Real-Time Electronic Health Record Mortality Prediction During the COVID-19 Pandemic: A Prospective Cohort Study

Background: The SARS-CoV-2 virus has infected millions of people, overwhelming critical care resources in some regions. Many plans for rationing critical care resources during crises are based on the Sequential Organ Failure Assessment (SOFA) score. The COVID-19 pandemic created an emergent need to develop and validate a novel electronic health record (EHR)-computable tool to predict mortality. Research Questions: To rapidly develop, validate, and implement a novel real-time mortality score for the COVID-19 pandemic that improves upon SOFA. Study Design and Methods: We conducted a prospective cohort study of a regional health system with 12 hospitals in Colorado between March 2020 and July 2020. All patients >14 years old hospitalized during the study period without a do not resuscitate order were included. Patients were stratified by the diagnosis of COVID-19. From this cohort, we developed and validated a model using stacked generalization to predict mortality using data widely available in the EHR by combining five previously validated scores and additional novel variables reported to be associated with COVID-19-specific mortality. We compared the area under the receiver operator curve (AUROC) for the new model to the SOFA score and the Charlson Comorbidity Index. Results: We prospectively analyzed 27,296 encounters, of which 1,358 (5.0%) were positive for SARS-CoV-2, 4,494 (16.5%) included intensive care unit (ICU)-level care, 1,480 (5.4%) included invasive mechanical ventilation, and 717 (2.6%) ended in death. The Charlson Comorbidity Index and SOFA scores predicted overall mortality with an AUROC of 0.72 and 0.90, respectively. Our novel score predicted overall mortality with AUROC 0.94. In the subset of patients with COVID-19, we predicted mortality with AUROC 0.90, whereas SOFA had AUROC of 0.85. Interpretation: We developed and validated an accurate, in-hospital mortality prediction score in a live EHR for automatic and continuous calculation using a novel model, that improved upon SOFA. Study Question: Can we improve upon the SOFA score for real-time mortality prediction during the COVID-19 pandemic by leveraging electronic health record (EHR) data? Results: We rapidly developed and implemented a novel yet SOFA-anchored mortality model across 12 hospitals and conducted a prospective cohort study of 27,296 adult hospitalizations, 1,358 (5.0%) of which were positive for SARS-CoV-2. The Charlson Comorbidity Index and SOFA scores predicted all-cause mortality with AUROCs of 0.72 and 0.90, respectively. Our novel score predicted mortality with AUROC 0.94. Interpretation: A novel EHR-based mortality score can be rapidly implemented to better predict patient outcomes during an evolving pandemic

Characteristics, satisfiers, development needs, and barriers to success for early-career academic hospitalists.

BackgroundAcademic hospitalists engage in many non-clinical domains. Success in these domains requires support, mentorship, protected time, and networks. To address these non-clinical competencies, faculty development programs have been implemented. We aim to describe the demographics, job characteristics, satisfiers, and barriers to success of early-career academic hospitalists who attended the Academic Hospitalist Academic (AHA), a professional development conference from 2009 to 2019.MethodsSurvey responses from attendees were evaluated; statistical analyses and linear regression were performed for numerical responses and qualitative coding was performed for textual responses.ResultsA total of 965 hospitalists attended the AHA from 2009 to 2019. Of those, 812 (84%) completed the survey. The mean age of participants was 34 years and the mean time in hospitalist practice was 3.2 years. Most hospitalists were satisfied with their job, and teaching and clinical care were identified as the best parts of the job. The proportion of female hospitalists increased from 42.2% in 2009 to 60% in 2019 (p = 0.001). No other demographics or job characteristics significantly changed over the years. Lack of time and confidence in individual skills were the most common barriers identified in both bedside teaching and providing feedback, and providing constructive feedback was an additional challenge identified in giving feedback.ConclusionsThough early-career hospitalists reported high levels of job satisfaction driven by teaching and clinical care, barriers to success include time constraints and confidence. Awareness of these factors of satisfaction and barriers to success can help shape faculty development curricula for early-career hospitalists

Characteristics, satisfiers, development needs, and barriers to success for early-career academic hospitalists

Abstract Background Academic hospitalists engage in many non-clinical domains. Success in these domains requires support, mentorship, protected time, and networks. To address these non-clinical competencies, faculty development programs have been implemented. We aim to describe the demographics, job characteristics, satisfiers, and barriers to success of early-career academic hospitalists who attended the Academic Hospitalist Academic (AHA), a professional development conference from 2009 to 2019. Methods Survey responses from attendees were evaluated; statistical analyses and linear regression were performed for numerical responses and qualitative coding was performed for textual responses. Results A total of 965 hospitalists attended the AHA from 2009 to 2019. Of those, 812 (84%) completed the survey. The mean age of participants was 34 years and the mean time in hospitalist practice was 3.2 years. Most hospitalists were satisfied with their job, and teaching and clinical care were identified as the best parts of the job. The proportion of female hospitalists increased from 42.2% in 2009 to 60% in 2019 (p = 0.001). No other demographics or job characteristics significantly changed over the years. Lack of time and confidence in individual skills were the most common barriers identified in both bedside teaching and providing feedback, and providing constructive feedback was an additional challenge identified in giving feedback. Conclusions Though early-career hospitalists reported high levels of job satisfaction driven by teaching and clinical care, barriers to success include time constraints and confidence. Awareness of these factors of satisfaction and barriers to success can help shape faculty development curricula for early-career hospitalists.http://deepblue.lib.umich.edu/bitstream/2027.42/173628/1/12909_2022_Article_3356.pd

Changes in Payer Mix and Physician Reimbursement After the Affordable Care Act and Medicaid Expansion

Although uncompensated care for hospital-based care has fallen dramatically since the implementation of the Affordable Care Act and Medicaid expansion, the changes in hospital physician reimbursement are not known. We evaluated if payer mix and physician reimbursement by encounter changed between 2013 and 2014 in an academic hospitalist practice in a Medicaid expansion state. This was a retrospective cohort study of all general medicine inpatient admissions to an academic hospitalist group in 2013 and 2014. The proportion of encounters by payer and reimbursement/inpatient encounter were compared in 2013 versus 2014. A sensitivity analysis determined the relative contribution of different factors to the change in reimbursement/encounter. Among 37 540 and 40 397 general medicine inpatient encounters in 2013 and 2014, respectively, Medicaid encounters increased (17.3% to 30.0%, P < .001), uninsured encounters decreased (18.4% to 6.3%, P < 0.001), and private payer encounters also decreased (14.1% to 13.3%, P = .001). The median reimbursement/encounter increased 4.2% from $79.98/encounter in 2013 to$83.36/encounter in 2014 ( P < .001). In a sensitivity analysis, changes in length of stay, proportions in encounter type by payer, payer mix, and reimbursement for encounter type by payer accounted for −0.7%, 0.8%, 2.0%, and 2.3% of the reimbursement change, respectively. From 2013 to 2014, Medicaid encounters increased, and uninsured and private payer encounters decreased within our hospitalist practice. Reimbursement/encounter also increased, much of which could be attributed to a change in payer mix. Further analyses of physician reimbursement in Medicaid expansion and non-expansion states would further delineate reimbursement changes that are directly attributable to Medicaid expansion