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Posted on Sep 25, 2020
byAmol Gavai (Assistant Vice President – Business Development)

How Prescriptive Analytics Can Help Healthcare Sector To Service Better?


What exactly Prescriptive Analytics is?

Prescriptive analytics is a statistical method used to generate recommendations and help in decision making based on the computational findings of algorithmic models. It focuses on finding the best course of action in a situation based on the available data. Prescriptive Analytics is related to descriptive analytics as well as predictive analytics but helps in understanding actionable insights instead of just monitoring the data.

Descriptive analytics offers valuable insights into what has happened, whereas predictive analytics helps to forecast possible outcomes. Prescriptive analytics on the other hand, factors information about possible situations or scenarios, available resources, past performance, and current performance, and suggests best possible course of action or strategy. It not only anticipates what will happen and when it will happen, but also why it will happen. Also, prescriptive analytics provides decision options to take advantage of a future opportunity or mitigate a future risk.

How Prescriptive Analytics works?
Prescriptive analytics processes business rules along with the structured data (such as numbers, categories etc.) as well as unstructured data (such as texts, images, sounds, videos, etc.). It uses various artificial intelligence techniques such as machine learning, natural language processing, computer vision, pattern recognition, image processing, speech recognition, and signal processing to predict what lies ahead and to prescribe how to take advantage of this predicted future limiting risks. It can help prevent losses, limit risk, increase efficiency and meet business goals. However, it can only be effective if businesses know what questions to ask and how to react to the answers. If the input rules are accurate, the output results will be incorrect.

Applying Prescriptive Analytics to Healthcare Sector
Prescriptive analytics software that uses machine learning, Decision Tree, Support Vector Machine (SVM) can be used to improve efficiency of doctors to diagnose patients of diseases accurately and in an economical way. It can also reduce time taken to analyse numerous variables to potentially improve upon/ assist doctor’s diagnosis.

  •  Prescriptive analytics finds its application both in patient care and healthcare administration. The practitioners and care providers use prescriptive analytics to improve clinical care and provide more satisfactory service to patients. It can help them in capacity planning by using analytics to leverage operational and usage data combined with data of external factors such as economic data, population demographic trends and population health trends.
  • Prescriptive analytics can prepare the healthcare companies for future and unforeseen events like COVID-19. The hospitals can know from historical as well as current data of people with pre-existing diseases and old-aged patients are more susceptible to infections. This can help hospitals to provide special care to the vulnerable category of patients. It will also help the hospitals to track the doctors and nurses who provide care to the patients.
  • Prescriptive analytics can help health insurers and pharmaceutical companies. Insurance companies can use it in their risk assessment models to provide pricing and premium information to their clients. The pharmaceutical companies can use it to speed up the process of developing drugs and getting faster approvals.
At Aress, we have completed a few mini projects (e.g. Chronic kidney disease (CKD) prediction, Predicting mental health disorders, Diagnosis of liver disease) based on used cases in healthcare domain pertaining to some complicated clinical data. Depending on the setup, clinical data accessibility and healthcare specific scenarios; we would be able to include additional functionalities and provide an AI based solution that would address any specific requirements. I am available at amol.gavai@aress.com and please feel free to get in touch with me your questions and requirements.

Category: Analytics, Artificial Intelligence, Big Data and BI

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