Time–motion analysis of external facilitation for implementing the Collaborative Chronic Care Model in general mental health clinics: Use of an interval-based data collection approach

Abstract

Background: Facilitation is an effective strategy to implement evidence-based practices, often involving external facilitators (EFs) bringing content expertise to implementation sites. Estimating time spent on multifaceted EF activities is complex. Furthermore, collecting continuous time–motion data for facilitation tasks is challenging. However, organizations need this information to allocate implementation resources to sites. Thus, our objectives were to conduct a time–motion analysis of external facilitation, and compare continuous versus noncontinuous approaches to collecting time–motion data. Methods: We analyzed EF time–motion data from six VA mental health clinics implementing the evidence-based Collaborative Chronic Care Model (CCM). We documented EF activities during pre-implementation (4–6 weeks) and implementation (12 months) phases. We collected continuous data during the pre-implementation phase, followed by data collection over a 2-week period (henceforth, “a two-week interval”) at each of three time points (beginning/middle/end) during the implementation phase. As a validity check, we assessed how closely interval data represented continuous data collected throughout implementation for two of the sites. Results: EFs spent 21.8 ± 4.5 h/site during pre-implementation off-site, then 27.5 ± 4.6 h/site site-visiting to initiate implementation. Based on the 2-week interval data, EFs spent 2.5 ± 0.8, 1.4 ± 0.6, and 1.2 ± 0.6 h/week toward the implementation’s beginning, middle, and end, respectively. Prevalent activities were preparation/planning, process monitoring, program adaptation, problem identification, and problem-solving. Across all activities, 73.6% of EF time involved email, phone, or video communication. For the two continuous data sites, computed weekly time averages toward the implementation’s beginning, middle, and end differed from the interval data’s averages by 1.0, 0.1, and 0.2 h, respectively. Activities inconsistently captured in the interval data included irregular assessment, stakeholder engagement, and network development. Conclusions: Time–motion analysis of CCM implementation showed initial higher-intensity EF involvement that tapered. The 2-week interval data collection approach, if accounting for its potential underestimation of irregular activities, may be promising/efficient for implementation studies collecting time–motion data.

Adaptation for sustainability in an implementation trial of team-based collaborative care

“…Third, active facilitation, as demonstrated by the time–motion study conducted during the original BHIP-CCM Enhancement Project, was delivered as 6 months of structured activities followed by ad hoc provision of as-needed support to the sites for an additional 6 months (i.e., a total of 12 months of facilitation; Kim et al, 2022 ). Based on sustainability data and multiple sources of input, the project team reached the conclusions that (a) the unstructured support (provided in months 6–12) was of limited utility and (b) making structured facilitation available to the sites for a longer duration of time would be helpful to enhance sustainability.…”

“…Thus, the BHIP-CCM Enhancement Project 2.0 will have 8 months of structured facilitation. To maintain facilitation resources at a reasonable level even with this increased duration of active facilitation, the overall active facilitation period will be limited to these 8 months instead of 12 months total ( Kim et al, 2022 ). Ideally, this provision of longer active facilitation—but in the context of a shorter overall implementation time period—will efficiently support the sustainability of CCM-based BHIP teams at the sites enrolled in the BHIP-CCM Enhancement Project 2.0.…”

Getting to implementation: Adaptation of an implementation playbook

“…Alternative approaches using pragmatic, efficient, and periodic methods are needed, while taking care to track granular changes over time. Continued innovative thinking and translation of other industrial engineering methods may both lessen the burden of tracking and improve the science (53). Importantly, as done in this study, ongoing and midcourse rather than solely post-hoc evaluation of modifications is needed to capture complete information and glean insights (54).…”

A mixed methods examination of session planning among public mental health therapists

“…25 Future research should investigate therapists' actual time spent on session planning and the kinds of session planning activities they engage in by deploying a time-motion study method, a method designed to document all time employees spend on work-related activities. 26,27 Another limitation is the relatively small number of participants who completed the initial survey. Additionally, the results of this study and others suggest that many Philadelphia public mental health therapists are overburdened by their many responsibilities, making it challenging to recruit these therapists for research studies.…”