Approximately half of the adults in the United States (116 million) have high blood pressure, or hypertension, with 91.7 million needing prescription medication in addition to lifestyle changes. As of 2017, the self-reported prevalence of hypertension in adults aged 20 and older in Georgia is 30.1% to 31.9%, reported Tim Hall, senior business intelligence developer at Piedmont Healthcare.
Piedmont Health is a not-for-profit health system with 1,755 locations serving communities that comprise 85% of Georgia's population.
"If patients were more adherent to their hypertension medications and blood pressure was better controlled, patients would decrease their risk for heart disease, stroke and chronic kidney disease, which are leading causes of death, disability and high healthcare expenditures," Hall explained.
"Using prescription fill data and predictive analytics systems integrated into its health information systems, Piedmont Healthcare developed a project to identify the highest priority patients for intervention to increase their medication adherence rates, improving clinical outcomes and patient safety while meeting value-based care goals."
A big success
Initial results showed improvements in adherence measured by the proportion of days covered, and diastolic and systolic blood pressure values in the treatment group as well as a reduction in wasted clinician intervention.
Hall will be presenting results and much more in a HIMSS25 session entitled "Implementing Predictive Analytics to Improve Medication Adherence," Thursday, March 6 at 8:30 a.m. in Caesars Forum 115. Hall's co-presenters will be Dr. Thomas Wells and Melissa Robinson, PharmD, both from Piedmont Healthcare.
"In addition to these promising results, we want to share in the session our approach to the development of a predictive analytics model and the feasibility of implementation into an existing workflow within our population health department," he added.
Predictive analytics is playing a crucial role in healthcare, particularly in tackling medication nonadherence, he said.
Earlier intervention
"By integrating predictive analytics scores into electronic health record systems and other health information technologies, providers can identify at-risk patients and intervene earlier," he continued. "Incorporating additional prescription fill history from a population health management system further refines prioritization, allowing for more precise, data-driven decisions.
"Additionally, by leveraging intervention-level data and social determinants of health from EHRs, healthcare organizations can develop more targeted and potentially automated interventions to improve adherence and patient outcomes," he said.
Hall has plenty of advice he shares here and in his educational session.
"Leveraging predictive analytics and prescription fill data to inform and design patient interventions, we can positively impact medication adherence, which, in turn, improves patient outcomes," he explained.
"Developing a successful predictive analytics model and implementation is an investment, both of time and resources," he concluded. "A multidisciplinary team approach that includes developers, business owners, executives, operations, clinicians, analysts and other stakeholders will help to ensure success. Choosing metrics to measure the success of your predictive analytics project should include the clinical impact in addition to any other financial or operations problem your organization is trying to solve."
The Piedmont education session, "Implementing Predictive Analytics to Improve Medication Adherence," is scheduled for Thursday, March 6, from 8:30-to 9:30 a.m. in Caesars | Forum 116 at HIMSS25 in Las Vegas.
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