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Can Big Data help reduce India’s burden of healthcare costs?

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India remains high on the list of medical tourists based on the high quality of healthcare available at comparatively lower costs when compared to the costs in more developed nations. In fact, medical tourism is growing at a compounded rate of over 20% y-o-y leading to a flourishing industry that is expected to touch US$ 6 billion by 2018. However the proverbial grass on the other side of the fence is not greener. It is no secret that healthcare costs for an average Indian family has seen significant increase year-on-year basis 10 year data collated by the National Sample Survey Organization that revealed a significant increase in expenses for public health services for both urban and rural patients between 2010-14.

Between 2004 and 2014, for example, the average medical expenditure per hospitalisation for urban patients increased by about 176% across both urban and rural patients. During the same period, India’s GDP per capita, based on purchasing power parity grew by 121%. While outpatient (OP) care increased by over 100%, inpatient care expenditure went up by an almost 300% increase during this period. With limited insurance coverage, a majority of rural and urban households depended on ‘household income / savings’ to meet healthcare costs while almost 21% of families had to rely on ‘borrowings’. Data also reveals that healthcare access in India is affected with 70:70 paradox – 70 per cent of healthcare expenses are incurred by people from their pockets, of which 70 per cent is spent on medicines alone.

The situation fares no better when it comes to the private healthcare burden on the population. Data reveals that the use of more expensive private healthcare is increasing in comparison to the use of public healthcare systems, which is reducing across both urban and rural areas. Here again the issue is that of consumers paying top dollar to healthcare service providers. While much of this is borne by insurance companies, a significant portion continues to be out-of-pocket expenses borne by the consumer. Claimants from India’s top six cities and metros (comprising of around 5% of the population) account for a disproportionately high (over 20%) health-insurance claims, receiving over 25% of all health insurance pay-outs, according to the Insurance Information Bureau of India.

Bringing in big data to make big changes

The challenges facing both insurance companies, public health institutions and policy makers is to improve financial performance, increase cost effectiveness while improving overall health indicators, and boosting quality of care. The increasing need is to address them all. In such a situation, the question that arises is, can the application of big data and analytics address these needs? Here’s how I believe it can.

Insurance companies and other stakeholders need to invest in predictive, statistical data modelling to more accurately determine ‘future possibilities’ basis ‘past happenings’. “Models” can be created to determine future variables that can ensure that stakeholders, whether insurance firms or healthcare service providers can get more accurate predictions for the future. The other is to generate greater streams of ‘real-time’ data that would be more useful in generating even better predictive modelling.

Integrating the service provider domain with wearable technology is one way to do this. Companies such as Goqii, a wearable start-up in India is already working with insurance service providers to enable this. Wearables can monitor a person’s habits and provide ongoing assessment of their lifestyle and activity levels. Internationally, many insurers are offering services based on the use of these devices. The great thing is that if consumers are willing to share data, consumers can benefit with cheaper insurance premiums by using these devices to better track and improve unhealthy behaviours. Insurance companies are also leveraging such learnings to increasingly move away from the concept of ‘one policy, one price’. As a result, the price of a health cover has become a complex variable, depending on where you live, what hospital you plan to use and your age.

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