Trial reportTranslational behavioral medicine2021
Costing a population health management approach for participant recruitment to a diabetes prevention study.
Trial report in Translational behavioral medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Reach and Weight Loss Among Comparison Group Participants Who Enrolled in the Active Intervention After a Diabetes Prevention Trial.Preventing chronic disease · 2024Trial
- Considerations for Cost Assessment of Implementing Family Healthy Weight Programs Across Community and Clinical Contexts.Childhood obesity (Print) · 2026Article
- Costs and cost-effectiveness of a culturally adapted diabetes self-management and education program for Marshallese adults.Journal of clinical and translational science · 2026Article
- Cost-Effectiveness Analysis of Implementing a Multisectoral Program for Colorectal Cancer Screening in an African American Community.AJPM focus · 2025Article
- The use of implementation science theoretical approaches in hybrid effectiveness-implementation type 1 randomised trials of healthcare interventions: A scoping review.Implementation science : IS · 2025Article
- Enhancing Text Message Support With Media Literacy and Financial Incentives for Vaping Cessation in Young Adults: Protocol for a Pilot Randomized Controlled Trial.JMIR research protocols · 2025Article
- Socioeconomic and behavioral determinants of non-compliance with physician referrals following community screening for diabetes, hypertension and hyperlipidemia: a mixed-methods study.Scientific reports · 2023Article
- Understanding implementation costs of a pediatric weight management intervention: an economic evaluation protocol.Implementation science communications · 2022Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Limited research has reported the economic feasibility-from both a research and practice perspective-of efforts to recruit and enroll an intended audience in evidence-based approaches for disease prevention. We aimed to retrospectively assess and estimate the costs of a population health management (PHM) approach to identify, engage, and enroll patients in a Type 1 Hybrid Effectiveness-Implementation (HEI), diabetes-prevention trial. We used activity-based costing to estimate the recruitment costs of a PHM approach integrated within an HEI trial. We took the perspective of a healthcare system that may adopt, and possibly sustain, the strategy in the typical practice. We also estimated replication costs based on how the strategy could be applied in healthcare systems interested in referring patients to a local diabetes prevention program from a payer perspective. The total recruitment and enrollment costs were $360,424 to accrue 599 participants over approximately 15 months. The average cost per screened and enrolled participant was $263 and $620, respectively. Translating to the typical settings, total recruitment costs for replication were estimated as $193,971 (range: $43,827-$210,721). Sensitivity and scenario analysis results indicated replication costs would be approximately $283-$444 per patient enrolled if glucose testing was necessary, based on the Medicare-covered services. From a private payer perspective, and without glucose testing, per-participant assessed costs were estimated at $31. A PHM approach can be used to accrue a large number of participants in a short period of time for an HEI trial, at a comparable cost per participant.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.