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Published on: February 2, 2017
Costs to Implement a Pediatric Weight Management Program Across 3 Distinct Contexts
Natalie Riva Smith1,2, Meg Simione3,4, Haley Farrar-Muir3
1Department of Social and Behavioral Sciences, Harvard TH Chan School of Public Health.
Insights
Implementing the Connect for Health pediatric weight management program costs between $77,103 and $142,721. Technology setup, clinician training, and stakeholder engagement were key cost drivers for this evidence-based intervention.
Area of Science:
- Public Health
- Health Services Research
- Pediatric Obesity
Background:
- The Connect for Health program is an evidence-based pediatric weight management intervention.
- It aligns with national recommendations and offers clinical decision support, educational materials, and community resources.
- Implementation costs significantly influence program adoption and sustainability, particularly in health systems serving low-income populations with high childhood obesity rates.
Purpose of the Study:
- To assess the implementation costs of the Connect for Health program across three diverse health systems.
- To identify major cost drivers associated with program implementation in settings serving vulnerable populations.
Main Methods:
- Utilized time-driven activity-based costing (TDABC) to evaluate implementation expenses.
- Health systems developed process maps and detailed reports of all implementation actions.
- Personnel time and associated costs were meticulously recorded for each activity, including electronic health record integration and clinician training.
Main Results:
- Overall implementation costs varied across the three health systems, ranging from $77,103 to $142,721.
- Technological setup represented a primary cost driver, alongside clinician training, stakeholder engagement, and audit/feedback activities.
- The program demonstrated ease of integration into routine well-child visits.
Conclusions:
- Key cost drivers for implementing the Connect for Health program include technological setup, training, and stakeholder engagement.
- Context-specific factors significantly influence implementation costs.
- Accurate cost projections for future implementations necessitate careful consideration of organizational context and chosen implementation strategies.
Background:
The Connect for Health program is an evidence-based program that aligns with national recommendations for pediatric weight management and includes clinical decision support, educational handouts, and community resources. As implementation costs are a major driver of program adoption and maintenance decisions, we assessed the costs to implement the Connect for Health program across 3 health systems that primarily serve low-income communities with a high prevalence of childhood obesity.
Methods:
We used time-driven activity-based costing methods. Each health system (site) developed a process map and a detailed report of all implementation actions taken, aligned with major implementation requirements (eg, electronic health record integration) or strategies (eg, providing clinician training). For each action, sites identified the personnel involved and estimated the time they spent, allowing us to estimate the total costs of implementation and breakdown costs by major implementation activities.
Results:
Process maps indicated that the program integrated easily into well-child visits. Overall implementation costs ranged from $77,103 (Prisma Health) to $84,954 (Denver Health) to $142,721 (Massachusetts General Hospital). Across implementation activities, setting up the technological aspects of the program was a major driver of costs. Other cost drivers included training, engaging stakeholders, and audit and feedback activities, though there was variability across systems based on organizational context and implementation choices.
Conclusions:
Our work highlights the major cost drivers of implementing the Connect for Health program. Accounting for context-specific considerations when assessing the costs of implementation is crucial, especially to facilitate accurate projections of implementation costs in future settings.
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