American Hospital Association Annual Survey Research Articles

When Agency Fails: An Analysis of the Association Between Hospital Agency Staffing and Quality Outcomes.

Staffing is critical to hospital quality, but recent years have seen hospitals grappling with severe shortages, forcing them to rely on contract or agency staff for urgent patient care needs. This shift in staffing mix has raised questions about its impact on quality. Consequently, this study investigated whether the increased use of agency staff has affected healthcare quality in hospitals. Given the limited recent research on this topic, practitioners remain uncertain about the effectiveness of their staffing strategies and their potential impact on quality. Drawing from agency theory, data were obtained from Definitive Healthcare which consolidates information from numerous public access databases pertaining to hospitals such as the American Hospital Association Annual Survey (hospital profile) and the Hospital Value-Based Purchasing Program (quality data). We conducted a cross-sectional study using a multivariable linear regression model (2021-2022) with appropriate organizational and market- level control variables. Quality was measured across eight variables while the independent variable of interest was agency labor cost ratio operationalized as the percentage of net patient revenue consumed by agency labor expense. Our results suggested that the employment of agency staff was significantly and negatively associated with six of eight quality measures tested, including the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) star rating, Hospital Compare rating, the hospital Total Performance Score (TPS), and three of the four sub-domains that comprise the TPS: clinical domain score, person and community engagement domain score, and the efficiency and cost reduction score. Our results indicated that the increased use of agency labor may have a significant negative influence on quality outcomes at the hospital level. Our findings support the premise that interventions that promote full-time staffing may be more supportive of the quality of care delivered as well as patients' perceptions of care.

Telemedicine critical care availability and outcomes among mechanically ventilated patients

PurposeTelemedicine Critical Care (TCC) improves adherence to evidence based protocols associated with improved mortality among patients receiving invasive mechanical ventilation (IMV). We sought to evaluate the relationship between hospital availability of TCC and outcomes among patients receiving IMV. Materials and methodsWe performed a cross-sectional study of 66,522 adults who received IMV for non-postoperative acute respiratory failure at 318 non-federal hospitals in New York, Massachusetts, Maryland, and Florida in 2018. Hospital-level TCC availability was ascertained from the 2018 American Hospital Association Annual Survey. The primary outcome was in-hospital mortality. Secondary outcomes included the composite of tracheostomy or reintubation and duration of IMV. We used two-level hierarchical multivariable regression models to investigate the association between TCC availability and outcomes. Results20,270 (30.5%) patients were admitted into 89 TCC-available hospitals. There was no difference between TCC and non-TCC-available hospitals in mortality (odds ratio [OR] 0.94, 99% confidence interval [CI] 0.84–1.05), composite of tracheostomy or reintubation (OR 0.95 [0.82–1.11], or duration of IMV (OR 0.95 [0.83–1.09]). There was no difference in outcomes among the subgroup of patients with acute respiratory distress syndrome. ConclusionsHospital TCC availability was not associated with improved outcomes among patients receiving IMV.

The Role of Hospital Characteristics in Clinical and Quality Outcomes for Gastrointestinal Bleeding in a National Cohort.

There is substantial variability in patient outcomes for gastrointestinal bleeding (GIB) across hospitals. This study aimed to identify hospital factors associated with GIB outcomes. This was a retrospective cohort study of Medicare fee-for-service beneficiaries hospitalized for GIB from 2016-2018. These data were merged with the American Hospital Association Annual Survey data to incorporate hospital characteristics. We used generalized linear mixed effects models to estimate the effect of hospital level characteristics on patient outcomes after adjusting for patient risk factors including anticoagulant and antiplatelet use, recent GIB, and comorbidities. The primary outcome was 30-day mortality and secondary outcomes included length of stay (LOS), and a composite outcome of 30-day readmission or mortality. Factors associated with improved GIB 30d mortality included large hospital size (defined as beds>400, OR: 0.93 (0.90, 0.97)), greater case volume (OR 0.97 (0.96, 0.98)) increased residents and nurse staffing (OR: 0.88 (0.83, 0.94)), and blood donor center designation (OR: 0.93 (0.88, 0.99)). Patients treated at a hospital with multiple advanced capabilities, such as availability of advanced endoscopy, advanced ICU capabilities (both a medical-surgical ICU and cardiac ICU), blood donor center, and liver transplant center, had a 22% reduction in 30-day mortality risk, compared to those hospitalized in a hospital with none of these services (OR: 0.78 (0.68, 0.91)). However, LOS increased with additional services. Patients hospitalized for GIB at hospitals with multiple advanced specialized capabilities have lower mortality but longer lengths of stay. Further research should examine the processes of care linked to these services that contribute to improved mortality in GIB.

Validation of a measure of hospital maternal level of care for the United States

BackgroundLack of a validated assessment of maternal risk-appropriate care for use in population data has prevented the existing literature from quantifying the benefit of maternal risk-appropriate care. The objective of this study was to develop a measure of hospital maternal levels of care based on the resources available at the hospital, using existing data available to researchers.MethodsThis was a secondary data analysis. The sample was abstracted from the American Hospital Association Annual Survey Database for 2018. Eligibility was limited to short-term acute general hospitals that reported providing maternity services as measured by hospital reporting of an obstetric service level, obstetric services, or birthing rooms. We aligned variables in the database with the ACOG criteria for each maternal level of care, then built models that used the variables to measure the maternal level of care. In each iteration, the distribution of hospitals was compared to the distribution in the CDC Levels of Care Assessment Tool Validation Pilot, assessing agreement with the Wilson Score for proportions for each level of care. Results were compared to hospital self-report in the database and measurement reported with another published method.ResultsThe sample included 2,351 hospitals. AHA variables were available to measure resources that align with ACOG Levels 1, 2, and 3. Overall, 1219 (51.9%) of hospitals reported resources aligned with Maternal Level One, 816 (34.7%) aligned with maternal level two, and 202 (8.6%) aligned with maternal level Three. This method overestimates the prevalence of hospitals with maternal level one compared to the CDC measurement of 36.1% (Mean 52.9%; 95% CI47.2%—58.7%), and likely includes hospitals that would not qualify as level one if all resources required by the ACOG guidelines could be assessed. This method underestimates the prevalence of hospitals with maternal critical care services (Level 3 or 4) compared to CDC measure of 12.1% (Mean 8.1%; 95%CI 6.2% – 10.0%) but is an improvement over hospital self-report (24.7%) and a prior published method (32.3%).ConclusionsThis method of measuring maternal level of care allows researchers to investigate the value of perinatal regionalization, risk-appropriate care, and hospital differences among the three levels of care. This study identified potential changes to the American Hospital Association Annual Survey that would improve identification of maternal levels of care for research.

Teaching and Safety-Net Hospital Penalization in the Hospital-Acquired Condition Reduction Program

The Hospital-Acquired Condition Reduction Program (HACRP) evaluates acute care hospitals on the occurrence of patient safety events and health care-associated infections. Since its implementation, several studies have raised concerns about the overpenalization of teaching and safety-net hospitals, and although several changes in the program's methodology have been applied in the last few years, whether these changes reversed the overpenalization of teaching and safety-net hospitals is unknown. To determine hospital characteristics associated with HACRP penalization and penalization reversal. This retrospective cross-sectional study assessed data from 3117 acute care hospitals participating in the HACRP. The HACRP penalization and hospital characteristics were obtained from Hospital Compare (2020 and 2021), the Inpatient Prospective Payment System impact file (2020), and the American Hospital Association annual survey (2018). Hospital characteristics, including safety-net status and teaching intensity (no teaching and very minor, minor, major, and very major teaching levels). The primary outcome was HACRP penalization (ie, hospitals that fell within the worst quartile of the program's performance). Multivariable models initially included all covariates, and then backward stepwise variable selection was used. Of 3117 hospitals that participated in HACRP in 2020, 779 (25.0%) were safety-net hospitals and 1090 (35.0%) were teaching institutions. In total, 771 hospitals (24.7%) were penalized. The HACRP penalization was associated with safety-net status (odds ratio [OR], 1.41 [95% CI, 1.16-1.71]) and very major teaching intensity (OR, 1.94 [95% CI, 1.15-3.28]). In addition, non-federal government hospitals were more likely to be penalized than for-profit hospitals (OR, 1.62 [95% CI, 1.23-2.14]), as were level I trauma centers (OR, 2.05 [95% CI, 1.43-2.96]) and hospitals located in the New England region (OR, 1.65 [95% CI, 1.12-2.43]). Safety-net hospitals with major teaching levels were twice as likely to be penalized as non-safety-net nonteaching hospitals (OR, 2.15 [95% CI, 1.14-4.03]). Furthermore, safety-net hospitals penalized in 2020 were less likely (OR, 0.64 [95% CI, 0.43-0.96]) to revert their HACRP penalization status in 2021. Findings from this cross-sectional study indicated that teaching and safety-net hospital status continued to be associated with overpenalization in the HACRP despite recent changes in its methodology. Most of these hospitals were also less likely to revert their penalization status. A reevaluation of the program methodology is needed to avoid depleting resources of hospitals caring for underserved populations.

Hospital Capabilities Associated With Behavioral Health Integration Within Emergency Departments.

To identify hospital capabilities associated with behavioral health (BH) processes in emergency departments (EDs). Six hundred two hospital responses to the 2017/2018 National Survey of Healthcare Organizations and Systems were linked to 2017 American Hospital Association Annual Survey data. Separate multivariable regressions estimated how hospital capabilities (the use of quality improvement methods, approaches to disseminate best patient-care practices, barriers to using care delivery innovations, and inpatient beds for psychiatric or substance use) were associated with each of 4 ED-based BH processes: mental health and substance use disorder screening, team-based approaches to BH, telepsychiatry, and direct referrals to community-based BH clinicians. Models controlled for hospital structural characteristics and area-level socioeconomic factors. Most hospitals screened for BH conditions and provided direct referrals to community-based BH clinicians. Approximately half of the hospitals used a team approach to BH. A minority had implemented telepsychiatry. Each additional process used to disseminate best patient-care practices was associated with more screening for BH conditions (an increase of 4.07 points on the screening index, P <0.01) and greater likelihood of using a team approach to BH [4.41 percentage point ( P <0.01) increase]. Hospitals reporting more barriers to the use of care delivery innovations reported less screening and use of a team approach [a decrease of 0.15 points on the screening index ( P <0.01) and 0.28 percentage points reduction in likelihood of team approach use ( P <0.001) for 1-point increase in the barrier index]. Research and interventions focused on removing innovation barriers or adding processes to disseminate best practices offer a path to accelerate BH integration in hospital EDs.

Racial and ethnic disparities in emergency department transfers to public hospitals.

To examine racial/ethnic differences in emergency department (ED) transfers to public hospitals and factors explaining these differences. ED and inpatient data from the Healthcare Cost and Utilization Project for Florida (2010-2019); American Hospital Association Annual Survey (2009-2018). Logistic regression examined race/ethnicity and payer on the likelihood of transfer to a public hospital among transferred ED patients. The base model was controlled for patient and hospital characteristics and year fixed effects. Models II and III added urbanicity and hospital referral region (HRR), respectively. Model IV used hospital fixed effects, which compares patients within the same hospital. Models V and VI stratified Model IV by payer and condition, respectively. Conditions were classified as emergency care sensitive conditions (ECSCs), where transfer is protocolized, and non-ECSCs. We reported marginal effects at the means. We examined 1,265,588 adult ED patients transferred from 187 hospitals. Black patients were more likely to be transferred to public hospitals compared with White patients in all models except ECSC patients within the same initial hospital (except trauma). Black patients were 0.5-1.3 percentage points (pp) more likely to be transferred to public hospitals than White patients in the same hospital with the same payer. In the base model, Hispanic patients were more likely to be transferred to public hospitals compared with White patients, but this difference reversed after controlling for HRR. Hispanic patients were - 0.6 pp to -1.2 pp less likely to be transferred to public hospitals than White patients in the same hospital with the same payer. Large population-level differences in whether ED patients of different races/ethnicities were transferred to public hospitals were largely explained by hospital market and the initial hospital, suggesting that they may play a larger role in explaining differences in transfer to public hospitals, compared with other external factors.

The Revival of US Hospital Care, 2004-2019.

Between 2004 and 2019, the US hospital industry reversed the 21-year decline in its share of national health spending. To measure and explain changes in hospital utilization, cost, charges, and inpatient case mix. Principal sources were the American Hospital Association annual survey, the National Inpatient Sample, and the Healthcare Cost Reporting Information System. The study included all US community hospitals (n=5141 in 2019). We used factor decomposition to separate the impacts of population, utilization, unit cost, and charge markups on the growth in cost and charges for inpatient and outpatient care nationwide and for each state. For unit cost, we separated the impacts of input price inflation and treatment intensity. To measure the inpatient case mix, we applied an all-patient diagnosis-related groups algorithm. Between 2004 and 2019, charges more than tripled to $4.11 trillion. The cost more than doubled to $911 billion. For inpatient care, discharges fell 5%, discharges per person fell 15%, cost per discharge increased 88%, and charge markups rose 43%. For outpatient care, visits rose 36%, visits per person rose 21%, cost per visit rose 119%, and charge markups rose 52%. Treatment intensity increased by 33% per discharge and 55% per visit. Nationwide, the inpatient case mix increased by 34%, reflecting sicker patients and better clinical documentation. We quantified 3 important trends: rapid growth in outpatient visits, increased treatment intensity, and sustained increases in markups. Increased treatment intensity was the largest factor behind $491 billion in hospital cost growth between 2004 and 2019.

Collaborating for COVID-19: Hospital Health Information Exchange and Public Health Partnership.

Background: The coronavirus disease (COVID-19) pandemic highlighted the need for effective communication and information sharing among health care organizations and public health systems (PHSs). Health information exchange (HIE) plays a vital role in improving quality control and efficiency in hospital settings, particularly in underserved areas. Objective: This study aimed to investigate the variation of HIE availability among hospitals based on their collaboration with the PHS and affiliation with Accountable Care Organizations (ACOs) in 2020, as well as variation by community social determinants of health. Methods: The primary data set used for this study comprised the linked data set of the 2020 American Hospital Association (AHA) Annual Survey and the AHA Information Technology Supplement. The measures used included the hospital's participation in HIE networks, availability of data exchange, and HIE measures during the COVID-19 pandemic, including whether hospitals effectively received electronically transmitted information from outside providers for COVID-19 treatment. Results: The sample size of hospitals ranged from 1,316 to 1,436, depending on different outcomes related to HIE questions. Of the hospitals surveyed, ∼67% reported public health collaboration and ACO affiliation, while 7% reported neither. Hospitals without public health collaboration or ACO affiliation were more likely to be located in underserved areas. Compared with hospitals without public health collaboration or ACO affiliation, hospitals with both were 9% more likely to report the availability of electronically transmitted clinical information from outside providers and to participate in local and national HIE networks. Furthermore, these hospitals were 30% (marginal effect [ME] = 0.30, p < 0.001) more likely to report effective receipt of information from outside providers for COVID-19 treatment and 12% (ME = 0.12, p = 0.02) more likely to always/often receive clinical information for COVID-19 treatment electronically. Conclusions: Hospital collaboration with the PHS and ACO affiliation are associated with greater availability of electronic health data, particularly during the COVID-19 pandemic.

Preventable Emergency Department Visits of Patients with Alzheimer's Disease and Related Dementias During the COVID-19 Pandemic by Hospital-Based Health Information Exchange.

Background: This study examined the relationship between hospital-based electronic health information exchange (HIE) and the likelihood of having a preventable emergency department (ED) visit during the COVID-19 pandemic for US patients with Alzheimer's Disease and Related Dementias (ADRD). Methods: We used multi-level data from six states. The linked data sets included the 2020 State Emergency Department Databases (SEDD), the Area Health Resources File, the American Hospital Association (AHA) Annual Survey, and the AHA Information Technology Supplement to study 85,261 hospital discharges from patients with ADRD. Logistic regression models were produced to determine the odds of having a preventable ED visit among patients with ADRD. Results: Our final sample included 85,261 hospital discharges from patients with ADRD. Patients treated in hospitals that received more types of clinical information for treating patients with COVID-19 from outside providers (OR = 0.961, p < .05) and/or hospitals that received COVID-19 test results from more outside entities were significantly less likely to encounter preventable EDs (OR = 0.964, p < .05), especially among patients who also had multiple chronic conditions (MCC) (OR = 0.89, p = .001; OR = 0.856, p < .001). Conclusion: Our results suggest that electronic HIE may be useful for reducing preventable ED visits during the COVID-19 pandemic for people with ADRD and ADRD alongside MCC.

Rural-urban disparities in the availability of hospital-based screening, medications for opioid use disorder, and addiction consult services

IntroductionHospitals are an ideal setting to stage opioid-related interventions with patients who are hospitalized due to overdose or other substance use–related complications. Transitional opioid programs—which initiate care and provide linkages upon discharge, such as screening, initiation of medications for opioid use disorder, and addiction consult services—have become the gold standard, but implementation has been uneven. The purpose of this study was to assess disparities in the availability of hospital-based transitional opioid programs, across rural and urban hospital settings in the United States. MethodsUsing hospital administrative data paired with county-level demographic data, we conducted bivariate and regression analyses to assess rural-urban differences in the availability of transitional opioid services including screening, addiction consult services, and MOUD in U.S general medical centers, controlling for hospital- and community-level factors. Our sample included 2846 general medical hospitals that completed the 2021 American Hospital Association (AHA) Annual Survey of Hospitals. Our primary outcomes were five self-reported measures: whether the hospital provided screening in the ED; provided screening in the inpatient setting; whether the hospital provided addiction consult services in the ED; provided addiction consult services in the inpatient setting; and whether the hospital provided medications for opioid use disorder. ResultsRural hospitals did not have lower odds of screening for OUD or other SUDs than urban hospitals, but both micropolitan rural counties and noncore rural counties had significantly lower odds of having addiction consult services in either the ED (OR: 0.74, 95 % CI: 0.58, 0.95; OR: 0.68, 95 % CI: 0.50, 0.91) or inpatient setting (OR: 0.76, 95 % CI: 0.59, 0.97; OR: 0.68, 95 % CI: 0.50, 0.93), respectively, or of offering MOUD (OR: 0.69, 95 % CI: 0.52, 0.90; OR: 0.52, 95 % CI: 0.37, 0.74). ConclusionsOur study suggests that evidence-based interventions, such as medications for opioid use disorder and addiction consult services, are less often available in rural hospitals, which may contribute to rural-urban disparities in health outcomes secondary to OUD. A priority for population health improvement should be developing implementation strategies to support rural hospital adoption of transitional opioid programs.

US HOSPITAL INFRASTRUCTURE: ARE ALZHEIMER’S CENTERS PREPARED TO ADDRESS DEMENTIA NATIONWIDE?

Abstract Evidence on the U.S. hospital infrastructure to address dementia is scant, obscuring health improvement efforts. This study investigates the availability of Alzheimer’s Centers (ACs) in U.S. hospitals. Data come from the: (1) 2010 – 2021 American Hospital Association Annual Survey; (2) 2020 Area Health Resource File; and (3) 2020 U.S. Census. Utilizing data from U.S. general hospitals (n = 3,251), we employed multivariable logistic regression to examine hospital (size, ownership, teaching status), county (metropolitan, poverty, racial/ethnic county composition), and regional (U.S. region) predictors of AC availability (Yes/No). ACs in U.S. hospitals increased from 4.5% in 2010 to 5.9% in 2020. Large hospitals (&amp;gt;399 beds) had approximately 14 times higher odds of having an AC than small hospitals (&amp;lt; 50 beds; OR = 14.0; 95% CI = 6.44 – 30.46). Counties with a higher proportion of Latinx residents, relative to non-Latinx Whites, had lower odds of having an AC (OR = 0.05; 95% CI = 0.01 – 0.41). Northeastern (OR = 1.92; 95% CI = 1.15 – 3.22) and Midwestern (OR = 2.12; 95% CI = 1.34 – 3.37) hospitals had higher odds of having an AC than Southern hospitals. Findings extend our understanding of U.S. hospital capacity to address dementia. Although ACs have increased over time, hospitals in non-metropolitan and Southern counties, and those in counties with a high proportion of Latinx adults are less likely to have an AC. To address dementia needs fully, investment in a national infrastructure is critical.

Is state trauma funding associated with mortality among injured hospitalized patients?

BackgroundWe sought to quantify the association between state trauma funding and (1) in-hospital mortality and (2) transfers of injured patients. MethodsWe conducted an observational cross-sectional study of states with publicly available trauma funding data. We analyzed in-hospital mortality using linked data from the Nationwide Inpatient Sample (NIS), American Hospital Association (AHA) Annual Survey, and these State Department of Public Health trauma funding data. ResultsA total of 594,797 injured adult patients were admitted to acute care hospitals in 17 states. Patients in states with >$1.00 per capita state trauma funding had 0.82 (95 ​% CI: 0.78–0.85, p ​< ​0.001) decreased adjusted odds of in-hospital mortality compared to patients in states with less than $1.00 per capita state trauma funding. ConclusionsIncreased state trauma funding is associated with decreased adjusted in-hospital mortality.

Improving Value in Colorectal Cancer Care: An Economic Analysis of Enhanced Recovery Protocols at a Community Hospital.

Enhanced recovery protocols (ERPs) have been shown to improve the outcomes of gastrointestinal cancer care, leading to reduced morbidity of gastrointestinal treatment and reduced delays in systemic therapy. ERP implementation has also previously shown a reduction in length of stay (LOS) without changing the readmission rate; however, the economic cost associated with these measures has not yet been quantified. The aim of this study was to evaluate the economic costs of ERP implementation for colorectal cancer at a community hospital. The Diagnostic Related Group (DRG) codes were used to assess costs associated with the hospitalizations of cases in the ERP versus non-ERP groups. The American Hospital Association (AHA) Annual Survey from 1999 to 2015 was used to provide the expenses per day for inpatient hospitalization in the United States. Postoperative LOS, average healthcare costs, and postoperative complications between ERP-protocol and non-ERP protocol groups were analyzed using analysis of variance (ANOVA) and independent t-tests. The AHA survey estimated that $2,265 was incurred per day for non-profit hospitals in Florida and $2,346 was incurred per day for the United States. For all DRG codes, the ERP-participating group was associated with a shorter LOS and reduced health care costs. LOS-associated cost was compared between ERP and non-ERP groups: for DRG 329, the total savings was $162,118.8 (n = 12 non-ERP versus n = 8 ERP, P = 4.39 × 10-18); for DRG 330, $314,552.64 (n = 36 non-ERP versus n = 24 ERP, P = 2.72 × 10-22); and for DRG 331, $89,302.73 (n = 11 non-ERP versus n = 23 for ERP, P = 4.19 × 10-20). The implementation of an ERP protocol for colorectal cancer was associated with significantly reduced costs in a community hospital.

Rate of Emergency Lower Extremity Amputations in the United States Among Medicare Beneficiaries.

To determine the rate of emergency versus elective lower extremity amputations in the United States. Lower extremity amputation is a common endpoint for patients with poorly controlled diabetes and multilevel peripheral vascular disease. Although the procedure is ideally performed electively, patients with limited access may present later and require an emergency operation. To what extent rates of emergency amputation for lower extremities vary across the United States is unknown. Evaluation of Medicare beneficiaries who underwent lower extremity amputation between 2015 and 2020. The rate was determined for each zip code and placed into rank order from lowest to highest rate. We merged each beneficiary's place of residence and location of care with the American Hospital Association Annual Survey using Google Maps Application Programming Interface to determine the travel distance for patients to undergo their procedure. Of 233,084 patients, 66.3% (154,597) were men, 69.8% (162,786) were White. The average age (SD) was 74 years (8). There was wide variation in rates of emergency lower extremity amputation. The lowest quintile of zip codes demonstrated an emergency amputation rate of 3.7%, whereas the highest quintile demonstrated 90%. The median travel distance in the lowest emergency surgery rate quintile was 34.6 miles compared with 10.5 miles in the highest quintile of emergency surgery ( P < 0.001). There is wide variation in the rate of emergency lower extremity amputations among Medicare beneficiaries, suggesting variable access to essential vascular care. Travel distance and rate of amputation have an inverse relationship, suggesting that barriers other than travel distance are playing a role.

Differential impact of hospital and community factors on breadth and depth of hospital population health partnerships.

The aim was to identify hospital and county characteristics associated with variation in breadth and depth of hospital partnerships with a broad range of organizations to improve population health. The American Hospital Association Annual Survey provided data on hospital partnerships to improve population health for the years 2017-2019. The study adopts the dimensional publicness theory and social capital framework to examine hospital and county characteristics that facilitate hospital population health partnerships. The two dependent variables were number of local community organizations that hospitals partner with (breadth) and level of engagement with the partners (depth) to improve population health. The independent variables include three dimensions of publicness: Regulative, Normative and Cultural-cognitive measured by various hospital factors and presence of social capital present at county level. Covariates in the multivariate analysis included hospital factors such as bed-size and system membership. We used hierarchical linear regression models to assess various hospital and county factors associated with breadth and depth of hospital-community partnerships, adjusting for covariates. Nonprofit and public hospitals provided a greater breadth (coefficient, 1.61; SE, 0.11; p < 0.001 and coefficient, 0.95; SE, 0.14; p < 0.001) and depth (coefficient, 0.26, SE, 0.04; p < 0.001 & coefficient, 0.13; SE, 0.05; p < 0.05) of partnerships than their for-profit counterparts, partially supporting regulative dimension of publicness. At a county level, we found community social capital positively associated with breadth of partnerships (coefficient, 0.13; SE, 0.08; p < 0.001). An environment that promotes collaboration between hospitals and organizations to improve population health may impact the health of the community by identifying health needs of the community, targeting social determinants of health, or by addressing patient social needs. However, findings suggest that publicness dimensions at an organizational level, which involves a culture of public value, maybe more important than county factors to achieve community building through partnerships.

Social and Medical Care Integration Practices Among Children's Hospitals.

In response to evidence linking social risk factors and adverse health outcomes, new incentives have emerged for hospitals to screen for adverse social determinants of health (SDOH). However, little information is available about the current state of social risk-related care practices among children's hospitals. To address outstanding knowledge gaps, we sought to describe social risk-related care practices among a national sample of children's hospitals. We analyzed responses to the 2020 American Hospital Association Annual Survey. Among children's hospitals, we calculated the prevalence of screening for social needs, strategies to address social risks/needs, partnerships with community-based organizations to address social risks/needs at the individual and community level, and rates of impact assessments of how social risk-related interventions affect outcomes. We also used χ2 tests to compare results by hospital characteristics. We weighted results to adjust for nonresponse. The sample included 82 children's hospitals. A total of 79.6% screened for and 96.0% had strategies to address at least 1 social risk factor, although rates varied by SDOH domain. Children's hospitals more commonly partnered with community-based organizations to address patient-level social risks than to participate in community-level initiatives. A total of 39.2% of hospitals assessed SDOH intervention effectiveness. Differences in social risk-related care practices commonly varied by hospital ownership and Medicaid population but not by region. We found wide variability in social risk-related care practices among children's hospitals based on the risk domain and hospital characteristics. Findings can be used to monitor whether social risk-related care practices change in the setting of new incentives.

Alzheimer's Centers in US Hospitals: Enough to Adequately Address Dementia Care Nationwide?

To investigate the availability of Alzheimer's Centers (ACs) in US hospitals. Utilizing the American Hospital Association Annual Survey, Area Health Resource File, and US Census (n = 3251), we employed multivariable logistic regression to examine hospital, county, and regional predictors of AC availability. Large hospitals (>399 beds) had approximately 14 times higher odds of having an AC than small hospitals (<50 beds; OR = 14.0; 95% CI = 6.44 - 30.46). Counties with a higher proportion of Latino residents, relative to non-Latino Whites, had lower odds of having an AC (OR = .05; 95% CI = .01 - .41). Northeastern (OR = 1.92; 95% CI = 1.15 - 3.22) and Midwestern (OR = 2.12; 95% CI = 1.34 - 3.37) hospitals had higher odds of having an AC than Southern hospitals. To address dementia needs and disparities, investment in a national infrastructure is critical.

Association between readmission care fragmentation and outcomes after interventions for peripheral arterial disease

ObjectiveLower extremity revascularization (LER) for peripheral artery disease is complicated by the frequent need for readmission. However, it is unclear if readmission to a nonindex LER facility (ie, a facility different from the one where the LER was performed) compared with the index LER facility is associated with worse outcomes. MethodsThis was a national cohort study of older adults who underwent open, endovascular, or hybrid LER for peripheral artery disease (January 1, 2010, to December 31, 2018) in the Vascular Quality Initiative who were readmitted within 90 days of their vascular procedure. This dataset was linked to Medicare claims and the American Hospital Association Annual Survey. The primary outcome was 90-day mortality and the secondary outcome was major amputation at 90 days after LER. The primary exposure was the location of the first readmission after LER (categorized as occurring at the index LER facility vs a nonindex LER facility). Generalized estimating equations logistic regression models were used to assess the association between readmission location and 90-day mortality and amputation. ResultsAmong 42,429 patients who underwent LER, 33.0% were readmitted within 90 days. Of those who were readmitted, 27.3% were readmitted to a nonindex LER facility, and 42.2% of all readmissions were associated with procedure-related complications. Compared with patients readmitted to the index LER facility, those readmitted to a nonindex facility had a lower proportion of procedure-related reasons for readmission (21.5% vs 50.1%; P < .001). Most of the patients readmitted to a nonindex LER facility lived further than 31 miles from the index LER facility (39.2% vs 19.6%; P < .001) and were readmitted to a facility with a total bed size of <250 (60.1% vs 11.9%; P < .001). Readmission to a nonindex LER facility was not associated with 90-day mortality or 90-day amputation. However, readmission for a procedure-related complication was associated with major amputation (90-day amputation: adjusted odds ratio, 3.33; 95% confidence interval, 2.89-3.82). ConclusionsReadmission after LER for a procedure-related complication is associated with subsequent amputation. This finding suggests that quality improvement efforts should focus on understanding various types of procedure-related failure after LER and its role in limb salvage.

Substance Use Disorder Program Availability in Safety-Net and Non–Safety-Net Hospitals in the US

Safety-net hospitals (SNHs) are ideal sites to deliver addiction treatment to patients with substance use disorders (SUDs), but the availability of these services within SNHs nationwide remains unknown. To examine differences in the delivery of different SUD programs in SNHs vs non-SNHs across the US and to determine whether these differences are increased in certain types of SNHs depending on ownership. This cross-sectional analysis used data from the 2021 American Hospital Association Annual Survey of Hospitals to examine the associations of safety-net status and ownership with the availability of SUD services at acute care hospitals in the US. Data analysis was performed from January to March 2022. This study used 2 survey questions from the American Hospital Association survey to determine the delivery of 5 hospital-based SUD services: screening, consultation, inpatient treatment services, outpatient treatment services, and medications for opioid use disorder (MOUD). A total of 2846 hospitals were included: 409 were SNHs and 2437 were non-SNHs. The lowest proportion of hospitals reported offering inpatient treatment services (791 hospitals [27%]), followed by MOUD (1055 hospitals [37%]), and outpatient treatment services (1087 hospitals [38%]). The majority of hospitals reported offering consultation (1704 hospitals [60%]) and screening (2240 hospitals [79%]). In multivariable models, SNHs were significantly less likely to offer SUD services across all 5 categories of services (screening odds ratio [OR], 0.62 [95% CI, 0.48-0.76]; consultation OR, 0.62 [95% CI, 0.47-0.83]; inpatient services OR, 0.73 [95% CI, 0.55-0.97]; outpatient services OR, 0.76 [95% CI, 0.59-0.99]; MOUD OR, 0.6 [95% CI, 0.46-0.78]). With the exception of MOUD, public or for-profit SNHs did not differ significantly from their non-SNH counterparts. However, nonprofit SNHs were significantly less likely to offer all 5 SUD services compared with their non-SNH counterparts (screening OR, 0.52 [95% CI, 0.41-0.66]; consultation OR, 0.56 [95% CI, 0.44-0.73]; inpatient services OR, 0.45 [95% CI, 0.33-0.61]; outpatient services OR, 0.58 [95% CI, 0.44-0.76]; MOUD OR, 0.61 [95% CI, 0.46-0.79]). In this cross-sectional study of SNHs and non-SNHs, SNHs had significantly lower odds of offering the full range of SUD services. These findings add to a growing body of research suggesting that SNHs may face additional barriers to offering SUD programs. Further research is needed to understand these barriers and to identify strategies that support the adoption of evidence-based SUD programs in SNH settings.