Pragmatic considerations and approaches for measuring staff time as an implementation cost in health systems and clinics: key issues and applied examples - Huebschmann, Amy G.; Trinkley, Katy E.; Gritz, Mark; Glasgow, Russell E. (Implementation science communications, 2022)
Background As the field of implementation science wrestles with the need for system decision-makers to anticipate the budget impact of implementing new programs, there has been a push to report implementation costs more transparently. For this purpose, the method of time-driven activity-based costing (TDABC) has been heralded as a pragmatic advance. However, a recent TDABC review found that conventional methods for estimating staff time remain resource-intensive and called for simpler alternatives. Our objective was to conceptually compare conventional and emerging TDABC approaches to measuring staff time. Methods Our environmental scan of TDABC methods identified several categories of approaches for staff time estimation; across these categories, staff time was converted to cost as a pro-rated fraction of salary/benefits. Conventional approaches used a process map to identify each step of program delivery and estimated the staff time used at each step in one of 3 ways: (a) uniform estimates of time needed for commonly occurring tasks (self-report), (b) retrospective “time diary” (self-report), or (c) periodic direct observation. In contrast, novel semi-automated electronic health record (EHR) approaches “nudge” staff to self-report time for specific process map step(s)—serving as a contemporaneous time diary. Also, novel EHR-based automated approaches include timestamps to track specific steps in a process map. We compared the utility of these TDABC approach categories according to the 5 R’s model that measures domains of interest to system decision-makers: relevance, rapidity, rigor, resources, and replicability, and include two illustrative case examples. Results The 3 conventional TDABC staff time estimation methods are highly relevant to settings but have limited rapidity, variable rigor, are rather resource-intensive, and have varying replicability. In contrast to conventional TDABC methods, the semi-automated and automated EHR-based approaches have high rapidity, similar rigor, similar replicability, and are less resource-intensive, but have varying relevance to settings. Conclusions This synthesis and evaluation of conventional and emerging methods for staff time estimation by TDABC provides the field of implementation science with options beyond the current approaches. The field remains pressed to innovatively and pragmatically measure costs of program delivery that rate favorably across all of the 5 R’s domains.