AI Article Synopsis

  • Behavioral interventions using electronic devices, financial incentives, and trained staff are important for promoting healthy behaviors but face challenges in cost assessment for wider adoption.
  • Current cost information is often lacking because traditional billing data can't capture the necessary resources, making pragmatic clinical trials crucial yet rarely inclusive of costing studies.
  • This article serves as a guide for researchers to effectively collect and analyze cost data during trials, emphasizing the separation of implementation costs from research costs and offering strategies for detailed cost data gathering.

Article Abstract

Behavioral interventions involving electronic devices, financial incentives, gamification, and specially trained staff to encourage healthy behaviors are becoming increasingly prevalent and important in health innovation and improvement efforts. Although considerations of cost are key to their wider adoption, cost information is lacking because the resources required cannot be costed using standard administrative billing data. Pragmatic clinical trials that test behavioral interventions are potentially the best and often only source of cost information but rarely incorporate costing studies. This article provides a guide for researchers to help them collect and analyze, during the trial and with little additional effort, the information needed to inform potential adopters of the costs of adopting a behavioral intervention. A key challenge in using trial data is the separation of implementation costs, the costs an adopter would incur, from research costs. Based on experience with 3 randomized clinical trials of behavioral interventions, this article explains how to frame the costing problem, including how to think about costs associated with the control group, and describes methods for collecting data on individual costs: specifications for costing a technology platform that supports the specialized functions required, how to set up a time log to collect data on the time staff spend on implementation, and issues in getting data on device, overhead, and financial incentive costs.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7772275PMC
http://dx.doi.org/10.1177/0272989X20973160DOI Listing

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