ST LOUIS, MISSOURI -

Background

With every passing hour within which 10 patients are discharged, one or more are likely to be readmitted to the same hospital for a more severe form of a disease previously treated.

Estimates show an increasing number of patients not adhering to their prescribed medications, thus increasing the likelihood of physical and emotional suffering, premature death, and readmission to hospital. For chronic diseases such as high blood pressure, heart failure, cancer, diabetes, and depression, more than half of patients with prescribed medications fail to comply or refill doses as agreed with their doctor.

Thanks to the use of artificial intelligence (AI) in active modeling, some variables have directly shown the population subset most prone to becoming nonadherent to prescribed medications.

This nonadherence has contributed to an increased reliance on the healthcare system by patients suffering from chronic diseases, as well as higher rates of hospital readmission and increased medical costs globally. Much of this is preventable, yet it continues to increase gross hospital spending and lead to worse patient outcomes. To get an idea of the impact, people could potentially save 4.6 percent of global healthcare costs - or USD269 billion - by simply adhering to their medication regimens. Our team deployed a case-by-case model to identify patients at risk of hospital readmission to focus the provision of medications and follow-up intervention on these patients before they deteriorate to the point where they must be readmitted to hospital.

Methodology

First, we explored the publicly available Medication Possession Ratio related data, which looks at how often patients refill their prescriptions. The data com