Implementation science for ambulatory care safety: a novel method to develop context-sensitive interventions to reduce quality gaps in monitoring high-risk patients

Abstract

Background: Missed evidence-based monitoring in high-risk conditions (e.g., cancer) leads to delayed diagnosis. Current technological solutions fail to close this safety gap. In response, we aim to demonstrate a novel method to identify common vulnerabilities across clinics and generate attributes for context-flexible population-level monitoring solutions for widespread implementation to improve quality.

Methods: Based on interviews with staff in otolaryngology, pulmonary, urology, breast, and gastroenterology clinics at a large urban publicly funded health system, we applied journey mapping to co-develop a visual representation of how patients are monitored for high-risk conditions. Using a National Academies framework and context-sensitivity theory, we identified common systems vulnerabilities and developed preliminary concepts for improving the robustness for monitoring patients with high-risk conditions ("design seeds" for potential solutions). Finally, we conducted a face validity and prioritization assessment of the design seeds with the original interviewees.

Results: We identified five high-risk situations for potentially consequential diagnostic delays arising from suboptimal patient monitoring. All situations related to detection of cancer (head and neck, lung, prostate, breast, and colorectal). With clinic participants we created 5 journey maps, each representing specialty clinic workflow directed at evidence-based monitoring. System vulnerabilities common to the different clinics included challenges with: data systems, communications handoffs, population-level tracking, and patient activities. Clinic staff ranked 13 design seeds (e.g., keep patient list up to date, use triggered notifications) addressing these vulnerabilities. Each design seed has unique evaluation criteria for the usefulness of potential solutions developed from the seed.

Conclusions: We identified and ranked 13 design seeds that characterize situations that clinicians described 'wake them up at night', and thus could reduce their anxiety, save time, and improve monitoring of high-risk patients. We anticipate that the design seed approach promotes robust and context-sensitive solutions to safety and quality problems because it provides a human-centered link between the experienced problem and various solutions that can be tested for viability. The study also demonstrates a novel integration of industrial and human factors methods (journey mapping, process tracing and design seeds) linked to implementation theory for use in designing interventions that anticipate and reduce implementation challenges.

Keywords: Ambulatory care; Cancer; Design seeds; Diagnostic error; Human factors; Journey mapping; Organizational interventions; Patient monitoring; Patient safety.

Fig. 1

a Technical Intervention Development Cycle. b Socio-Technical Intervention Development Cycle: Design Seed Theory. The figures show that the socio-technical design seed intervention development adds an intermediate step that translates expressed vulnerabilities into multiple solution possibilities and evaluation markers. In contrast to a singular solution provided when linking a problem directly to a proposed solution, design seeds tease apart the expressed vulnerability to offer a distinct set of evaluable solutions that can be tested independently. Design seeds yield a menu of modular options for implementers considering differing organizational context

Fig. 2

a Abnormal Colonoscopy Journey Map. b Ear Nose and Throat (ENT) Cancer Journey Map. Investigators constructed journey maps that follow the management of patients who are being monitored and treated for cancer, as articulated by clinical participants. Similar activities and actions are clustered into vertical “swim lanes,” arrows indicate the flow between actions, and bull’s eye targets mark actions that are particularly vulnerable to missed monitoring. For example, an action that does not have an “owner” may instigate a higher risk for patient loss to follow-up

Fig. 3

Process Trace Sequences. The display shows process trace sequences of major activities, and the constant tracking to monitor high-risk patients. Each clinic sequence is derived from a tricolor-coded version of its original journey map (Additional file 5).

Fig. 4

a Technical Intervention Development Cycle: Example. b Socio-Technical Intervention Development Cycle: Design Seed Example. The Pivotal Role of Design Seeds for Intervention Development: Design seeds offer an important bridge between identifying problems and solutions. For the design seed– a population registry for high-risk patients – the diagram shows the evaluable components of the design seed in the light blue boxes. At the solution development stage, different technical and/or organizational interventions can be tested to see if they meet the design seed requirement. Solution components, shown in dark blue boxes, that meet the design seed requirement (based on iterative testing) can be assembled as a comprehensive intervention for further testing and deployment