Real-world quantification of implementation dose across twenty-five implementation instances

There are many approaches in implementation science research and practice to prospectively and pragmatically measure the amount of effort required to implement a particular evidence-based practice (EBP). We sought to 1) demonstrate how to prospectively and pragmatically document implementation activities in a real-world implementation trial; 2) quantify implementation dose (frequency and time spent) across the implementation of four EBPs; and 3) explore potential drivers of variation in implementation dose across EBP, sites, implementation progress, and wave.

We built on the existing literature to develop a prospective and pragmatic way to track implementation activities during a type III hybrid effectiveness-implementation stepped wedge trial. We then quantified both total implementation dose (defined as total time spent by the implementer team) and how much of this dose was synchronous (defined as time spent working directly with local implementers at the sites receiving the intervention). We used multiple linear regression to understand what factors may influence differences in total implementation dose delivered (such as which evidence-based practice was being implemented, in which wave of the stepped wedge, at which medical centers), as well as how dose was related to implementation progress, categorized by 1) decision to participate, 2) training, 3) implementation with support, and 4) independent implementation.

From 2022 to 2023, we prospectively captured implementation dose across 25 implementation instances related to four EBPs that were implemented at seven VA medical centers. We implemented Surgical Pause seven times, TAP six times, CAPABLE six times, and EMPOWER six times. We captured and categorized 1,271 h of implementation activities. Asynchronous administrative activities were most common across implementation phases. Other common synchronous activities include engaging collaborators, problem solving, providing updates, and ongoing action/implementation planning. The EBP was the largest driver of variation in implementation dose overall. Site, implementation progress, and wave did not independently explain variations in implementation dose.

The EBP being implemented was a much stronger predictor of the implementation dose required than were other factors, such as experience implementing the EBP or characteristics of the medical center where the intervention was being implemented.