Application of contextual design methods to inform targeted clinical decision support interventions in sub-specialty care environments

Abstract

Background & objectives: In healthcare, the routine use of evidence-based specialty care management plans is mixed. Targeted computerized clinical decision support (CCDS) interventions can improve physician adherence, but adoption depends on CCDS' 'fit' within clinical work. We analyzed clinical work in outpatient and inpatient settings as a basis for developing guidelines for optimizing CCDS design.

Methods: The contextual design approach guided data collection, collation and analysis. Forty (40) consenting physicians were observed and interviewed in general internal medicine inpatient units and gastroenterology (GI) outpatient clinics at two academic medical centers. Data were collated using interpretive debriefing, and consolidated using thematic analysis and three work modeling approaches (communication flow, sequence and artifact models).

Results: Twenty-six consenting physicians were observed at Site A and 14 at Site B. Observations included attending (33%) and resident physicians. During research team debriefings, 220 of 341 unique topics were categorized into 5 CCDS-relevant themes. Resident physicians relied on patient assessment & planning processes to support their roles as communication and coordination hubs within the medical team. Artifact analysis further elucidated the evolution of assessment and planning over work shifts.

Conclusions: The usefulness of CCDS tools may be enhanced in clinical care if the design: 1) accounts for clinical work that is distributed across people, space, and time; 2) targets communication and coordination hubs (specific roles) that can amplify the usefulness of CCDS interventions; 3) integrates CCDS with early clinical assessment & planning processes; and 4) provides CCDS in both electronic & hardcopy formats. These requirements provide a research agenda for future research in clinician-CCDS integration.

Keywords: Cirrhosis; Computerized clinical decision support; Contextual design methods; Human factors engineering; Specialty care.