In the United States, approximately half of all adults—116 million people—suffer from hypertension, a critical condition that often requires medication management. To tackle this widespread health concern, Piedmont Healthcare, a not-for-profit health system with an extensive reach across Georgia, has turned to predictive analytics to enhance adherence to blood pressure medications. This innovative approach targets the intricate challenges of medication adherence, aiming to mitigate serious health risks and improve clinical outcomes for patients struggling with hypertension.
Understanding the Importance of Medication Adherence
The Impact on Public Health
Medication adherence is crucial in the management of hypertension, as failure to take prescribed medications as directed can lead to severe health complications. The consequences of non-adherence include high risks associated with heart disease, stroke, and chronic kidney disease, which are among the leading causes of morbidity and mortality in the United States. Tim Hall, senior business intelligence developer at Piedmont Healthcare, emphasizes that maintaining consistent medication routines significantly reduces these risks, ultimately contributing to lower healthcare costs and improved patient outcomes.
A striking factor in the fight against hypertension is the significant number of patients who do not adhere to their prescribed medication regimens. In Georgia alone, self-reported hypertension prevalence among adults was between 30.1% and 31.9% in 2017. Given these statistics, Piedmont Healthcare recognized a critical need to address this issue head-on, employing advanced data analytics to proactively manage and improve medication adherence. By integrating prescription fill data with predictive analytics within their health information systems, Piedmont seeks to identify at-risk patients and prioritize their care accordingly.
The Role of Predictive Analytics
Predictive analytics has become a powerful tool in addressing the challenges of medication non-adherence. By analyzing historical data and identifying patterns that predict future behavior, healthcare providers can intervene earlier and more effectively. Piedmont Healthcare’s integration of predictive analytics scores into electronic health records (EHRs) enhances patient prioritization and enables healthcare providers to make precise, data-driven decisions. This proactive approach allows for targeted interventions, which can lead to significant improvements in patient adherence and overall health outcomes.
The integration of intervention-level data and social determinants of health from EHRs further refines the predictive analytics model. These additional layers of data help healthcare providers to tailor interventions more effectively, sometimes automating them to ensure timely and consistent follow-up with patients. The result is a more comprehensive strategy that addresses the multifaceted issues contributing to medication non-adherence. Such integration not only enhances patient care but also aligns with value-based care goals, emphasizing quality and outcomes over the volume of services provided.
Implementation and Results
Multidisciplinary Team Approach
The successful development and implementation of an effective predictive analytics model for medication adherence require a substantial investment of time and resources. Piedmont Healthcare has taken a multidisciplinary team approach, enlisting the expertise of developers, business owners, executives, operations staff, clinicians, analysts, and other stakeholders. This collaborative effort ensures that the model is robust, accurate, and can be seamlessly integrated into existing workflows within the organization’s population health department.
Tim Hall, along with Dr. Thomas Wells and Melissa Robinson, PharmD, from Piedmont Healthcare, plans to present the findings and discuss the development and implementation of their predictive analytics model at the HIMSS25 session. This session aims to provide attendees with a comprehensive understanding of how to implement predictive analytics to improve medication adherence and ultimately enhance patient outcomes. By sharing their insights and experiences, the team hopes to inspire other healthcare organizations to adopt similar strategies in their own medication adherence initiatives.
Measuring Success and Future Considerations
In the United States, about half of the adult population—116 million people—live with hypertension, a serious condition often requiring medication for management. To address this widespread health issue, Piedmont Healthcare, a not-for-profit health system with a significant presence in Georgia, has turned to predictive analytics. This advanced method is designed to improve adherence to blood pressure medications, a crucial factor in managing hypertension effectively. By focusing on the complex challenges associated with medication adherence, Piedmont Healthcare aims to reduce severe health risks and enhance clinical outcomes for patients dealing with hypertension. Their innovative approach not only targets individual patient needs but also aims to implement broader strategies that can be adapted across various healthcare settings to improve overall patient health. This commitment to leveraging technology for better healthcare outcomes highlights Piedmont’s dedication to tackling one of the most pervasive health concerns in America today.
