcare CIO by Inder Davalur, @INDERDAVALUR & Nishita Mehta


Q1. Nishita Mehta: What is data’s role in healthcare & how do you see it influencing future health sector growth in India?

A. Inder Davalur: 

Big Data Analytics (BDA) will have a huge role in healthcare. Healthcare has been a latecomer to using IT as a tool but the future looks good. AI and its children – ML, IoT, and M2M are excellent candidates for advancing technology in healthcare. There is a real potential for technology to advance what I have termed “Connected Continuum of Care” in one of my blogs. This means that with wearables and other Internet of Healthcare Things (IoHT), creating a biome where the patient and doctor/hospital are always connected would become a reality. Always-on Internet is the future and extending that to healthcare is a natural progression. With the price of Internet in India being one of the lowest in the world, we will be in an excellent position to incorporate technology in advancing healthcare delivery.   


Q2. Nishita Mehta: What are the unique challenges of working with clinical data? 

A. Inder Davalur: 

Doctors. Well, the challenge lies with the fact that most clinical data is unstructured. Doctors and hospitals are notorious for NOT wanting to follow standards when it comes to coding diagnoses and treatment. Adoption of DSM, Snomed, ICD codes is very spotty. Physicians complain about the inconvenience in the classifications and prefer to use free text in writing their diagnoses and treatment protocols. This creates a credibility gap in how clinical data can be meaningfully classified and analyzed for any useful prediction or AI driven protocols. EMR applications in India struggle with the similar challenges with physicians disagreeing on a set of standards in capturing and documenting clinical data. 

Q3. Nishita Mehta: Healthcare seems to be moving from the use of structured data to unstructured data. What is the difference between them when it comes to clinical utility & improving patient outcomes?

A. Inder Davalur:  

Healthcare has always suffered from a lack of structured data. Unstructured data creates several challenges in a software trying to classify the same diagnosis written with slight variations. The same fate awaits treatment plans. If medical coding (DSM, ICD etc.) is followed, it will enable any analytics software to make sense of the data and provide useful insights. With AI, structured data is still king. Predictability of an outcome for a set of patient symptoms, medications, prior history, genetic propensity, lifestyle habits would have a high accuracy 

Q4. Nishita Mehta:What do you think does a hospital need to implement Big Data solutions, i.e. Big Data Analytics Capabilities in terms of infrastructure and personnel requirement?

A. Inder Davalur:  

One of the major challenges a CIO or an IT head faces in a hospital is the lack of budget allocation for anything beyond the basic networking, computing and storage needs. Hospitals do not see the value in the data they currently possess most likely because they are more empirically driven rather than evidence driven. What this means is that hospitals and by nature the doctors who hold a sway over management decisions are more comfortable with their own decades of experience over some hotshot CIO trying to promote the idea of data mining and predictive value of patient outcomes based on past data. There is also a severe shortage of technology-rich personnel in hospitals due to the dull routine of maintenance of existing hardware and software rather than experimenting with new technology. The pay structure for IT personnel in hospitals is also woefully poor in comparison to the technology companies. All these factors combine to deter anyone who is driven to create in hospitals a digital core

Q5. Nishita Mehta: While Big Data can generate a plethora of interesting patterns or hypotheses, there is still a need of experts to analyze the results to confirm whether they make sense or merit further inquiry. Would you like to comment on this?

A. Inder Davalur:  

Absolutely. Right now, there is a paucity of people with skills to interpret and recommend action plans once an organization implements any sort of analytics software. Unlike other verticals, healthcare is lagging far behind in its focus on data interpretation and application in its business model. It might be a whole decade before hospitals wake up to the reality of meaningful interpretation of data and building an action plan around it


Q6. Nishita Mehta: What are the major drivers of Big Data Analytics in healthcare in India?

A. Inder Davalur:  

Have not seen much evidence of it. Perhaps some hospitals have ventured into some basic AI driven applications in specific areas such as pharmacy sales or patient wait times. Other than that, BDA is yet to catch up.

Q7. Nishita Mehta: What are the key benefits Indian hospitals will draw from implementation of Big Data Analytics? 

A. Inder Davalur:  

First and foremost, hospitals will get to see for themselves how poorly structured their data is. BDA for Indian hospitals can cover a better management of the following: 
  1. Sponsored
  2. Accounts Receivables
  3. Professional Fees
  4. Disposables and Consumables
  5. Pharmacy – Generic vs brand name consumption
  6. Targeted marketing
  7. Continuum of Care post-discharge
  8. Predictability of illness propensity from regular Health Check ups
  9. Results-oriented tasking for better output from employees

Besides these areas, hospitals can contribute tremendously to public health issues by sharing anonymized patient data with the State Health Department which can then study outbreaks and lifestyle disease patters in the general public. 

Q8. Nishita Mehta: How does Big Data Analytics help better decision-making & building disease understanding?

A. Inder Davalur:  

One of the most ignored areas is a deeper dive into results from investigations. Empirically speaking, the values considered “normal range” are never questioned. If a better study is conducted, what is normal for one cohort may not be so for another cohort. As an academic exercise, I had a simple deep analysis done to study the correlation between borderline values of lipid profile and any other element from a blood test. The result was a high (>70%) correlation between borderline lipid profile values and an elevated monocytes count. It turned out that among those who fell in this group, nearly 78% of them were later admitted for some coronary complication. The medical reason is that the monocyte levels are elevated when there is presence of a heart disease. Every one of these patient was merely getting a Health Check. Imagine if hospitals did such studies on a multitude of investigations routinely conducted for patients and conducted regular follow ups as a preventive measure

Q9. Nishita Mehta: One of the biggest concerns in healthcare is the rising costs. What potential solutions does Big Data offer for this problem in Indian context?

A. Inder Davalur:  

India’s population is now facing more mortalities from lifestyle diseases – Non Communicable Diseases (NCD) as opposed to communicable diseases. There is a great potential to flip the business model of the healthcare industry to go from disease management to health management. I have written blogs on this topic. The premise is very simple. Make it more profitable for hospitals to keep the public healthy than to treat them. If the payment structure is modified to increase the prices for health checkups and promoting healthy prophylactic therapy methods as opposed to coronary by-pass surgeries, it could completely change the paradigm. These prices can be graded based on age. All old age related treatments can receive higher prices; while treatments like a heart surgery for a 40-year old can be less. At the same time, therapeutic treatments for younger population geared for promoting good health can receive higher prices. A larger healthy population means a larger market for the hospitals. This ensures that the hospitals have a higher incentive to make the healthy population larger

Q10. Nishita Mehta: What would you highlight as being the major challenges today in developing & actually implementing Big Data Analytics capabilities to truly extract meaningful insights?

A. Inder Davalur:  

An urgent awareness creation among promoters and owners of hospitals of the benefits of investing in the technical hardware and personnel resources to build and maintain a BDA infrastructure. Without that awareness, IT costs are always seen as a sunken wasteful expenditure as opposed to an investment. There is nothing else lacking in this respect.

Q11. Nishita Mehta: Do most doctors now have a checklist for what they should be doing with patients with certain conditions? How does Big Data solution change what they are doing currently?

A. Inder Davalur:  

Hard to predict. Most clinical pathways and treatment protocols are traditionally empirically driven. It is hard to imagine a medical community to take notice of what BDA might reveal and radically change their protocols. That said, things have changed – take robotic surgery – and there is hope and a high degree of probability that medicine might be “data-powered” (my phrase over the more commonly used data-driven) offering the physician to choose to use such data-powered results wherever she finds it viable or desirables

Q12. Nishita Mehta: How do hospitals need to adapt to embrace the full potential of data-driven innovation?

A. Inder Davalur:  

Promoters and owners having a greater understanding of the power of data

Q13. Nishita Mehta: How important do you think Big Data Management & Analytics is right now to enhance healthcare in India?

A. Inder Davalur:  

Tremendously. With the technical resources at its disposal, India would be imprudent not to take full advantage of the benefits of BDA. Population health data is one of the most ignored among developing nations. India would do extremely well to develop and use BDA for advancing population health

Q14. Nishita Mehta: What do you see as the main emerging opportunities for hospitals from greater adoption of Big Data Analytics?

A. Inder Davalur:  

Connected Continuum of Care (a phrase I first used in a blog) is a concept of keeping the patient engaged post treatment and post discharge through the use of wearables and IoHTs (Internet of Healthcare Things). This ensures that hospitals are not merely agents in episodic encounters and instead become agents of well-being. BDA will help provide the big picture in the overall health and well-being of the population it serves

Q15. Nishita Mehta: What are some of the biggest challenges facing the healthcare industry in terms of its ability to use Big Data to improve healthcare outcomes?

A. Inder Davalur:  

A better understanding and incentive to invest in the infrastructure is all it takes. Once that happens, India is best equipped to leverage from its large technology-aware population. At the hospital level, BDA could help establish a new approach to purely outcomes-driven pricing structure and treatment protocols that would be data-powered. 

Q16. Nishita Mehta: Would you like to share additional insights on the topic, which I might have missed?

A. Inder Davalur:  

Public-Private-Partnerships with educational institutions and hospitals would also be beneficial. There is going to be a severe shortage of technical resources who are trained in AI and BDA by 2020. If the government partnered with colleges to promote courses and training in AI and BDA India could be the largest supplier of technical talent to the world. If hospitals also partnered with the government to share health data, the state of overall population health will rise and costs will come down.

The article was first published on Mr. Inder Davalur’s LinkedIn Pulse page. The blog was Mr. Inder’s answers to Ms. Nishita Mehta’s Survey published on the HCITExpert Blog earlier, here. I would like to thank both the Author’s for sharing their insights via the HCITExperts Blog. 
Team @HCITExperts [Updated: 03 rd Sep 2018]
Authors
Nishita Mehta

Ph.D. Scholar at SYMBIOSIS INTERNATIONAL UNIVERSITY

Inder Davalur

Inderjith Davalur is a healthcare technology specialist, speaker, writer and utopian dreamer.
Inder works with hospitals committed to transforming the healthcare paradigm with the aid of new innovative technologies. His primary area of interest lies in using data analytics and technologies such as Deep Learning to shift the current physician-driven healthcare model to a patient-driven market dynamic.
Inder focuses on the manifold ways in which data crunching and machine learning can lead to better diagnoses that can not only be made at the time of illness, but predicted way before any symptoms surface. The path ahead in the sector, he believes, lies in the deployment of evolving technologies that immensely influence both diagnostic and therapeutic aspects of healthcare, delivering real patient-driven, data-enabled, informed healthcare.
Inder currently works as the Group CIO at KIMS Hospitals Private Limited, Hyderabad and has previously assumed leadership roles at leading hospitals and companies, in India and the United States of America.

Glossary of terms and acronyms for #Blockchain and #Cryptocurrency


Blockchain: The foundational technology behind the blockchain and cryptocurrency sector. It is a virtual, immutable (unchangeable), distributed store of data stored on servers around the world. This is a new way of distributing both trust and data. It is an alternative to traditional systems where a central organization holds all the data.

Think of it as a chain of blocks of data, verified by consensus by any computer that chooses to participate. Each block of data containing anything from who has sent cryptocurrency to others to who owns what plot of land in a land registry.
Blockchain is a distributed ledger.
Block: A package of data containing multiple transactions over a given period of time.
Chain: The cryptographic link that keeps blocks together using a ‘hash’ function.
Distributed ledger: This is an analogy often made about blockchains. Instead of a centralized bank ledger, blockchains offer the promise of distributing balances throughout a network of computer servers.
You aren’t going to a single bank to store where you send your value — instead, you are going to a decentralized network of peers.
Distributed ledgers aren’t a new concept: the island of Yap used individual tables as early as 500 AD. They yelled at one another whenever they made a new transaction. Blockchains and cryptocurrencies offer the global, virtual network equivalent of that system.
Cryptocurrency: A token or currency built on top of blockchain technology. This token helps capture and distribute value from users of the blockchain. You can think of Bitcoin as the first application and cryptocurrency stemming from the blockchain. Cryptocurrencies are a subset of what are known as cryptoassets. 
Tokens: The means of exchange to give value to a transaction; typically a native cryptocurrency. Some non-currency blockchain architectures can be tokenless.
Cryptocurrency Exchange: Cryptocurrency exchanges are websites or services that let you exchange digital cryptoassets and cryptocurrencies between one another or exchange fiat currencies such as the US dollar for cryptoassets. Two of the most prominent examples of these exchanges are Coinbase and Binance.
Public/Private Keys: Keys are your way to access crypto balances and to send and receive value or data in cryptocurrency. Your public key is like your email address. It’s what allows other people to send you funds. You can share your public key with the general public.
Services like Etherscan can scan account balances and transactions associated with a public key.
Private keys are the password to your email account. Anybody who holds the private key to a wallet can access and control it and spend any tokens within it. It’s a unique string of data that represents proof of identification within the blockchain, including the right to access and own that participant’s wallet within a cryptocurrency. It must be kept secret: it is effectively a personal password
A unique string of data that identifies a participant within the blockchain. It can be shared publicly.
If you lose your private key or forget it, you’ll lose control of all the crypto assets tied to that private key/public key combination.
Cryptocurrency Wallets: Cryptocurrency wallets are ways of storing your private and public keys to your cryptoassets. A wallet is a safe you can access to then get your keys.
Wallets allow for easier access and backups if you don’t remember your private key with techniques such as the mnemonic seed phrase, a series of 25 random words you have to input to get access to your private key.
There are software wallets and hardware wallets: software wallets store your keys online, while hardware wallets use a physical device such as the Trezor to protect your private key.
MultiSig: MultiSig is a permissions system for crypto wallets. The majority of cryptocurrency wallets are single-signature. This means you only need one person’s private key to control the balance within it.
MultiSig means you need more than one private key to spend funds. This allows you to set up an M-of-M scheme. As an example, you might need 5 out of 9 signers to approve of a transaction for it to go through. This is useful for corporate wallets, where many owners and employees have to approve before a transaction is sent.
Platforms like BitGo and Xapo provide MultiSig wallets for their users.
Proof-of-work: A system where blocks of transaction data on the blockchain are mined and validated by specialized computers who earn a reward for solving specific math equations. Repeatedly running a hash function, the mechanism by which data miners win the right to add blocks to a bitcoin-style blockchain.
Mining: A practice in proof-of-work systems where computers are dedicated to solving math problems in order to claim the right to mine a block of data and to get an amount of cryptocurrency.
How it works in some more detail: the cryptographic mining piece involves solving cryptographic puzzles. A computer needs to find a nonce to combine with unverified transactions to output a verified string.
Data Mining:  The process of solving cryptographic problems using computer hardware to add newly hashed blocks to a public blockchain such as bitcoin. In fulfilling this function, successful data miners keep the blockchain actively recording transactions and, as an incentive, are awarded newly minted bitcoins for their trouble.
Mining poolA mining pool aggregates computing resources dedicated to mining cryptocurrencies and allocates any of the mined blocks proportionally. In practice, mining cryptocurrencies has some randomness to it, so mining pools serve an essential purpose in keeping volatility down for individual miners.
Proof-of-stake: Proof-of-stake pushes people who own a selection of a blockchain’s tokens to make decisions on validating the chain. In practice, it’s a much less energy-intensive practice than mining.
Resource to read: Proof-of-stake – Wikipedia
Node: Any computing server around the world can run as a cryptocurrency node, which can store a copy of the blockchain and serve to verify transactions.
Hash The result of applying an algorithmic function to data in order to convert them into a random string of numbers and letters. This acts as a digital fingerprint of that data, allowing it to be locked in place within the blockchain.
Hash Rate: A measure of the computing power dedicated to any blockchain by the miners validating transactions and blocks. The higher the hash rate, the more active the chain is and the more appealing it is to miners. It then becomes harder to attack the chain, and infiltrate it with false transactions (known as a 51% attack).  
Decentralization: A measure of how much authority is held by a central holder. You can argue that blockchains are naturally more decentralized than other methods of distributing data because there is (at least in public chains) no gatekeeper on who can join: as long as you have the computing power, you can participate in the blockchain.
Instead of all of your data residing in one central provider (ex: Equifax), it now sits and is processed and verified by a global network of computers.
Decentralization is an ideal of the blockchain community. However, it has not been perfectly achieved.
For example, the mining pools that mine most of Bitcoin are mostly based in China: a consortium of these mining pools might decide to do what is called a 51% attack. They would use their assembled computing power to change the rules of the blockchain and facilitate conditions such as “double spend”: the ability to infinitely spend the same block of cryptocurrencies, essentially creating wealth out of nothing. The control of mining resources is very centralized.
Public vs. Private Chains: There are blockchains open entirely to the public (anybody can participate) such as Bitcoin and Ethereum. There are also private blockchains that have gatekeepers who determine who can join.
Private blockchainA closely controlled network operated by consortia in which the data is confidential and is accessed only by trusted members. Private blockchains do not require a token.
Interoperability: Blockchains and cryptocurrencies are often isolated with one another, and need to be exchanged in order to be used.  
Blockchains like Aion are looking to solve the interoperability piece by making different blockchains and cryptocurrencies interoperable, or compatible with one another: imagine, for example, a world where you can trade Bitcoin and Ethereum seamlessly (without exchanges) and use them interchangeably.
Atomic Swaps: Atomic swaps involve cryptocurrencies that are tradeable with one another without needing an exchange in the middle. Typically, they have to follow the same encryption standard and have a payment channel protocol such as Lightning Network. With what’s called a hash-time locked smart contract, two individuals can trustlessly trade cryptocurrency pairs with one another: solving the interoperability piece.  
Hash functions/tables: A more technical and precise description of the underlying technical foundation of how data is shared and stored on a blockchain. Hash tables are a mainstay of computer science.
Bitcoin: Bitcoin was created by Satoshi Nakamoto in 2008 as the first application of the blockchain and as the first cryptocurrency. It is still the dominant cryptocurrency now.
Fork: There are soft forks, where a cryptocurrency maintains its value and its rules are simply rolled forward and changed in a reversible manner, usually with the assent of the majority of the community.
Hard forks are when a blockchain fails to reach consensus and has to do a hard reset and splits off into two chains. One chain adopts one set of rules and another continues the original set of rules. This is non-reversible. A hard fork is how Bitcoin and Bitcoin Cash split.
SegWit: Segmented Witness (or SegWit) is a soft fork that happened with the Bitcoin blockchain. It solved congestion on the network by increasing the blockchain’s block size limit and splitting blocks of data in two. It separated out the unlocking signature with the scripts that send and receive data with the transactional data.
This allows the network to process more transactions per second. Users don’t have to wait as long for bitcoin transactions.
Resource to read: Segregated Witness, Part 1  
Lightning Network: Lightning Network is an off-chain solution that can settle transactions without having to use the underlying blockchain. It opens up bidirectional payment channels between different individuals, allowing Bitcoin to process many more transactions per second.
Payment channels have pre-deposited amounts of crypto placed into them. They allow individuals with channels open between them to transact seamlessly without using the blockchain. Once you get a final balance, it is validated into the blockchain.
This allows for many more payments to be done per second. It also means there is some centralization between large payers.
Resource to read: Lightning Network
Schnorr: A large Bitcoin update brewing as of the time of drafting for this article, Schnorr proposes to give users a new way to generate the private and public keys critical to cryptocurrencies. It replaces the Elliptic Curve technique currently used to generate keys with the Schnorr technique.
This update increases both privacy and security by grouping together MultiSig and regular transactions in the same category, allowing the blockchain process to more transactions and hiding whether or not a transaction is MultiSig or not.
Ethereum: The blockchain behind the second largest cryptocurrency. Ethereum differentiates itself from Bitcoin by allowing programmers to build on top of the blockchain with a Turing-complete programming language. This allows programmers to build distributed applications.
While Bitcoin can be seen as one application (transfer of value) on the distributed web just like email, Ethereum is a network that allows for many different applications to come to the fore.  
The cryptocurrency associated with the Ethereum blockchain is known as Ether.
Decentralized Apps (DApps): A decentralized application is a specific type of app that serves a specific purpose within a blockchain network. It must be open-source, autonomous, and it must make changes to the underlying software via consensus from its users. It must store all its data on a public blockchain, which is auditable by the public, and it must generate tokens and be accessible via those same tokens.
DApps seem like regular web applications. Client-side, the same mechanism is in play, but server-side (or the back-end), data and control are distributed among a network of P2P (peer-to-peer) nodes and smart contracts rather than a centralized set of servers and server code.
Resource to read: DApps – Flipside Crypto
Smart Contracts:  Smart contracts refer to code that is placed on a blockchain and is then executed on it. The code can be audited by the public. Smart contracts are often regarded as a compliment or a replacement to traditional legal contracts.
A smart contract might algorithmically implement escrow payments without having the need to create a binding legal contract to hold parties accountable.
However, the term is often seen as overly broad as it can mean any block of code placed on the blockchain.
Gas: Gas is used as a transactional cost in the Ethereum blockchain. When you use Ether to access distributed applications, you have to spend a portion of gas associated with it. Gas is correlated with how much computational work your request takes. This ensures that transactional costs are rightly set for the amount of work the system needs to do.
Gas is a way to ensure that nobody tries to attack the Ethereum network by filling it with invalid requests.
Solidity: Solidity is currently the most popular programming language to write smart contracts on the Ethereum blockchain, based around EMCAScript (the basis of JavaScript).
DAO: DAOs or decentralized autonomous organizations are a collective grouping in which smart contracts make choices. The entire organization is run on the blockchain. Shareholders buy tokens that give them the right to vote on future decisions.
Resource to read: DAO – Flipside Crypto
Casper:  Casper is an implementation of the Ethereum blockchain that promises to process more transactions per second. Ethereum used to be able to process 20 transactions a second. Bitcoin could only process 4. Visa and Mastercard can process about 20000 transactions a second. Casper is an in-between step for the Ethereum blockchain to change over from proof-of-work to proof-of-stake. It implements sharding (dividing the main Ethereum chain into smaller subcomponent chains) to provide parallel processing and increased throughput.
ERC20: A set of standards based on the Ethereum blockchain. ERC20 allows anybody to create a token built on top of Ethereum’s blockchain. It is the basis of the initial coin offering craze and the advent of new “altcoins”.
Altcoins: Altcoins are tokens, cryptocurrencies and cryptoassets outside of Bitcoin and Ethereum. Coinmarketcap gives you a good view of how many there are!
Stablecoins: Stablecoins are cryptoassets pegged to a certain value or asset — for example, you have stablecoins that trade 1:1 with the US dollar. These are collateralized or not with other cryptoassets.
Initial Coin Offering: Another way to originate tokens for a blockchain. An ICO involves a marketing process, private sale, then a public sale of a newly-listed token, which then aims to be listed on as many cryptocurrency exchanges as possible. Note that there is no standard way of conducting initial coin offerings.
Hyperledger An umbrella project set up by the Linux Foundation comprising various tools and systems for building open-source blockchains.
Oracle: A bridge from a blockchain to an external data source that allows a smart contract to complete its business by referencing timely real-world information. An oracle might allow a smart contract to access consumer energy usage, live train timetables, election results, and so on.
Peer-to-peer (P2P)The direct sharing of data between nodes on a network, as opposed to via a central server. 
Permissioned ledgerA large, distributed network using a native token, with access restricted to those with specific roles.
Proof of stake The mechanism by which participants earn the right to add new blocks and so earn new tokens, based on how much of that currency they already hold.
Public blockchainA large distributed network using a native token (such as bitcoin), open to everyone to participate and maintain.

References: 

[1]: A definitive glossary of blockchain and cryptocurrency terms: 
https://thenextweb.com/contributors/2018/08/21/a-definitive-glossary-of-blockchain-and-cryptocurrency-terms/

[2]: Flipside Crypto’s guide to blockchain and cryptocurrencies:  https://flipsidecrypto.com/wealthadvisor-ebook/
Team @HCITExperts [Updated: 1st Sep 2018]
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