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:
Q2. Nishita Mehta: What are the unique challenges of working with clinical data?
A. Inder Davalur:
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:
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:
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Sponsored
- Accounts Receivables
- Professional Fees
- Disposables and Consumables
- Pharmacy – Generic vs brand name consumption
- Targeted marketing
- Continuum of Care post-discharge
- Predictability of illness propensity from regular Health Check ups
- Results-oriented tasking for better output from employees
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:
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:
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:
Q12. Nishita Mehta: How do hospitals need to adapt to embrace the full potential of data-driven innovation?
A. Inder Davalur:
Q13. Nishita Mehta: How important do you think Big Data Management & Analytics is right now to enhance healthcare in India?
A. Inder Davalur:
Q14. Nishita Mehta: What do you see as the main emerging opportunities for hospitals from greater adoption of Big Data Analytics?
A. Inder Davalur:
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:
Nishita Mehta
Inder Davalur
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.
