The healthcare industry is generating a massive amount of data every day. This presents healthcare providers with an opportunity to improve patient care and up efficiency by using previous data to make more strategic informed decisions. And as a result, the healthcare analytics market is growing.
According to the 2019 Healthcare Provider Analytics Market Trends report by analyst firm Chilmark, healthcare analytics comes in two distinct flavours – mainstream analytics and advanced analytics. About 90% of the use cases for healthcare analytics fall into the mainstream category, which rely on electronic health records and claims history to provide an overview of a healthcare provider’s performance. Mainstream analytics is all about using past data to change processes in an effort to perform better in the future. It also provides basic predictive capabilities, such as readmission risk, for example.
Advanced analytics, on the other hand, is all about making predictions and includes the use of artificial intelligence (AI), natural language processing and machine learning. The value of advanced analytics is that it enables the healthcare industry to make illness predictions, improve care pathways boost adherence.
Here are some of the main examples that showcase how data science is making a big difference in the healthcare industry.
Drug discovery: Developing drugs is far from simple. But with smart data science, different sets of structured and unstructured biomedical data obtained from numerous tests, treatment results and case studies can be used to create simulations of how the drug would interact with the body and predict the rate of success.
Passive information gathering: Wearables encourage people to take better care of themselves and can be used to record vital medical markers like blood pressure, heart rate, sleep patterns, and pulse, among other things. These devices create a database of information that can be used to understand a patient’s needs.
Optimal staffing: As healthcare needs increase providers will find it tough to have adequate medical staff at all times. Data analytics can predict fluctuations in patient visits based on historical information over the years and identify patterns that can be used to guide staff allocation.
Reduced healthcare costs: Using AI and smart analytics, data scientists can drill down on trends in room usage and the potential wastage of medical resources. This makes it possible to lower costs.
With efficiency at the top of every modern organisation’s agenda, AI and analytics offer the clinical and operational solutions required to improve the quality of healthcare. Keeping tabs on all of the tech trends having an impact on your industry can be tough. Let us help you with our monthly newsletter, which features these and other insights about all things digital, innovation and business strategy. Subscribe below.