Rural Hospitals Experienced More Patient Volume Variability Than Urban Hospitals During The COVID-19 Pandemic, 2020-21.

Fluctuations in patient volume during the COVID-19 pandemic may have been particularly concerning for rural hospitals. We examined hospital discharge data from the Healthcare Cost and Utilization Project State Inpatient Databases to compare data from the COVID-19 pandemic period (March 8, 2020-December 31, 2021) with data from the prepandemic period (January 1, 2017-March 7, 2020). Changes in average daily medical volume at rural hospitals showed a dose-response relationship with community COVID-19 burden, ranging from a 13.2 percent decrease in patient volume in periods of low transmission to a 16.5 percent increase in volume in periods of high transmission. Overall, about 35 percent of rural hospitals experienced fluctuations exceeding 20 percent (in either direction) in average daily total volume, in contrast to only 13 percent of urban hospitals experiencing similar magnitudes of changes. Rural hospitals with a large change in average daily volume were more likely to be smaller, government-owned, and critical access hospitals and to have significantly lower operating margins. Our findings suggest that rural hospitals may have been more vulnerable operationally and financially to volume shifts during the pandemic, which warrants attention because of the potential impact on these hospitals' long-term sustainability.

Mortality for Time-Sensitive Conditions at Urban vs Rural Hospitals During the COVID-19 Pandemic.

Importance: COVID-19 pandemic-related disruptions to the health care system may have resulted in increased mortality for patients with time-sensitive conditions. Objective: To examine whether in-hospital mortality in hospitalizations not related to COVID-19 (non-COVID-19 stays) for time-sensitive conditions changed during the pandemic and how it varied by hospital urban vs rural location. Design, Setting, and Participants: This cohort study was an interrupted time-series analysis to assess in-hospital mortality during the COVID-19 pandemic (March 8, 2020, to December 31, 2021) compared with the prepandemic period (January 1, 2017, to March 7, 2020) overall, by month, and by community COVID-19 transmission level for adult discharges from 3813 US hospitals in the State Inpatient Databases for the Healthcare Cost and Utilization Project. Exposure: The COVID-19 pandemic. Main Outcomes and Measures: The main outcome measure was in-hospital mortality among non-COVID-19 stays for 6 time-sensitive medical conditions: acute myocardial infarction, hip fracture, gastrointestinal hemorrhage, pneumonia, sepsis, and stroke. Entropy weights were used to align patient characteristics in the 2 time periods by age, sex, and comorbidities. Results: There were 18 601 925 hospitalizations; 50.3% of patients were male, 38.5% were aged 18 to 64 years, 45.0% were aged 65 to 84 years, and 16.4% were 85 years or older for the selected time-sensitive medical conditions from 2017 through 2021. The odds of in-hospital mortality for sepsis increased 27% from the prepandemic to the pandemic periods at urban hospitals (odds ratio [OR], 1.27; 95% CI, 1.25-1.29) and 35% at rural hospitals (OR, 1.35; 95% CI, 1.30-1.40). In-hospital mortality for pneumonia had similar increases at urban (OR, 1.48; 95% CI, 1.42-1.54) and rural (OR, 1.46; 95% CI, 1.36-1.57) hospitals. Increases in mortality for these 2 conditions showed a dose-response association with the community COVID-19 level (low vs high COVID-19 burden) for both rural (sepsis: 22% vs 54%; pneumonia: 30% vs 66%) and urban (sepsis: 16% vs 28%; pneumonia: 34% vs 61%) hospitals. The odds of mortality for acute myocardial infarction increased 9% (OR, 1.09; 95% CI, 1.06-1.12) at urban hospitals and was responsive to the community COVID-19 level. There were significant increases in mortality for hip fracture at rural hospitals (OR, 1.32; 95% CI, 1.14-1.53) and for gastrointestinal hemorrhage at urban hospitals (OR, 1.15; 95% CI, 1.09-1.21). No significant change was found in mortality for stroke overall. Conclusions and Relevance: In this cohort study, in-hospital mortality for time-sensitive conditions increased during the COVID-19 pandemic. Mobilizing strategies tailored to the different needs of urban and rural hospitals may help reduce the likelihood of excess deaths during future public health crises.

Medicare Advantage in rural areas: implications for hospital sustainability.

OBJECTIVES: A growing number of Medicare beneficiaries in rural areas are enrolled in Medicare Advantage plans, which negotiate hospital reimbursement. This study examined the association between Medicare Advantage penetration levels in rural areas and hospital financial distress and closure. STUDY DESIGN: This retrospective cohort study followed rural general acute care hospitals open in 2008 through 2019 or until closure using Healthcare Cost and Utilization Project State Inpatient Databases for 14 states. METHODS: The primary independent variables were the percentage of Medicare Advantage stays out of total Medicare stays at the hospital and the percentage of Medicare Advantage beneficiaries out of total beneficiaries in the hospital's county. Financial distress was defined using the Altman Z score, where values less than or equal to 1.1 indicate financial distress and values greater than 2.8 indicate stability. The Z score was examined as a continuous outcome in hospital and county fixed-effects models. Risk of closure was examined using Cox proportional hazard models adjusted for hospital and market factors. RESULTS: Rural hospital Medicare Advantage penetration grew from 6.5% in 2008 to 20.6% in 2019. A 1-percentage point increase in hospital penetration was associated with an increase in financial stability of 0.04 units on the Altman Z score (95% CI, 0.00-0.08; P = .03) and a 4% reduction in risk of closure (HR, 0.96; 95% CI, 0.92-1.00; P = .04). Results were consistent when measuring Medicare Advantage penetration at the county level. CONCLUSIONS: Our findings counter the notion that Medicare Advantage plans financially hurt rural hospitals because they pay less generously than traditional Medicare.

Preventable tragedies: findings from the #NotAnAccident index of unintentional shootings by children.

BACKGROUND: Between 2015 and 2021, 3,498 Americans died from unintentional gun injuries, including 713 children 17 years and younger. Roughly 30 million American children live in homes with firearms, many of which are loaded and unlocked. This study assesses the scope of unintentional shootings by children 17 and younger in the US and the relationship between these shootings and state-level secure storage laws. METHODS: Demographic and injury data of both perpetrators and victims of unintentional shootings by children 17 and younger in the US from 1/1/2015-12/31/2021 were extracted from the #NotAnAccident Index. The #NotAnAccident Index contains media-report data, which is systematically flagged through Google Alerts. We describe characteristics of incidents and examine incident rates over time. The association between state-level secure storage laws and rates of unintentional shootings by children is assessed in multivariate negative binomial regression models. RESULTS: 2,448 unintentional shootings by children resulted in 926 deaths and 1,603 nonfatal gun injuries over a period of seven years. Most perpetrators (81%) and victims (76%) were male. The mean age was 10.0 (SD 5.5) for shooters and 10.9 (SD 8.1) for victims. Children were as likely to shoot themselves (49%) as they were to shoot others (47%). The majority of victims were under 18 years old (91%). Shootings most often occurred in or around homes (71%) and with handguns (53%). From March to December 2020, coinciding with the COVID-19 pandemic, incidents increased 24% over the same period in 2019, which was driven largely by an increase among shooters ages 0-5. Depending on the type of law, rates of unintentional shootings by children were 24% to 72% lower in states with secure storage laws, compared to states without such laws. CONCLUSIONS: Unintentional shootings by children are on the rise, particularly among children 0-5 years old, but are preventable tragedies. Our results show that secure firearm storage policies are strongly correlated with lower rates of unintentional shootings by children. Firearm storage policies, practices, and education efforts are needed to ensure guns are kept secured and inaccessible to children.

Effects of the COVID-19 early pandemic on delivery outcomes among women with and without COVID-19 at birth.

BACKGROUND: The COVID-19 pandemic may influence delivery outcomes through direct effects of infection or indirect effects of disruptions in prenatal care. We examined early pandemic-related changes in birth outcomes for pregnant women with and without a COVID-19 diagnosis at delivery. METHODS: We compared four delivery outcomes-preterm delivery (PTD), severe maternal morbidity (SMM), stillbirth, and cesarean birth-between 2017 and 2019 (prepandemic) and between April and December 2020 (early-pandemic) using interrupted time series models on 11.8 million deliveries, stratified by COVID-19 infection status at birth with entropy weighting for historical controls, from the Healthcare Cost and Utilization Project across 43 states and the District of Columbia. RESULTS: Relative to 2017-2019, women without COVID-19 at delivery in 2020 had lower odds of PTD (OR = 0.93; 95% CI = 0.92-0.94) and SMM (OR = 0.88; 95% CI = 0.85-0.91) but increased odds of stillbirth (OR = 1.04; 95% CI = 1.01-1.08). Absolute effects were small across race/ethnicity groups. Deliveries with COVID-19 had an excess of each outcome, by factors of 1.07-1.46 for outcomes except SMM at 4.21. The effect for SMM was more pronounced for Asian/Pacific Islander non-Hispanic (API; OR = 10.51; 95% CI = 5.49-20.14) and Hispanic (OR = 5.09; 95% CI = 4.29-6.03) pregnant women than for White non-Hispanic (OR = 3.28; 95% CI = 2.65-4.06) women. DISCUSSION: Decreasing rates of PTD and SMM and increasing rates of stillbirth among deliveries without COVID-19 were small but suggest indirect effects of the pandemic on maternal outcomes. Among pregnant women with COVID-19 at delivery, adverse effects, particularly SMM for API and Hispanic women, underscore the importance of addressing health disparities.

Background rates of adverse events of special interest for COVID-19 vaccine safety monitoring in the United States, 2019-2020.

BACKGROUND: The U.S. Food and Drug Administration (FDA) Biologics Effectiveness and Safety (BEST) Initiative conducts active surveillance of adverse events of special interest (AESI) after COVID-19 vaccination. Historical incidence rates (IRs) of AESI are comparators to evaluate safety. METHODS: We estimated IRs of 17 AESI in six administrative claims databases from January 1, 2019, to December 11, 2020: Medicare claims for adults ≥ 65 years and commercial claims (Blue Health Intelligence®, CVS Health, HealthCore Integrated Research Database, IBM® MarketScan® Commercial Database, Optum pre-adjudicated claims) for adults < 65 years. IRs were estimated by sex, age, race/ethnicity (Medicare), and nursing home residency (Medicare) in 2019 and for specific periods in 2020. RESULTS: The study included >100 million enrollees annually. In 2019, rates of most AESI increased with age. However, compared with commercially insured adults, Medicare enrollees had lower IRs of anaphylaxis (11 vs 12-19 per 100,000 person-years), appendicitis (80 vs 117-155), and narcolepsy (38 vs 41-53). Rates were higher in males than females for most AESI across databases and varied by race/ethnicity and nursing home status (Medicare). Acute myocardial infarction (Medicare) and anaphylaxis (all databases) IRs varied by season. IRs of most AESI were lower during March-May 2020 compared with March-May 2019 but returned to pre-pandemic levels after May 2020. However, rates of Bell's palsy, Guillain-Barré syndrome, narcolepsy, and hemorrhagic/non-hemorrhagic stroke remained lower in multiple databases after May 2020, whereas some AESI (e.g., disseminated intravascular coagulation) exhibited higher rates after May 2020 compared with 2019. CONCLUSION: AESI background rates varied by database and demographics and fluctuated in March-December 2020, but most returned to pre-pandemic levels after May 2020. It is critical to standardize demographics and consider seasonal and other trends when comparing historical rates with post-vaccination AESI rates in the same database to evaluate COVID-19 vaccine safety.

Risk of Closure Among Independent and Multihospital-Affiliated Rural Hospitals.

Importance: The increase in rural hospital closures has strained access to inpatient care in rural communities. It is important to understand the association between hospital system affiliation and access to care in these communities to inform policy on this issue. Objective: To examine the association between affiliation and rural hospital closure. Design Setting and Participants: This cohort study used survival models with a time-dependent variable for affiliation vs independent status to assess risk of closure among a national cohort of US rural hospitals from January 2007 through December 2019. Data analysis was conducted from March to October 2021. Hospital affiliations were identified from the American Hospital Association Annual Survey and Irving Levin Associates and closures from the University of North Carolina Sheps Center (Chapel Hill). Additional covariates came from the Healthcare Cost and Utilization Project State Inpatient Databases and other national sources. Exposures: Affiliation with another hospital or multihospital health system. Main Outcomes and Measures: Closure was the main outcome. The models included hospital, market, and utilization characteristics and were stratified by financial distress in 2007. Results: Among 2237 rural hospitals operating in 2007, 140 (6.3%) had closed by 2019. The proportion of rural hospitals that were independent decreased from 68.9% in 2007 to 47.0% in 2019; the proportion that were affiliated increased from 31.1% to 46.7%. Among financially distressed hospitals in 2007, affiliation was associated with lower risk of closure compared with being independent (adjusted hazard ratio [aHR], 0.49; 95% CI, 0.26-0.92). Conversely, among hospitals that were financially stable in 2007, affiliation was associated with higher risk of closure compared with being independent (aHR, 2.36; 95% CI, 1.20-4.62). For-profit ownership was also strongly associated with closure for hospitals that were financially stable in 2007 (aHR, 4.08; 95% CI, 1.86-8.97). Conclusions and Relevance: The results of this cohort study suggest that affiliations may be associated with lower risk of closure for some rural hospitals in financial distress. However, among initially financially stable hospitals, an increased risk of closure for hospitals associated with affiliation and proprietary ownership raises concerns about the association of affiliation with closures in some circumstances. Policy interventions to stabilize inpatient care in rural areas should account for these findings.

Contributors to disparities in postpartum readmission rates between safety-net and non-safety-net hospitals: A decomposition analysis.

BACKGROUND: Safety-net hospitals (SNHs) treat more maternal patients with risk factors for postpartum readmission. OBJECTIVE: To assess how patient, hospital, and community characteristics explain the SNH/non-SNH disparity in postpartum readmission rates. DESIGN: A linear probability model assessed covariates associated with postpartum readmissions. Oaxaca-Blinder decomposition estimates quantified the contribution of covariates to the SNH/non-SNH disparity in postpartum readmission rates. SETTING: Healthcare Cost and Utilization Project 2016-2018 State Inpatient Databases from 25 states. PARTICIPANTS: 3.5 million maternal delivery stays. MEASUREMENTS: The outcome was inpatient readmission within 42 days of delivery. SNHs had a share of Medicaid/uninsured stays in the top quartile. A range of patient, hospital, and community characteristics was considered as covariates. RESULTS: The unadjusted postpartum readmission rate was 4.2 per 1000 index deliveries higher at SNHs than at non-SNHs (19.1 vs. 14.9, p < .001). Adjustment reduced the risk difference to 0.65 per 1000 (95% confidence interval [CI]: -0.14, 1.44). Patient (66%), hospital (14%), and community (4%) characteristics explained 84% of the disparity. The single largest contributors to the disparity were race/ethnicity (20%), hypertension (12%), hospital preterm delivery rate (10%), and preterm delivery (7%). Collectively, patient comorbidities explained 31% of the disparity. CONCLUSION: Higher postpartum readmission rates at SNHs versus non-SNHs were largely due to differences in the patient mix rather than hospital factors. Hospital initiatives are needed to reduce the risk of postpartum readmissions among SNH patients. Improving factors that contribute to the disparity, including underlying health conditions and health inequities associated with race, requires enduring investments in public health.

Access To Obstetric, Behavioral Health, And Surgical Inpatient Services After Hospital Mergers In Rural Areas.

Despite rural hospitals' central role in their communities, they are increasingly in financial distress and may merge with other hospitals or health systems, potentially reducing service lines that are less profitable or duplicative of services that the acquirer also offers. Using hospital discharge data from thirty-two Healthcare Cost and Utilization Project State Inpatient Databases from the period 2007-18, we examined the influence of rural hospital mergers on changes to inpatient service lines at hospitals and within their catchment areas. We found that merged hospitals were more likely than independent hospitals to eliminate maternal/neonatal and surgical care. Whereas the number of mental/substance use disorder-related stays decreased or remained stable at merged hospitals and within their catchment areas, it increased for unaffiliated hospitals and their catchment areas, indicating a potential unmet need in the communities of rural hospitals postmerger. Although a merger could salvage a hospital's sustainability, it also could reduce service lines and responsiveness to community needs.

Quality of Care Before and After Mergers and Acquisitions of Rural Hospitals.

Importance: Rural hospitals are increasingly merging with other hospitals. The associations of hospital mergers with quality of care need further investigation. Objectives: To examine changes in quality of care for patients at rural hospitals that merged compared with those that remained independent. Design, Setting, and Participants: In this case-control study, mergers at community nonrehabilitation hospitals in Federal Office of Rural Health Policy-eligible zip codes during 2009 to 2016 in 32 states were identified from Irving Levin Associates and the American Hospital Association Annual Survey. Outcomes for inpatient stays for select conditions and elective procedures were derived from the Healthcare Cost and Utilization Project State Inpatient Databases. Difference-in-differences linear probability models were used to assess premerger to postmerger changes in outcomes for patients discharged from merged vs comparison hospitals that remained independent. Data were analyzed from February to December 2020. Exposures: Hospital mergers. Main Outcomes and Measures: The main outcome was in-hospital mortality among patients admitted for acute myocardial infarction (AMI), heart failure, stroke, gastrointestinal hemorrhage, hip fracture, or pneumonia, as well as complications during stays for elective surgeries. Results: A total of 172 merged hospitals and 266 comparison hospitals were analyzed. After matching, baseline patient characteristics were similar for 303 747 medical stays and 175 970 surgical stays at merged hospitals and 461 092 medical stays and 278 070 surgical stays at comparison hospitals. In-hospital mortality among AMI stays decreased from premerger to postmerger at merged hospitals (9.4% to 5.0%) and comparison hospitals (7.9% to 6.3%). Adjusting for patient, hospital, and community characteristics, the decrease in in-hospital mortality among AMI stays 1 year postmerger was 1.755 (95% CI, -2.825 to -0.685) percentage points greater at merged hospitals than at comparison hospitals (P < .001). This finding held up to 4 years postmerger (DID, -2.039 [95% CI, -3.388 to -0.691] percentage points; P = .003). Greater premerger to postmerger decreases in mortality at merged vs comparison hospitals were also observed at 5 years postmerger among stays for heart failure (DID, -0.756 [95% CI, -1.448 to -0.064] percentage points; P = .03), stroke (DID, -1.667 [95% CI, -3.050 to -0.283] percentage points; P = .02), and pneumonia (DID, -0.862 [95% CI, -1.681 to -0.042] percentage points; P = .04). Conclusions and Relevance: These findings suggest that rural hospital mergers were associated with better mortality outcomes for AMI and several other conditions. This finding is important to enhancing rural health care and reducing urban-rural disparities in quality of care.

Price elasticity of demand for buprenorphine/naloxone prescriptions.

Although there have been supply-side efforts in response to the opioid crisis (e.g., prescription drug monitoring programs), little information exists on demand-side approaches related to patient cost sharing that may affect utilization of and adherence to pharmacotherapy by individuals with opioid use disorder. Among individuals who had initiated pharmacotherapy, we estimated the price elasticity of demand of prescription fills of buprenorphine/naloxone, a common pharmacotherapy drug, overall and by patient characteristics. Using the IBM MarketScan® Commercial Claims and Encounters Database for individuals with employer-sponsored private health insurance coverage, we examined the relationship between cost sharing and the number of buprenorphine/naloxone prescription fills using enrollee-level longitudinal fixed effects models. Cost sharing was expressed as a price index for each employer-plan. By including enrollee-level fixed effects, the identification of the effect of interest comes from longitudinal variation in prices across multiple time points for each enrollee. Overall, the demand for buprenorphine/naloxone was price inelastic (p = 0.191). However, some subgroups were responsive to price. A doubling of price was associated with a decrease in fills by 3.0% for enrollees aged 45-64 years (p = 0.029); 5.7% for those in rural areas (p = 0.033); 5.8% for residents of the South (p ≤0.001); and 3.0% for those enrolled in an HMO (p = 0.004). Insurers should consider the effects on these groups before increasing beneficiary out-of-pocket costs for pharmacotherapy and efforts to increase adherence should consider that price may be a barrier for some subgroups with OUD.

Comparison of 3 Safety-Net Hospital Definitions and Association With Hospital Characteristics.

Importance: No consensus exists on how to define safety-net hospitals (SNHs) for research or policy decision-making. Identifying which types of hospitals are classified as SNHs under different definitions is key to assessing policies that affect SNH funding. Objective: To examine characteristics of SNHs as classified under 3 common definitions. Design, Setting, and Participants: This cross-sectional analysis includes noncritical-access hospitals in the Healthcare Cost and Utilization Project State Inpatient Databases from 47 US states for fiscal year 2015, linked to the Centers for Medicare & Medicaid Services Hospital Cost Reports and to the American Hospital Association Annual Survey. Data were analyzed from March 1 through September 30, 2018. Exposures: Hospital characteristics including organizational characteristics, scope of services provided, and financial attributes. Main Outcomes and Measures: Definitions of SNH based on Medicaid and Medicare Supplemental Security Income inpatient days historically used to determine Medicare Disproportionate Share Hospital (DSH) payments; Medicaid and uninsured caseload; and uncompensated care costs. For each measure, SNHs were defined as those within the top quartile for each state. Results: The 2066 hospitals in this study were distributed across the Northeast (340 [16.5%]), Midwest (587 [28.4%]), South (790 [38.2%]), and West (349 [16.9%]). Concordance between definitions was low; 269 hospitals (13.0%) or fewer were identified as SNHs under any 2 definitions. Uncompensated care captured smaller (200 of 523 [38.2%]) and more rural (65 of 523 [12.4%]) SNHs, whereas DSH index and Medicaid and uncompensated caseload identified SNHs that were larger (264 of 518 [51.0%] and 158 of 487 [32.4%], respectively) and teaching facilities (337 of 518 [65.1%] and 229 of 487 [47.0%], respectively) that provided more essential services than non-SNHs. Uncompensated care also distinguished remarkable financial differences between SNHs and non-SNHs. Under the uncompensated care definition, median (interquartile range [IQR]) bad debt ($27.1 [$15.5-$44.3] vs $12.8 [$6.7-$21.6] per $1000 of operating expenses; P < .001) and charity care ($19.9 [$9.3-$34.1] vs $9.1 [$4.0-$18.7] per $1000 of operating expenses) were twice as high and median (IQR) unreimbursed costs ($32.6 [$12.4-$55.4] vs $23.6 [$9.0-$42.7] per $1000 of operating expenses; P < .001) were 38% higher for SNHs than for non-SNHs. Safety-net hospitals defined by uncompensated care burden had lower median (IQR) total (4.7% [0%-9.9%] vs 5.8% [1.2%-11.2%]; P = .003) and operating (0.3% [-8.0% to 7.2%] vs 2.3% [-3.9% to 8.9%]; P < .001) margins than their non-SNH counterparts, whereas differences between SNH and non-SNH profit margins generally were not statistically significant under the other 2 definitions. Conclusions and Relevance: Different SNH definitions identify hospitals with different characteristics and financial conditions. The new DSH formula, which accounts for uncompensated care, may lead to redistributed payments across hospitals. Our results may inform which types of hospitals will experience funding changes as DSH payment policies evolve.

Shifts in Medicaid and Uninsured Payer Mix at Safety-Net and Non-Safety-Net Hospitals During the Great Recession.

EXECUTIVE SUMMARY: There has been ongoing concern regarding the viability of safety-net hospitals (SNHs), which care for vulnerable populations. The authors examined payer mix at SNHs and non-SNHs during a period covering the Great Recession using data from the 2006 to 2012 Healthcare Cost and Utilization Project State Inpatient Databases from 38 states. The number of privately insured stays decreased at both SNHs and non-SNHs. Non-SNHs increasingly served Medicaid-enrolled and uninsured patients; in SNHs, the number of Medicaid stays decreased and uninsured stays remained stable. These study findings suggest that SNHs were losing Medicaid-enrolled patients relative to non-SNHs before the Medicaid expansion under the Affordable Care Act (ACA). Postexpansion, Medicaid stays will likely increase for both SNHs and non-SNHs, but the increase at SNHs may not be as large as expected if competition increases. Because hospital stays with private insurance and Medicaid help SNHs offset uncompensated care, a lower-than-expected increase could affect SNHs' ability to care for the remaining uninsured population. Continued monitoring is needed once post-ACA data become available.

Early Impact of the Affordable Care Act Coverage Expansion on Safety-Net Hospital Inpatient Payer Mix and Market Shares.

OBJECTIVE: To examine the impact of the Affordable Care Act's coverage expansion on safety-net hospitals (SNHs). STUDY SETTING: Nine Medicaid expansion states. STUDY DESIGN: Differences-in-differences (DID) models compare payer-specific pre-post changes in inpatient stays of adults aged 19-64 years at SNHs and non-SNHs. DATA COLLECTION METHODS: 2013-2014 Healthcare Cost and Utilization Project State Inpatient Databases. PRINCIPAL FINDINGS: On average per quarter postexpansion, SNHs and non-SNHs experienced similar relative decreases in uninsured stays (DID = -2.2 percent, p = .916). Non-SNHs experienced a greater percentage increase in Medicaid stays than did SNHs (DID = 13.8 percent, p = .041). For SNHs, the average decrease in uninsured stays (-146) was similar to the increase in Medicaid stays (153); privately insured stays were stable. For non-SNHs, the decrease in uninsured (-63) plus privately insured (-33) stays was similar to the increase in Medicaid stays (105). SNHs and non-SNHs experienced a similar absolute increase in Medicaid, uninsured, and privately insured stays combined (DID = -16, p = .162). CONCLUSIONS: Postexpansion, non-SNHs experienced a greater percentage increase in Medicaid stays than did SNHs, which may reflect patients choosing non-SNHs over SNHs or a crowd-out of private insurance. More research is needed to understand these trends.

Returns to Emergency Department, Observation, or Inpatient Care Within 30 Days After Hospitalization in 4 States, 2009 and 2010 Versus 2013 and 2014.

BACKGROUND: Nationally, readmissions have declined for acute myocardial infarction (AMI) and heart failure (HF) and risen slightly for pneumonia, but less is known about returns to the hospital for observation stays and emergency department (ED) visits. OBJECTIVE: To describe trends in rates of 30-day, all-cause, unplanned returns to the hospital, including returns for observation stays and ED visits. DESIGN: By using Healthcare Cost and Utilization Project data, we compared 210,007 index hospitalizations in 2009 and 2010 with 212,833 matched hospitalizations in 2013 and 2014. SETTING: Two hundred and one hospitals in Georgia, Nebraska, South Carolina, and Tennessee. PATIENTS: Adults with private insurance, Medicaid, or no insurance and seniors with Medicare who were hospitalized for AMI, HF, and pneumonia. MEASUREMENTS: Thirty-day hospital return rates for inpatient, observation, and ED visits. RESULTS: Return rates remained stable among adults with private insurance (15.1% vs 15.3%; P = 0.45) and declined modestly among seniors with Medicare (25.3% vs 25.0%; P = 0.04). Increases in observation and ED visits coincided with declines in readmissions (8.9% vs 8.2% for private insurance and 18.3% vs 16.9% for Medicare, both P ≤ 0.001). Return rates rose among patients with Medicaid (31.0% vs 32.1%; P = 0.04) and the uninsured (18.8% vs 20.1%; P = 0.004). Readmissions remained stable (18.7% for Medicaid and 9.5% for uninsured patients, both P > 0.75) while observation and ED visits increased. CONCLUSIONS: Total returns to the hospital are stable or rising, likely because of growth in observation and ED visits. Hospitalists' efforts to improve the quality and value of hospital care should consider observation and ED care.

Racial Disparities in Sepsis-Related In-Hospital Mortality: Using a Broad Case Capture Method and Multivariate Controls for Clinical and Hospital Variables, 2004-2013.

OBJECTIVES: As sepsis hospitalizations have increased, in-hospital sepsis deaths have declined. However, reported rates may remain higher among racial/ethnic minorities. Most previous studies have adjusted primarily for age and sex. The effect of other patient and hospital characteristics on disparities in sepsis mortality is not yet well-known. Furthermore, coding practices in claims data may influence findings. The objective of this study was to use a broad method of capturing sepsis cases to estimate 2004-2013 trends in risk-adjusted in-hospital sepsis mortality rates by race/ethnicity to inform efforts to reduce disparities in sepsis deaths. DESIGN: Retrospective, repeated cross-sectional study. SETTING: Acute care hospitals in the Healthcare Cost and Utilization Project State Inpatient Databases for 18 states with consistent race/ethnicity reporting. PATIENTS: Patients diagnosed with septicemia, sepsis, organ dysfunction plus infection, severe sepsis, or septic shock. MEASUREMENTS AND MAIN RESULTS: In-hospital sepsis mortality rates adjusted for patient and hospital factors by race/ethnicity were calculated. From 2004 to 2013, sepsis hospitalizations for all racial/ethnic groups increased, and mortality rates decreased by 5-7% annually. Mortality rates adjusted for patient characteristics were higher for all minority groups than for white patients. After adjusting for hospital characteristics, sepsis mortality rates in 2013 were similar for white (92.0 per 1,000 sepsis hospitalizations), black (94.0), and Hispanic (93.5) patients but remained elevated for Asian/Pacific Islander (106.4) and "other" (104.7; p < 0.001) racial/ethnic patients. CONCLUSIONS: Our results indicate that hospital characteristics contribute to higher rates of sepsis mortality for blacks and Hispanics. These findings underscore the importance of ensuring that improved sepsis identification and management is implemented across all hospitals, especially those serving diverse populations.

The Shifting Landscape in Utilization of Inpatient, Observation, and Emergency Department Services Across Payers.

Recent policies by public and private payers have increased incentives to reduce hospital admissions. Using data from four states from the Agency for Healthcare Research and Quality Healthcare Cost and Utilization Project, this study compared the payer-specific population-based rates of adults using inpatient, observation, and emergency department (ED) services for 10 common medical conditions in 2009 and in 2013. Patients had an expected primary payer of private insurance, Medicare, Medicaid, or no insurance. Across all four payer populations, inpatient admissions declined, and care shifted toward treat-and-release observation stays and ED visits. The percentage of hospitalizations that began with an observation stay increased. Implications for quality of care and costs to patients warrant further examination. Journal of Hospital Medicine 2017;12:443-446.

Reassessing the Association between WIC and Birth Outcomes Using a Fetuses-at-Risk Approach.

Objectives Women with longer, healthier pregnancies have more time to enroll in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), biasing associations between WIC and birth outcomes. We examined the association between WIC and preterm birth (PTB), low birth weight (LBW), and perinatal death (PND) using a fetuses-at-risk approach to address this bias, termed gestational age bias. Methods We linked California Medi-Cal recipients with a singleton live birth or fetal death from the 2010 Birth Cohort to WIC participant data (n = 236,564). We implemented a fetuses-at-risk approach using survival analysis, which compared, in each week of gestation, women whose pregnancies reached the same length and who had the same opportunity to utilize WIC. In each gestational week, we assessed WIC enrollment and the number of food packages redeemed thus far and computed hazard ratios (HR) using survival models with time-varying exposures and effects. Results Adjusting for maternal socio-demographic and health characteristics, WIC enrollment was associated with a lower risk of PTB from week 29-36 (HR29 = 0.71; HR36 = 0.52); LBW from week 26-40 (HR26 = 0.77; HR40 = 0.64); and PND from week 29-43 (HR29 = 0.78; HR43 = 0.69) (p < 0.05). The number of food packages redeemed was associated with a lower risk of PTB from week 27-36 (HR27 = 0.90; HR36 = 0.84); LBW from week 25-42 (HR25 = 0.93; HR42 = 0.88); and PND from week 27-46 (HR27 = 0.94; HR46 = 0.91) (p < 0.05). Conclusions for Practice To our knowledge this is the first study to examine the association between WIC and birth outcomes using this approach. We found that beginning from about 29 weeks, WIC enrollment was associated with a reduced risk of PTB by 29-48 %, LBW by 23-36 %, and PND by 22-31 %.

Association Between the Opening of Retail Clinics and Low-Acuity Emergency Department Visits.

STUDY OBJECTIVE: We assess whether the opening of retail clinics near emergency departments (ED) is associated with decreased ED utilization for low-acuity conditions. METHODS: We used data from the Healthcare Cost and Utilization Project State Emergency Department Databases for 2,053 EDs in 23 states from 2007 to 2012. We used Poisson regression models to examine the association between retail clinic penetration and the rate of ED visits for 11 low-acuity conditions. Retail clinic "penetration" was measured as the percentage of the ED catchment area that overlapped with the 10-minute drive radius of a retail clinic. Rate ratios were calculated for a 10-percentage-point increase in retail clinic penetration per quarter. During the course of a year, this represents the effect of an increase in retail clinic penetration rate from 0% to 40%, which was approximately the average penetration rate observed in 2012. RESULTS: Among all patients, retail clinic penetration was not associated with a reduced rate of low-acuity ED visits (rate ratio=0.999; 95% confidence interval=0.997 to 1.000). Among patients with private insurance, there was a slight decrease in low-acuity ED visits (rate ratio=0.997; 95% confidence interval=0.994 to 0.999). For the average ED in a given quarter, this would equal a 0.3% reduction (95% confidence interval 0.1% to 0.6%) in low-acuity ED visits among the privately insured if retail clinic penetration rate increased by 10 percentage points per quarter. CONCLUSION: With increased patient demand resulting from the expansion of health insurance coverage, retail clinics may emerge as an important care location, but to date, they have not been associated with a meaningful reduction in low-acuity ED visits.