Introduction
Covid-19 has proved that our healthcare system is not well developed to handle a contingency situation, let alone a major catastrophe or pandemic. It is in this context that there is an immediate need to revamp the physical as well as the digital infrastructure of our healthcare system. While a large number of steps have been taken to identify the lacuna in the physical infrastructure, little has been done to make the digital infrastructure of our healthcare equally strong. Strictly speaking, it is very difficult to improve the digital infrastructure of our healthcare without the aid of data science. With the help of data science, the entire decision-making process can be improved which can directly translate into effective diagnostics as well as telemedicine. The need of the hour is to promote data science courses in India so that we are able to prepare professionals who can leverage the power of data across various verticals including decision-making in healthcare.
In this article, we examine the need for data science in rethinking the decision-making prospects in the healthcare sector.
Healthcare analytics: Gathering critical insights
Healthcare analytics involves the improvisation in various aspects of the healthcare system by aid and advice of data science while simultaneously reducing the costs involved therein. This means that healthcare analytics gives us an insight into the patient history and allows us to adopt various kinds of IT solutions like HIE and EMR.
In simple terms, healthcare analytics involves a range of methodologies and tools that mine raw data and derive meaningful insights from it. These insights can then be used for adequate decision-making processes in the healthcare system leading to the greater good of the patients. Healthcare analytics can allow us to make sense of the colossal amount of data that is generated in this industry like doctor prescriptions, patient history, records of various tests as well as the overall feedback of patients.
At the present time, we are devoid of a centralized digital healthcare system that can keep track of all the above-mentioned factors. The fragmentation of data is one of the most herculean challenges that we are confronted with in the present time. This fragmentation of data is keeping the right decision-making process at bay and also keeping us far from value creation using digital technology.
Niti Aayog has identified the National Health stack as a unanimous solution to countering the challenge of fragmented data. However, this project is still at its nascent stage and more needs to be done in this regard. Furthermore, this system does not take into account the need for healthcare analytics to boost the decision-making process in the entire setup.
Data science to shape the roadmap of decision-making in healthcare
The process of decision-making in healthcare is dependent upon multiple factors. The first important factor is related to the medical history of the patient. This means that the decision-making process that is followed for the treatment of one patient is different from the one that is followed for other patients. In this context, it becomes even more difficult to conceive a decision-making system that is fully autonomous. This also points out the need for a customized decision-making system that is aided and advised by doctors and is guided by them as well. The role of data science is restricted to deriving effective insights from data in order to support the decisions of doctors. The aim is to provide the quantitative analysis as well as a competitive advantage so that discrete and specific data sets can be used by them and redundant ones can be avoided at an early stage.
Roadblocks to a digitally-driven health care system
With the help of data science, it is quite possible to clear the roadblocks that have slowed our potential to conceive an advanced healthcare analytics system. The set of challenges in the domain of healthcare can be broadly grouped into five categories. Firstly, the lack of EMR is a fundamental challenge to which we have not been able to find solutions as of now. Secondly, we lack the professionals who have the competitive advantage of harnessing the power of data to treat patients in an effective way. Thirdly, the costs accrued by the healthcare sector are already at a high after the Covid-19 pandemic. It is highly likely that leveraging analytical tools and data science methodologies will put an extra financial burden on the health care sector. Furthermore, there is a lack of collaboration between the healthcare sector, the industrial sector as well as the research industry that strives for innovations in the medical sector. Finally, other technological challenges have also stopped us from developing robust digital healthcare infrastructure.
Overcoming the roadblocks with the aid of data science
In this section, we examine how we can work on the roadblocks in the healthcare system with the help of data science. Firstly, data science can allow us to cut down on the physical machinery as well as the administrative costs. Secondly, data science can help us to derive effective analytics that can aid the decision-making system. With the help of a decision-making system, the process of treatment would be fast-tracked. The use of analytics would allow us to develop better coordination between various departments in the medical sector. Furthermore, data science and data analytics would also help us to keep track of patient health after they have been treated. This would culminate in long-term patient monitoring as well as patient wellness. The challenge of fragmentation of data as well as duplication of data will be completely resolved.
National Health stack: A case study
The National Health stack is the brainchild of Niti Aayog and aims to keep a record of patient data as well as the treatment that they receive in specific hospitals. The National Health stack will have five main advantages. Firstly, it will help in mitigating the burden on the physical infrastructure of hospitals by providing digital delivery of healthcare services. Secondly, it will help in reaching out to a large section of the population. It will also help in catering to the needs of rural populations who don’t have access to a well-maintained physical healthcare system. Thirdly, it will also help in streamlining patient care and providing timely treatment by prioritizing the same. Fourthly, it will also allow us to make sufficient advances in the geriatric care system that has not been taken care of properly in the past. Finally, it will also help in conceiving grievance redressal mechanisms so that the concerns of the patients, as well as the doctors, can be addressed on a single platform.
Future prospects and the way ahead
The role of data science in the digital delivery of healthcare services is the need of the hour. With the help of data science, we would be able to derive effective analytics and channelize the same to the medicos. This type of analytics will help the medicos to precisely diagnose diseases at an early stage. This will improve the decision making capabilities of the doctors and lead to great coordination between primary, secondary and tertiary healthcare systems.
