Physician Coaching by Professionally Trained Peers for Burnout and Well-Being: A Randomized Clinical Trial.

Importance: Physician burnout is problematic despite existing interventions. More evidence-based approaches are needed. Objective: To explore the effect of individualized coaching by professionally trained peers on burnout and well-being in physicians. Design, Setting, and Participants: This randomized clinical trial involved Mass General Physician Organization physicians who volunteered for coaching from August 5 through December 1, 2021. The data analysis was performed from February through October 2022. Interventions: Participants were randomized to 6 coaching sessions facilitated by a peer coach over 3 months or a control condition using standard institutional resources for burnout and wellness. Main Outcomes and Measures: The primary outcome was burnout as measured by the Stanford Professional Fulfillment Index. Secondary outcomes included professional fulfillment, effect of work on personal relationships, quality of life, work engagement, and self-valuation. Analysis was performed on a modified intention-to-treat basis. Results: Of 138 physicians enrolled, 67 were randomly allocated to the coaching intervention and 71 to the control group. Most participants were aged 31 to 60 years (128 [93.0%]), women (109 [79.0%]), married (108 [78.3%]), and in their early to mid career (mean [SD], 12.0 [9.7] years in practice); 39 (28.3%) were Asian, 3 (<0.1%) were Black, 9 (<0.1%) were Hispanic, 93 were (67.4%) White, and 6 (<0.1%) were of other race or ethnicity. In the intervention group, 52 participants underwent coaching and were included in the analysis. Statistically significant improvements in burnout, interpersonal disengagement, professional fulfillment, and work engagement were observed after 3 months of coaching compared with no intervention. Mean scores for interpersonal disengagement decreased by 30.1% in the intervention group and increased by 4.1% in the control group (absolute difference, -0.94 poimys [95% CI, -1.48 to -0.41 points; P = .001), while mean scores for overall burnout decreased by 21.6% in the intervention group and increased by 2.5% in the control group (absolute difference, -0.79 points; 95% CI, -1.27 to -0.32 points; P = .001). Professional fulfillment increased by 10.7% in the intervention group compared with no change in the control group (absolute difference, 0.59 points; 95% CI, 0.01-1.16 points; P = .046). Work engagement increased by 6.3% in the intervention group and decreased by 2.2% in the control group (absolute difference, 0.33 points; 95% CI, 0.02-0.65 points; P = .04). Self-valuation increased in both groups, but not significantly. Conclusions and Relevance: The findings of this hospital-sponsored program show that individualized coaching by professionally trained peers is an effective strategy for reducing physician burnout and interpersonal disengagement while improving their professional fulfillment and work engagement. Trial Registration: ClinicalTrials.gov Identifier: NCT05036993.

Concurrent immune checkpoint inhibition and selective immunosuppressive therapy in patients with immune-related enterocolitis.

PURPOSE: Immune checkpoint inhibitor (ICI) therapy is often suspended because of immune-related enterocolitis (irEC). We examined the effect of resumption of ICIs with or without concurrent selective immunosuppressive therapy (SIT) on rates of symptom recurrence and survival outcomes. METHODS: This retrospective, multicenter study examined patients who were treated with ICI and developed irEC requiring SIT (infliximab or vedolizumab) for initial symptom control or to facilitate steroid tapering between May 2015 and June 2020. After symptom resolution, patients were restarted either on ICI alone or on concurrent ICI and SIT at the discretion of the treating physicians. The associations between irEC recurrence and treatment group were assessed via univariate analyses and multivariate logistic regression. Cox proportional hazards model was used for survival analysis. RESULTS: Of the 138 included patients who required SIT for initial irEC symptom control, 61 (44.2%) patients resumed ICI without concurrent SIT (control group) and 77 (55.8%) patients resumed ICI therapy with concurrent SIT: 33 with infliximab and 44 with vedolizumab. After symptom resolution, patients in the control group were more commonly restarted on a different ICI regimen (65.6%) compared with those receiving SIT (31.2%) (p<0.001). The total number of ICI doses administered after irEC resolution and ICI resumption was similar in both groups (four to five doses). Recurrence of severe colitis or diarrhea after ICI resumption was seen in 34.4% of controls compared with 20.8% of patients receiving concurrent SIT. Concurrent SIT was associated with reduced risk of severe irEC recurrence after ICI resumption in a multivariate logistic regression model (OR 0.34; 95% CI 0.13 to 0.92; p=0.034). There was no difference in survival outcomes between patients in the control group and patients concurrently treated with SIT. CONCLUSION: After resolution of irEC symptoms, reinitiation of ICI with concurrent SIT is safe, reduces severe irEC recurrence, and has no negative impact on survival outcomes.

Late Surges in COVID-19 Cases and Varying Transmission Potential Partially Due to Public Health Policy Changes in 5 Western States, March 10, 2020, to January 10, 2021.

OBJECTIVE: This study investigates the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission potential in North Dakota, South Dakota, Montana, Wyoming, and Idaho from March 2020 through January 2021. METHODS: Time-varying reproduction numbers, R t , of a 7-d-sliding-window and of non-overlapping-windows between policy changes were estimated using the instantaneous reproduction number method. Linear regression was performed to evaluate if per-capita cumulative case-count varied across counties with different population size or density. RESULTS: The median 7-d-sliding-window R t estimates across the studied region varied between 1 and 1.25 during September through November 2020. Between November 13 and 18, R t was reduced by 14.71% (95% credible interval, CrI, [14.41%, 14.99%]) in North Dakota following a mask mandate; Idaho saw a 1.93% (95% CrI [1.87%, 1.99%]) reduction and Montana saw a 9.63% (95% CrI [9.26%, 9.98%]) reduction following the tightening of restrictions. High-population and high-density counties had higher per-capita cumulative case-count in North Dakota on June 30, August 31, October 31, and December 31, 2020. In Idaho, North Dakota, South Dakota, and Wyoming, there were positive correlations between population size and per-capita weekly incident case-count, adjusted for calendar time and social vulnerability index variables. CONCLUSIONS: R t decreased after mask mandate during the region's case-count spike suggested reduction in SARS-CoV-2 transmission.

SARS-CoV-2 Transmission Potential and Policy Changes in South Carolina, February 2020 - January 2021.

INTRODUCTION: We aimed to examine how public health policies influenced the dynamics of coronavirus disease 2019 (COVID-19) time-varying reproductive number (R t ) in South Carolina from February 26, 2020, to January 1, 2021. METHODS: COVID-19 case series (March 6, 2020, to January 10, 2021) were shifted by 9 d to approximate the infection date. We analyzed the effects of state and county policies on R t using EpiEstim. We performed linear regression to evaluate if per-capita cumulative case count varies across counties with different population size. RESULTS: R t shifted from 2-3 in March to <1 during April and May. R t rose over the summer and stayed between 1.4 and 0.7. The introduction of statewide mask mandates was associated with a decline in R t (-15.3%; 95% CrI, -13.6%, -16.8%), and school re-opening, an increase by 12.3% (95% CrI, 10.1%, 14.4%). Less densely populated counties had higher attack rates (P < 0.0001). CONCLUSIONS: The R t dynamics over time indicated that public health interventions substantially slowed COVID-19 transmission in South Carolina, while their relaxation may have promoted further transmission. Policies encouraging people to stay home, such as closing nonessential businesses, were associated with R t reduction, while policies that encouraged more movement, such as re-opening schools, were associated with R t increase.

SARS-CoV-2 Transmission in Alberta, British Columbia, and Ontario, Canada, December 25, 2019, to December 1, 2020.

OBJECTIVE: This study aimed to investigate coronavirus disease (COVID-19) epidemiology in Alberta, British Columbia, and Ontario, Canada. METHODS: Using data through December 1, 2020, we estimated time-varying reproduction number, Rt, using EpiEstim package in R, and calculated incidence rate ratios (IRR) across the 3 provinces. RESULTS: In Ontario, 76% (92 745/121 745) of cases were in Toronto, Peel, York, Ottawa, and Durham; in Alberta, 82% (49 878/61 169) in Calgary and Edmonton; in British Columbia, 90% (31 142/34 699) in Fraser and Vancouver Coastal. Across 3 provinces, Rt dropped to ≤ 1 after April. In Ontario, Rt would remain < 1 in April if congregate-setting-associated cases were excluded. Over summer, Rt maintained < 1 in Ontario, ~1 in British Columbia, and ~1 in Alberta, except early July when Rt was > 1. In all 3 provinces, Rt was > 1, reflecting surges in case count from September through November. Compared with British Columbia (684.2 cases per 100 000), Alberta (IRR = 2.0; 1399.3 cases per 100 000) and Ontario (IRR = 1.2; 835.8 cases per 100 000) had a higher cumulative case count per 100 000 population. CONCLUSIONS: Alberta and Ontario had a higher incidence rate than British Columbia, but Rt trajectories were similar across all 3 provinces.

Assessing Early Heterogeneity in Doubling Times of the COVID-19 Epidemic across Prefectures in Mainland China, January-February, 2020.

To describe the geographical heterogeneity of COVID-19 across prefectures in mainland China, we estimated doubling times from daily time series of the cumulative case count between 24 January and 24 February 2020. We analyzed the prefecture-level COVID-19 case burden using linear regression models and used the local Moran's I to test for spatial autocorrelation and clustering. Four hundred prefectures (~98% population) had at least one COVID-19 case and 39 prefectures had zero cases by 24 February 2020. Excluding Wuhan and those prefectures where there was only one case or none, 76 (17.3% of 439) prefectures had an arithmetic mean of the epidemic doubling time <2 d. Low-population prefectures had a higher per capita cumulative incidence than high-population prefectures during the study period. An increase in population size was associated with a very small reduction in the mean doubling time (-0.012, 95% CI, -0.017, -0.006) where the cumulative case count doubled ≥3 times. Spatial analysis revealed high case count clusters in Hubei and Heilongjiang and fast epidemic growth in several metropolitan areas by mid-February 2020. Prefectures in Hubei and neighboring provinces and several metropolitan areas in coastal and northeastern China experienced rapid growth with cumulative case count doubling multiple times with a small mean doubling time.

Doubling Time of the COVID-19 Epidemic by Chinese Province.

COVID-19 epidemic doubling time by Chinese province was increasing from January 20 through February 9, 2020. The harmonic mean of the arithmetic mean doubling time estimates ranged from 1.4 (Hunan, 95% CI, 1.2-2.0) to 3.1 (Xinjiang, 95% CI, 2.1-4.8), with an estimate of 2.5 days (95% CI, 2.4-2.6) for Hubei.

Doubling Time of the COVID-19 Epidemic by Province, China.

In China, the doubling time of the coronavirus disease epidemic by province increased during January 20-February 9, 2020. Doubling time estimates ranged from 1.4 (95% CI 1.2-2.0) days for Hunan Province to 3.1 (95% CI 2.1-4.8) days for Xinjiang Province. The estimate for Hubei Province was 2.5 (95% CI 2.4-2.6) days.