India Leads the Way in Digital Health

 

India is in the midst of what some have dubbed the “world’s biggest healthcare overhaul.” In addition to recently launching one of the world’s largest publicly funded health insurance programs, set to cover some 500 million people living in poverty, the government has also been working diligently to develop a new digital health strategy for the nation.

The work on the strategy began more than five years ago, when the Ministry of Health and Family Welfare and the Ministry of Communication and Technologies developed a new set a metadata and data standards for health – essentially a common set of standards for the collection, creation, and coding of all health data that can be easily transferred across computers and information systems anywhere in the country. The standards were based on global best practices but adapted to better serve the local context. Previous to its work on data standards, the government also developed a system to allow it to issue a National Identification Number to all healthcare facilities in India.

These efforts have now put the government of India in a position to launch a new National Digital Health Blueprint. The blueprint, which is now open for public comments and consultations, validates the six pillar strategy that ACCESS Health has advocated for, namely:

1. A governance methodology and framework to help the digital health blueprint bring balance between patient privacy and scale.
2. Highlight the value and role of standards-based system design, including meta data and data standards for health, the health data dictionary, and registries.
3. A Health Delivery Information System to better manage healthcare provider operations, including software for patients medical records.
4. A Health Insurance Information Platform to provide better underwriting support for government schemes and to manage fraud and risks.
5. Electronic Health Records and a Health Information Exchange to provide citizens access to their health records and allow policy experts to understand disease burdens patterns.
6. Information and communications technology for infrastructure and capacity building to support digital health transformation.

A number of key members now on the ACCESS Health Digital Health team previously worked on the metadata and data standards initiative and on developing the national identification numbers. Their work was carried forward in the national blueprint.

In addition to its impact in India, the work the government has undertaken is likely to become a model for other emerging nations. The blueprint highlights some of the key points that ACCESS Health believes should be a part of any national digital health strategy. These include:

The need for federated governance and technology models to reflect the healthcare system, given that healthcare in India is a state-related subject;

The need to shift focus to more preventive medicine via a focus on strengthening the primary healthcare system and promoting alternative schools of medicine;

The importance of issuing of a personal health identification number that allows consent-based identification and portability of medical records across the continuum of care;

The importance of a mobile-first design approach that recognizes the growing penetration of telecommunication links on the back of low data tariffs;

The need for a data-driven approach to health policy making that recognizes the role of disease registries for accurate capturing of health burden; and

Recognition that there’s a need for keeping citizens healthy and productive to achieve economic growth as sick citizens become a burden on the system.

ACCESS Health Digital team looks forward to supporting the Government of India in its ongoing efforts to develop and implement this critical new strategy to improve health in the country.

https://accessh.org/india-leads-the-way-in-digital-health/

Healthcare Wallet will Emerge!

 

Healthcare Wallet will Emerge!

India is poised for 10 fold increase in digital payments. Will become 4th largest in the world after Singapore, Sweden and USA. This will have a profound impact on Digital Health. Will become a major driver in adoption of Digital Health across payer and provider systems.

Consider This:

Health Insurance coverage has gone up from 3% of Indias population to over 40% with Ayushman Bharat.

90% of Health Insurance claims is reimbursement of out of pocket out patient expenses related to the inpatients episode.

Insurance is more comfortable reimbursing a Digital expense because it reduces the chances of fraud and abuse. From a Actuarial perspective the risk comes down because of full traceability.

Patients will gravitate toward clinics and hospitals that provide Referrals, Prescriptions, Reports in Standards based electronic format. Because Insurance companies will clear the standard eClaims format faster.

About 8% of out patient gets converted to inpatient procedures for any hospital OPD. Any reduction in out patient foot fall will negatively impact the inpatient load and hence the top line.

A Fintech based rating engine will appear to rate the clinics and hospitals. This rating engine will be far more pervasive than the Practo rating engine because money in the pocket is always a more powerful driver.

A whole new sand box gets created for the digital health startups, software vendors and fintech companies to play. Someone will fill the vacuum. For lack of a better word a Paytm or Jio Wallet for Healthcare expenses and reimbursements is on the anvil.

India will be the next battleground for Global Retail and Healthcare! After USA, India has the largest user base for the Internet Giants like FB and Google. Amazon is in India. Walmart is picking up majority stake in Flipkart. All the Internet and Retail giants have expressed interest in Healthcare.

Can you extrapolate the Dots? I can see the Trend! Fintech fueled transformations are underway.

The real innovation in mobile payments in India began a few months prior to the cash ban. It’s called a unified payment interface, or UPI.

With more than 140 Indian banks sharing the interface, and Alphabet Inc.’s Google and Facebook Inc.’s WhatsApp offering instantaneous payment services on it, UPI has become a keenly watched experiment. By the looks of it, things are going well: From nothing to 800 million monthly transactions in less than three years, India’s UPI has taken off. Growing smartphone use and crashing data costs have helped immensely.

Google and WhatsApp will fight for market share. So will PhonePe, now owned by Walmart Inc. as well as new entrant Amazon Pay, which hasn’t made much of a dent globally into PayPal’s dominance of e-commerce. Indian banks that run their own UPI services. Indian tycoon Mukesh Ambani’s Jio with its 300 million subscribers will push JioMoney. Masayoshi Son and Warren Buffett will keep an eye on their Paytm stakes.

Now RBI has removed charges on RTGS/NEFT transactions; and asked banks to pass on benefits.

Cities Perspective:

Tier 1 cities: Pune, Bengaluru, Chennai are leading the wave in UPI transactions. Pune topped the city list, with the highest average digital spend — per person per month — of ₹16,513. Followed by Chennai at ₹14,208 and Bengaluru at ₹14,000.

Tier II and III Cities: Razorpay says by 2020, 40 per cent of digital payment transactions in the country will be driven by businesses and consumers in Tier-II and -III cities, and 50 per cent of internet users will be using digital payments. Whereas Paytem says - We have been witnessing a tremendous increase in adoption of digital payments in tier II & tier III cities that constitute 50% of our total user base. Surat, Durgapur, Rajkot, Meerut, Imphal, Rohtak, Panipat, Mangalore, Ranchi, Puducherry, Rajamundri, Warangal, Jodhpur, Thrissur, Karnal, Madurai and Jamnagar are among the fastest adopters and are leading the wave of digital payments adoption.

Users of wallets are not updating their KYC (know your customer) details. Instead, they are using UPI (Unified Payment Interface) to make digital payments. Anyhow total payments via digital instruments are expected to be between $400-500 billion in 2020, up from $50 billion in 2017.

Hold your breath guys! Fintech is the digital health roller coasters.

India has its own National Digital Health Standards Now

Role of #DataQuality and #DataGovernance in #PrimaryHealth and #PublicHealth

Dr Pankaj Gupta, Primary Health Care 2017, 7:1(Suppl), DOI: 10.4172/2167-1079-C1-005, ISSN: 2167-1079 PHCOA.

Meta Data and Data Standards [MDDS] for Health was written in 2013, 
the MDDS for Health was Released and Notified in August 2018, 
now included in the National Digital Health Blueprint [NDHB] in 2019.

Abstract:

The Public Health System in India is struggling with multiplicity of information systems being used at central as well as at state level. Each of these systems is unable to exchange data and information with each other. To overcome similar challenges across ministries, the Ministry of Communication and Technologies initiated semantic standardization across various domains under Metadata and Data Standards (MDDS) project. The intent was to promote the growth of e-Governance within the country by establishing interoperability across e-Governance applications for seamless sharing of data and services. MDDS for health domain was created by adopting global standards in such a way that existing applications could be easily upgraded to the MDDS standards. The exercise yielded approximately 1000 data elements. These data elements were expected to serve as the common minimum data elements for development of IT applications for various sub domains of health care. The need for the CDE arose because most of the primary and public health IT applications are being developed without any standards by different agencies and vendors in public and private sector in India. Each application is developed for standalone use without much attention to semantic interoperability.

Later when the thought of interoperability emerges – it becomes difficult to connect the primary and public health systems and make them talk to each other because they were never designed for that purpose. Even if technical and organizational interoperability is done the semantic interoperability may remain a challenge. For example – all primary and public health applications must have the same Facility Master. When application A sends the ANC data for facility 123, the receiving application B should understand ANC and uniquely identify facility 123. Another example is if a hospital application sends the insurance reimbursement bill to insurance company/government, the recipient application should be able to understand and represent the same meaning of bill information.

Ministry of Health & Family Welfare has initiated development of the national health facility registry. The registry was intended to standardize facility masters used across public health information systems. Standardization of facility masters is required for two purposes, first when exchanging data the sending and receiving applications should be able to identify health facility similarly. For example – when application A sends the maternal health data for facility 123, the receiving application B should understand maternal health data and uniquely identify facility 123. Second, in public health, performance of each of the facility is assessed using aggregate indicators and facility master serve as the secondary data source on which primary program specific data is aggregated. For example data from number of doctors from system A and total outpatient attendance data from system B could be analyzed to get per doctor patient load across health facilities only when both applications use common facility masters.

Specific On the Ground:

E-Governance systems for Health which are operational today include a variety of applications such as Mother and Child Tracking System (MCTS), Health Management Information System (HMIS), Hospital Information Systems (HIS), Supply Chain Management for Drugs and Vaccines, Integrated Disease Surveillance Project (IDSP), Revised National Tuberculosis Program (RNTCP) etc. There are states with over 30 distinct operational systems. The Private Healthcare sector also eludes transparency by hiding behind an equally diverse maze of complicated data silos.

1. Introduction:

The Metadata and Data Standards is an initiative taken by Ministry of Communication and Technologies under National e-Governance Plan (NeGP). The intent was to promote the growth of e-Governance within the country by establishing interoperability across eGovernance applications for seamless sharing of data and services. Under the MDDS initiative domain specific committees have been constituted in priority areas. The Health Domain MDDS Committee was one such initiative, which was constituted on Sept 2012, under the chairmanship of Joint Secretary in pursuance of communication received from Secretary, Ministry of Electronics and Information Technology (MeitY) previously known as Ministry of Communication and Technology.

Post formation, the Committee had initial orientation meetings on Metadata and Data Standards development for health domain. After initial discussions, National Health System Resource Centre was constituted as secretariat for the committee. To help develop Meta Data & Data Standards, two agencies were brought on-board following a proper selection process based on their merit on Health informatics. The due diligence was thoroughly done to study the landscape of existing health domain by involving all relevant stakeholders and knowledge partners including Program Officers and System Managers of Central and State Health IT Systems. As part of terms of reference, a thorough study of global data and interoperability standards were taken into account.

Initially generic data elements were extracted from the existing health IT systems. However these existing systems were geared towards addressing specific program requirements which was falling short to address the vast scope of Health domain. The other challenge was that data elements of these systems were not aligned with global data standards. Efforts were made to adopt and modify global standards in such a way that these existing applications could easily be upgraded to MDDS standards.

The exercise yielded to approximate 1000 data elements which were regrouped and formatted into 39 entities for better assimilation and presentation. These data elements will serve as the common minimum data elements for development of IT applications for various sub domains of health care. This is intended to facilitate interoperability among all these applications.

2. Purpose of Health Domain MDDS

The adoption of Metadata and Data Standards across healthcare IT systems will enable easier, efficient exchange and processing of data. It will also remove ambiguities and inconsistencies in the use of data. Once the MDDS standards are adopted by all eGovernance applications in healthcare, the interoperability would be easier.

Inevitably the migration to these new Standards may appear at the outset to be costly and time-consuming to some parts of government. However this burden should be outweighed by reduced development costs through the use of the agreed schemas that use these standards. It is also expected that new IT system in healthcare, as and when they come will use MDDS standard and will participate in information sharing and data exchange.

3. Structure of the MDDS Standard

The Metadata and Data Standards in Health Domain are developed following below mentioned guidelines set by MeitY. a. Metadata and Data Standards – Demographic v1.1 b. Operational Manuals for formulation of Domain specific MDDS c. Institutional Mechanism for formulation of Domain specific MDDS

As per the guidelines the MDDS Standards are broadly covered under three sections as given below. 1. Data Element Quick Reference (ref: Part-II) 2. Code Directory Quick Reference, Sample values and their structure (ref: Part-III) 3. Data Element Metadata (ref: Part-IV)

Data Elements common across all health domain applications are listed, defined and standardised in the Data Element Quick Reference document (Part II). This list gives brief description about the data elements in addition to the data format & size it follows. For easy readability the data elements are grouped in various entities. However these entities should be considered as logical grouping only and users are free to regroup these data elements as per their need. Under the quick reference document, each data element is classified into four categories to help identify following:-

Data elements which can be used from health domain to other domains (Prospective Generic Across Domain (Viz.: PGAD) Data elements which are common within health domain (Prospective Generic Within Domain (Viz.: PGWD)),  Data elements which are customised from already standardized generic data elements (Custom (Viz.: C))  Data elements which are application specific in health domain (Application (Viz.: A)).

Health Domain MDDS has followed ISO/IEC 11179 standard for development of data elements, value sets and code directories. As per the conceptual design of data element in ISO/IEC 11179, each data element can have a single value or multiple values attached to it. The data element which has a single value will be complete in itself and if a data element has a limited list of values associated with it, then those values will be a part of value list for that data element. However if there is a long list of complex values for the data element, they have been put in relevant code directories. Values in the code directories can grow and mature with review and modification.

Code Directory Quick Reference document is ready reference to the code directories developed (Part III). This indicates name of code directory, source of code directory and the ownership rights for each of the code directory. The metadata of each code directory is given in the Code Directory Meta Data and the sample values for each code directory are also populated in the Part III of the MDDS Standard. The sample value for each code directory is populated in the Part III. Some code directories (i.e. Inventory Store Master; Employee Master; Service Tariff; Package; OT Preference Card; Blood Bank Master; Ward; Bed; Authority; Supplier Master; Laboratory Master; Floor Master), which are highly implementation specific, no sample values are populated and it is expected that each implementer will populate the values in these code directories and help MDDS committee to enrich these code directories. In addition there are few code directories (i.e. Test Result Reference Range; Homeopathic Generic Drug; Non-Drug Item Brand; Homeopathic Brand Drug; Brand Drug; Manufacturer Master; Equipment Classification; Equipments; Ayurvedic Generic Drugs; Ayurvedic Brand Drugs; Unani Generic Drugs; Unani Brand Drugs) for which standard value set is presently not available. Domain specific Working Groups would be constituted to help populate these code directories. Work is presently going on for population of remaining 8 Code Directories (Facility Master; Facility Type; Ownership Authority; Facility Area Coverage; Facility Beds; Facility Human Resources Type; Administrative Linked or Referral Facility; Facility Services Master) which are part of the National Health Facility Registry initiative of MoHFW.

4. What is Common Data Elements

The Health Domain MDDS Committee provides a list of data elements that will serve as the common data elements [CDE] for any new application being developed in Health domain.

The need for the CDE arose because most of the Healthcare-IT applications are being developed without any standards by different agencies and vendors in public and private sector in India. Later it becomes difficult to connect the systems and make them talk to each other because they were never designed for that purpose.

Due to the inherent complexity of Health domain - It is difficult to create minimum set of data elements that every sub-domain must adhere. Each sub-domain’s minimum data element may not be completely applicable to other sub-domains – meaning ‘My minimum need not be your minimum’. For example the Lab Order data elements required at Primary care setting will be far less than the Lab Order data elements required at Secondary care and Tertiary care settings.

Therefore the health domain MDDS committee has come up with the Common Data Elements. CDE will provide most of the data elements required for any new Healthcare application to be built. However the users may add additional data elements above and beyond the CDE for their local needs. Using CDE the applications would be able to share information with each other. There are two ways to use CDE, either use CDE from the design phase of application development or make applications compliant with the CDE post implementation. The latter option is cost and efforts intensive and may be difficult to implement. It would be easy to use CDE from the design phase of application development.

While developing CDE the attempt was to be universal. However the healthcare is so vast that some specific data elements on the fringes may have been left out inadvertently. CDE is intended to be a living document and a designated Health Domain MDDS Committee will have the authority to add any new data elements, values or code directories that were left out at this stage or that may emerge as a result of natural evolution of the Healthcare domain. When new applications do not find the relevant data element or values for their use, they will have to use ‘Free Text’ data element or ‘Other’ Value from the code directory or value list. Though the usage of ‘Free Text’ data element or ‘Other’ Values will have to be discouraged in principle; however this usage of ‘Free Text’ data element or ‘Other’ Values has to be regularly monitored by the Health Domain MDDS Committee and used as valuable feedback for the next versions of the CDE.

Therefore CDE is intended to be a living document and a designated Health Domain MDDS Committee will have the authority to add any new data elements, values or code directories that were left out at this stage or that may emerge as a result of natural evolution of the Healthcare domain.

Why is Common Data Elements Required?

Organizations often want to exchange data quickly and precisely between computer systems. The need for the CDE arose because most of the Healthcare-IT applications are being developed without any standards by different agencies and vendors in public and private sector in India. Each application is developed for standalone use without much attention to semantic interoperability. Later when the thought of interoperability emerges – it becomes difficult to connect the systems and make them talk to each other because they were never designed for that purpose. Even if technical and organizational interoperability is done the semantic interoperability may remain a challenge. For example – all applications must have the same Facility master. When Application A sends the ANC data for Facility 123, the receiving Application B should understand ANC and uniquely identify Facility 123. Another example is if a hospital application sends the insurance reimbursement bill to insurance company/government, the recipient application should be able to understand and re-present the same meaning of bill information.

5. Health Domain MDDS: Conceptual Framework

The holy grail of Healthcare is the Provider – Patient relationship. The entire common data elements have been designed by keeping the Provider – Patient relationship in mind rather than either entity as the centre. The CDE has been designed based on the standard ISO/IEC 11179.This standard is a result of the following principles of semantic theory, combined with basic principles of data modelling.

Conceptual Domain: The first principle from semantic theory is the thesaurus type relation between wider and more specific concepts; For Example- the wider concept ‘Order’ has a relationship with similar more specific concept Pharmacy Order And immunization order. Therefore the CDE has created Pharmacy Order and Immunization Order entity.

Concept: The second principle from semantic theory is the relation between a concept and its representation. Different synonyms or closely related keywords can convey the same concept. For Example –The number of times the drug/medication has to be taken at what interval is a concept. ‘Frequency of Drug’ and ‘Frequency of Medication’ are different representations of the same concept.

Data Element: The basic principle of data modelling is the combination of an Object class and an Attribute to form a more specific ‘data element concept’. For example- the abstract concept ‘Frequency of Medication’ is combined with the object class ‘Medication Order’ and is associated with Attribute ‘Frequency’ to form the data element concept ‘Medication Frequency’. The standard must select the most appropriate keyword as the representation of the concept. In the above case the o Object: is ‘Medication Order’ and, o Attribute: is ‘Frequency’

Value Domain: A value domain is the permitted range of values for a Concept. If the data element concept has a single value then it will remain as a single data element. If it has a limited set of values attached to it then it will have a value list. If the data element has a long list of values that are liable to change or be modified due to the business needs of the Health domain then it is advisable to create a Code Directory for those values. For Example- For data element concept ‘Medication Frequency’ the related Code Directory will have values: BID, TID, QID, HS, SOS, and Stat.

The associated Code Directories are drawn from standards such as –

• ICD-10 for Diagnosis and Classification: ICD is used to classify diseases and other health problems recorded on many types of health and vital records including death certificates.
• LOINC for Lab and Diagnostics: LOINC is a universal code system to identify laboratory and clinical observations to facilitate exchange and storage of clinical results or vital signs for patient care and research
• Procedure & Radiotherapy Codes (preferred primary terminology): SNOMED CT.
• WHO Morbidity list: The noun morbidity means "the quality of being un-healthful." The special tabulation list for morbidity published in ICD-10 volume 1 consists of 298 groups defined by their ICD-10 codes.
• WHO Mortality list: The noun mortality means "Death" The special tabulation list for mortality published in ICD-10 volume 1 consists of groups defined by their ICD-10 codes.
• WHO ICF: The International Classification of Functioning, Disability and Health (ICF) are used for defining functionality & disability.
• WHO Verbal Autopsy Standards: Is list of standards for causes of death with mapping to ICD-10 Codes.

6. Identifiers and Registries

For data exchange across applications, accurate identification of each person/ facility receiving or providing healthcare services, and also anyone accessing or using this information is extremely important. It is critical that a set of standards be established for identifying the Facility, the Medical Provider, Patient, and all others handling healthcare data so that information across different locations can be exchanged easily and securely.

An Identifier could be a number, image (e.g. Bar Code or Blackberry ID), Biometrics (e.g. finger print or retinal scan), Radio Frequency Identifier Tag (RFID), Smart Card or a combination of these. Considering that none of these identifier standards exist today in Public Health space- The Health Domain MDDS Committee proposes basic number based identifiers. The standard can be upgraded to include Alternate Identifiers such as Bar Codes, RFIDs, Digital Signature etc., as the healthcare industry matures. For now appropriate Data Elements have been created to capture information about these Alternate Identifiers.

With regards to the nomenclature of the Identifiers some qualifiers were followed to maintain the uniformity.

a) Identifiers which were drawn from established sources were used as it is and no change is made in their names. e.g. Unique Identification Number (UID), PAN etc.

b) Identifiers which are proposed to be used uniquely and uniformly across states are termed as “Numbers” e.g. Unique Facility Identification Number, Alternate Unique Identification Number etc.

c) Identifiers where code directory or value list from established source is used are termed as ‘Codes” e.g. Diagnosis Codes (ICD10 Codes) etc.

d) Identifiers which were transaction specific are termed as “Identifiers or IDs”. E.g. Employee ID, Document ID etc. However some of these can come from code directory master but are named as IDs because they are transaction identifiers to be populated at the time of implementation.

I. Facility Identifiers: Facility Identity management is complex – therefore a Facility Code Directory is created to give a structure to it. This Facility code directory will serve as a Master to which all the Applications will refer. Two set of identifiers are proposed to uniquely identify each facility-GUID & NIN.

a. Global Unique Identifier (GUID) – This data element is a 16-bit number, which will be generated following a standardized algorithm by system. An example of a GUID in its standard form is 40e74fae-c0ab-11dfb090-0017f2300bf5. GUID will be used at the back-end to uniquely identify each facility. GUID will guarantee global uniqueness of each facility no matter where or by whom they are generated. All prospective systems need to follow standard algorithm in their backend to use GUID.

b. Facility National Identification Number (NIN)-NIN is a 10 digit random number given for each facility (public & private) engaged in providing some form of health care services. NIN will be used at the front-end with some form of human readability. There are two ways to do this.  Give the facility a number with facility related information embedded in it (e.g. ABC-13-05-0001, where AB&C represents State, District & Block respectively and next two digits represent year of facility formation and next two digits represent type of facility and last four digits represent the facility itself). However this approach has certain challenges as facilities might upgrade or facility attributes change due to administrative, geographic or political realignments.  The other way of doing it is by giving a unique running number to each facility without making this number dependent on any other factor. Where the facility related information can be added as an attribute to the NIN. The Health Domain MDDS Committee has adopted the later approach to uniquely identify each facility.

Why two identifiers for a facility? Although each facility will also be given a sequential 10 digit integer number (NIN) and this is used as a unique facility identifier by all users, still the uniqueness of these codes will be dependent on database system which generate these numbers, which still does not necessarily guarantees to be always unique e.g. if the database is ported from one Database Management System (DBMS) to another, the unique sequential number (or auto increment primary keys of tables) will change. In order to avoid this problem GUID is proposed along with NIN.

Summary:

• MDDS for Health is a library of 1000+ Data Elements logically organised into 39 Entities. Data Elements are Containers that carry the Semantics.
• MDDS has over 140 Code Directories providing the values that go into the Data Element Containers and give the meaning to the Container.
• MDDS leaves it to the market to organize the Data Elements into Minimum Viable Product Definitions or Minimum Viable building blocks.
• Most of these standards are drawn from global standards however these are developed keeping in view local health information systems requirements.

---- Read the Rest in # MDDS for Health Domain Standards on STQC website --

Date Line:

2011, 12th Plan requested for Min. of Health and Family Welfare [MoHFW] and Ministry of Electronics and Information Technology [MeitY] to come together and write Digital Health Standards for India; references to this recommendation are available in the 12th Plan. Public Health IT Study Report coined the term national ehealth authority [#NeHA], now being called national digital health authority [#NDHA]. national health systems resource center [NHSRC] had proposed Health Information exchange [HIE] in the Public Health IT Study Report. You can see it here under Studies and Evaluations: http://nhsrcindia.org/resource-detail/studies-and-evaluations/OTI0

2012, Dr Pankaj Gupta spoke about Digital Health Standards, Health Information exchange [HIE] at the WITFOR. You can read it here: http://www.witfor.org/images/stories/presentations/dr.%20pankaj%20gupta%2C%20partner%2C%20taurus%20glocal%20consulting%2C%20india.pdf

Dr Pankaj Gupta again spoke about Digital Health Standards, Health Information exchange [HIE] @ the eHealth conference Hyderabad 2012. You can watch it here: https://www.youtube.com/watch?v=v048j04FCd0

2013, Dr Pankaj Gupta and Dr Amit Mishra were leading the team that wrote the meta data and data [MDDS] standards for health domain. This was written as a reference Architecture for Digital Healthcare Software and as a framework for Interoperability - Semantic, Syntactic and Institutional Interoperability. MDDS is an Meta Data and Data Standard defined by Ministry of Electronics and Information Technology [MeitY] mandated to be implemented across Ministries.

#MDDS for Health: Committee on Health Domain Metadata and Data Standards has approved the Health Domain MDDS standards. The MDDS is intended to bring semantic interoperability among all health IT system. This is a prerequisite for establishing interoperability among disparate health information systems. The standards were developed following a rigorous consultation and review process and public opinion was also sought and incorporated on these standards.

2016, #NIN_HFI: Completed the National Identification Number for Healthcare facilities of India [NIN_HFI] project. NIN is like a AADHAAR card for all Healthcare Facilities. Facility Registry of the HIE and NHIN will be NIN_HFI. It is based on the Facility Registry defined in the Metadata and Data Standards (MDDS) of Health.

#NIN_HFI is a unique identification number, which a key requirement for achieving inter-operability and creation of EHRs, is being assigned to all health facilities (both public & private) to facilitate inter-operability among health IT systems deployed. So far more than 2 lakh Public Health Facilities have been allocated NIN. The process for setting up mechanism for allocating NIN to private facilities is underway. In other words the National Identification Number for Healthcare facilities of India is the Healthcare Facility Registry.

2017, Role of meta data and data standards in primary and public healthcare, 3rd Annual Congress & Medicare Expo on Primary Healthcare, Clinical & Medical Case Reports. April 17-19, 2017 Dubai, UAE. Pankaj Gupta, Primary Health Care 2017, 7:1(Suppl), DOI: 10.4172/2167-1079-C1-005, ISSN: 2167-1079 PHCOA. https://www.slideshare.net/PankajGupta9/role-of-meta-data-and-data-standards-in-primary-and-public-healthcare

2018, # MDDS for Health Domain Standards Notified by the STQC, Meity, GoI

References:

# PMJAY #AyushmanBharat launch speech by PM Modi.

# Healthcare For All - Four Years of Transforming India (May 2014 - April 2018) - Ayushman Bharat, MDDS for Health, NIN Facility Register..

# Public Health IT Study Report

#MDDS for Health: EHR Standards, Public Health IT Standards, Interoperability Framework and Health Information Exchange

#NIN_HFI: Will serve as the Healthcare Facility Registry https://nin.nhp.gov.in/about_nin2hfi.php

#Digilocker: Will serve as the HIS/LIS/RIS/EHR Document Registry: http://indianexpress.com/article/india/india-news-india/digital-india-scheme-to-focus-on-health-sector-arvind-gupta/

Building a healthy India: The government’s National Health Policy will improve health outcomes and reduce out of pocket expenses - JP Nadda. The Policy recommends establishing federated national health information architecture, consistent with Metadata and Data Standards (MDDS) http://blogs.timesofindia.indiatimes.com/toi-edit-page/building-a-healthy-india-the-governments-national-health-policy-will-improve-health-outcomes-and-reduce-out-of-pocket-expenses/

Informatics in Healthcare - The Statesman: http://epaper.thestatesman.com/c/18200138

Modicare: Worlds Largest Healthcare Coverage Social Security

PM Speech on #PMJAY Launch on 25 Sep 2018

#PMJAY #AyushmanBharat a.k.a NHPM a.k.a Modicare will bring an era of Digital HealthTech platforms [read IHIP] with EHR and MDDS for Health Interoperability Standards to Deliver the worlds largest Health coverage.

Big opportunity for global Health Insurance companies, FinTech and InsurTech to line up and get listed for the program. With Govt acting as a Payer, Provider and Re-Insurer.

Healthcare is a state subject. Centre govt funds 85% of most public health programs. However all the regulation and execution authority is with States. The states are free to accept or totally reject any healthcare ruling from the center. India is too diverse to expect a single Healthcare solution across all States. Unity in diversity is elusive. Hence MDDS for Health based IHIP Exchange platform is required to deliver Health insurance coverage across India.

#PMJAY > Health Insurance will be the driver for the shift to Standard Code Sets based HIS/EHR e.g. ICD-10, SNOMED, LOINC, NPI, etc. As defined in EHR and MDDS for Health Standards. This was the missing link in the Healthcare Ecosystem thus far in India.

JAM (Jandhan Aadhaar Mobile) coupled with NIN HFI Registery will be the delivery model to reach every beneficiary. Similar to Pradhan Mantri Ujjwala Yojana.

#PMJAY > Health Insurance will be the driver for the shift to clinical protocols, pharmacogenomics and precision medicine driven managed care. I can see the end of the 'Doc Sahib Bhagwan hai' era.

#PMJAY > Health Insurance will bring a check on unnecessary tests, expensive drugs, high end procedures and overcharging frauds. Machine learning and Analytics on the EHR data will be valuable in making the system adhere to protocols.

The Hospitals, Doctors and all other medical establishments are concentrated in Tier 1 and Tier 2 cities. #PMJAY will shift the demand to Tier 2 cities and below. It is a no brainer that the supply side will follow.

Big opportunity for EHR, Telemedicine, global Healthcare providers to line up and get listed for the program. Takeover the District Hospitals and upgrade them and convert 24 of them to Medical Colleges. With Govt acting as a guarantor in PPP model.

Big opportunities for global, online and organised Pharmacies to line up for listing in the program. Drug supply chain is set to be completely redefined. 70% cost of any treatment is drugs. Govt has started restructuring the NPI and essential lists.

India's private hospitals jack up prices of drugs and consumables up to 18 times. A study by National Pharmaceutical Pricing Authority shows that hospitals in Delhi-NCR routinely make a margin of 350-1,700% on consumables, and 160-1200% on drugs outside price control. The modus operandi? Pressuring manufacturers to print higher MRPs on products in lieu of bulk supply orders, and profiteering from sale of such medicines at their pharmacies. “This is a clear case of market distortion... patients have to incur huge out-of-pocket expenditure,” NPPA said. Consumables, drugs, and diagnostics make up nearly half to 70% of a patient’s bill.

Let's take the example of Diabetes as a disease burden. India has 65-70 Million Diabetics. The absolute numbers make India the Diabetes capital of the world. But as a % of the population its under 7%. Per month average cost of Diabetes management is INR 3K-5K. Only 33 out of 100 Diabetic patient days will need any kind of Hospital intervention. Hence #PMJAY coverage of 10 Cr families i.e. 500 Million people i.e. 40% of India's population can collectively pickup the Diabetes disease burden and more much more...

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100 Days Report Card: In little over 3 months, #PMJAY has been able to distribute nearly 5 Million #PMJAY cards, serve about 700K patient admissions, in 16K em-paneled hospitals, > 66% claims are from tertiary care.

Going Forward: Ayushman Bharat is set to provide coverage to 40% of India's population. Millions of claims will be coming daily from plethora of unstructured non-standard HIS systems. How many claims can be processed with manual vitrification? Hence the TPA industry is ready for disruption. TPAs have been servicing merely 3% of India's population i.e. covered by the private health insurance. Now this market is shooting up to 40% of India's population. Obviously we stand at the cusp of a new paradigm of intelligent revenue cycle management [RCM]. We need a digital claims engine built on meta data Standards to automatically process the millions of claims. Hence I see MDDS for Health Standards is the logical way forward...

-- Dr Pankaj Gupta is the Managing Partner @ Taurus Glocal Consulting --

References:

# MDDS for Health Domain Standards Notified by the STQC, Meity, GoI

India will be the next battleground for Global Retail and Healthcare!

India had 60 million online shoppers in 2016, which is only 14% of the internet user base in the country. This will rise to over 50% by 2026, according to a report by Morgan Stanley.
On top of that India has over 900+M mobile phones. 60% of these are smart phones. 90% of these are Android phones. 200M Jan Dhan Accounts have been opened at the bottom of the pyramid. Digital transactions have crossed 1 Billion every month. Rupay has emerged as the largest payment gateway in India dislodging Visa and Mastercard. Electricity has reached 500K villages. All this is expected to fuel the organized retail market.

Online retail is fast catching on, not just in the larger metros but also in the Tier II and Tier III cities. This growth can be attributed to increasing internet penetration and smartphone revolution. The Indian retail industry has come of age and has emerged as one of the most dynamic industries in the world. Accounting for over 10 per cent of the country's Gross Domestic Product (GDP) and approximately 8 per cent of the employment, it is expected to nearly double to $1 trillion by 2020 from $600 billion in 2017, registering a Compound Annual Growth Rate (CAGR) of 16.7 per cent over 2018-2020. Keeping in mind the growing online potential, brands and retail chains alike are upgrading their online presence to draw customers to their e-shops. India's growing per capita income, a rising middle class, changing demographic profile, urbanization, and attitudinal shifts in the consumer spending pattern, all indicate the retail sector's potential to be the real growth engine of the country's economy.
NHPM or Ayushman Bharat has created a huge Healthcare market i.e. INR 500K cover per family for 100 Million families in India. This is a game changer and all big players will run after it. Drugs form approximately 70% cost of any treatment. Obviously this Coverage needs an e-commerce platform, telemedicine apps, and digital community to support the physical Healthcare Ecosystem.

Myntra, Online retail store for fashion and lifestyle products, acquires smart wearables devices startup WitWorks. Flipkart owns India’s largest online fashion retailers -- Myntra and Jabong -- both of which it acquired. Together, Flipkart-Myntra-Jabong has a 70 percent market share of the online fashion business in India. It also owns eBay’s India business as well as popular mobile payments app, PhonePe. With over 100 million users and these popular properties, Flipkart is a valuable asset in the global internet economy for its long-term potential. Walmart is now looking to pick up majority stake in Flipkart. Walmart may rope in Alphabet [Google] also for Flipkart.

Amazon is already in India Retail sector. Amazon is already selling its services to many in Healthcare and has also announced it's desire to do more in Healthcare markets in US. Amazon said that it is working with Berkshire Hathaway (BRKA) and JPMorgan Chase (JPM) to better control costs and reduce spending on the health insurance they offer for the 840,000 people who work for them. Amazon has invested $4.74 billion in Amazon.in, to go after the India market and compete with Flipkart, Myntra, Jabong.

For traditional physical world Retailers, this means entering the playing field with the likes of e-commerce behemoths Amazon and Alibaba, both of which are leveraging big data and powerful AI algorithms to transform the retail space. The traditional Retailer Shopping giants are feeling the heat from Flipkart and Amazon in India.

Cooper Smith, who advises retail clients with Galloway's firm, L2, thinks we may be years away from a serious discussion on breaking up Amazon, but he advises retailers to not sit around and wait for that to happen. He thinks the announcement that Wal-Mart is partnering to sell some of its products on Google Home is significant for struggling retail survivors: "A lot of luxury brands like LVMH, which has refused to touch Amazon with a 10-foot pole, are talking about banding together to create a new luxury e-commerce space. Amazon hasn't been able to disrupt that market yet. Google and Facebook are the platforms with the reach, those are the alternative platforms that would help brands and retailers reach consumers without having to partner with Amazon."

In the US, Wal-Mart shoppers can link their Wal-Mart accounts to Google Express and quickly order — either through voice on Google Home or by shopping on Google Express. By linking a shopper's past Wal-Mart purchase history, Google will be able to more quickly learn the customer's shopping patterns and recommend suitable products. Using the platform now, a customer can say, "Google, buy peanut butter." Google will then suggest the brand it thinks the customer would like the most. The same can be leveraged by many other smaller struggling Retailers in India to compete with likes of Amazon and Alibaba.
On top of that Google is betting that the future of healthcare is going to be structured data and AI. The company is applying AI to disease detection, new data infrastructure, and potentially insurance.

FinTech mobile based payments developments supported by Govt of India's Digital India, Jandhan/Aadhaar/Mobile and BHIM App are only adding to the fire. Many local startups like Paytm and All big Internet and Retail giants are jumping into the ring - Flipkart, WhatsApp, Samsung, Android...

After USA, India has the largest user base for these Internet Giants. Obviously India is fast becoming the next battleground for Retail and Healthcare?

Can you extrapolate the Dots? I can see the Trend!

#India #Retail #Healthcare #NHPS #AyushmanBharat #Amazon #Flipkart #Walmart #Alibaba #Digital #e-commerce

The lines are beginning to Blurr!

RISE OF PRECISION MEDICINE AND PHARMACOGENOMICS

The lines are beginning to Blurr! between BioTech, Devices, Genetics, Genomics, Bioinformatics [GGB] and HealthTech, EHR, LIMS, RIS coupled with Digital, SMAC, IoT, AI, VR, CRM, Precision Medicine, Evidence Based Medicine, Population Health.

With the Apple Watch 4 having ECG and other vitals built-in and it being FDA class 2 medical device certified, is Apple now a Medical Device company? Whole ecosystem of ios developers are busy churning out medical devices on ios. Fitbit is having a wealth of breathing, circulation, cardiac, thermal, exercise and sleep data. Google, Moto and Samsung are Medical Device companies? as they are building an ecosystem of Medical Device capabilities on the Android platform. The lines are blurring faster than we think.

UnitedHealth Buys Large Doctors Group as Lines Blur in Health Care. UHG already owns Code Sets, RCM, Insurance, EHR, Big Data, AI...now Physician Offices too! An earlier Report by UHG in 2012 found Greater Use of Genetic Testing, but Half of Physicians Concerned About Their Lack of Familiarity with Genetic Tests. So UHG is Preparing for Precision Medicine?

CVS has been building retail Primary Care centres and Diagnostics in its Pharmacies. Now CVS is Purchasing Aetna! Obviously CVS wants to know genetic basis for the Diagnosis, PGx for the Drug Ordered, How much was Billed, Whats covered by Insurance...and going forward control the entire value chain. Highlights Critical Role of Precision Medicine and Consumer Experience in Healthcare.

John Hancock leaves traditional Life Insurance model behind to incentivize longer, Healthier lives; in other words turns the Life insurance model on its head and gets into Disease management and Precision medicine.

BD the injectable major, has acquired 21 companies across Devices, Supply Chain, Logistics, EMR, IoT, AI, Genomics etc.; CareFusion EHR for $12B; GenCell for Genomics; Bard Devices for $24B. What is an injectables company doing in EHR and Genomics?

Verily an Alphabet/Google company has deals with Medicxi $300M Genomics fund, GlaxoSmithKline, Sanofi, Novartis and J&J to apply novel technology. Verily is investing in areas ranging from Genomics, Bioinformatics, EMR, IoT, AI, disease management to robotic surgery. Calico another Biotech company from Google wants to beat aging and apoptosis. Google makes AI tool for precision medicine open source. What is going on...an Internet company in EHR, Drug R&D, Medical Devices and Genomics?

Quest Diagnostics is a Diagnostics giant from North America with a market Cap of $12.47 Billion. Has made 19 Acquisitions including Celera Genomics for $671 million in 2011. Celera did the Human Genome project in US. Quest is now acting as a investment fund. They have made their first series A investment in Lemonaid Health. What is a Diagnostic Lab doing in EHR and Genomics?

Big Pharma: The most active pharma investors in Genomics, BioTech, DigitalHealth since 2014 are Novartis, Johnson & Johnson, GlaxoSmithKline, Pfizer, and Celgene. J&J investing heavily into Genomics R&D through its PRD, JLABS, Jansen vehicles. $914M Series B of GRAIL with participation from Johnson & Johnson, Merck, Bristol-Myers Squibb, and Celgene. In a distant second, Verily and Sanofi took a $500M minority stake in Onduo in September 2016. Some of the Oncology investments are $474M Series F of Moderna Therapeutics, and the $320M Series A of Immunocore. Pharma majors extending into Genomics is logical for Drug R&D; but this is getting into clinical decision making and heading towards Precision Medicine! The same was validated again by the Pharma and Genetics/Genomic company announcements in H1 of 2018. Roche acquired Flatiron EHR and MySugr App for complete Genomics based Diabetes Disease management. Novartis, Sanofi, BMS are also shifting to Precision medicine, Pharmacogenomics, Data and Digital.

Takeda is 230 years old Pharma giant from Japan. Focus is oncology, gastroenterology, and the central nervous system, as well as vaccines. The focus is shifting to Genomics, BioTech and HealthTech Devices.

Color Genomics has raised $80 million more, bringing its funding total to $150 million. The company is planning to move beyond genetics into preventative health more broadly. 23andMe gets $300 Million boost from GlaxoSmithKline to develop new drugs for precision medicine.

Deep Genomics is applying AI to GGB data. Got $13M Series A funding. Ever since my work on Bioinformatics in 1999 to 2003 we have said Human brain and current technology cant fathom the depths of the data unleashed by the Human Genome project and the Proteomics thereafter. Obviously machine learning and EHR now come to fill the gap.

Grail Liquid Biopsy: GRAIL aims to develop a blood test to detect cancer early before symptoms appear. Grail has raised $1.1 billion, a sum that puts it among the top three most heavily funded private biotech companies, according to EvaluatePharma. Investors include Illumina, Johnson & Johnson, and Amazon founder Jeff Bezos. What is going on...why a Pharma major and an eCommerce/Cloud company funding a major BioTech device company?

Genentec was a $2B IPO in 1999. Now acquired by Roche, a $210B Market Cap Pharma major. Roche has made 38 acquisitions; The focus is shifting to Genomics, BioTech and HealthTech space.

Quintiles CRO have been consolidating GGB portfolio. Omicia software bought Spiral NGS.

Macrogen is a Korean Service provider on Genome research - sequencing, Oligo, Microarrays, Mouse models, Bioinformatics, Genetic Diagnostics, PGx. Strength is the proprietary Asian Genomic Databases, Process and Devices.

Illumina [China] has the Databases, Processes and Devices for DNA and RNA sequencing, Microarrays. Has built the map of gene variations associated with health, disease, and drug response. Trying to understand the clinical significance of the genome. What causes a cancer cell to mutate? What is the origin of a puzzling disease? Is it possible to prevent the next outbreak?

“Illumina and IBM announced that they would be bundling IBM’s Watson Genomics product with Illumina’s TruSight Tumor 170, a tool used to help match very sick cancer patients with drugs that might help them” – Forbes JAN 9, 2017.

EONE-DIAGNOMICS Genome Center [EDGC] is an international joint venture established in 2013 between Eone Life Science Institute in Korea and DiagnomicsInc in California, USA. Eone Life Science provides 30 years know-how and experience in clinical diagnostics reference lab expertise in Korea, and Diagnomics contributes cutting edge genomics and next generation sequencing expertise from USA to revolutionize next generation healthcare from personalized medicine.

BGI Genomics provides next generation sequencing services and a portfolio of genetic tests for medical institutions, research institutions, and other public and private partners. It offers DNA, RNA, and customized sequencing services.

Thermo Fisher Scientific, Agilent, Mettler-Toledo and PerkinElmer [TAMP] Lifesciences is making Facebook, Amazon, Netflix and Google [FANG ] Internet stocks look dull.

Effect of Demonetization on Healthcare

Demonetization is a master stroke by PM Modi. It has done to Healthcare what all Transformation consultants put together couldn't achieve in 75 years.

These are few of my observations. Maybe isolated incidents and may not represent a wider trend; But this is what I saw...'pratyaksh athwa pramanit'.

1. Cash payments in Hospitals have gone Digital! Patients come and say 'cash nahin hai saab ji'. Hence acting as a filter between need and want. Will pay Digitally for only what is required and not what can be postponed. What was under the table has come overboard. Only 5% of the GDP is spent on health and 80% of this is in the form of out of pocket expenditure. Almost all of this out of pocket was cash; out of which I think 70% will get converted to Digital that will show in the books and attract relevant tax. Over 80% bed utilization is usually considered profitable. However I have seen bed utilization falling by 30% in the demonetization period. I think this could be a short term shock effect, hope not a long term trend!
2. The biggest impact is on Doctors in private practice for primary and secondary Healthcare. They can no longer hide some of the cash payments. Their cut practice will stop or be washed overboard. Labs, Pharmacy, Specialists, Hospitals have stopped paying cash [cuts] back to the practitioner. 'aap ko pata hai, cash to ab hai hi nahin Doc saab'. As per some estimates cut practice forms 80% of their income but hidden from income tax. About 60% of total health expenditure in India was paid by the common man from his own pocket. Almost all of this out of pocket was cash, out of which I think 70% will get converted to Digital that will show in the books and attract relevant tax. 
3. Sales of OPD prescriptions and OTC has become Digital! Pharmacies were already geared for Digital payments but now the % of Cash payments has gone down to minimal. This is a good thing because now the traceability of the sale has gone up. Each transaction has a unique number and can be traced by batch number. Out of all health expenditure, 72% in rural and 68% in urban areas is for buying medicines for non-hospitalised treatment. Almost all of this was cash, out of which I think 70% will get converted to Digital that will show in the books and attract relevant tax. 
4. IPD Medicines are fully Digital now. Whatever came through the HIS was Digital anyways. Now the medicines being bought directly by the patient are also Digital. Soon Pharma companies will have access to reliable Digital data for forecasting, which was a struggle thus far. Organised retail Pharmacy stores can handsomely monetize this Digital data.
5. Hospital consumables and materials are about 30% of the operations cost; where the procurement has gone Digital! Where is the cash to pay for all the material supplies? Hence forced to do direct funds transfer to the bank.
6. Medical consumables and material supplies to primary care and secondary care sector were all cash transactions. Now becoming cashless online payment. Small material suppliers risk getting wiped out as their business margin [< 8%] is lesser than the total tax liability!
7. Although P&C/Gen Insurance saw heavy FDI inflow after the amended law last year; but same didn't happen to Health Insurance thus far. This is because the Actuaries can't calculate the risk when the Indian Healthcare relies on hidden cash transactions and under the table deals. It's happening now because of demonetization. Insurance feels more comfortable dealing with claims that have a Digital footprint. i.e. Insurance is more comfortable reimbursing a Digital expense because it reduces the chances of fraud and abuse. From a Actuarial perspective the risk comes down. Full traceability. Hence I saw a large Healthcare group offering OPD Insurance cover. Now that is a commendable change! Thus far private Health Insurance coverage is between 3-5% and total Health Insurance coverage is between 14-18% of India's population; this is expected to grow exponentially because insurance becomes attractive in a clean business environment.
8. MNC Medical device OEM want to sell directly in India now. Not through dealers because the payments have become Digital and 100% FDI is allowed and overboard. As per FICCI the Medical Devices and Equipment industry, valued at US$ 2.5 billion contributes only 6% of India’s US$ 40 billion healthcare sector. It was growing at a annual rate of 15%. The need for Digital records, Digital payments and with IoT coming in, I expect it to grow @ over 20% annually.
9. Labs were already Digital ahead of other Healthcare stakeholders. Now thinking of leapfrogging to SMAC, IoT, Automation and AI in a big way. LOINC standardsapproved and notified for India! International Lab chains eyeing India as a viable market.
10. Radiology business is falling. Unnecessary imaging is going down. Traceability and transparency is reducing repeat tests. Obviously Patient benefit and Insurance wins.
11. Drug counterfeit market that was expected to be 50% of the market in India has been hit badly as it was all cash market. Pretty much struggling to survive. Obviously plugging such a leak is a huge benefit for all. Recognised Pharma companies should be celebrating. The total yearly drug spend of US$ 36.7 billion currently should see a huge jump this year as the market spend shifts from counterfeit to genuine drugs. It will be interesting to watch if this shift will benefit generic or patented drugs!
12. All the ad-hoc or lower level staff were daily wagers and are on daily or weekly cash payments. No one really knew if these daily wagers were real or existed only on paper. Salary payments under 30K per month did not attract TDS and hence were mostly used as a buffer or to siphon the black money. Now the ordinance of all Salary to be paid Digital brings all this out in the open! Going forward 'Ram lal 1, Ram lal 2, Babu Ram x, Babu Ram y' will no longer exist.
13. National Health Protection Scheme - Health Insurance cover of up to INR 1 Lakh per family for the poor and BPL has been hanging fire for a year now; But PM Modi announcing INR 6K direct benefit transfer [DBT] for every pregnant woman in the country is the last straw on the corrupt public healthcare systems back. The Govt will need to establish unique Digital Identifiers and registries for Services, Patient, Provider and Facility; hence EHR v2 and MDDS Standards notified. Where the DBT will be done by Jandhan, AADHAAR and mBanking [JAM]. This is start of the Public Health Transformation!
14. Real estate use for Healthcare is suddenly in demand! The dealers and builders are calling me and offering spaces at 75% discounted rentals, the same were unwilling to talk because they could get higher prices elsewhere. Now I tell them I dont have the cash to rent/buy.
15. Didn't you wonder - !! - when the balance sheets of large hospital/healthcare chains were showing losses year-on-year? Obviously this was a siphon going on. Demonetization wiped out the [black?] cash stores of HNI and traditional Indian business houses. Hence Demonetization has given a major blow to the investment confidence in green field and brown field hospitals and other capital intensive Healthcare businesses. Soon these siphon businesses will start getting sold out or wiped out of the game. Hence democratisation of funds creates a level playing field for new age digital healthcare business to compete with the old boys club. Let's bet on the winning horse now!
16. 80% of healthcare infrastructure is in public sector whereas 80% of healthcare spend is in the private sector. Majority of the spend in private sector was in cash. These cash based revenue sources for private Hospitals have taken a big hit. Value of volumes from Govt Insurance programs like CGHS, ECHS etc. have gone up. With demonetization and Digital payments the corruption is expected to come down significantly. Hence the public sector hospital functioning is expected to improve and give private sector hospitals a run for their money. Nalayak beta bhi ab layak ho gaya ;-)
17. India sovereign is now ready to become probably one of the largest Reinsurers in the world. Banking system is flush with unprecedented funds. Insurance companies will be fools to not notice! Health Insurance is no exception. Hence sets the stage for rolling out one of the world's largest Universal Health Coverage [UHC]. The number of Indians falling below the poverty line [BPL] every year due to health spending is anything between 2 to 7% of the nation’s population, and this total is on the rise. Hopefully UHC will stem this.

India's demographics playing in favor of shift to Digital payments. About 70% of India now is below the age of 40. Over 900 Million mobile phones in India. Over 60% are smart phones. AADHAAR has crossed over 1 Billion mark; its coverage is now at 93 percent among adults, 67 in children in the 5-18 age group and 20 percent of those aged zero to 5. Massive spread of Jan Dhan accounts, RuPay Cards in rural India, BHIM payment platform, Tax incentives for Digital payments, India's own GPS [NAVIC] are all preparations for the Digital onslaught on traditional lala and cash ka dhanda.

This year all balance sheets will show huge jump in revenue, assets and tax! win win for all. India will be soon ready for Universal Health Coverage! All the Healthcare MNC big boys are already eyeing India as it emerges from the shadows.

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Healthcare will have to learn Cashless Business! CBDT as per Amended Sec 285BA read with Rule 114E of The IT Rules 1962: has made it mandatory to report on Cash Transactions recorded on or after 01st April, 2016.

1. Tax Assessees (covered under the Tax Audit Norms) have to mandatorily report to the Authorities " Receipt of Cash Payments exceeding Rs. 2 Lacs for sale of goods or services of any Nature".

2. The FINANCIAL INSTITUTION must report cash Deposit or Cash Withdrawal (including through bearer cheques) aggregating valued to Rs. 50 Lacs or more in one F.Y. in one or more Current Account of any person."

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