Highlights from the Independence Day Speech
- National Digital Health Mission
- Health ID for each Indian
The Prime Minister announced the National Health Mission today, so what does it really mean?
Every individual would have a choice to apply for a
Health ID and store/share digitally the health information such as prescriptions, diagnostic reports, discharge summary, medicines etc. under this health ID. Now how would it really work? Here are the understanding, interpretation and opinion.
The Doctor’s prescription, diagnostic reports or discharge summaries do not have a standard format as of now and it would be very difficult for looking at the past health records of a person to be read and analysed by a doctor or medical staff. Thre are two broad problems here, first is the format and the quality of digital documents and the second one is an analysis of the content automatically so that it can be matched with information from any other format or match to a requirement from another system/machine/doctor. The second one can be achieved only by the means of APIs tagging each simple entity in the report while the information is being created or by another system after the data is available in the form of document/pdf/images.
Hence, interoperability for the previous documents would require huge intelligent (AI/ML) processing even if all new documents/reports use some sophisticated formats and mechanism to get generated (which is highly unlikely to have in place instantly).
Security, Confidentiality and Ethical issues
Digital Health Records (DHR) or Electronic Health Records (EHR) are increasingly becoming popular adoption in many countries including India but there are inherent issues of identity theft, confidentiality related issues. Based on the low confidence around confidentiality,
people may not opt for sharing the EHR and may end up receiving poor treatment.
There are methods of de-identification of the personal data from the records. Each health record (prescription/diagnostic report/discharge summary/pharmacy data/other data) have different ways to make them de-identifiable. For example, a blood test report requires personal data such as name, mobile number, age, gender etc. to be removed but a video requires de-identification of the face. De-identification of the face in the video again has different levels of implementation – in one, just a blur or pixelation be sufficient while in another one the expressions required to be preserved
using GAN based deep learning algorithms while de-identification of faces.
For each health record deidentified has to be attached with a unique patient ID which is encrypted. This ID should be deciphered with basic information such as mobile number, name, age and gender or with biometrics or both. This module would become Patient Identity Management (PIM).
Strict laws against data theft and misuse and their enforcement can also be helpful in instilling confidence in the public.
Benefit to the Health Insurance Industry
Health insurance companies are sandwiched between the easy claim processing and fraud detection and prevention. Many healthcare centres and doctors either engage in fraud or abuse of the health insurance of the patients. In most cases the patients are innocent and they either are denied pre-processing stage approvals or themselves get dragged into an organised crime of the insurance fraud or abuse by the healthcare providers.
In any case, the patient is in the loss and health insurance companies incur operating losses and face the tough competition to operate.
Digital records of the medical condition of the patient will greatly help health insurance approvals and claim to process in better/faster manner. But one common thing surveyed and found across India and the US is that
the patient has an insignificant role in the insurance application, pre-approval or claim processing, meaning that the patient is never consulted directly by the insurance companies on his health condition. This is a gap which has to be filled in by technological innovations.
The easy and interactive conversations in the local language with the end consumer would generate a new set of data which would add unique value to the decision making on approvals and fraud detection.
The effective and useful direct interaction with the consumer or patient is not an easy task, hence the recent conversational AI and Machine Learning technology-based innovations would bring the about the easy adoption and right data collection.
Right to Health
Unlike Right to Education, there is no right to health yet in India. Why can’t the government implement Right to Health?
The government can not easily make the Right to Health to the people because it does not know the current health conditions of the population at large and hence can not estimate the expense and resources/infrastructure required. There is a strong belief that the initiatives such as Health ID for all and Digital Health Mission are steps towards knowing the population of the country better with respect to their health conditions and hence a step closure to the realization of the Right to Health.
National Health Stack
The NITI Ayog released a 44-page document under the name National Health Stack – Strategy and Approach in July 2018. The National Health Stack (NHS) explains a variety of topics other than Health ID and Electronic Health Records. It talks about other components such as Federal Personal Health Records Framework, National Health Analytics Framework, Coverage and Claims Platform etc. It also talks about the benefits of NHS and the private sector participation and hooks for innovative algorithms and solutions.
This is just the start of the NHS implementation at the national level and there is a long way to go.
Private players have to innovate pieces of algorithms and systems to hook into the framework the government has been designing and make available to the people a much better healthcare experience through technology.