The efficient delivery of high-quality care can be a key indicator to patient satisfaction in medical settings. In this project, I worked with a team of analysts to provide suggestions to assist a major East Coast hospital decrease the wait time at a pharmacy for medication. To do this, I preformed a Contexual Inquiry with pharmacy technicians, taking detailed notes and observations on employee actions, attitudes, and thoughts as they preformed their work. I then collaborated with a data scientist who modeled employee behavior, to determine the optimal layout of the pharmacy laboratory, and placement of workers to greatly reduce pharmacy wait times.

Collaborator: Ryan Gillard

Photo credit: Victor via Flickr

As a first step in this process, I sketched out the layout of the pharmacy and noted the general area in which pharmacy technicians and pharmacists worked. Next, I made copies of these sketches so that I could quickly note the movement of pharmacists throughout the laboratory during my Contextual Inquiry.

For my Contextual Inquiry, I arranged to shadow employees at every major stage of the medication filling process, from the clerk which took in prescriptions at the front window, to the tech who filled prescriptions, to the pharmacist who rechecked the prescriptions.

During my Contexual Inquiries, I sketched out sequence models, showing the actual flow of a person's work, from the trigger that initiated the action to the individual steps that each user actually took in the process, including breakdowns.

I also noted actions which diverted or changed the workflow, like a telephone call, or a pause to have a conversation with a coworker. These notes, assisted the data scientist that I worked with every Friday in modeling the complexities of the lab, which went beyond the detail available in a regular process map.

Throughout my observations, I would ask questions of the worker I was following, probing to see not only what they were doing, buy why they were doing certain actions. These questions, probing into the "why" of the workers actions was useful in understanding the true motivations behind behavior, and gave clues to strategies for change management.

Pharmacist Photo Credit: Doug Waldron, Flickr (photo not from project)

At the end of each week I would discuss my findings with the data scientist modeling the pharmacy and recreate the sequence maps on the board with him.

These maps helped to fill in the gaps of understanding left by previous process maps and allowed the data scientist I to model the processes with a greater level of nuance and precision.

Later, I created digital versions of the white-boarded sequence models, which could be shared by our distributed team.