The physician CEO advantage and hospital performance during the COVID-19 pandemic: capacity utilization and patient satisfaction.

PURPOSE: Prior studies have shown that physician-led hospitals have several advantages over non-physician-led hospitals. This study seeks to test whether these advantages also extend to periods of extreme disruptions such as the COVID-19 pandemic, which affect bed availability and hospital utilization. DESIGN/METHODOLOGY/APPROACH: The authors utilize a bounded Tobit estimation to identify differences in patient satisfaction rates and in-hospital utilization rates of top-rated hospitals in the United States. FINDINGS: Among top-rated US hospitals, those that are physician-led achieve higher patient satisfaction ratings and are more likely to have higher utilization rates. RESEARCH LIMITATIONS/IMPLICATIONS: While the COVID-19 pandemic generated greater demand for inpatient beds, physician-led hospitals improved their hospitals' capacity utilization as compared with those led by non-physician leaders. A longitudinal study to show the change over the years and whether physician Chief Executive Officers (CEOs) are more likely to improve their hospitals' ratings than non-physician CEOs is highly recommended. PRACTICAL IMPLICATIONS: Recruiting and retaining physicians to lead hospitals, especially during disruptions, improve hospital's operating efficiency and enhance patient satisfaction. ORIGINALITY/VALUE: The paper reviews prior research on physician leadership and adds further insights into the crisis leadership literature. The authors provide evidence based on quantitative data analysis that during the COVID-19 pandemic, physician-led top-rated US hospitals experienced an improvement in operating efficiency.

Throwing caution to the wind: How hurricanes affect COVID-19 spread.

This study exploits the pathway of Hurricane Laura to assess its impact on the spread of COVID-19. Using US hospital data on confirmed and suspected adult COVID-19 cases, we find average daily cases per week rose by more than 12% primarily in tropical storm-affected counties in subsequent weeks. We suspect the key mechanisms involve constraints on social distancing for two reasons. First, there is significant evidence of storm-induced mobility. Second, lower income areas endured higher growth in hospital cases during the post-hurricane period. These findings provide crucial insights for policy-makers when designing natural disaster protocols to adjust for potential respiratory viral illnesses.

Demographics matter: the potentially disproportionate effect of COVID-19 on hospital ratings.

OBJECTIVE: To identify how features of the community in which a hospital serves differentially relate to its patients' experiences based on the quality of that hospital. DESIGN: A Finite Mixture Model (FMM) is used to uncover a mix of two latent groups of hospitals that differ in quality. In the FMM, a multinomial logistic equation relates hospital-level factors to the odds of being in either group. And a multiple linear regression relates the characteristics of communities served by hospitals to the patients' expected ratings of their experiences at hospitals in each group. Thus, this association potentially varies with hospital quality. The analysis was conducted via Stata. SETTING: Hospital Ratings are measured by Hospital Compare using the HCAHPS survey, a patient satisfaction survey required by the Centers for Medicare and Medicaid Services (CMS) for hospitals in the United States. Participants: 2,816 Medicare-certified acute care hospitals across all US states.

Provider-patient communication and hospital ratings: perceived gaps and forward thinking about the effects of COVID-19.

OBJECTIVES: To highlight clinical and operational issues, identify factors that shape patient responses in Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) and test the correlations between composite measures and overall hospital ratings. DESIGN: Responses to HCAHPS surveys were used in a partial correlation analysis to ascertain those HCAHPS composite measures that most relate to overall hospital ratings. The linear mean scores for the composite measures and individual and global items were analyzed with descriptive analysis and correlation analysis via JMP and SPSS statistical software. SETTING: HCAHPS is a patient satisfaction survey required by the Centers for Medicare and Medicaid Services for hospitals in the USA. The survey is for adult inpatients, excluding psychiatric patients. PARTICIPANTS: 3382 US hospitals. INTERVENTION: None. MAIN OUTCOME MEASURE: Pearson correlation coefficients for the six composite measures and overall hospital rating. RESULTS: The partial correlations for overall hospital rating and three composite measures are positive and moderately strong for care transition (0.445) and nurse communication (0.369) and weak for doctor communication (0.066). CONCLUSIONS: From a health policy standpoint, it is imperative that hospital administrators stress open and clear communication between providers and patients to avoid problems ranging from misdiagnosis to incorrect treatment. Additional research is needed to determine how the coronavirus of 2019 pandemic influences patients' perceptions of quality and willingness to recommend hospitals at a time when nurses and physicians show symptoms of burnout due to heavy workloads and inadequate personal protective equipment.