Objective: To test the hypothesis that a greater proportion of physician time on primary care teams are associated with decreased emergency department (ED) visits, hospital admissions, and readmissions, and to determine clinician and care team characteristics associated with greater utilization. Patients and Methods: We retrospectively analyzed administrative data collected from January 1 to December 31, 2017, of 420 family medicine clinicians (253 physicians, 167 nurse practitioners/physician assistants [NP/PAs]) with patient panels in an integrated health system in 59 Midwestern communities serving rural and urban areas in Minnesota, Wisconsin, and Iowa. These clinicians cared for 419,581 patients through 110 care teams, with varying numbers of physicians and NP/PAs. Primary outcome measures were rates of ED visits, hospitalizations, and readmissions. Results: The proportion of physician full-time equivalents on the team was unrelated to rates of ED visits (rate ratio [RR] ¼ 0.826; 95% confidence interval [CI], 0.624 to 1.063), hospitalizations (RR ¼ 0.894; 95% CI, 0.746 to 1.072), or readmissions (RR ¼ e0.026; 95% CI, 0.364 to 0.312). In separate multivariable models adjusted for clinician and practice-level characteristics, the rate of ED visits was positively associated with mean panel hierarchical condition category (HCC) score, urban vs rural setting, NP/PA vs physician, and lower years in practice. The rate of inpatient admissions was associated with HCC score, and 30-day hospital readmissions were positively associated with HCC score, lower years in practice, and male clinicians. Conclusion: Care team physician and NP/PA composition was not independently related to utilization. More complex panels had higher rates of ED visits, hospitalization, and readmissions. Statistically significant differences between physician and NP/PA panels were only evident for ED visits.
The COVID-19 pandemic has presented new challenges in how Primary Care clinicians care for community patients. Our organization quickly allocated 1 of our community clinic sites into a dedicated COVID Clinic caring for the COVID positive or any patient with COVID like symptoms to minimize contact with the well patients. A prerequisite for all patients to be seen in the COVID Care Clinic was a virtual visit staffed with Advanced Practice Providers that would further determine if the patient needed to seek emergency medical care or be seen in the COVID Clinic. From March 23, 2020 through May 15, 2020, 852 patients with COVID symptoms were seen in this clinic rather than the emergency department. This article describes a collaborative effort to care for a community during the COVID-19 pandemic. This unique setting allowed us to focus an appropriate level of care to a high risk population in a safe and effective manner in the ongoing effort to flatten the epidemiological curve.
Background and Objectives: Clinician workload is a key contributor to burnout and well-being as well as overtime and staff shortages, particularly in the primary care setting. Appointment volume is primarily driven by the size of patient panels assigned to clinicians. Thus, finding the most appropriate panel size for each clinician is essential to optimization of patient care. Methods: One year of appointment and panel data from the Department of Family Medicine were used to model the optimal panel size. The data consisted of 82 881 patients and 105 clinicians. This optimization-based modeling approach determines the panel size that maximizes clinician capacity while distributing heterogeneous appointment types among clinician groups with respect to their panel management time (PMT), which is the percent of clinic work. Results: The differences between consecutive PMT physician groups in total annual appointment volumes per clinician for the current practice range from 176 to 348. The optimization-based approach for the same PMT physician group results in having a range from 211 to 232 appointments, a relative reduction in variability of 88%. Similar workload balance gains are also observed for advanced practice clinicians and resident groups. These results show that the proposed approach significantly improves both patient and appointment workloads distributed among clinician groups. Conclusion: Appropriate panel size has valuable implications for clinician well-being, patients' timely access to care, clinic and health system productivity, and the quality of care delivered. Results demonstrate substantial improvements with respect to balancing appointment workload across clinician types through strategic use of an optimization-based approach.
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