Improving clinical access and continuity through physician panel redesign

Abstract

Background: Population growth, an aging population and the increasing prevalence of chronic disease are projected to increase demand for primary care services in the United States.

Objective: Using systems engineering methods, to re-design physician patient panels targeting optimal access and continuity of care.

Design: We use computer simulation methods to design physician panels and model a practice's appointment system and capacity to provide clinical service. Baseline data were derived from a primary care group practice of 39 physicians with over 20,000 patients at the Mayo Clinic in Rochester, MN, for the years 2004-2006. Panel design specifically took into account panel size and case mix (based on age and gender).

Measures: The primary outcome measures were patient waiting time and patient/clinician continuity. Continuity is defined as the inverse of the proportion of times patients are redirected to see a provider other than their primary care physician (PCP).

Results: The optimized panel design decreases waiting time by 44% and increases continuity by 40% over baseline. The new panel design provides shorter waiting time and higher continuity over a wide range of practice panel sizes.

Conclusions: Redesigning primary care physician panels can improve access to and continuity of care for patients.

Figure 1

Distribution of weekly visits. Histograms of the percentage (or fraction) of total patients requesting appointments in a week for two different patient age and gender categories, based on historical data from 2004–2006 (156 weeks). There are 708 males ages 48–53 years (48–53 M) and 986 females ages 73–78 years (73–78 F) empanelled in the practice. The mean of the two distributions differs, and so do their variances (see standard deviation); 8.4% of all 73–78 F patients request appointments on average in a week as opposed to 4.8% of all 48–53 M patients. The standard deviation of 73–78 F (3.07%) is more than double that of 48–53 M (1.1%).

Figure 2

Panel redesign example—part I. Conceptual example showing how panel allocations can result in mismatches between requested appointments and available capacity. Panel allocations are indicated with arrows; the width of the arrows indicates the appointment demand. Physician C is overburdened because of her case mix with the result that her requests are well over her available capacity. Physician A, on the other hand, has spare capacity.

Figure 3

Panel redesign example—part II. Conceptual example showing how panel allocations from Figure 2 are redesigned so that requests for each physician are in balance with available capacity. Some of Physician C’s patients are redistributed to the other two physicians (especially Physician A), with the result that her requests match with available capacity.