Impact of the COVID-19 Pandemic on Inpatient and Outpatient Utilization of Bariatric Surgery.

BACKGROUND: During the COVID-19 pandemic, deferral of inpatient elective surgical procedures served as a primary mechanism to increase surge inpatient capacity. Given the benefit of bariatric surgery on treating obesity and associated comorbidities, decreased access to bariatric surgery may have long-term public health consequences. Understanding the extent of the disruption of the COVID-19 pandemic to bariatric surgery will help health systems plan for appropriate access. MATERIALS AND METHODS: This is an observational cohort study using the PINC AI Healthcare Database from 1/1/2019-6/31/2021. A Poisson regression model with patient characteristics and hospital-fixed effects was used to assess the relative monthly within-hospital reduction in surgical encounters, variations by race and ethnicity, and shift from inpatient to outpatient procedures. A multivariate linear probability model was used to assess the change in 30-day readmissions from 2020 and 2021 compared to 2019. RESULTS: Among 309 hospitals, there were 46,539 bariatric procedures conducted in 2019 with a 14.8% reduction in volume to 39,641 procedures in 2020. There were 22,642 bariatric procedures observed from January to June of 2021. The most pronounced decrease in volume occurred in April with an 89.7% relative reduction from 2019. Black and Hispanic patients were more likely to receive bariatric surgery after the height of the pandemic compared to white patients. A clinically significant shift from inpatient to outpatient bariatric surgical procedures was not observed. Relative to 2019, there were no significant differences in bariatric surgical readmission rates. CONCLUSION: During the pandemic there was a sizable decrease in bariatric surgical volume. There did not appear to be disparities in access to bariatric surgery for minority patients. We did not observe a meaningful shift toward outpatient bariatric surgical procedures. Post-pandemic, monitoring is needed to assess if hospitals have been able to meet the demand for bariatric surgical procedures.

The role of digital technology in surgical home hospital programs.

Home hospital (HH), a care delivery model of providing hospital-grade care to patients in their homes, has become increasingly common in medical settings, though surgical uptake has been limited. HH programs have been shown to be safe and effective in a variety of medical contexts, with increased usage of this care pathway during the COVID-19 pandemic. Though surgical patients have unique clinical considerations, surgical Home Hospital (SHH) programs may have important benefits for this population. Various technologies exist for the delivery of hospital care in the home, such as clinical risk prediction models and remote patient monitoring platforms. Here, we use institutional experiences at Brigham and Women's Hospital (BWH) to discuss the utility of technology in enabling SHH programs and highlight current limitations. Additionally, we comment on the importance of data interoperability, access for all patients, and clinical workflow design in successfully implementing SHH programs.

Assessment of Strategies Used in US Hospitals to Address Social Needs During the COVID-19 Pandemic.

This survey study uses 2020 American Hospital Association data to assess strategies of US hospitals serving vulnerable populations in addressing social needs during the COVID-19 pandemic.

Comparison of Pregnancy and Birth Outcomes Before vs During the COVID-19 Pandemic.

Importance: Little is known about changes in obstetric outcomes during the COVID-19 pandemic. Objective: To assess whether obstetric outcomes and pregnancy-related complications changed during the COVID-19 pandemic. Design, Setting, and Participants: This retrospective cohort study included pregnant patients receiving care at 463 US hospitals whose information appeared in the PINC AI Healthcare Database. The relative differences in birth outcomes, pregnancy-related complications, and length of stay (LOS) during the pandemic period (March 1, 2020, to April 31, 2021) were compared with the prepandemic period (January 1, 2019, to February 28, 2020) using logistic and Poisson models, adjusting for patients' characteristics, and comorbidities and with month and hospital fixed effects. Exposures: COVID-19 pandemic period. Main Outcomes and Measures: The 3 primary outcomes were the relative change in preterm vs term births, mortality outcomes, and mode of delivery. Secondary outcomes included the relative change in pregnancy-related complications and LOS. Results: There were 849 544 and 805 324 pregnant patients in the prepandemic and COVID-19 pandemic periods, respectively, and there were no significant differences in patient characteristics between periods, including age (≥35 years: 153 606 [18.1%] vs 148 274 [18.4%]), race and ethnicity (eg, Hispanic patients: 145 475 [47.1%] vs 143 905 [17.9%]; White patients: 456 014 [53.7%] vs 433 668 [53.9%]), insurance type (Medicaid: 366 233 [43.1%] vs 346 331 [43.0%]), and comorbidities (all standardized mean differences <0.10). There was a 5.2% decrease in live births during the pandemic. Maternal death during delivery hospitalization increased from 5.17 to 8.69 deaths per 100 000 pregnant patients (odds ratio [OR], 1.75; 95% CI, 1.19-2.58). There were minimal changes in mode of delivery (vaginal: OR, 1.01; 95% CI, 0.996-1.02; primary cesarean: OR, 1.02; 95% CI, 1.01-1.04; vaginal birth after cesarean: OR, 0.98; 95% CI, 0.95-1.00; repeated cesarean: OR, 0.96; 95% CI, 0.95-0.97). LOS during delivery hospitalization decreased by 7% (rate ratio, 0.931; 95% CI, 0.928-0.933). Lastly, the adjusted odds of gestational hypertension (OR, 1.08; 95% CI, 1.06-1.11), obstetric hemorrhage (OR, 1.07; 95% CI, 1.04-1.10), preeclampsia (OR, 1.04; 95% CI, 1.02-1.06), and preexisting chronic hypertension (OR, 1.06; 95% CI, 1.03-1.09) increased. No significant changes in preexisting racial and ethnic disparities were observed. Conclusions and Relevance: During the COVID-19 pandemic, there were increased odds of maternal death during delivery hospitalization, cardiovascular disorders, and obstetric hemorrhage. Further efforts are needed to ensure risks potentially associated with the COVID-19 pandemic do not persist beyond the current state of the pandemic.

Algorithmic fairness in pandemic forecasting: lessons from COVID-19.

Racial and ethnic minorities have borne a particularly acute burden of the COVID-19 pandemic in the United States. There is a growing awareness from both researchers and public health leaders of the critical need to ensure fairness in forecast results. Without careful and deliberate bias mitigation, inequities embedded in data can be transferred to model predictions, perpetuating disparities, and exacerbating the disproportionate harms of the COVID-19 pandemic. These biases in data and forecasts can be viewed through both statistical and sociological lenses, and the challenges of both building hierarchical models with limited data availability and drawing on data that reflects structural inequities must be confronted. We present an outline of key modeling domains in which unfairness may be introduced and draw on our experience building and testing the Google-Harvard COVID-19 Public Forecasting model to illustrate these challenges and offer strategies to address them. While targeted toward pandemic forecasting, these domains of potentially biased modeling and concurrent approaches to pursuing fairness present important considerations for equitable machine-learning innovation.

Marketplace Health Insurance Ratings: Most Potential Enrollees Have Access To Plans Of Medium Or High Quality.

The Affordable Care Act (ACA) Marketplace plays a critical role in providing affordable health insurance for the nongroup market, yet the accessibility of plans from insurers with high quality ratings has not been investigated. Our analysis of recently released insurer quality star ratings for plan year 2020 found substantial variation in access to high rated plans in the federally facilitated ACA Marketplace. In most participating counties (1,390 of 2,265, or 61.4 percent), the highest-rated ACA Marketplace insurer had a three-star rating. Fewer than one-third of counties (703, or 31.0 percent) had access to four- or five-star-rated insurers. Fewer than 10 percent (172, or 7.6 percent) had access to only one- or two-star-rated insurers. In plan-based analyses, each one-point increase in star rating was associated with a $28 increase in the average monthly plan premium. Counties with the highest proportion of residents obtaining individual coverage through the ACA Marketplace and counties with more insurers were the most likely to have access to plans from high-rated insurers. We found no systematic racial or ethnic disparities in access to plans from high-rated insurers. Policy makers should continue to monitor the quality of available health plans.

Association of city-level walkability, accessibility to biking and public transportation and socio-economic features with COVID-19 infection in Massachusetts, USA: An ecological study.

With people restricted to their residences, neighbourhood characteristics may affect behaviour and risk of coronavirus disease 2019 (COVID-19) infection. We aimed to analyse whether neighbourhoods with higher walkability, public transit, biking services and higher socio-economic status were associated with lower COVID-19 infection during the peak of the COVID-19 pandemic in Massachusetts. We used Walk Score®, Bike Score®, and Transit Score® indices to assess the walkability and transportation of 72 cities in Massachusetts, USA based on availability of data and collected the total COVID-19 case numbers of each city up to 10 April 2021. We used univariate and multivariate linear models to analyse the effects of these scores on COVID-19 cases per 100,000 in each city, adjusting for demographic covariates and all covariates, respectively. In the 72 cities studied, the average Walk Score, Transit Score and Bike Score was 48.7, 36.5 and 44.1, respectively, with a total of 426,182 COVID-19 cases. Higher Walk Score, Transit Score, and Bike Score rankings were negatively associated with COVID-19 cases per 100,000 persons (<0.05). Cities with a higher proportion of Hispanic population and a lower median household income were associated with more COVID-19 cases per 100,000 (P<0.05). Higher Walk Score, Transit Score and Bike Score were shown to be protective against COVID-19 transmission, while socio-demographic factors were associated with COVID-19 infection. Understanding the complex relationship of how the structure of the urban environment may constrain commuting patterns for residents and essential workers during COVID-19 would offer potential insights on future pandemic preparedness and response.

Variation in Use of Surgical Care During the COVID-19 Pandemic by Surgical Urgency and Race and Ethnicity

Key Points Question To what extent did the COVID-19 pandemic reduce access to surgical care, and were racial and ethnic minority groups more likely to have reduced access to surgical care? Findings In this cohort study of more than 13 million inpatient and outpatient surgical encounters in 767 US hospitals in a hospital administrative database, surgical use was 13% lower in 2020 compared with 2019, with the greatest decrease concentrated in elective surgical procedures. While Black and Hispanic patients experienced a reduction in surgical encounters, White patients experienced the greatest reduction in surgical encounters. Meaning Despite severe and persistent disruptions to health systems during the COVID-19 pandemic, racial and ethnic minority groups did not experience a disproportionate decrease in access to surgical care. Importance The extent of the disruption to surgical care during the COVID-19 pandemic has not been empirically characterized on a national level. Objective To characterize the use of surgical care across cohorts of surgical urgency during the COVID-19 pandemic, and to assess for racial and ethnic disparities. Design, Setting, and Participants This was a retrospective observational study using the geographically diverse, all payer data from 767 hospitals in the Premier Healthcare Database. Procedures were categorized into 4 cohorts of surgical urgency (elective, nonelective, emergency, and trauma). A generalized linear regression model with hospital-fixed effects assessed the relative monthly within-hospital reduction in surgical encounters in 2020 compared with 2019. Main Outcomes and Measures Outcomes were the monthly relative reduction in overall surgical encounters and across surgical urgency cohorts and race and ethnicity. Results The sample included 13 175 087 inpatient and outpatient surgical encounters. There was a 12.6% relative reduction in surgical use in 2020 compared to 2019. Across all surgical cohorts, the most prominent decreases in encounters occurred during Spring 2020 . For example, elective encounters began falling in March, reached a trough in April, and subsequently recovered but never to prepandemic levels (March: −26.8%;95% CI, −29.6% to −23.9%;April: −74.6%;95% CI, −75.5% to −73.5%;December: −13.3%;95% CI, −16.6%, −9.8%). Across all operative surgical urgency cohorts, White patients had the largest relative reduction in encounters. Conclusions and Relevance As shown by this cohort study, the COVID-19 pandemic resulted in large disruptions to surgical care across all categories of operative urgency, especially elective procedures. Racial and ethnic minority groups experienced less of a disruption to surgical care than White patients. Further research is needed to explore whether the decreased surgical use among White patients was owing to patient discretion and to document whether demand for surgical care will rebound to baseline levels. This cohort study examines the use of surgical care across cohorts of surgical urgency during the COVID-19 pandemic and assesses whether there are racial or ethnic disparities in care.

Variation in Use of Surgical Care During the COVID-19 Pandemic by Surgical Urgency and Race and Ethnicity.

Importance: The extent of the disruption to surgical care during the COVID-19 pandemic has not been empirically characterized on a national level. Objective: To characterize the use of surgical care across cohorts of surgical urgency during the COVID-19 pandemic, and to assess for racial and ethnic disparities. Design Setting and Participants: This was a retrospective observational study using the geographically diverse, all payer data from 767 hospitals in the Premier Healthcare Database. Procedures were categorized into 4 cohorts of surgical urgency (elective, nonelective, emergency, and trauma). A generalized linear regression model with hospital-fixed effects assessed the relative monthly within-hospital reduction in surgical encounters in 2020 compared with 2019. Main Outcomes and Measures: Outcomes were the monthly relative reduction in overall surgical encounters and across surgical urgency cohorts and race and ethnicity. Results: The sample included 13 175 087 inpatient and outpatient surgical encounters. There was a 12.6% relative reduction in surgical use in 2020 compared to 2019. Across all surgical cohorts, the most prominent decreases in encounters occurred during Spring 2020 . For example, elective encounters began falling in March, reached a trough in April, and subsequently recovered but never to prepandemic levels (March: -26.8%; 95% CI, -29.6% to -23.9%; April: -74.6%; 95% CI, -75.5% to -73.5%; December: -13.3%; 95% CI, -16.6%, -9.8%). Across all operative surgical urgency cohorts, White patients had the largest relative reduction in encounters. Conclusions and Relevance: As shown by this cohort study, the COVID-19 pandemic resulted in large disruptions to surgical care across all categories of operative urgency, especially elective procedures. Racial and ethnic minority groups experienced less of a disruption to surgical care than White patients. Further research is needed to explore whether the decreased surgical use among White patients was owing to patient discretion and to document whether demand for surgical care will rebound to baseline levels.

Association of community-level social vulnerability with US acute care hospital intensive care unit capacity during COVID-19.

The COVID-19 pandemic has placed unprecedented stress on US acute care hospitals, leading to overburdened ICUs. It remains unknown if increased COVID-19 ICU occupancy is crowding out non-COVID-related care and whether hospitals in vulnerable communities may be more susceptible to ICUs reaching capacity. Using facility-level hospitalization data, we conducted a retrospective observational cohort study of 1753 US acute care hospitals reporting to the US Department of Health and Human Services Protect database from September 4, 2020 to February 25, 2021. 63% of hospitals reached critical ICU capacity for at least two weeks during the study period, and the surge of COVID-19 cases appeared to be crowding out non-COVID-19-related intensive care needs. Hospitals in the South (OR = 3.31, 95% CI OR 2.31-4.78) and West (OR = 2.28, 95% CI OR 1.51-3.46) were more likely to reach critical capacity than those in the Northeast, and hospitals in areas with the highest social vulnerability were more than twice as likely to reach capacity as those in the least vulnerable areas (OR = 2.15, 95% CI OR 1.41-3.29). The association between social vulnerability and critical ICU capacity highlights underlying structural inequities in health care access and provides an opportunity for policymakers to take action to prevent strained ICU capacity from compounding COVID-19 inequities.

Early social distancing policies in Europe, changes in mobility & COVID-19 case trajectories: Insights from Spring 2020.

BACKGROUND: Social distancing have been widely used to mitigate community spread of SARS-CoV-2. We sought to quantify the impact of COVID-19 social distancing policies across 27 European counties in spring 2020 on population mobility and the subsequent trajectory of disease. METHODS: We obtained data on national social distancing policies from the Oxford COVID-19 Government Response Tracker and aggregated and anonymized mobility data from Google. We used a pre-post comparison and two linear mixed-effects models to first assess the relationship between implementation of national policies and observed changes in mobility, and then to assess the relationship between changes in mobility and rates of COVID-19 infections in subsequent weeks. RESULTS: Compared to a pre-COVID baseline, Spain saw the largest decrease in aggregate population mobility (~70%), as measured by the time spent away from residence, while Sweden saw the smallest decrease (~20%). The largest declines in mobility were associated with mandatory stay-at-home orders, followed by mandatory workplace closures, school closures, and non-mandatory workplace closures. While mandatory shelter-in-place orders were associated with 16.7% less mobility (95% CI: -23.7% to -9.7%), non-mandatory orders were only associated with an 8.4% decrease (95% CI: -14.9% to -1.8%). Large-gathering bans were associated with the smallest change in mobility compared with other policy types. Changes in mobility were in turn associated with changes in COVID-19 case growth. For example, a 10% decrease in time spent away from places of residence was associated with 11.8% (95% CI: 3.8%, 19.1%) fewer new COVID-19 cases. DISCUSSION: This comprehensive evaluation across Europe suggests that mandatory stay-at-home orders and workplace closures had the largest impacts on population mobility and subsequent COVID-19 cases at the onset of the pandemic. With a better understanding of policies' relative performance, countries can more effectively invest in, and target, early nonpharmacological interventions.

Impacts of social distancing policies on mobility and COVID-19 case growth in the US.

Social distancing remains an important strategy to combat the COVID-19 pandemic in the United States. However, the impacts of specific state-level policies on mobility and subsequent COVID-19 case trajectories have not been completely quantified. Using anonymized and aggregated mobility data from opted-in Google users, we found that state-level emergency declarations resulted in a 9.9% reduction in time spent away from places of residence. Implementation of one or more social distancing policies resulted in an additional 24.5% reduction in mobility the following week, and subsequent shelter-in-place mandates yielded an additional 29.0% reduction. Decreases in mobility were associated with substantial reductions in case growth two to four weeks later. For example, a 10% reduction in mobility was associated with a 17.5% reduction in case growth two weeks later. Given the continued reliance on social distancing policies to limit the spread of COVID-19, these results may be helpful to public health officials trying to balance infection control with the economic and social consequences of these policies.