American Hospital Association Research Articles

Availability of hospital-based cancer services before and after rural hospital closure, 2008-2017.

Rural populations have less access to cancer care services and experience higher cancer mortality rates than their urban counterparts, which may be exacerbated by hospital closures. Our objective was to examine the impact of hospital closures on access to cancer-relevant hospital services across hospital service areas (HSAs). We used American Hospital Association survey data from 2008 to 2017 to examine the change in access to cancer-related screening and treatment services across rural HSAs that sustained hospitals over time, experienced any closures, or had all hospitals close. We performed a longitudinal analysis to assess the association between hospital closure occurrence and maintenance or loss of cancer-related service lines accounting for hospital and HSA-level characteristics. Maps were also developed to display changes in the availability of services across HSAs. Of the 2,014 rural HSAs, 3.8% experienced at least 1 hospital closure during the study period, most occurring in the South. Among HSAs that experienced hospital closure, the loss of surgery services lines was most common, while hospital closures did not affect the availability of overall oncology and radiation services. Screening services either were stable (mammography) or increased (endoscopy) in areas with no closures. Rural areas persistently experience less access to cancer treatment services, which has been exacerbated by hospital closures. Lack of Medicaid expansion in many Southern states and other policy impacts on hospital financial viability may play a role in this. Future research should explore the impact of closures on cancer treatment receipt and outcomes.

How to calculate the life cycle of high-risk medical devices for patient safety.

In this study, we analyzed Korean and foreign systems, focusing on high-risk medical devices that urgently need to be managed, and we present an life cycle calculation method for determining replacement time. A literature review was conducted to confirm the regulations of the medical device management system and life cycle by country, and a case analysis was performed to verify the replacement evaluation criteria of actual medical institutions. In addition, durability data from the Public Procurement Service, American Hospital Association, and Samsung Medical Center were used to calculate the life cycle of high-risk medical devices. The analysis showed that in the case of Korean and foreign medical device regulatory agencies, there were no specific life cycle regulations for high-risk medical devices. In addition, the important items in the medical device replacement evaluation were found to be the year of introduction, repair cost, component discontinuation, and several failures. On calculating the life cycle of high-risk medical devices revealed that the replacement time is 13 years for anesthesia machines, 14 years for defibrillators, 16 years for heart-lung machines, and 13 years for ventilators. To introduce a uniform medical device replacement standard and life cycle calculation method, the government will need to reorganize the medical device replacement laws and systems. In addition, in the case of medical institutions, it is necessary to secure patient safety by using expert groups to prepare specific life cycle standards that consider the characteristics of medical devices.

Enriching the American Heart Association COVID-19 Cardiovascular Disease Registry Through Linkage With External Data Sources: Rationale and Design.

Background The AHA Registry (American Heart Association COVID-19 Cardiovascular Disease Registry) captures detailed information on hospitalized patients with COVID-19. The registry, however, does not capture information on social determinants of health or long-term outcomes. Here we describe the linkage of the AHA Registry with external data sources, including fee-for-service (FFS) Medicare claims, to fill these gaps and assess the representativeness of linked registry patients to the broader Medicare FFS population hospitalized with COVID-19. Methods and Results We linked AHA Registry records of adults ≥65 years from March 2020 to September 2021 with Medicare FFS claims using a deterministic linkage algorithm and with the American Hospital Association Annual Survey, Rural Urban Commuting Area codes, and the Social Vulnerability Index using hospital and geographic identifiers. We compared linked individuals with unlinked FFS beneficiaries hospitalized with COVID-19 to assess the representativeness of the AHA Registry. A total of 10 010 (47.0%) records in the AHA Registry were successfully linked to FFS Medicare claims. Linked and unlinked FFS beneficiaries were similar with respect to mean age (78.1 versus 77.9, absolute standardized difference [ASD] 0.03); female sex (48.3% versus 50.2%, ASD 0.04); Black race (15.1% versus 12.0%, ASD 0.09); dual-eligibility status (26.1% versus 23.2%, ASD 0.07); and comorbidity burden. Linked patients were more likely to live in the northeastern United States (35.7% versus 18.2%, ASD 0.40) and urban/metropolitan areas (83.9% versus 76.8%, ASD 0.18). There were also differences in hospital-level characteristics between cohorts. However, in-hospital outcomes were similar (mortality, 23.3% versus 20.1%, ASD 0.08; home discharge, 45.5% versus 50.7%, ASD 0.10; skilled nursing facility discharge, 24.4% versus 22.2%, ASD 0.05). Conclusions Linkage of the AHA Registry with external data sources such as Medicare FFS claims creates a unique and generalizable resource to evaluate long-term health outcomes after COVID-19 hospitalization.

Nurse-Reported Staffing Guidelines and Exclusive Breast Milk Feeding.

Nursing care is essential to overall quality of healthcare experienced by patients and families-especially during childbearing. However, evidence regarding quality of nursing care during labor and birth is lacking, and established nurse-sensitive outcome indicators have limited applicability to maternity care. Nurse-sensitive outcomes need to be established for maternity care, and prior research suggests that the initiation of human milk feeding during childbirth hospitalization is a potentially nurse-sensitive outcome. The aim of this study was to determine the relationship between nurse-reported staffing, missed nursing care during labor and birth, and exclusive breast milk feeding during childbirth hospitalization as a nurse-sensitive outcome. 2018 Joint Commission PC-05 Exclusive Breast Milk Feeding rates were linked to survey data from labor nurses who worked in a selected sample of hospitals with both PC-05 data and valid 2018 American Hospital Association Annual Survey data. Nurse-reported staffing was measured as the perceived compliance with Association of Women's Health, Obstetric and Neonatal Nurses staffing guidelines by the labor and delivery unit. Data from the nurse survey were aggregated to the hospital level. Bivariate linear regression was used to determine associations between nurse and hospital characteristics and exclusive breast milk feeding rates. Generalized structural equation modeling was used to model relationships between nurse-reported staffing, nurse-reported missed care, and exclusive breast milk feeding at the hospital level. The sample included 184 hospitals in 29 states and 2,691 labor nurses who worked day, night, or evening shifts. Bivariate analyses demonstrated a positive association between nurse-reported staffing and exclusive breast milk feeding and a negative association between missed nursing care and exclusive breast milk feeding. In structural equation models controlling for covariates, missed skin-to-skin mother-baby care and missed breastfeeding within 1 hour of birth mediated the relationship between nurse-reported staffing and exclusive breast milk feeding rates. This study provides evidence that hospitals' nurse-reported compliance with Association of Women's Health, Obstetric and Neonatal Nurses staffing guidelines predicts hospital-exclusive breast milk feeding rates and that the rates are a nurse-sensitive outcome.

Association of Measured Quality and Future Financial Performance Among Hospitals Performing Cardiac Surgery.

For decades, hospitals performing cardiac surgery have carried the cost of implementing quality improvement activities and reporting quality outcomes. However, the financial return of such investments is unclear, which weakens the incentive for hospitals to invest in quality improvement activities. This study explored the relationship between a hospital's measured quality and its financial performance. Using data from the American Hospital Association and Hospital Compare from 2014 to 2018, we performed an observational study of hospitals performing cardiac surgery. We used mixed-effects regression models with fixed-year effects and random intercepts to explore associations between measured quality and hospital financial performance. Our dependent variables were margins (profit divided by revenue) and financial distress; our independent variables included Patient Safety Indicator 90 (PSI-90) and hospital characteristics. Our sample included 4,927 hospital-years from 1,209 unique hospitals. Hospitals in the worst-performing PSI-90 score quartile experienced a lower operating margin (-1.26%, 95% CI [-2.10 to -0.41], p = .004), a lower total margin (-0.92%, 95% CI [-1.66 to -0.17], p = .016), and an increased odds of financial distress in the next year (OR: 2.12, 95% CI [1.36-3.30], p = .001) when compared with the best-performing hospitals. Our exploration into financial distress provides managers with a better understanding of the relationship between a hospital's measured quality and its financial position. In reflecting on our findings, hospital leaders may consider viewing patient safety as a modifiable factor that can improve their organization's overall financial health. Our findings suggest that excellent safety performance may be both financially and clinically beneficial to hospitals.

Correlates of Price Transparency for Healthcare Services in United States Hospitals.

PurposeThe purpose of this study is to investigate demographic and hospital characteristics that predict hospital price transparency in the United States.MethodsWe identified 6214 hospitals and extracted characteristics of each using the American Hospital Association Annual Survey, as well as cash prices for a representative selection of commonly performed procedures and visits from the Turquoise Health dataset. Descriptive statistics were used to determine compliance rates and price variation, and a Poisson regression model was used to calculate incidence rate ratios (IRR) and 95% confidence intervals (CI) for predictors of price transparency.ResultsPrice transparency compliance ranged from 13% to 49% of hospitals, and across-center ratios ranged from 244.8 to 4789.0. Number of hospital beds was marginally associated with price transparency for more services (IRR: 1.01 [95% CI: 1.01–1.02]); in contrast, location in the Southern (IRR: 0.91 [95% CI: 0.87–0.96]) or Western (IRR: 0.94 [95% CI: 0.90–0.99]) regions of the US was associated with transparency for fewer services.ConclusionSmaller hospitals as well as those located in the South and West regions were less likely to be compliant with the CMS mandate for price transparency for hospital standard charges. Additionally, the poor usability of price transparency directories on hospital websites limits information access and undermines transparency efforts.

Nursing Resources Linked to Postsurgical Outcomes for Patients With Opioid Use Disorder: An Observational Study.

Objectives:To determine whether better nursing resources (ie, nurse education, staffing, work environment) are each associated with improved postsurgical outcomes for patients with opioid use disorder (OUD).Background:Hospitalized patients with OUD are at increased risk of adverse outcomes. Evidence suggests that adverse postsurgical outcomes may be mitigated in hospitals with better nursing resources, but this has not been evaluated among surgical patients with OUD.Methods:Cross-sectional (2015–2016) data were utilized from the RN4CAST-US survey of hospital nurses, the American Hospital Association Annual Survey of hospitals, and state patient hospital discharge summaries. Multivariate logistic and zero-truncated negative binomial regression models were employed to examine the association between nursing resources and 30-day readmission, 30-day in-hospital mortality, and length of stay for surgical patients with OUD.Results:Of 919,601 surgical patients in 448 hospitals, 11,610 had identifiable OUD. Patients with compared to without OUD were younger and more often insured by Medicaid. Better nurse education, staffing, and work environment were each associated with better outcomes for all surgical patients. For patients with OUD, each 10% increase in the proportion of nurses with a bachelor’s degree in nursing was associated with even lower odds of 30-day readmission (odds ratio [OR] = 0.88; P = 0.001), and each additional patient-per-nurse was associated with even lower odds of 30-day readmission (OR = 1.09; P = 0.024).Conclusions:All surgical patients fare better when cared for in hospitals with better nursing resources. The benefits of having more nurses with a bachelor’s degree and fewer patients-per-nurse in hospitals appear greater for surgical patients with OUD.

The Moderating Effect of the Social Deprivation Index (SDI) on the Relationship Between Hospital Strategy and Financial Performance

Background: One of the major tenets of contingency theory is that the appropriate fit between strategy and environmental contingencies results in better financial performance. The purpose of this study was to investigate whether the Social Deprivation Index (SDI) moderates the association between hospital strategy and financial performance. Methods: We used longitudinal data from 2011 to 2016 from US urban general acute care hospitals. Four secondary datasets were used: the American Hospital Association (AHA) Annual Survey, Medicare cost reports (CMS), Area Health Resource File (AHRF), and the Robert Graham Center’s SDI. A generalized estimating equation (GEE) regression model was used to analyze the data. An interaction term was used to test the moderating effect of the SDI on the strategy–financial performance relationship. Results and Discussion: Our results showed that compared to hybrids, the SDI moderates the relationship between strategy and financial performance for cost leaders and hybrids. Increasing market social deprivation increases the hospital operating margin of cost leaders by 0.06%. Similarly, increasing levels of market social deprivation increases the hospital operating margin of hybrids by 0.06% (p < 0.05). As such, our results suggest that social deprivation may affect the viability of hospital strategy.

Demographics of Patients Traveling Notable Distances to Receive Total Knee Arthroplasty.

Introduction:Although disparities exist in patient access to and outcomes after total knee arthroplasty (TKA), there are limited data regarding the relationship between travel distance and patient demographics or postoperative complications.Methods:We identified patients who underwent TKA in Florida and New York between 2006 and 2014 using the Healthcare Cost and Utilization Project State Inpatient Databases. The American Hospital Association and UnitedStatesZipCodes.org Enterprise databases were further used to calculate distance traveled from patient population-weighted zip code centroid points to the hospitals at which they underwent TKA. Patients were grouped by travel distance: 25 to 50, 50 to 100, 100 to 500 miles, and greater than 500 miles. Patient demographic characteristics and postoperative outcomes were compared between the travel distance groups.Results:Older age, increased medical comorbidities, White race, Medicare insurance coverage, and living in zip codes with greater mean income levels were associated with greater travel distance (P < 0.001). There were no clinically significant relationships between various postoperative complications and distance traveled.Discussion:Certain demographic variables are associated with increased travel distance to undergo TKA. These relationships were most pronounced at the extremes of distance traveled (>500 miles). These differences may indicate that specific patient groups are either electing to or being forced to travel notable distances for orthopaedic care. Additional research is needed to determine the causative mechanisms underlying these findings.

What is Driving Hospital-Community Partnerships to Address Social Determinants of Health?

Social determinants of health (SDOH) are strongly linked to individual and population health outcomes. Hospitals and health systems are in a unique position to initiate or partner on community-wide efforts address SDOH. However, such efforts typically require collaboration with other healthcare and local community organizations since SDOH affect more than just medical care. Despite studies that have identified specific organizational and environmental factors associated with hospital-community partnerships, the role of social capital and community health needs as drivers of such partnerships remains unexplored. This study examines whether hospital partnerships with community organizations in the United States are driven predominantly by community social capital or the prevailing health needs of the community, and whether these drivers are similar for overall partnerships as well as for partnerships with individual organizations. We use 2020 data from the American Hospital Association, US County Health Rankings, and Social Capital Project and employ feasible generalized least-squares (FGLS) regression and logit models to assess the relationship between social capital, community health needs and hospital-community partnerships to address SDOH. Our results indicate that for community social capital was significantly and positively associated with total hospital partnerships (ß=0.05, p=0.01). We also found that community social capital was significantly more likely to be associated with hospitals’ partnerships with local/state public health agencies, schools, local service agencies, other healthcare providers, and organizations that assist with food insecurity. On the other hand, community health needs were not associated with total partnerships and had limited associations with hospital partnerships with individual organizations. Overall, this research suggests that social capital is a critical determinant of hospital partnerships with community organizations, and hospitals may seek partnerships with organizations that allow them to address community health issues outside of their own expertise since such partnerships and collaborative efforts can help address SDOH and manage population health.

For All: Atrium Health Efforts Create a More Diverse, Inclusive Culture

Atrium Health, headquartered in Charlotte, North Carolina, is the recipient of this year's American Organization for Nursing Leadership's Prism Award, which recognizes excellence in diversity efforts. The nurse leaders at the hospital network, which includes health centers in North Carolina, South Carolina, Georgia, and Alabama, made diversity a priority across the entire enterprise. In the last 5 years, Atrium Health has powered-up its diversity, equity, and inclusion initiatives, signing the American Hospital Association Equity of Care Pledge and offering a plethora of programs and tools such as diversity certification classes, a leadership speaker series, and a Racial Justice Toolkit.

What Constitutes a Competitive Environment? A Case Study of the FQHCs Industry In California

Objective: This study aims to identify competitive forces in the FQHCs environment using Porter’s Five Force model. Data Sources: The study utilized various secondary data sources. The Health Resources and Services Administration (HRSA) requires FQHCs to submit a performance report using the measures defined in the Uniform Data System (UDS). The UDS provides data such as the scope and volume of services provided by FQHCs, staffing, number of delivery sites, and finances. The UDS consider being a census of aggregate level health center data for FQHCs. Secondly, the American Hospital Association Annual Survey (AHA), which provides organizational details regarding hospitals. The third dataset is the Area Health Resources File (AHRF). It includes county-level data about health services volume, demographics, and health professional supply. The fourth dataset is the Internal Revenue Service (IRS) Form 990, which was used was used to calculate FQHCs’ total margin. The fifth dataset is the California Health and Human Services Open Data Portal (CHHS), which includes county-level data such as the number of Medicaid eligible populations and the number of primary care clinics. Finally, the study used the U.S. Department of Housing and Urban Development (HUD) United States Postal Service Zip Code Crosswalk Files. The Crosswalk Files was used to allocate both FQHC’s and FQHC’s sites Zip-Codes to counties. Method: this was a descriptive study. Descriptive statistics included frequencies and percentages to describe categorical variables. In addition, means (standard deviations, SD) will describe continuous variables. The study utilized bivariate analysis, including the chi-square test and ANOVA test, to find differences regarding the competitive forces variables among counties that had a new established FQHCs and counties that did not have newly established FQHCs in California for the years 2014 and 2015. Result: the study found that the number of FQHCs sites and primary care clinics in a county is statistically different between counties that had a newly established FQHC compared to counties that did not have a newly established FQHC. Counties that had newly established FQHCs had on an average a lower number of FQHCs sites and primary care clinics. Competition for FQHCs might arise when more FQHCs exist in a market. More research can be conducted to understand how FQHCs behave in a competitive environment.

Contextual factors and business strategy choice: The case of us hospitals.

US hospitals are struggling with how to compete and remain viable in an increasingly turbulent and competitive environment. Using Porter's generic strategies and resource dependence theory, this study examined the relationship between environmental factors and business strategy choice among U.S. hospitals. The study used longitudinal data from 2006 to 2016 of US urban, general acute care hospitals from the American Hospital Association Annual Survey, Medicare cost reports, and Area Health Resource File. Multinomial regression was used to analyze the data. and Discussion: Our findings showed four types of hospital strategy: cost-leadership, differentiation, hybrid, and stuck-in-the-middle. A greater number of physicians (county-level) increases the likelihood of pursuing differentiation and hybrid strategy. On the other hand, a higher older adult population (65 years+) increases the likelihood of pursuing a cost-leadership strategy. Similarly, lower competition and higher Medicare Advantage penetration increases the likelihood of pursuing cost-leadership over hybrid strategy. An increase in the unemployment rate decreases the likelihood of pursuing differentiation and cost-leadership strategies versus the hybrid strategy. Finally, hospitals pursuing a differentiation strategy tended to be larger, teaching, and not-for-profit. The results showed the importance of environmental and organizational factors in predicting the strategy choice of hospitals.

Acceptance of Simulated Adult Patients With Medicaid Insurance Seeking Care in a Cancer Hospital for a New Cancer Diagnosis

Although there have been significant increases in the number of US residents insured through Medicaid, the ability of patients with Medicaid to access cancer care services is less well known. To assess facility-level acceptance of Medicaid insurance among patients diagnosed with common cancers. This national cross-sectional secret shopper study was conducted in 2020 in a random sample of Commission on Cancer-accredited facilities in the United States using a simulated cohort of Medicaid-insured adult patients with colorectal, breast, kidney, and melanoma skin cancer. Telephone call requesting an appointment for a patient with Medicaid with a new cancer diagnosis. Acceptance of Medicaid insurance for cancer care. Descriptive statistics, χ2 tests, and multivariable logistic regression models were used to examine factors associated with Medicaid acceptance for colorectal, breast, kidney, and skin cancer. High access hospitals were defined as those offering care across all 4 cancer types surveyed. Explanatory measures included facility-level factors from the 2016 American Hospital Association Annual Survey and Centers for Medicare & Medicaid Services General Information database. A nationally representative sample of 334 facilities was created, of which 226 (67.7%) provided high access to patients with Medicaid seeking cancer care. Medicaid acceptance differed by cancer site, with 319 facilities (95.5%) accepting Medicaid insurance for breast cancer care; 302 (90.4%), colorectal; 290 (86.8%), kidney; and 266 (79.6%), skin. Comprehensive community cancer programs (OR, 0.4; 95% CI, 0.2-0.7; P = .007) were significantly less likely to provide high access to care for patients with Medicaid. Facilities with nongovernment, nonprofit (vs for-profit: OR, 3.5; 95% CI, 1.1-10.8; P = .03) and government (vs for-profit: OR, 6.6; 95% CI, 1.6-27.2; P = .01) ownership, integrated salary models (OR, 2.6; 95% CI, 1.5-4.5; P = .001), and average (vs above-average: OR, 6.4; 95% CI, 1.4-29.6; P = .02) or below-average (vs above-average: OR, 8.4; 95% CI, 1.5-47.5; P = .02) effectiveness of care were associated with high access to Medicaid. State Medicaid expansion status was not significantly associated with high access. This study identified access disparities for patients with Medicaid insurance at centers designated for high-quality care. These findings highlight gaps in cancer care for the expanding population of patients receiving Medicaid.

Rural Medicare beneficiaries are increasingly likely to be admitted to urban hospitals.

To determine whether rural Medicare FFS beneficiaries are more likely to be admitted to an urban hospital in 2018 than in 2010. We combined data from the 2010 to 2018 Hospital Service Area File (HSAF) and the 2010-2017 American Hospital Association (AHA) survey. We conducted a fixed-effects negative-binomial regression to determine whether urban hospital admissions from rural ZIP codes were increasing over time. We also conducted an exploratory geographically weighted regression. We transformed the HSAF data into a ZIP code-level file with all rural ZIP codes. We defined rural as having a Rural-Urban Commuting Area (RUCA) code ≥4. A hospital's system affiliation status was incorporated from the AHA survey. Controlling for distance to the nearest hospitals, an increase of 1 year was associated with a 2.0% increase (p < 0.001) in the number of admissions to urban hospitals from each rural ZIP code. New system affiliation of the nearest rural hospital was associated with an increase of 1.7% (p < 0.001). Even when controlling for distance to the nearest rural hospital (which reflects hospital closures), rural patients were increasingly likely to be admitted to an urban hospital.

Risk of Closure Among Independent and Multihospital-Affiliated Rural Hospitals

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. To examine the association between affiliation and rural hospital closure. 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. Affiliation with another hospital or multihospital health system. Closure was the main outcome. The models included hospital, market, and utilization characteristics and were stratified by financial distress in 2007. 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). 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.

Examining the Ratio of Obstetric Beds to Births, 2000-2019.

The number of U.S. births has been declining. There is also concern about rural obstetric units closing. To better understand the relationship between births and obstetric beds during 2000-2019, we examined changes over time in births, birth hospital distributions (i.e., hospital birth volume, ownership, and urban-rural designation), and the ratio of births to obstetric beds. We analyzed American Hospital Association Annual Survey data from 2000 to 2019. We included U.S. hospitals with at least 25 reported births during the year and at least 1 reported obstetric bed. We categorized birth volume to identify and describe hospitals with maternity services using seven categories. We calculated ratios of number of births to number of obstetric beds overall, by annual birth volume category, by three categories of hospital ownership, and by six urban-rural categories. The ratio of births to obstetric beds, which may represent need for maternity services, has stayed relatively consistent at 65 over the past two decades, despite the decline in births and changes in birth hospital distributions. The ratios were smallest in hospitals with < 250 annual births and largest in hospitals with ≥ 7000 annual births. The largest ratios of births to obstetric beds were in large metro areas and the smallest ratios were in noncore areas. At a societal level, the reduction in obstetric beds corresponds with the drop in the U.S. birth rate. However, consistency in the overall ratio can mask important differences that we could not discern, such as the impact of closures on distances to closest maternity care.

Taking the Long Way to Care: Who is Traveling Farthest to Undergo Elective Total Hip Arthroplasty?

BackgroundDisparities in access to total hip arthroplasty (THA) exist. The purpose of this study is to examine how distance traveled to undergo elective THA correlates with sociodemographic variables and postoperative outcomes.Material and methodsThe Healthcare Cost and Utilization Project New York and Florida state inpatient databases were used to identify patients who underwent elective THA between 2006 and 2014. Data from the American Hospital Association and United States Postal Service were used to calculate the distance patients traveled to receive THA, and only those who traveled more than 25 miles were included. We stratified patients into 4 groups based on their distance traveled (25-50 miles, 50.01-100 miles, 100.01-500 miles, and >500.01 miles) and compared demographic characteristics and postoperative outcomes between groups.ResultsAge, race, insurance provider, zip code income quartile, and Charlson Comorbidity Index scores were each significantly associated with travel distance (P < .001) among our cohort of 25,734 patients. Patients who were older, were white, had Medicare insurance coverage, lived in zip codes with a higher median household income, and had increased comorbidities were more likely to travel the farthest to receive care. There were minimal associations between travel distance and postoperative outcomes.ConclusionThere may be specific demographic groups who either are forced to travel long distances to receive care or have the resources to seek out and travel to distant hospitals in an effort to receive optimal care. Understanding the interconnected relationships between demographic variables is necessary to address disparities in access to specialized orthopedic surgical care.

The Hospital Value-Based Purchasing Program: Do hospitalists improve health care value.

As healthcare organizations examine the associated benefits of employing a larger hospitalist workforce, there is a need to better understand the association with patients' quality, experience, and efficiency. However, there is a lack of information regarding how hospital use of hospitalists over time influences hospital scoring on quality programs, such as the Center for Medicare and Medicaid Services (CMS) Hospital Inpatient Value-Based Purchasing (HVBP) Program. This study examines the association between hospitalist staffing between 2014 and 2019 and HVBP scores. We used a cross-sectional panel study design. Total Performance Score (TPS) and its domains were obtained from CMS from 2014 to 2019 and merged with the American Hospital AssociationAnnual Survey Database. We utilized random-effects multivariable panel regression models and zero-inflated negative binomial regression to examine the association between the hospitalist-staffing ratio and the HVBP Program. All models were adjusted for hospital characteristics. A total of 2126 hospitals were included in the study. The average ratio of hospitalists per staffed bed was 0.06, with a standard deviation of 0.15. This study suggests that hospitals that employ a higher percentage of hospitalists see improvement in their overall TPS (β = 5.40; p < .001), Patient Experience (β = 2.49; p <.05), andEfficiency (incidence-rate ratio= 1.41; p < .001) domain. However, the Clinical Care domain was no different in organizations employing more hospitalists. There are benefits associated with TPS, Patient Experience, and Efficiency from employing hospitalists. Managers should seek opportunities to leverage hospitalists' expertise in providing care, particularly in improving care processes.

Association of hospital and community factors on the attainment of Baby-Friendly designation: A breastfeeding health promotion.

The Baby‐Friendly Hospital Initiative is a global health promotion intervention that outlines the Ten Steps hospitals should implement to support newborns' breastfeeding. This US‐based study aimed to determine which hospital characteristics and community factors are associated with hospitals' attainment of Baby‐Friendly designation. We used a cross‐sectional design and used 2018 data from the Baby‐Friendly, USA Inc. designation program merged with the American Hospital Association annual survey data set. Multilevel logistic regression analysis was used to assess hospital characteristics of interest among the sample consisting of 312 Baby‐Friendly hospitals and 1449 non‐Baby‐Friendly. Our results show that Baby‐Friendly hospitals are more likely to be government nonfederal hospitals, in the Midwest or South regions, serve communities with higher birth totals, and reside in competitive markets. Based on the results of this study, hospitals should seek further and examine their community's characteristics and structures to identify opportunities and encourage the attainment of improved breastfeeding initiatives such as Baby‐Friendly designation.