Big Data Analytics: The New Magic Bullet of the Healthcare Industry
Healthcare institutions and professionals have access to a massive amount of valuable data – be it clinical, administrative, patient medical records, or patient surveys and feedback. With the help of today’s advanced data analytics tools and techniques, it is possible to draw valuable insights from this data, which can be used to improve treatments, reduce cost and time, predict outbreaks, prevent diseases, and to save lives.
Here are top 3 areas where big data analytics is revolutionizing the healthcare sector.
Recent advances in machine learning algorithms for big data analysis has created unparalleled opportunities for early-stage diagnosis of a number of diseases, medical research, and in studying infectious disease dynamics.
Access to such diagnostic and epidemiologically relevant information is enabling healthcare professionals to quickly identify efficacies of alternative treatments and to potentially prevent epidemics.
For example, recently, a European group of scientists, using data-driven cluster analysis of highly heterogeneous diabetics diagnosis data, found out diabetics to be a group of 5 diseases, instead of just type 1 and 2. Such insightful findings certainly enable healthcare institutions to provide more effective and personalized treatment.
Shift managers at hospitals stay in the constant dilemma ‘how many staff members should be present at any given time?’ Too many staff members can cause unnecessary labor cost; and too few, poor customer service, which sometimes can be a matter of life and death for patients.
In France, Publique-Hôpitaux de Paris chain of hospitals is using big data to deal with this problem. By using time series analysis techniques on about 10 years’ worth of admission record, and using machine learning algorithms, they can forecast hospital admission rates for any given time period with good accuracy; therefore, can deploy optimum amount of resources for seamless operations and customer service.
EHR (Electronic Health Records)
Digital version of patient’s medical history (diagnoses, medications, treatments, allergies, test results, etc.), EHRs are available to healthcare providers via secure systems and have been quite helpful in reducing healthcare cost (such as by preventing duplicate tests) and improving patient care.
How big data analysis comes into play is that it allows healthcare providers access to evidence-based results, which they can use to make quick and assured decisions about a patient’s care and further assist in streamlining the workflow. According to a McKinsey report, “The integrated system has improved outcomes in cardiovascular disease and achieved an estimated $1 billion in savings from reduced office visits and lab tests.”
The prospect of big data in the healthcare sector is quite large and goes well beyond the above-discussed advances. However, its implementation is still a hard nut to crack. For instance, outside the US, there is no comprehensive EHR database to leverage. There is also lack of enthusiasm for technology enablement that drastically changes the way of doing things or may threaten some jobs. Despite these roadblocks, healthcare institutions must react to the call of the hour and begin implementing big data and related technologies to improve their services and stay competitive.