Balancing Clinician Workload Through Strategic Patient Panel Designs.

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.

A Digitally Capable Mobile Health Clinic to Improve Rural Health Care in America: A Pilot Quality Improvement Study.

Objective: To address the problem of limited health care access for patients in rural southern Minnesota, a digitally capable mobile health clinic (MHC) quality improvement initiative was launched in a rural community-based health system. Methods: This project was designed and implemented according to our institutional strategic plan, guiding principles for virtual community care, and existing approved standards of care. A quality improvement development and pilot implementation framework was rapidly developed using Agile methodology. Results: The resulting technology and equipment selection, overall clinic design, vehicle vendor selection, clinical schedule and workflows, staffing model, equipment and technology selection, and testing were achieved in 12 months. The pilot site communities were chosen on the basis of size, interest, and lack of existing access. Four underserved rural communities now have access to telehealth consultations, laboratory testing, and in-person primary care examinations. By April 30, 2022, the MHC had provided 1498 patient appointments while maintaining our standards of care. Newly established broadband internet access for these communities and their residents was a valuable secondary outcome. Conclusion: By designing and implementing an MHC quality improvement intervention that provides both in-person and advanced telehealth options for patients in rural communities, our institution rapidly provided a potential solution for the rural health care crisis. The MHC not only replaces traditional brick-and-mortar facilities but also expands service offerings and access to technology for rural communities and the people who live and work in them.

Rapid Independent Health Literacy Assessment: A Pilot Study Among Native English-speaking and Low English Proficiency Patients.

OBJECTIVES: Health literacy is an individual's capacity to obtain, process, and understand basic health information needed to make appropriate health decisions. Failure to understand and correctly execute a plan of care often leads to poor health outcomes. Determining patient health literacy allows health care providers to tailor their plan of care instructions, increasing the probability of understanding, and adherence. Several validated health literacy tests have been developed to assess the health literacy of individuals and ethnic groups. However, because a proctor is required to administer these tests, their usefulness in clinical settings is limited. The issue of health literacy is especially relevant within minority groups. This research focused on producing a translatable assessment that can be administered quickly without a proctor. METHODS: We developed a 15-question instrument (the RIHLA) in English using the Delphi method with a panel of bilingual experts and translated it into Spanish. Internal reliability was assessed using Cronbach's alpha for 3 groups: Native English-speaking College students (NESC), Native English-speaking patients (NES), and Limited English Proficient Spanish-speaking patients (LEP). External validity was assessed using Pearson's correlation coefficient to compare our instrument to a previously validated, proctored instrument measuring health literacy (the SAHL-E). RESULTS: Four hundred fifteen subjects completed the RIHLA. Of these, 192 (46.3%) were NESC, 208 (50.1%) were NES, and 15 (3.6%) were LEP. The mean number of correct answers was 11.2, 11.6, and 8.3 respectively with the LEP group scoring lower (P < .01). Cronbach's alpha was >.70 for each group. Moderate correlation between the RIHLA and the previously validated instrument was present (P < .01) with Pearson's r = .47 (95% CI: 0.18-0.69). CONCLUSION: The RIHLA is a non-proctored assessment tool that may provide a measure of patients' health literacy in multiple languages. Further studies with larger sample sizes are necessary to confirm the reliability, validity, and generalizability to a wider population.

Relationship of Clinician Care Team Composition and Diabetes Quality Outcomes.

The objective was to determine if a greater proportion of physician full-time equivalent (FTE%) relative to nurse practitioners/physician assistants (NPs/PAs) on care teams was associated with improved individual clinician diabetes quality outcomes. The authors conducted a retrospective cross-sectional study of 420 family medicine clinicians in 110 care teams in a Midwest health system, using administrative data from January 1, 2017 to December 31, 2017. Poisson regression was used to examine the relationship between physician FTE% and the number of patients meeting 5 criteria included in a composite metric for diabetes management (D5). Covariates included panel size, clinician type, sex, years in practice, region, patient satisfaction, care team size, rural location, and panel complexity. Of the 420 clinicians, 167 (40%) were NP/PA staff and 253 (60%) were physicians. D5 criteria were achieved in 37.9% of NP/PA panels compared with 44.5% of physician panels (P < .001). In adjusted analysis, rate of patients achieving D5 was unrelated to physician FTE% on the care team (P = .78). Physicians had a 1.082 (95% confidence interval 1.007-1.164) times greater rate of patients with diabetes achieving D5 than NPs/PAs. Clinicians at rural locations had a .904 (.852-.959) times lower rate of achieving D5 than those at urban locations. Physicians had a greater rate of patients achieving D5 compared with NPs/PAs, but physician FTE% on the care team was unrelated to D5 outcomes. This suggests that clinician team composition matters less than team roles and the dynamics of collaborative care between members.

Association of Primary Care Team Composition and Clinician Burnout in a Primary Care Practice Network.

OBJECTIVE: To determine the relationship of the emotional exhaustion domain of burnout with care team composition in a Midwestern primary care practice network. PARTICIPANTS AND METHODS: We studied 420 family medicine clinicians (253 physicians and 167 nurse practitioners/physician assistants [NP/PAs]) within a large integrated health system throughout 59 Midwestern communities. The observational cross-sectional study utilized a single-question clinician self-assessment of the emotional exhaustion domain of burnout on a scale of 0 (never) to 6 (daily) conducted between March 1 and April 2, 2018, and administrative data collected between January 1, 2017, and December 31, 2017. We used a multivariable linear mixed model for data analysis, adjusted for clinical- and team-level factors, including clinician sex, panel size and complexity, clinician type (physician or NP/PA), clinician full-time equivalent (FTE), total care team panel size, and number of clinicians on the care team. RESULTS: Among 217 survey respondents (51.7%), the median frequency of the emotional exhaustion domain of burnout was once per week. Adjusted analyses revealed that a greater proportion of physician FTE on the care team was associated with a lower emotional exhaustion domain of burnout among individual clinicians (P=.05). Female clinicians had a higher emotional exhaustion domain of burnout than male clinicians (P=.05). None of the other variables in the model were associated with emotional exhaustion. CONCLUSION: Primary care teams containing both physicians and NP/PAs had lower levels of emotional exhaustion with increasing proportion of physician FTE. More work is needed to explore what other variables may be associated with burnout in primary care team-based practices.

Family Medicine Patients Have Shorter Length of Stay When Cared for on a Family Medicine Inpatient Service.

INTRODUCTION: Hospitalists have been shown to have shorter lengths of stays than physicians with concurrent outpatient practices. However, hospitalists at academic medical centers may be less aware of local resources that can support the hospital to home transition for local primary care patients. We hypothesized that local family medicine patients admitted to a family medicine inpatient service have shorter length of stay than those admitted to general hospitalist services which also care for tertiary patients at an academic medical center. METHODS: A retrospective cohort study was conducted at an academic medical center with a department of family medicine providing primary care to over 80 000 local patients. A total of 3100 consecutive family medicine patients admitted to either the family medicine inpatient service or a general medicine inpatient service over 3 years were studied. The primary outcome was length of stay, which was adjusted using multivariate linear regression for demographics, prior utilization, diagnosis, and disease severity. RESULTS: Adjusted length of stay was 33% longer (95% CI 24%-44%) for local family medicine patients admitted to general medicine inpatient services as compared with the family medicine inpatient service. Readmission rates within 30 days were not different (19% vs 16%, P = .14). CONCLUSIONS: Local primary care patients were safely discharged from the hospital sooner on the family medicine inpatient service than on general medicine inpatient services. This is likely because the family physicians staffing their inpatient service are more familiar with outpatient resources that can be effectively marshaled to help local patients with the transition from hospital to home.

Family Medicine Panel Size with Care Teams: Impact on Quality.

PURPOSE: The demand for comprehensive primary health care continues to expand. The development of team-based practice allows for improved capacity within a collective, collaborative environment. Our hypothesis was to determine the relationship between panel size and access, quality, patient satisfaction, and cost in a large family medicine group practice using a team-based care model. METHODS: Data were retrospectively collected from 36 family physicians and included total panel size of patients, percentage of time spent on patient care, cost of care, access metrics, diabetic quality metrics, patient satisfaction surveys, and patient care complexity scores. We used linear regression analysis to assess the relationship between adjusted physician panel size, panel complexity, and outcomes. RESULTS: The third available appointments (P < .01) and diabetic quality (P = .03) were negatively affected by increased panel size. Patient satisfaction, cost, and percentage fill rate were not affected by panel size. A physician-adjusted panel size larger than the current mean (2959 patients) was associated with a greater likelihood of poor-quality rankings (≤25th percentile) compared with those with a less than average panel size (odds ratio [OR], 7.61; 95% confidence interval [CI], 1.13-51.46). Increased panel size was associated with a longer time to the third available appointment (OR, 10.9; 95% CI, 1.36-87.26) compared with physicians with panel sizes smaller than the mean. CONCLUSIONS: We demonstrated a negative impact of larger panel size on diabetic quality results and available appointment access. Evaluation of a family medicine practice parameters while controlling for panel size and patient complexity may help determine the optimal panel size for a practice.