In previous APEX of Innovation posts, we’ve looked at how predictive analytics is driving improvements in the insurance and aviation sectors, among others. Today, we’ll be diving into the healthcare industry and examining interesting predictive analytics use cases that are improving processes in all healthcare settings, ranging from small private practices to large academic hospitals. 

Clinical Predictions 

Drawing on EHR data, biometric information, claims data, and national disease data and statistics, healthcare stakeholders can predict the likelihood of patients developing certain medical conditions—such as cardiac issues, diabetes, stroke, or COPD. While the ability to make these predictions carries a variety of implications for health insurance companies, healthcare organizations, and clinicians alike, perhaps the most significant is the potential to improve patient outcomes by identifying those in need or interventions to avert or mitigate the impact of these diseases. 

Hospital Overstays

Hospital overstays drive up costs and are an unnecessary drain of limited clinical resources. In addition, the practice may endanger patient health by keeping them in an environment that could expose them to secondary infections. Predictive analytics can help healthcare organizations address this issue by identifying which patients are likely to exceed the average length of stay for their conditions by analyzing patient, clinical, and departmental data. With this insight, providers can then adjust care protocols to ensure that patients’ recoveries stay on track and that they can be safely discharged as soon as possible.

Patient Engagement and Behavior

Personalized medicine has been a buzzword for numerous years, but predictive analytics is helping providers give it more than just lip service. The technology allows clinicians to better understand and engage their patients, both individually and as part of larger demographic groups. For example, predictive analytics can identify which interventions or healthcare messages would work best with certain patients or patient populations. This and other predictive analytics applications make providers more effective in their communications with patients, which can improve healthcare outcomes.

The above are just a few ways in which predictive analytics is changing healthcare. Head over to SearchBusinessAnalytics for more examples, and take a look at this previous APEX of Innovation post for more benefits that are emerging as a result of healthcare’s digital transformation.