Development of a Tool for Population Health Risk Stratification in Primary Care Through Consensus-Seeking Techniques
Author(s)
Carolina Castagna, MD, MPH1, Andrew Huff, MPH1, Aaron Douglas, PhD1, Matteo Garofano, MS2, Massimo Fabi, MD3, Richard Hass, PhD1, Vittorio Maio, MS, MSPH, PharmD1;
1Thomas Jefferson University, Philadelphia, PA, USA, 2Local Health Authority of Parma, Parma, Emilia-Romagna, Italy, Parma, Italy, 3University Hospital, Parma, Emilia-Romagna, Italy, Parma, Italy
1Thomas Jefferson University, Philadelphia, PA, USA, 2Local Health Authority of Parma, Parma, Emilia-Romagna, Italy, Parma, Italy, 3University Hospital, Parma, Emilia-Romagna, Italy, Parma, Italy
Presentation Documents
OBJECTIVES: This study aimed to develop a risk stratification tool for managing population health and allocating healthcare resources in primary care using expert consensus-seeking techniques.
METHODS: A multidisciplinary expert panel of 24 healthcare professionals, including primary care providers (PCPs), specialists, and allied health professionals, was convened by Local Health Authority of Parma, Italy. Using the Nominal Group Technique, the panel was asked to define ‘health risk’ and identify contributing factors based on clinical and social relevance and data availability in patients’ PCP electronic medical records. A modified Delphi process, following ACCORD guidelines for consensus-based methods, was conducted in three rounds (July-October 2024) to derive numerical weights for the factors. Survey questions rated the perceived importance of factors using a Likert scale (1 = no importance to 9 = critical importance). Consensus, defined as ≥75% agreement among panelists, set each factor’s weight to the median importance rating.
RESULTS: Health risk was defined as “the likelihood of a progressive deterioration of an individual’s health status due to medical and/or psychosocial-welfare conditions that could lead to hospitalization or death within a year.” A total of 31 clinical and social factors were identified, and consensus about importance was achieved for all factors. Higher-weighted factors included advanced age, excessive polypharmacy, cancer, cognitive impairment, and social-psychological distress, followed by clinical conditions such as renal failure, stroke, and heart failure, and previous hospitalizations and emergency room visits.
CONCLUSIONS: The tool provides a robust framework for population health risk stratification in primary care, aligning with Italy's healthcare reform goals. Future phases will validate the tool’s predictive performance using patient-level PCP data and assess its implications for policy and practice.
METHODS: A multidisciplinary expert panel of 24 healthcare professionals, including primary care providers (PCPs), specialists, and allied health professionals, was convened by Local Health Authority of Parma, Italy. Using the Nominal Group Technique, the panel was asked to define ‘health risk’ and identify contributing factors based on clinical and social relevance and data availability in patients’ PCP electronic medical records. A modified Delphi process, following ACCORD guidelines for consensus-based methods, was conducted in three rounds (July-October 2024) to derive numerical weights for the factors. Survey questions rated the perceived importance of factors using a Likert scale (1 = no importance to 9 = critical importance). Consensus, defined as ≥75% agreement among panelists, set each factor’s weight to the median importance rating.
RESULTS: Health risk was defined as “the likelihood of a progressive deterioration of an individual’s health status due to medical and/or psychosocial-welfare conditions that could lead to hospitalization or death within a year.” A total of 31 clinical and social factors were identified, and consensus about importance was achieved for all factors. Higher-weighted factors included advanced age, excessive polypharmacy, cancer, cognitive impairment, and social-psychological distress, followed by clinical conditions such as renal failure, stroke, and heart failure, and previous hospitalizations and emergency room visits.
CONCLUSIONS: The tool provides a robust framework for population health risk stratification in primary care, aligning with Italy's healthcare reform goals. Future phases will validate the tool’s predictive performance using patient-level PCP data and assess its implications for policy and practice.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
HSD95
Topic
Health Service Delivery & Process of Care
Disease
No Additional Disease & Conditions/Specialized Treatment Areas