My thoughts on DISHA - The Digital Information Security in Healthcare Act, India by Mr. Inder Davalur @inderdavalur

Here's my tuppence on DISHA (Draft Digital Information Security in Health Care Act)

I have listed the areas that the CIO would do well to examine the capabilities in the HIS/EMR used at her/his hospital. The dependency for the CIO on the vendor goes up multiple fold because, the ability of the hospital to respond to the Government/Courts with reports and evidence and also provide flexibility to the patient to request and effect changes to their consent are key. I have attempted here to respond with my thoughts on some salient points in the draft legislation.
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2018 Internet Trends Rerport by Mary Meeker @KPCB



Review the Mary Meeker 2018 Internet Report to understand the most important technology statistics and trends. Legendary Venture Capitalist has released the 2018 Internet Report covering insights about mobile, commerce, competition between Tech Giants, Freelance workers, Job Trends, Healthcare spend, and many other aspects in the entire 294 page report.


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Comparison of #telemedicine with in-person care for follow-up after elective neurosurgery: results of a cost-effectiveness analysis of 1200 patients

Comparison of telemedicine with in-person care for follow-up after elective neurosurgery: results of a cost-effectiveness analysis of 1200 patients using patient-perceived utility scores


Authors

Sumit Thakar, MCh,1 Niranjana Rajagopal, DNB,1 Subramaniyan Mani, MTech,2 Maya Shyam, PGDM,3 Saritha Aryan, MS, MCh,1 Arun S. Rao, DNB,1 Rakshith Srinivasa, MCh,1 Dilip Mohan, MS, MCh, DNB,1 and Alangar S. Hegde, MCh, PhD 1Department of Neurological Sciences, 2Hospital Management Information System, and 3Finance and Accounts, Sri Sathya Sai Institute of Higher Medical Sciences, Bangalore, India

OBJECTIVES

The utility of telemedicine (TM) in neurosurgery is underexplored, with most of the studies relating to teletrauma or telestroke programs. In this study, the authors evaluate the cost-effectiveness of TM consultations for followup care of a large population of patients who underwent neurosurgical procedures.

METHODS

A decision-analytical model was used to assess the cost-effectiveness of TM for elective post–neurosurgical care patients from a predominantly nonurban cohort in West Bengal, India. The model compared TM care via a nodal center in West Bengal to routine, in-person, per-episode care at the provider site in Bangalore, India. 

Cost and effectiveness data relating to 1200 patients were collected for a 52-month period. The effectiveness of TM care was calculated using efficiency in terms of the percentage of successful TM consultations, as well as patient-perceived utility values for overall experience of the type of health care access that they received. 

Incremental cost-effectiveness ratio (ICER) analysis was done using the 4-quadrant charting of the cost-effectiveness plane. One-way sensitivity and tornado analyses were performed to identify thresholds where the care strategy would change.

RESULTS

The overall utility for the 3 TM scenarios was found to be higher (89%) than for the utility of routine care (80%). TM was found to be more cost-effective (Indian rupee [INR] 2630 per patient) compared to routine care (INR 6848 per patient). 

The TM strategy “dominates” that of routine care by being more effective and less expensive (ICER value of -39,400 INR/unit of effectiveness). Sensitivity analysis revealed that cost-effectiveness of TM was most sensitive to changes in the number of TM patients, utility and success rate of TM, and travel distance to the TM center.

CONCLUSIONS

TM care dominates the in-person care strategy by providing more effective and less expensive follow-up care for a remote post–neurosurgical care population in India. In the authors’ setting, this benefit of TM is sustainable even if half the TM consultations turn out to be unsuccessful. The viability of TM as a cost-effective care protocol is attributed to a combination of factors, like an adequate patient volume utilizing TM, patient utility, success rate of TM, and the patient travel distance.

Link to Full Article : https://thejns.org/doi/abs/10.3171/2018.2.FOCUS17543


Link to VIDEO Presentation by the Authors: https://vimeo.com/262374146


The Article has been published earlier and is re-published here with the author's permission 

AUTHORS

Sumit Thakar: Sri Sathya Sai Institute of Higher Medical Sciences, Bangalore, India | https://www.linkedin.com/in/sumit-thakar-25748b12/
Subramanyan Mani, Sri Sathya Sai Institute of Higher Medical Sciences, Bangalore, India. https://www.linkedin.com/in/subramaniyan-m-22583618/ 


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Why India needs Healthcare Information Technology (HIT) by Dr Pramod D. Jacob


India with its vast population of over 1.3 billion firstly has a challenge in keeping a track of this vast population's health, much less keep them healthy.  One of the major reasons for this is lack of timely, accurate and reliable healthcare information in today's paper world



State of Health in India


In healthcare India ranks very poorly, even compared to our neighbouring countries. For example in the following health indicators: -

Maternal Mortality Rate (year 2015): defined as number of women who die during pregnancy and childbirth, per 100,000 live births. India has a rate of 174 maternal deaths per 100,000 live births, which is worse than Bhutan (148 /  100,000) or Sri Lanka (30 / 100,000 ). China which also has a large population is much better (27 / 100,000) 

Infant Mortality Rate (year 2017): defined as number of children who die less than one year of age per 1000 live births. In India the figure is 39 per 1000 live births, behind Bangladesh ( 32 / 1000 ) and Nepal ( 28 / 1000 ). China is 12 / 1000.


State of healthcare information collection for events like epidemics in India

Before 2010, it would take about six months for the health information to be collected, collated and analysed to prove that a given region in India had an epidemic as the entire process was paper based. By that time the disease (with most being self-limiting) would have struck, had its toll of morbidity and mortality and run its course. With most data collection being paper based this delay costs India loss of lives and productivity with high morbidity, especially in rural areas ( in urban areas- private hospitals and clinics have a process of notifying the public health authorities for notifiable diseases, hence epidemics are identified earlier in urban areas) .

To top it all there is general disbelief in the official published health statistics in India. For example, official data claimed that Malarial deaths in India was only 1,023 in 2010, however a Lancet published study showed the figure to be actually 46,800. Following the Lancet article, the official data agreed that they had their figures off by twenty to thirty times.  Even for a common disease like Cholera, which strikes every monsoon in endemic areas along the Ganges and Brahmaputra, the official estimate for India is 3,631 cases per year, while research has shown this to be about 22,200 per year.   

While the immediate reaction is to blame the public health authorities and Government in India, one must understand the limitations in a paper world to collect health information of 1.3 billion people across 3,200,000 square kilometres. Compare that to collection of information electronically - an electron can travel around the world in about 19 seconds. 

The solution - Healthcare Information Technology (HIT)

The solution is to produce healthcare information in a timely manner with accuracy and reliability. To achieve speed, it is best to do so with Information Technology - hence HIT. To achieve accuracy and reliability, it is best if the patient's data is put into the HIT system by the providers of healthcare such as doctors, nurses, pharmacist etc at the point of care. This patient level data can then be collated and processed to get timely, accurate and reliable population-based healthcare information.

 In addition, HIT systems provides the power of IT to healthcare such as giving alerts for drug-drug interactions, duplication in lab tests and bringing about efficiency in processes and workflows in a healthcare setting, producing reports quickly which will help in planning and deployment of healthcare. It is estimated that healthcare doubles in knowledge every few months and it is difficult for doctors to keep up. With HIT it will be possible to keep up with the latest and deploy best practice evidence-based medicine applicable for India.

The proof of HIT bringing exponential improvement in speed and access to important healthcare information like epidemics even in Indian public health, is best exemplified by the IDSP program. The IDSP program has gone digital from district level upwards to state and then to the National Centre for Disease Control (NCDC), Delhi. As a result, the NCDC now publishes data on epidemics and events on a month to month basis and will soon be publishing it on a weekly basis. Will cover the details of this program in a future write up. 

This article has been republished here with the author's permission. The article was first published here.

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 has been a Healthcare Information Technology consultant to Benton County, Oregon and Santa Cruz County, California. In 2007 he relocated to India and did consultancy work for the state governments of Tamil Nadu and Himachal Pradesh. He was a member of the HIMSS Global EHR Task Force and the lead for India in the task force.

At present he is the Chief Medical Officer of dWise Healthcare IT solutions, involved in the designing and implementation of Clinical Information Systems and the EHR for the company. He is also a consultant for WHO India in the IDSP project and for PHFI for a Non Communicable Diseases Decision Support Application.
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How can Digital Health be Implemented as envisaged in the National Health Policy 2017? by Prof. Supten Sarbadhikari @supten



The National Health Policy 2017 (NHP-2017) of India correctly identified the need for creating many new institutions like the National Digital Health Authority (NDHA).  However, the ground realities don’t appear to have been considered well enough. Early setting up of a functional NDHA is essential for India to avoid a digital health mess in future. The first job for the proposed NDHA will be to formulate a robust National Digital Health Strategy / Policy, in consultation with all the stakeholders. Caution needs to be exercised before cross referrals and sharing disparate information among different systems of medicine. Health informatics education must be embedded as an integral part for health and hospital management. It may be prudent to include Health in the Concurrent list of the Constitution of India. That will ensure a smooth adoption of digital health in India. Seeking comments on the Draft Bill DISHA (Digital Information Security in Healthcare Act) is a good start.

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Clinical Decision Support Systems: Resolving the “Build or Buy” Dilemma - Part 2 by Dr. Ujjwal Rao, @drujjwalrao


The 2 part paper (review part 1 here): Discusses the key role of evidence-adaptive clinical decision support systems (CDSS) in the healthcare system of the future. Weighs the pros and cons that hospitals should consider when deciding to buy or build such decision support tools


Healthcare providers today face the challenge of delivering up-to-date, evidence-based care given the ever burgeoning pool of medical evidence, which is not only prone to inconsistencies but also take an average of 17 years to make their way into routine clinical practice. 

Coupled with the hassle of meeting advance electronic health record (EHR) platform integration requirements, Dr. Rao proposes that buying knowledge-based CDSS is increasingly more favorable and the way forward. 

A number of major initial and ongoing hurdles with home-grown solutions – including the significant time and effort needed to constantly update evidence – could overwhelm and overburden healthcare organizations, taking time away from delivering standardized and evidence-based care. 

Dr. Rao offers five ways on how these challenges can be avoided with the purchase of third-party CDSS platforms.


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Clinical Decision Support Systems: Resolving the “Build or Buy” Dilemma - Part 1 by Dr. Ujjwal Rao, @drujjwalrao

The 2 part paper: Discusses the key role of evidence-adaptive clinical decision support systems (CDSS) in the healthcare system of the future. Weighs the pros and cons that hospitals should considered when deciding to buy or build such decision support tools


Healthcare providers today face the challenge of delivering up-to-date, evidence-based care given the ever burgeoning pool of medical evidence, which is not only prone to inconsistencies but also take an average of 17 years to make their way into routine clinical practice. 

Coupled with the hassle of meeting advance electronic health record (EHR) platform integration requirements, Dr. Rao proposes that buying knowledge-based CDSS is increasingly more favorable and the way forward. 

A number of major initial and ongoing hurdles with home-grown solutions – including the significant time and effort needed to constantly update evidence – could overwhelm and overburden healthcare organizations, taking time away from delivering standardized and evidence-based care. 

Dr. Rao offers five ways on how these challenges can be avoided with the purchase of third-party CDSS platforms.


Read more »



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