Clinician Care Team Composition and Health Care Utilization

Comparison of Ambulatory Quality Measures Between Shared Practice Panels and Independent Practice Panels

Objective

To assess for differences in patient care outcomes in the primary care setting for patients assigned to an independent practice panel (IPP) or a shared practice panel (SPP).

Patients and Methods

We retrospectively reviewed the electronic health records of patients of 2 Mayo Clinic family medicine primary care clinics from January 1, 2019 to December 31, 2019. Patients were assigned to either an IPP (physician or advanced practice provider [APP]) or an SPP (physician and ≥1 APP). We assessed 6 measures of quality care and compared them between IPP and SPP groups: diabetes optimal care, hypertension control, depression remission at 6 months, breast cancer screening, cervical cancer screening, and colon cancer screening.

Results

The study included 114,438 patients assigned to 140 family medicine panels during the study period: 87 IPPs and 53 SPPs. The IPP clinicians showed improved quality metrics compared with the SPP clinicians for the percentage of assigned patients achieving depression remission (16.6% vs 11.1%; P<.01). The SPP clinicians showed improved quality metrics compared with that of the IPP clinicians for the percentage of patients with cervical cancer screening (79.1% vs 74.2%; P<.01). The mean percentage of the panels achieving optimal diabetes control, hypertension control, colon cancer screening, and breast cancer screening were not significantly different between IPP and SPP panels.

Conclusion

This study shows a considerable improvement in depression remission among IPP panels and in cervical cancer screening rates among SPP panels. This information may help to inform primary care team configuration.

The effect of primary care clinician type and care team characteristics on health care costs

OBJECTIVE

To evaluate health care costs as a function of assigned primary care clinician type and care team characteristics.

METHODS

Administrative data were collected for 68 family medicine clinicians (40 physicians and 28 nurse practitioners [NPs]/physician assistant [PAs]), on 11 care teams (variable MD, NP and PA on teams), caring for 77,141 patients. We performed a generalized linear mixed multivariable regression model of standardized per member per month (PMPM) median cost as the outcome, with four practice sites included as random effects.

RESULTS

In bivariate analysis, cost was higher in physicians than NP/PAs, in more complex patients, and associated with emergency department (ED) visit rate. On multivariate analysis, patient complexity, ED visit rate and higher patient experience ratings were independently associated with greater PMPM cost. More time in practice was associated with lower PMPM cost. In the adjusted multivariate model, physicians had 8.3% lower median PMPM costs than NP/PAs (p = 0.046).

CONCLUSIONS

The primary drivers of greater PMPM cost were patient complexity, ED visits and patient satisfaction.

Development and Early Experience of a Primary Care Learning Collaborative in a Large Health Care System

Introduction:

Primary care clinicians are presented with hundreds of new clinical recommendations and guidelines. To consider practice change clinicians must identify relevant information and develop a contextual framework. Too much attention to information irrelevant to one’s practice results in wasted resources. Too little results in care gaps. A small group of primary care clinicians in a large health system sought to address the problem of vetting new information and providing peer reviewed context. This was done by engaging colleagues across the system though a primary care learning collaborative.

Methods:

The collaborative was a grass roots initiative between community and academic-based clinicians. They invited all the system’s primary care clinicians to participate. They selected new recommendations or guidelines and used surveys as the principal communication instrument. Surveys shared practice experience and also invited members to give narrative feedback regarding their acceptance of variation in care relate to the topic. A description of the collaborative along with its development, processes, and evolution are discussed. Process changes to address needs during the COVID-19 pandemic including expanded information sharing was necessary.

Results:

Collaborative membership reached across 5 states and included family medicine, internal medicine, and pediatrics. Members found involvement with the collaborative useful. Less variation in care was thought important for public health crises: the COVID pandemic and opioid epidemic. Greater practice variation was thought acceptable for adherence to multispecialty guidelines, such as diabetes, lipid management, and adult ADHD care. Process changes during the pandemic resulted in more communications between members to avoid practice gaps.

Conclusion:

An internet-based learning collaborative in a health system had good engagement from its members. Using novel methods, it was able to provide members with feedback related to the importance of new practice recommendations as perceived by their peers. Greater standardization was thought necessary when adopting measures to address public health crisis, and less necessary when addressing multispecialty guidelines. By employing a learning collaborative, this group was able to keep members interested and engaged. During the first year of the COVID pandemic the collaborative also served as a vehicle to share timely information.