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How Can Data Science Be Used in Healthcare?

Healthcare requires constant improvement, not only in terms of introducing modern methods and treatments. Equally important is improving the functioning of medical facilities, especially in terms of comprehensive patient service. Both theory and practice show that data science can significantly improve diverse aspects of modern healthcare.

For instance, data science in this sector can contribute to:

  • Improving patient service
  • Determining and implementing appropriate paths (methods) for treating patients
  • Supporting clinical treatment
  • Monitoring health care safety
  • Preventing epidemics

 Therefore, let’s take a closer look at the possibilities of using data science in healthcare.

Data science is changing healthcare

For centuries, treating patients has been based on the judgment of physicians who made treatment decisions. However, in recent years, evidence-based medicine has become increasingly important. Thanks to this, it becomes possible to carry out both business analyzes (current expenses, costs of deliveries, operations, increase of personnel competencies, investment costs) and medical analyzes (length of patient’s stay, related including revenues and expenses, the profitability of individual departments, units, health services, monitoring of the presence and availability of staff, a list of drugs and detection of irregularities).

The use of analytics by various healthcare entities

Data science is used by many entities operating in the healthcare industry. Generally, we can divide them into four groups.


Solutions such as electronic medical documentation give medical practitioners access to data and the possibility of using analytical systems. On their basis, institutions can compose health services offers, maximizing their usefulness and profitability without lowering the quality of services. Furthermore, thanks to data science, medical institutions will have a complete picture of their activities, considering the clinical, management, financial, and quality perspective.


Data science will allow payers to develop management plans for health and preventive programs. Therefore, it may improve patients’ health insurance quality and improve insured persons’ health and quality of life. For example, it will be possible to make analyzes to determine the structure and profitability of medical procedures for a given disease or the risk of its occurrence. At the same time, payers will implement preventive programs that will inform patients about potential exposure to the disease.


In pharmaceutical companies and enterprises producing medical equipment, data science has been used for several years. However, these industries are evolving at a breakneck pace. The current analytical systems are slowly adapting to the challenges of personalized medicine, allowing the treatment, procedures, and prevention to be adapted to the individual genomes of patients and their problems. Pharmaceutical manufacturers, companies and enterprises working in the medical industry have been using data science for several years now.


Data science can be helpful for patients in their search for the best medical facilities and doctors. Thanks to analytics, they will also check the effectiveness of prescribed drugs and compare the prices and quality of services of individual doctors or service providers. Thanks to Data science, patients will also be able to use advanced IT systems via Internet browsers. In addition, they will be able to find reliable information on diseases.

Healthcare is an up-and-coming area for data science. The examples presented above showing various applications are just a tip of an iceberg. Medical facilities and other healthcare entities increasingly recognize that integrated data and analytical systems are crucial in the decision-making process. As a result, they can improve patient outcomes and the quality of medical services. Contact us if you want to learn more about the possibilities of improving the functioning of health care thanks to Data Science. Find out more: