Physician Wellness Measures and Clinical Performance on a Critically Ill Simulated Patient: Does a Lack of Well-Being Impact Patient Care?

Background/objectiveBurnout is common among resident physicians, which has the potential to translate into diagnostic and management errors. Our study investigates the relationship between sleepiness, depression, anxiety, burnout, and lack of professional fulfillment with clinical performance during a critically ill patient simulation. Methods/Approach: Emergency medicine residents were recruited to participate in a high-fidelity simulation case of a critically ill patient. A survey with validated wellbeing measures (National Institutes of Health Patient-Reported Outcomes Measurement Information System (NIH PROMIS), Linzer burnout measure, and professional fulfillment index) was administered prior to the simulation. Each encounter was video-recorded and analyzed by two blinded raters based on a binary critical-actions checklist. Time-to-intubation, management errors, and misdiagnosis rates were assessed.ResultsTwenty residents participated, with most subjects endorsing sleepiness (70%) and less than half reporting depression (40%) and anxiety (45%). Burnout was identified to be in 50% of participants by the Linzer measure and 85% by the professional fulfillment index. No significant difference was found between mean performance scores in sleepy, depressed, and anxious cohorts in comparison to groups without those symptoms. Similarly, burnout and professional fulfillment did not yield any significant difference, nor did comparisons with time to intubation, management errors, and frequency of misdiagnosis.ConclusionResident burnout, depression, anxiety, sleepiness, and lack of professional fulfillment did not appear to have a measurable impact on clinical performance in managing a critically ill patient. There is no evidence from this study that the lack of resident physician well-being adversely impacts patient care by increasing errors in management or misdiagnoses during this high-fidelity simulation

Impact of primary care provider density on detection and diagnosis of cutaneous melanoma.

INTRODUCTION:Early diagnosis of cutaneous melanoma is critical in preventing melanoma-associated deaths, but the role of primary care providers (PCPs) in diagnosing melanoma is underexplored. We aimed to explore the association of PCP density with melanoma incidence and mortality. METHODS:All cases of cutaneous melanoma diagnosed in the United States from 2008-2012 and reported in the Surveillance, Epidemiology, and End Results (SEER) database were analyzed in 2016. County-level primary care physician density was obtained from the Area Health Resources File (AHRF). We conducted multivariate linear regression using 1) average annual melanoma incidence or 2) average annual melanoma mortality by county as primary outcomes, adjusting for demographic confounders and dermatologist density. Cox proportional hazard regression was conducted using individual outcome data from SEER with the same covariates. RESULTS:Across 611 counties, 167,305 cases of melanoma were analyzed. Per 100,000 people, an additional 10 PCPs per county was associated with 1.62 additional cases of melanoma per year (95% CI 1.06-2.18, p<0.001). This increased incidence occurred disproportionally in early-stage melanoma (Stage 0: 0.69 cases (0.38-1.00), p<0.001; Stage I: 0.63 cases (0.37-0.89), p<0.001; Stage II: 0.11 cases (0.03-0.19), p = 0.005). There was no statistically significant association between PCP density and incidence of stage III or IV melanoma, or with melanoma-specific mortality. Survival analysis demonstrated elimination of 5-year post-diagnosis mortality risk in medically underserved counties after adjusting for stage. CONCLUSIONS:Higher densities of PCPs may be linked to increased diagnosis of early-stage melanoma without corresponding decreases in late-stage diagnoses or melanoma-associated mortality

Streamlining Care in Crisis: Rapid Creation and Implementation of a Digital Support Tool for COVID-19

The unprecedented COVID-19 pandemic has resulted in rapidly evolving best practices for transmission reduction, diagnosis, and treatment. A regular influx of new information has upended traditionally static hospital protocols, adding additional stress and potential for error to an already overextended system. To help equip frontline emergency clinicians with up-to-date protocols throughout the evolving COVID-19 crisis, our team set out to create a dynamic digital tool that centralized and standardized resources from a broad range of platforms across our hospital. Using a design thinking approach, we rapidly built, tested, and deployed a solution using simple, out-of-the-box web technology that enables clinicians to access the specific information they seek within moments. This platform has been rapidly adopted throughout the emergency department, with up to 70% of clinicians using the digital tool on any given shift and 78.6% of users reporting that they “agree” or “strongly agree” that the platform has affected their management of COVID-19 patients. The tool has also proven easily adaptable, with multiple protocols being updated nearly 20 times over two months without issue. This paper describes our development process, challenges, and results to enable other institutions to replicate this process to ensure consistent, high-quality care for patients as the COVID-19 pandemic continues its unpredictable course

Streamlining Care in Crisis: Rapid Creation and Implementation of a Digital Support Tool for COVID-19

The unprecedented COVID-19 pandemic has resulted in rapidly evolving best practices for transmission reduction, diagnosis, and treatment. A regular influx of new information has upended traditionally static hospital protocols, adding additional stress and potential for error to an already overextended system. To help equip frontline emergency clinicians with up-to-date protocols throughout the evolving COVID-19 crisis, our team set out to create a dynamic digital tool that centralized and standardized resources from a broad range of platforms across our hospital. Using a design thinking approach, we rapidly built, tested, and deployed a solution using simple, out-of-the-box web technology that enables clinicians to access the specific information they seek within moments. This platform has been rapidly adopted throughout the emergency department, with up to 70% of clinicians using the digital tool on any given shift and 78.6% of users reporting that they “agree” or “strongly agree” that the platform has affected their management of COVID-19 patients. The tool has also proven easily adaptable, with multiple protocols being updated nearly 20 times over two months without issue. This paper describes our development process, challenges, and results to enable other institutions to replicate this process to ensure consistent, high-quality care for patients as the COVID-19 pandemic continues its unpredictable course

County-level descriptive statistics, 2008–2012.

<p>County-level descriptive statistics, 2008–2012.</p

Cox proportional hazard survival analysis, by HPSA status.

<p>Cox proportional hazard survival analysis, by HPSA status.</p

Incidence as a function of PCP density, stratified by stage at diagnosis.

<p>Melanoma incidence per 100,000 person-years shown as a function of PCPs per 100,000 people across all US counties in SEER from 2008–2012, split by AJCC stage at diagnosis. Points are scaled in size by total county population, and the 95% CI for each line of fit is shown in gray. Stages 0, I, and II were statistically significant (*), and the last panel compares coefficients for all stages.</p

Multivariate regressions of incidence and mortality with PCP density and co-variates.

<p>Multivariate regressions of incidence and mortality with PCP density and co-variates.</p

Discharge Navigator: Implementation and Cross-Sectional Evaluation of a Digital Decision Tool for Social Resources upon Emergency Department Discharge

Introduction: Many patients have unaddressed social needs that significantly impact their health, yet navigating the landscape of available resources and eligibility requirements is complex for both patients and clinicians. &nbsp;Methods: Using an iterative design-thinking approach, our multidisciplinary team built, tested, and deployed a digital decision tool called “Discharge Navigator” (edrive.ucsf.edu/dcnav) that helps emergency clinicians identify targeted social resources for patients upon discharge from the acute care setting. The tool uses each patient’s clinical and demographic information to tailor recommended community resources, providing the clinician with action items, pandemic restrictions, and patient handouts for relevant resources in five languages. We implemented two modules at our urban, academic, Level I trauma center. &nbsp;Results: Over the 10-week period following product launch, between 4-81 on-shift emergency clinicians used our tool each week. Anonymously surveyed clinicians (n = 53) reported a significant increase in awareness of homelessness resources (33% pre to 70% post, P&lt;0.0001) and substance use resources (17% to 65%, P&lt;0.0001); confidence in accessing resources (22% to 74%, P&lt;0.0001); knowledge of eligibility criteria (13% to 75%, P&lt;0.0001); and ability to refer patients always or most of the time (11% to 43%, P&lt;0.0001). The average likelihood to recommend the tool was 7.8 of 10. &nbsp;Conclusion: Our design process and low-cost tool may be replicated at other institutions to improve knowledge and referrals to local community resources.&nbsp