Data Analytics in Healthcare Sector

Healthcare data, when used with data analytics, provides valuable insights for the hospitals to improve their quality and patient welfare. Hospitals have long been using descriptive analytics to diagnose the patient based on their medical record. Doctors also use descriptive analytics to find the current health state of the patients.

But descriptive is only the tip of the value that data analytics provides. The real use of analytics comes by using predictive and prescriptive analytics. Hospitals in developed and developing countries have started to use predictive analytics only recently aided by the vast collection of medical records and increasing computer resources.

The predictive analytics brings much value to the hospital than the descriptive. Instead of just analyzing the past data and presenting the information by the descriptive, prescriptive analytics predicts the future outcome by analyzing the past data. It gives the hospital a great advantage by staying one step ahead.

Here are some of the ways in which hospitals use predictive analytics.

Predicting the risk of illness

Healthcare organizations use predictive analytics to find the probability of a person getting a medical condition in the future. With the use of the patient’s medical data and the historical record of that particular medical condition, predictive analytics can find the probability for the person diagnosing with the medical condition.

The healthcare organization can also find the progressiveness of a medical condition in a person given the medical record. This process of predicting the risk of a medical condition for the patient helps the doctor get ahead of the condition and cure it.

Avoid patient readmission

In addition to finding the risk of a medical condition for a patient, predictive analytics can find whether a patient is about readmitted to the hospital. After being cured by a medical condition, there is always a chance for a patient to be admitted to the hospital again for the same condition or a related one. That is, the condition reappears for some patients. Data analytics can accurately predict whether the patient is about to readmit to the hospital. This helps the doctor to fully address the medical condition of the patient and avoid readmission.

Manage Supply Chain

Hospitals require a variety of medical and non-medical products each day for smoothly running the operation. The stock and the supply chain should be managed efficiently so that no product is limited or much.

This is where predictive analytics comes in. The demand for medical products can be found with a good probability by using predictive analytics. And using the result, the hospital can stock up their products. Also, the supply chain process can be optimized with analytics to save time and money. Optimizing the supply chain process has been used in many sectors successfully for many years.

Boosting patient and hospital satisfaction

Data analytics is also used to predict when the hospital might get busy or when a patient might skip an appointment. This can be found by analyzing the previous record of the hospital and patient to find a pattern.

This could help the patient to know the busy time at the hospital and avoid it. It also helps the hospital about the patient’s appointment and schedule based on it. On the whole, this process of analytics helps better satisfy hospital staff and patients.

Developing new medicines faster

Developing a new drug is a time-consuming process. There is a chance that the current drug variant might fail. If it succeeds, then animal trials must proceed with success. Then human trial and finally, the FDA approval.

With the introduction of the big data approach to the drug trial, the drug trial process can be accelerated. The predictive analytics helps in finding whether the current variant of the drug will succeed provided the relevant data and thereby saving valuable time.

Analytics also helps in finding new insights with medicine. For eg: aspirin, a pain reliever is found to have the property to treat colorectal cancer by using different analytic techniques. There is a huge potential for analytics to play in the field of medical science.


Analytics is transforming the Healthcare sector in a good way and it is a good example of true value in using data analytics. In this decade, we will see hospitals using predictive analytics often to improve patient care.

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