Healthcare routines are a series of events and interdependent elements needed for patient care.  Understanding clinic visit processes requires knowledge of all the roles involved and work done during the visit. In business, knowing how routines support work activities is key to efficiency. We interviewed individuals in each role in dermatology clinics at University of Rochester to see how the understanding of clinic visit processes differ by role. Interviewers obtained a description of a typical clinic visit from check-in to checkout as a sequence of actions from physicians, residents, LPNs, technicians, and office staff.  The variations of these steps for different clinic visit scenarios were noted (i.e., follow-up, new, surgery, biopsy). Each interviewee had detailed knowledge of their own actions, but also had some knowledge of the larger process. We used ThreadNet, a novel, R-coded, graph-theoretic methodology to convert the narrative threads of interview data into event networks summarizing the clinical visit routine from the point of view of each participant.  We found different roles have different perspectives on each other’s work. Office staff and residents seemed largely unaware of each other’s work. In contrast, LPNs had a clear view of residents’ work, while residents minimized the work of LPNs.  Evaluation of the whole clinical process from four points of view showed that LPNs had a more complete view of the overall visit process (37%) compared to office staff (25%) or residents (27%). While physicians had the best overall view of visit process (54%), their point of view only accounted for half of the whole process. A complete picture of clinic visit process required aggregation of the multiple points of view. We conclude that clinic staff are primarily aware of their own work instead of the overall process. Educational interventions portraying clinic process as aggregated networks of interdependent roles and actions may improve comprehension of clinic process, clinic efficiency, and quality of care.

Visualizing clinic routines from multiple points of view