AI in Medication Adherence
Client
Pharmacy Support Services Provider
Region
Ohio, US
Industry
Healthcare
Completed
26 Aug 2024
Project Overview
Our client is the largest provider of pharmacy support services in the US, serving more than 700 hospitals and healthcare facilities. Their suite of offerings includes inpatient pharmacy management, tele-pharmacy, consulting and specialty/outpatient pharmacy management service lines.
Medication non-adherence or failure to take medications as prescribed, is a significant area of concern. Solving the challenge has the potential to significantly improve patient outcomes, quality of care, and drive revenue growth.
Using Finarb's expertise in developing AI-powered solutions, the client was able to pinpoint factors contributing to non-adherence and devise interventions to reduce non-adherence. The solution enabled targeted and impactful interventions by prioritizing and segregating high risk and low risk patients into stratified actionable groups.
The Challenge
Medication non-adherence leads to high costs for healthcare systems, with estimates suggesting it adds about $500 billion to annual healthcare spending in the U.S., which is 16% of all healthcare expenses.
It also undermines treatment efficacy and results in sub-optimal health outcomes. Timely identification of high-risk patients in a large population and making prompt interventions to reduce non-adherence is a hard problem to solve. AI-powered solutions can aid in alleviating some of these challenges.
The task was to quantify the risk of medication non-adherence for a set of rheumatoid arthritis patients. Once patients were segregated into high-risk and low-risk categories, it became possible to identify drivers of non-adherence and recommend measures to mitigate them.
Business Impact Delivered
Finarb's solution significantly improved patient outcomes and healthcare efficiency. This aligned with our client's vision of transforming community healthcare. As many as 42% of the patients were at risk of non-adherence initially. Our solution delivered a 35%-40% reduction in risk of non-adherence over a deployment period of 6-12 months.
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