SUMMARY
The research interests of Benjamin (Ben) D. Pollock, Ph.D., include predictive analytics and methodologies for measuring hospital quality and clinical outcomes. His research uses electronic health record (EHR) and registry and claims data to blend epidemiologic methods, health services research, and risk adjustment and prediction.
Focus areas
- Evaluating the ways that inappropriate data, definitions and modeling can yield misleading results. There are many domains of clinical outcomes by which hospitals are measured, scored, compared and potentially penalized for poor performance. These measures include mortality, readmissions, hospital-acquired infections and patient safety indicators. Dr. Pollock engages in critical analysis of these risk-adjustment methodologies to suggest ways to reduce potential biases in these metrics.
- Novel development of risk-adjusted hospital value metrics. Historically, clinicians and hospital administrators have rightly focused on the quality of care they provide. Today, the cost and value of that care are becoming increasingly important to patients. In addition to studying hospital quality outcome methodologies, Dr. Pollock seeks to develop novel hospital metrics to assess the value of care a patient receives; this begins with the basic assumption that value equals quality over cost.
- Observational epidemiologic methods and life course cardiovascular health. As a doctoral student at Tulane University, Dr. Pollock gained experience in the design and analysis of observational studies through working within the National Institutes of Health-funded Bogalusa Heart Study, the world's longest-running biracial cardiovascular cohort. Through this work, it was identified that the overall cardiovascular health of children is very flexible as they transition to adulthood. This implies that children with low-risk cardiovascular profiles compared with those of their peers are not necessarily destined for better adult cardiovascular health, but rather they must continue to practice preventive cardiovascular measures throughout the lifespan.
- Exploring disparities in clinical outcomes and scientific research between men and women. Dr. Pollock's research in this area has shown that women have significantly higher risk of mortality after coronary artery bypass graft surgery than men. Findings from this study also show that women remain underrepresented as first authors in major medical journals despite recent increases.
Significance to patient care
When choosing where to seek hospital care, patients often rely on external hospital rankings such as the U.S. News & World Report's Best Hospitals list and the Centers for Medicare & Medicaid Services' Overall Hospital Quality Star Ratings. Dr. Pollock's research seeks to ensure that these rankings are based on valid metrics and methodologies in their assessment and comparison of hospital outcomes. For example, his research has suggested that 30-day mortality metrics may be biased against hospitals that see larger volumes of patients with do-not-resuscitate orders when in fact those hospitals may actually provide better patient-centered end-of-life care. Ultimately, the goal is to provide patients with the most reliable data possible so they can make their own well-informed decisions.
In addition, Dr. Pollock, along with other clinical and statistical leaders, participated in Mayo Clinic's COVID-19 Predictive Modeling Task Force, which provided key insight on the short- and intermediate-term predicted hospital COVID-19 census to allow operational planning of future bed availability so that hospitals could continue to safely provide elective and nonurgent procedures during the pandemic.
Professional highlights
- Robert D. and Patricia E. Kern Scientific Director for Data Science, 2021-present.