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A 400 provider multispecialty medical group wanted to reevaluate its care delivery models and restructure the clinic scheduling template within its surgical practices as a result of long patient cycle times.


Background

This multispecialty medical group with more than 400 providers in 120 locations wanted to reevaluate its care delivery models and restructure the clinic scheduling template within its surgical practices as a result of long patient cycle times. Inefficiencies in the current practice lead to providers working well past the clinic’s hours of operation, resulting in patient and provider dissatisfaction. Average cycle time ranged from 62 to 139 minutes for patients with scheduled appointments.  This physician network engaged GEHC Camden Group to help determine if a 1:1 physician to advanced practice provider (“APP”) model created greater efficiencies than utilizing a pool of APPs.

Our Approach

GEHC Camden Group utilized simulation modeling technology to test four combinations of two primary variables: the care model (e.g., 1:1 vs. pool scenarios) and clinic schedule alignment (e.g., APP and MD schedule alignment vs. no change) in order to evaluate the effects on patient waiting and cycle time. We obtained detailed information on the APP and physician clinic scheduling grids, including the number of slots by appointment type each day, processing times of medical assistant’s duties, and the time providers spend with their patients. A current state model was built and validated with the client to ensure model efficacy.

Scenario 1 represented the current state with a pooling care model and no adjustments to the clinic schedules. Scenario 2 used the same pooling care model with modification to the scheduling grids to determine if alignment of the APP’s schedule to better match the physicians would decrease patient waiting. In order to test the 1:1 care model ratio for Scenario 3, the simulation model was modified to include an additional APP which required touch points with a specific physician, but no changes to the schedule were made. In Scenario 4 both the 1:1 model and schedule adjustments were made. It was quickly identified from Scenario 3 that the exam rooms become a bottleneck when an additional APP is added to the clinic, so an optimization was run, and an additional three rooms were added to this scenario to allow for a comparison of cycle times absent this constraint.

A number of variables were discovered to have a direct impact on the simulation modeling results including clinic start time, duration of appointments, appointment schedule cohesiveness among physicians and APPs, the number and type of patients seen per day, as well as resources such as exam rooms. Changes were made to streamline provider schedules to maximize appointment availability.

Based on our simulation modeling with streamlined schedules we determined that the pool scenario created the most efficiencies in productivity reducing average wait time per provider by 27 minutes.  We also determined that the 1:1 ratio increased wait time, as physician time and space were major constraints.  Given the current space and with no changes to the duration of physician appointments, the client was best served to streamline schedules using the pool scenario. 

Results

  • Reduced Wait Times
    Identified reduction in wait time by 27 minutes per provider using the pool scenario.
  • Efficiency 
    Changes were made to streamline provider schedules to maximize appointment availability.
  • Satisfaction
    Optimized schedule increased provider and patient satisfaction due to reduced  patient wait time and improved physician work life balance.

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