Big data can be a game-changer, only if adequate measures for capacity building, technological advancement, data privacy, logistics and governance are put in place
'Big data' has become the buzzword in the world of data and statistics. It means a large volume of data which is usually complex and analysed using advanced software applications to reveal information like trends, patterns, attributes, associations, etc, about the subject to which the data belongs.
Big data is different from traditional data in the way that it is bigger, varied, faster; and cannot be stored and analysed by the traditional data processing software applications.
In the context of health, as explained in a 2016 study by the European Commission, big data refers to “large routinely or automatically collected datasets, which are electronically captured and stored. It is reusable in the sense of multipurpose data and comprises the fusion and connection of existing databases for the purpose of improving health and health system performance. It does not refer to data collected for a specific study.”
With the revolution in information technology over the past few years, the working landscape of many businesses, organisations, governments etc, has also rapidly evolved, and continues to do so. Decision making is becoming more and more data-driven. In the future, one can easily predict a similar trend.
In healthcare, data can be used for multiple purposes like genetics, surveillance, causal inferences, impact assessment, monitoring progress of the health programmes, etc. In fact, big data is not new to the health field.
Since long, few people/institutions/organisations have been using the voluminous data to check for specific information.
In public health, big data can be useful for:
So where does this voluminous and valuable big data come from? Traditionally, at the demographic level, major sources of regular data were vital statistics registries and hospital admission statistics.
Since a couple of decades, more data is available through electronic medical records (EMR), laboratories, pharmacies, insurance companies, mobile phones, and last but not least social media. However, there is huge uncertainty around the quality (veracity) of such data.
At the individual level, with modern day’s focus on quality of healthcare delivery, clinicians are obtaining data in the form of advanced laboratory (including imaging like CAT scan, MRI, etc) results along with time-tested methods like patient history, vital signs and examination etc, thus providing more accurate, tailored care to their patients.
In public health, developed countries have been able to harness the technology much better due to their organised and advanced systems, compared to the developing and under-developed countries. For example, in the United States of America, the Centre of Disease Control and Prevention (CDC) uses data from pharmacies (purchasing patterns), commuting traffic, and school and work attendance to predict outbreaks and prepare beforehand accordingly.
In the Indian context
In the developing world, where millions are outside the ambit of healthcare services, what role does big data play? Presently, and in the long-term, implications of big data are mixed for a developing country like India.
The country can harness the data being generated and disseminated ‘real-time’ to provide healthcare to millions of people who are out of the ambit of the healthcare system. However, that seems more of a distant dream as those who are out of the ambit of healthcare coverage are mostly out of network coverage as well.
They are inaccessible in several aspects. Other areas like research and development can help, but that too depends on several prerequisites.
Largely, due to inadequate capacity of the public health sector, there are challenges at every step from data collection to analysis. Given the sheer population size, the policy level or operational decisions might do more harm than good.
Recently, there has been a lot of discourse about the independence of data globally and locally. Allegedly, the institutions/agencies responsible for collection, interpretation, and dissemination of data are being “hijacked” by those in power — they are losing their independence to produce unbiased information based on unmanipulated data.
The Ayushman Bharat Yojana attaches a patient’s health records with their Aadhaar Cards. The scheme will generate enormous data; and we are yet to see the quality, credibility and utility of that data.
Aadhaar is facing its own challenges around data privacy. In that case, it is a challenge for the government to safeguard the public’s personal and sensitive information especially that belonging to vulnerable populations — which might lead to discrimination and reduction in personal safety.
In countries like ours where there is high levels of corruption, intentional data breaches may be high along with accidental breaches due to lack of capacity.
Data is such a thing that it gets adulterated, sometimes even unintentionally, by the people involved in the process of converting data into information.
Imagine what would happen if this adulteration is done to the extent that it becomes toxic? When the information generated to inform public is so misleading that people do not know what is good for them or not?
Given the sheer population, inherent complexity of the healthcare system, logistic, technological and governance issues warn against underestimating the complexities presented with big data.
Countries with scarce resources have a mountain of challenges before the sea of opportunities presented by big data applications in the public health. It can be a game-changer, only if adequate measures for capacity building, technological advancement, data privacy, logistics, and governance are put in place.
Till then, we can enjoy the benefits of selective and limited application which by design avoid major challenges and by robust design, smaller challenges can be conquered.
Big data revolution will continue and with the avalanche of data, we can only hope and wish that the ship of public health sails through safe.
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