OBJECTIVES: The shift in the balance of health care, bringing services 'closer to home', is a well-established trend. This study sought to provide insight into the consequences of this trend, in particular the stimulation of demand, by exploring the underlying feedback structure. METHODS: We constructed a simulation model using the system dynamics method, which is specifically designed for the analysis of feedback structure. The model was calibrated to two cases of the shift in cardiac catheterization services in the UK. Data sources included archival data, observations and interviews with senior health care professionals. Key model outputs were the basic trends displayed by waiting lists, average waiting times, cumulative patient referrals, cumulative patient activity and cumulative overall costs. RESULTS: Demand was stimulated in both cases via several different mechanisms. We revealed the roles for clinical guidelines and capacity changes, and the typical responses to imbalances between supply and demand. Our analysis also demonstrated the potential benefits of changing the goals that drive activity by seeking a waiting list goal rather than a waiting time goal. CONCLUSIONS: Appreciating the wider consequences of shifting the balance of care is essential if services are to be improved overall. The underlying feedback mechanisms of both intended and unintended effects need to be understood. Using a systemic approach, more effective policies may be designed through coordinated programmes rather than isolated initiatives, which may have only a limited impact.
OBJECTIVES: The shift in the balance of health care, bringing services 'closer to home', is a well-established trend. This study sought to provide insight into the consequences of this trend, in particular the stimulation of demand, by exploring the underlying feedback structure. METHODS: We constructed a simulation model using the system dynamics method, which is specifically designed for the analysis of feedback structure. The model was calibrated to two cases of the shift in cardiac catheterization services in the UK. Data sources included archival data, observations and interviews with senior health care professionals. Key model outputs were the basic trends displayed by waiting lists, average waiting times, cumulative patient referrals, cumulative patient activity and cumulative overall costs. RESULTS: Demand was stimulated in both cases via several different mechanisms. We revealed the roles for clinical guidelines and capacity changes, and the typical responses to imbalances between supply and demand. Our analysis also demonstrated the potential benefits of changing the goals that drive activity by seeking a waiting list goal rather than a waiting time goal. CONCLUSIONS: Appreciating the wider consequences of shifting the balance of care is essential if services are to be improved overall. The underlying feedback mechanisms of both intended and unintended effects need to be understood. Using a systemic approach, more effective policies may be designed through coordinated programmes rather than isolated initiatives, which may have only a limited impact.
Authors: Lukas K Schoenenberger; Steffen Bayer; John P Ansah; David B Matchar; Rajagopal L Mohanavalli; Sean Sw Lam; Marcus Eh Ong Journal: SAGE Open Med Date: 2016-10-04