Hospital-level Variables Research Articles

Role of Hospital Connectedness in Brain Metastasis Outcomes

Although patients with brain metastases receive interdisciplinary and multi-institutional care, the association between neuro-oncologic care networks and patient outcomes remains unknown. As patients often interact with multiple facilities, quantifying this association across a network of hospitals is critical to capture the complexity of the health care journey for patients with brain metastases. To evaluate how statewide health care network metrics are associated with inpatient mortality and hospital length of stay (LOS) for patients with brain metastases. This multicenter, statewide cohort study used data from the 2018 to 2019 Healthcare Cost and Utilization Project State Inpatient and Emergency Department Databases. Primary analyses were completed by August 2023. Participants included adults with a brain metastases receiving care in Massachusetts. All inpatient and emergency department visits mapped for patients following the first diagnosis of brain metastasis. Inpatient mortality and hospital LOS were the main outcomes assessed. Hospital interdependence in brain metastases care was calculated using a connectedness score (weighted degree: weighted sum of ties to other care facilities). The association between hospital connectedness and clinical outcomes was analyzed using mixed-effects logistic and linear regression models, adjusting for hospital-level features. In this cohort study, 4679 patients with brain metastases were identified with inpatient or ED encounters in Massachusetts (from 2018 to 2019). The median (IQR) age was 64 (57-73) years, and 2559 (55%) were female. There was interdependence in brain metastases care, with 993 patients (21%) visiting 2 or more unique hospitals. Highly connected hospitals were heterogeneous, with many being small and one-half lacking subspecialty neuro-oncologic care or teaching status. Increased hospital connectedness was significantly associated with improved inpatient mortality for patients with brain metastases, with the lowest connectedness quartile associated with more than double the risk of mortality compared with the highest quartile (odds ratio, 2.34; 95% CI, 1.33-4.11; P = .003). A stepwise increase in inpatient mortality risk was observed as hospital connectedness decreased, independently of hospital volume. Furthermore, intermediate hospital connectedness was associated with increased hospital LOS (coefficient, 1.08; 95% CI, 0.17-1.95; P = .006). This study found that hospital-to-hospital interconnectedness was significantly associated with improved clinical outcomes for patients with brain metastases. The salience of network metrics highlights their potential role alongside other patient-level and hospital-level variables to evaluate and improve oncology care delivery.

Hospital–Skilled Nursing Facility Integration and Participation in a Bundled Payment Initiative

Reduced institutional postacute care has been associated with savings in alternative payment models. However, organizations may avoid voluntary participation if participation could threaten their own revenues. To characterize the association between hospital-skilled nursing facility (SNF) integration and participation in Medicare's Bundled Payments for Care Improvement Advanced (BPCI-A) program. This is a cross-sectional analysis of hospital participation in BPCI-A beginning with its launch in 2018. Each SNF-integrated hospital was matched with 2 nonintegrated hospitals for each of 4 episode-specific analyses. Fifteen hospital-level variables were used for matching: beds, case mix index, days, area SNF beds, metropolitan location, ownership, region, system membership, and teaching status. Hospitals were also matched on episode-specific volume, target price, and the interaction of target price and case mix. Episode-specific logistic models were estimated regressing hospital participation on integration and the previously listed variables. The marginal effect of integration on participation was then calculated. Analysis took place from August 2022 to May 2024. Hospital-SNF integration, as defined by common ownership and referral patterns and identified using cost reports, Medicare claims, and Provider Enrollment, Chain, and Ownership System records. Additional sources included records of target prices and participation, the Area Health Resources File, and the Compendium of US Health Systems. Participation in BPCI-A. In total, 1524 hospitals met criteria for inclusion in the hip and femur (HFP) analysis, 1825 were included in the major joint replacement of the lower extremity (MJRLE) analysis, 2018 were included in the sepsis analysis, and 1564, were included in the stroke-specific analysis. Across episodes, 191 HFP-eligible hospitals (12.5% of HFP-eligible hospitals), 302 MJRLE-eligible hospitals (16.5%), 327 sepsis-eligible hospitals (16.2%), and 185 sepsis-eligible hospitals (11.8%) were SNF integrated. In total, 79 hospitals (5.2%) participated in the HFP episode, 128 (7.0%) participated in the MJRLE episode, 204 (10.1%) participated in the sepsis episode, and 141 (9.0%) participated in the stroke episode. Integration was associated with a 4.7-percentage point decrease (95% CI, 2.4 to 6.9 percentage points) in participation in the MJRLE episode. There was no association between integration and participation for HFP (0.5-percentage point increase in participation moving from nonintegrated to integrated; 95% CI, -2.9 to 3.8 percentage points), sepsis (1.0-percentage point increase; 95% CI, -2.2 to 4.2 percentage points), and stroke (0.3-percentage point decrease; 95% CI, -3.1 to 3.8 percentage points). In this cross-sectional study, there was an uneven association between hospital-SNF integration and participation in Medicare's BPCI-A program. Other factors may be more consistent determinants of selection into voluntary payment reform.

Interhospital transfer dynamics for patients with intracranial hemorrhage in Massachusetts.

Intracranial hemorrhages present across a spectrum of clinical phenotypes, with many patients transferred across hospitals to access higher levels of neurocritical care. We sought to characterize patient dispositions following intracranial hemorrhage and examine disparities associated with interhospital transfers. Using the Healthcare Cost and Utilization Project database, we mapped and identified factors influencing the likelihood of patient transfers and receipt of specialist interventional procedures following intracranial hemorrhage. Of 11,660 patients with intracranial hemorrhage, 59.4% had non-traumatic and 87.5% single compartment bleeds. After presentation, about a quarter of patients were transferred to another facility either directly from the ED (23.0%) or after inpatient admission (1.8%). On unadjusted analysis, patients who were white, in the upper income quartiles, with private insurance, or resided in suburban areas were more frequently transferred. After adjusting for patient-and hospital-level variables, younger and non-white patients had higher odds of transfer. Hospital capabilities, residence location, insurance status, and prior therapeutic relationship remained as transfer predictors. Transferred patients had a similar hospital length of stay compared to admitted patients, with 43.1% having no recorded surgical or specialist interventional procedure after transfer. Our analysis reveals opportunities for improvement in risk stratification guiding transfers, as well as structural challenges likely impacting transfer decisions.

In-hospital outcomes in people with autism and epilepsy – A population-based study

Autism is a common comorbid diagnosis in those with epilepsy. Understanding the health needs and outcomes in patients with this dual diagnosis is important for optimizing healthcare outcomes. We compared hospital-level variables amongst patients with co-occurring autism and epilepsy, to those with epilepsy alone. Non-elective hospital admissions amongst patients with epilepsy alone and co-occurring autism and epilepsy were identified in the 2003–14 National Inpatient Sample (NIS) using previously validated ICD-9-CM case definitions. One patient with co-occurring epilepsy and autism was matched to three epilepsy patients for age and sex. Multinomial logistic regressions were performed to examine outcomes of interest. Compared to those with epilepsy alone (n = 27,762), patients with autism and epilepsy (n = 9254) had a higher odds of transfer to another facility (OR = 1.09, p = 0.048), in-hospital mortality (OR = 1.36, p = 0.011), longer mean length of stay (5.63 days vs. 5.12 days, p < 0.0001), and septicemia (4.21 % vs. 3.08 %, p < 0.0001). Distributions of demographics, insurance type, socioeconomic status, and comorbidities significantly differed between both groups. Our findings demonstrate that patients with comorbid autism and epilepsy are a unique population with health outcomes significantly differing from those with epilepsy alone. Given the effect that dual diagnosis has on hospital trajectory, focused treatment plans must be adopted to optimize care and hospital outcomes in these patients.

Burn Care Funding in the Era of Price Transparency-Does Verification Signal Bargaining Power?

The Price Transparency Rule of 2021 forced payors and hospitals to publicly disclose negotiated prices to foster competition and reduce the cost. Burn care is costly and concentrated at less than 130 centers in the US. We aimed to analyze geographic price variations for inpatient burn care and measure the effects of American Burn Association (ABA) verification status and market concentration on prices. All available commercial rates for 2021-2022 for burn-related diagnosis-related groups (DRGs) 927, 928, 929, 933, 934, and 935 were merged with hospital-level variables, ABA verification status, and Herfindahl-Hirschman Index (HHI) data. For the DRG 927 (most intensive burn admission), a linear mixed effects model was fit with cost as the outcome and the following variables as covariates: HHI, plan type, safety net status, profit status, verification status, rural status, and teaching hospital status. Random intercepts allowed for individual burn centers. There were 170,738 rates published from 1541 unique hospitals. Commercial reimbursement rates for the same DRG varied by a factor of approximately three within hospitals for all DRGs. Similarly, rates across different hospitals varied by a factor of 3 for all DRGs, with DRG 927 having the most variation. Burn center status was independently associated with higher reimbursement rates adjusting for facility-level factors for all DRGs except for 935. Notably, HHI was the largest predictor of commercial rates (P < .001). Negotiated prices for inpatient burn care vary widely. ABA-verified centers garner higher rates along with burn centers in more concentrated/monopolistic markets.

Effect of neurosurgical residency programs on neurosurgical patient outcomes in a single health care system: a cohort study.

The evidence on the benefits and drawbacks of involving neurosurgical residents in the care of patients who undergo neurosurgical procedures is heterogeneous. We assessed the effect of neurosurgical residency programs on the outcomes of such patients in a large single-payer public health care system. Ten population-based cohorts of adult patients in Ontario who received neurosurgical care from 2013 to 2017 were identified on the basis of procedural codes, and the cohorts were followed in administrative health data sources. Patient outcomes by the status of the treating hospital (with or without a neurosurgical residency program) within each cohort were compared with models adjusted for a priori confounders and with adjusted multilevel models (MLMs) to also account for hospital-level factors. A total of 46 608 neurosurgical procedures were included. Operative time was 8%-30% longer in hospitals with neurosurgical residency programs in 9 out of 10 cohorts. Thirty-day mortality was lower in hospitals with neurosurgical residency programs for aneurysm repair (odds ratio [OR] 0.30, 95% confidence interval [CI] 0.20-0.44), cerebrospinal fluid shunting (OR 0.52, 95% CI 0.34-0.79), intracerebral hemorrhage evacuation (OR 0.66, 95% CI 0.52-0.84), and posterior lumbar decompression (OR 0.32, 95% CI 0.15-0.65) in adjusted models. The mortality rates remained significantly different only for aneurysm repair (OR 0.19, 95% CI 0.05-0.69) and cerebrospinal shunting (OR 0.42, 95% CI 0.21-0.85) in MLMs. Length of stay was mostly shorter in hospitals with neurosurgical residents, but this finding did not persist in MLMs. Thirty-day reoperation rates did not differ between hospital types in MLMs. For 30-day readmission rates, only extracerebral hematoma decompression was significant in MLMs (OR 1.41, 95% CI 1.07-1.87). Hospitals with neurosurgical residents had longer operative times with similar to better outcomes. Most, but not all, of the differences between hospitals with and without residency programs were explained by hospital-level variables rather than direct effects of residents.

Level of implementation of multimodal strategies for infection prevention and control interventions and prevalence of healthcare-associated infections in Northern Italy

BackgroundIn November 2022, Italy participated in the third edition of the European Centre for disease prevention and control (ECDC) point prevalence survey (PPS) of healthcare-associated infections (HAIs) in acute-care hospitals. A questionnaire based on the WHO infection prevention and control assessment framework (IPCAF) was included, which aims to investigate multimodal strategies for the implementation of IPC interventions.MethodsA PPS was conducted using the ECDC PPS protocol version 6.0. The Regional health authority of the region of Piedmont, in north-western Italy, chose to enlist all public acute-care hospitals. Data were collected within one day per each ward, within 3 weeks in each hospital, at hospital, ward and patient level. A score between 0–1 or 0–2 was assigned to each of the 9 items in the IPCAF questionnaire, with 14 points representing the best possible score. HAI prevalence was calculated at the hospital-level as the percentage of patients with at least one HAI over all included patients. Relations between HAI prevalence, IPCAF score, and other hospital-level variables were assessed using Spearman's Rho coefficient.ResultsIn total, 42 acute-care hospitals of the region of Piedmont were involved, with a total of 6865 included patients. All participant hospitals reported they employed multimodal strategies to implement IPC interventions. The median IPCAF overall score was 11/14 (interquartile range, IQR: 9.25–12). The multimodal strategy with the highest level of adherence was education and training, followed by communication and reminders. Strategies with the lowest level of adherence were safety climate and culture of change, and system change. Overall HAI prevalence was 8.06%. A weak to moderate inverse relation was found between IPCAF score and HAI prevalence (Spearman’s Rho -0.340, p 0.034). No other significant correlation was found.ConclusionsThis study found a high self-reported overall level of implementation of multimodal strategies for IPC in the region. Results of this study suggest the relevance of the multimodal approach and the validity of the IPCAF score in measuring IPC programs, in terms of effectiveness of preventing HAI transmission.

16 Sociodemographic and Hospital-Level Characteristics Associated with Hospital-Onset Bacteremia in the Neonatal Intensive Care Unit

OBJECTIVES/GOALS: The primary objective is to measure the independent association of hospital-level and sociodemographic variables on the rate of hospital-onset bacteremia among infants admitted to the neonatal intensive care unit in a United States of America retrospective cohort. The secondary outcome will be relative blood culture collection rate. METHODS/STUDY POPULATION: The study is an analysis of a retrospective cohort comprised of infants admitted to 322 neonatal intensive care units (NICUs) in the United States of America between 2016-2021. The primary outcome will be hospital-onset bacteremia (HOB), defined as a positive blood culture with a bacteria or fungi after day 3 of admission. Independent risk factors will include birthweight, postnatal age, central venous catheter presence, sociodemographic variables (race, ethnicity, insurance status and ZIP code-level demographic data from the US Census American Community Survey (ACS), and hospital-level variables. Infants will be stratified by sociodemographic groups and a Poisson model will be utilized to measure the adjusted association between risk of HOB and clinical and hospital-level variables. RESULTS/ANTICIPATED RESULTS: I anticipate that infants in sociodemographic groups with a history of socioeconomic marginalization will have a higher unadjusted rate of HOB; however, sociodemographic variables will not be independently associated with HOB risk after adjusting for markers of hospital quality and acuity, such as quartiles of the following: mean admissions per year, percentage of infants born &lt;1500g, annual blood culture contamination rate, and percentage infants born at another facility. DISCUSSION/SIGNIFICANCE: Neonatal bacteremia has high morbidity and mortality; however, its contribution to known infant mortality inequities is unknown. This study will estimate the burden of infant HOB stratified by sociodemographic groups and measure the independent association of sociodemographic and hospital-level variables on the adjusted rate of HOB.

National Institutes of Health Stroke Scale Reporting in Medicare Claims Data: Reporting in the First 3 Years.

Since 2016, hospitals have been able to document International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes for the National Institutes of Health Stroke Scale (NIHSS). As of 2023, the Centers for Medicare & Medicaid Services uses NIHSS as a risk adjustment variable. We assessed associations between patient- and hospital-level variables and contemporary NIHSS reporting. We performed a retrospective cross-sectional analysis of 2019 acute ischemic stroke admissions using deidentified, national 100% inpatient Medicare Fee-For-Service data sets. We identified index acute ischemic stroke admissions using the ICD-10-CM code I63.x and abstracted demographic information, medical comorbidities, hospital characteristics, and NIHSS. We linked Medicare and Mount Sinai Health System (New York, NY) registry data from 2016 to 2019. We calculated NIHSS documentation at the patient and hospital levels, predictors of documentation, change over time, and concordance with local data. There were 231 383 index acute ischemic stroke admissions in 2019. NIHSS was documented in 44.4% of admissions and by 66.5% of hospitals. Hospitals that documented ≥1 NIHSS were more commonly teaching hospitals (39.0% versus 5.5%; standardized mean difference score, 0.88), stroke certified (37.2% versus 8.0%; standardized mean difference score, 0.75), higher volume (mean, 80.8 [SD, 92.6] versus 6.33 [SD, 14.1]; standardized mean difference score, 1.12), and had intensive care unit availability (84.9% versus 23.2%; standardized mean difference score, 1.57). Adjusted odds of documentation were lower for patients with inpatient mortality (odds ratio, 0.64 [95% CI, 0.61-0.68]; P<0.0001), in nonmetropolitan areas (odds ratio, 0.49 [95% CI, 0.40-0.61]; P<0.0001), and male sex (odds ratio, 0.95 [95% CI, 0.93-0.97]; P<0.0001). NIHSS was documented for 52.9% of Medicare cases versus 93.1% of registry cases, and 74.7% of Medicare NIHSS scores equaled registry admission NIHSS. Missing ICD-10-CM NIHSS data remain widespread 3 years after the introduction of the ICD-10-CM NIHSS code, and there are systematic differences in reporting at the patient and hospital levels. These findings support continued assessment of NIHSS reporting and caution in its application to risk adjustment models.

Effect of the Presence of Emergency Departments With 300 or More Hospital Beds in Health Service Areas on 30-Day Mortality in Korea: A Nationwide Retrospective Cross-sectional Study.

Disparities in emergency care accessibility exist between health service areas (HSAs). There is limited evidence on whether the presence of an emergency department (ED) that exceeds a certain hospital bed capacity is associated with emergency patient outcomes at the regional level. The objective of this study was to evaluate the effect of HSAs with or without of regional or local emergency centers with 300 or more hospital beds (EC300 or nEC300, respectively) by comparing the 30-day mortality of patients with severe emergency diseases (SEDs) admitted to the hospital through the ED. The study retrospectively evaluated data from the National Health Information Database (NHID) of the National Health Insurance Service (NHIS) Claims database and enrolled patients who were admitted from the ED for SEDs. SEDs were defined using ICD-10 (International Classification of Diseases 10th Revision) codes for 28 disease categories with high severity, and 56 HSAs were designated as published by the NHIS. We performed hierarchical logistic regression analysis using multilevel models with the generalized linear mixed model (GLIMMIX) procedure to evaluate whether EC300 was associated with the 30-day mortality of SED patients, adjusting for patient-level, prehospital-level, hospital-level, and HSA-level variables. In total, 662 478 patients were analyzed, of whom 54 839 (8.3%) died within 30 days after hospital discharge. Of the 56 HSAs, 46 (82.1%) were included in the EC300 group. After adjustment for patient-level, prehospital-level, hospital-level, and HSA-level variables, nEC300 was significantly associated with increased 30-day mortality in SED patients (adjusted odds ratio [AOR]: 1.33, 95% CI: 1.137-1.153). In addition, patients who visited EDs with fewer annual SED admissions were associated with higher 30-day mortality. nEC300 had a greater risk of 30-day mortality in patients treated with SEDs than EC300. The results indicate that not only the number of EDs in each HSA is important for ensuring adequate patient outcomes but also the presence of EDs with adequate receiving capacity.

The impacts of multiple privacy regulations and national security infrastructure on health information exchange: a study of hospitals across Europe

PurposeSharing patient health information (PHI) among hospitals has been much slower than the adoption of health record systems. This paper aims to investigate if privacy regulation (PR) or security measures (SMs) influence hospitals’ use of health information exchange (HIE) to share PHI with other providers (e.g. physicians, labs, hospitals). The study specifically focuses on how multiple PRs can impede and a strong national security infrastructure (NSI) can support HIE.Design/methodology/approachThe study uses secondary data from a multi-national and multi-hospital survey administered by the European Union. The multi-level structure of the cross-sectional panel data is used to test the influence of both hospital-level (e.g. PR) and national-level variables (e.g. NSI) on HIE. A total of nine types of HIE, three types of PRs, nine SMs and other relevant control variables are considered. This study uses a two-level random intercept generalized linear model to test the hypothesis proposed in the study.FindingsThe study finds that national-level PRs (NLPR) have the strongest positive influence on HIE in comparison to regional (RLPR) and hospital-level (HLPR) PRs. Moreover, the study finds evidence that the presence of RLPR and HLPR, on average, decreases the positive impact of NLPR by 264%. The SMs also have a significant and positive impact on HIE. Adoption of an additional SM can increase the odds of engaging in a certain type of HIE between 21% and 61%. On the other hand, a strong NSI can also amplify the positive impact of SM on certain types of HIE.Originality/valueThis study extends prior research on the role of PRs in enabling HIE by considering the complexities brought up by adopting multiple PRs. NLPRs have the strongest impact on HIE in comparison to RLPRs or HLPRs. Moreover, public infrastructure initiatives such as those related to secure communications can also complement SMs adopted by the providers by encouraging HIE.

Impact of Sociodemographic and Hospital Factors on Inpatient Bilateral Reduction Mammaplasty: A National Inpatient Sample Analysis

Background: Although reduction mammaplasty remains a common procedure in plastic surgery, its interaction with sociodemographic and economic disparities has remained relatively uncharacterized on a nationwide scale. Methods: Patients who underwent reduction mammaplasty were identified within the 2016–2018 National Inpatient Sample databases. In addition to clinical comorbidities, sociodemographic characteristics, hospital-level variables, and postoperative outcomes of each patient were collected for analysis. Statistical analyses, including univariate comparison and multivariate logistic regression, were applied to the cohort to determine significant predictors of adverse outcomes, described as extended length of stay, higher financial cost, and postoperative complications. Results: The final patient cohort included 414 patients who underwent inpatient reduction mammaplasty. The average age was 45.2 ± 14.5 years. The average length of stay was 1.6 ± 1.5 days, and the average hospital charge was $53,873.81 ± $36,014.50. Sixty (14.5%) patients experienced at least one postoperative complication. Black race and treatment within a nonmetropolitan or rural county predicted postoperative complications (P &lt; 0.01). Black race, lower relative income, and concurrent abdominal contouring procedures also predicted occurrence of extended length of stay (P &lt; 0.01). Hospital factors, including larger bed capacity and for-profit ownership, predicted high hospital charges (P &lt; 0.05). Severity of comorbidities, measured by a clinical index, also predicted all three outcomes (P &lt; 0.001). Conclusion: In addition to well-described clinical variables, multiple sociodemographic and economic disparities affect outcomes in inpatient reduction mammaplasty.

Association between social vulnerability index and admission urgency for transcatheter aortic valve replacement

BackgroundTranscatheter aortic valve replacement (TAVR) are not offered equitably to vulnerable population groups. Adequate levels of insurance may narrow gaps among patients with higher social vulnerability index (SVI). Among a national population of individuals with commercial or Medicare insurance, we sought to determine whether SVI was associated with urgency of receipt of TAVR for aortic stenosis. Methods and resultsUsing Optum's de-identified Clinformatics Data Mart Database (CDM), we identified admissions for TAVR with aortic stenosis between January 2018 and March 2022. Admission urgency was identified by CDM claims codes. SVI was cross-referenced to patient zip codes and grouped into quintiles. Generalized linear mixed effects models were used to predict the probability of a TAVR admission being urgent based on SVI quintiles, adjusting for patient and hospital-level covariates. ResultsAmong 6680 admissions for TAVR [median age 80 years (interquartile range 75–85), 43.9 % female], 8.5 % (n = 567) were classified as urgent. After adjusting for patient and hospital-level variables, there were no significant differences in the odds of urgent admission for TAVR according to SVI quintiles [OR 5th (greatest social vulnerability) vs 1st quintile (least social vulnerability): 1.29 (95 % CI: 0.90–1.85)]. ConclusionsAmong commercial or Medicare beneficiaries with aortic stenosis, SVI was not associated with admission urgency for TAVR. To clarify whether cardiovascular care delivery is improved across SVI with higher paying beneficiaries, future investigation should identify whether relationships between SVI and TAVR urgency vary for Medicaid beneficiaries compared to commercial beneficiaries.

National Hospitalization Rates and In-Hospital Mortality Rates of HIV-Related Opportunistic Infections in the United States, 2011-2018.

Human immunodeficiency virus (HIV)-related opportunistic infections (OIs) cause substantial morbidity and mortality among people with HIV (PWH). US hospitalization and in-hospital mortality rates associated with OIs have not been published using data from the past decade. We analyzed the National Inpatient Sample for the years 2011 through 2018. We used sociodemographic, financial, and hospital-level variables and identified hospitalizations for PWH and OI diagnoses. Using survey-weighted methods, we estimated all OI-related US hospitalization rates and in-hospital mortality per 100 000 PWH and modeled associated factors using survey-based multivariable logistic regression techniques. From 2011 to 2018, there were an estimated 1 710 164 (95% confidence interval [CI], 1 659 566-1 760 762) hospital discharges for PWH with 154 430 (95% CI, 148 669-159 717 [9.2%]) associated with an OI, of which 9336 (95% CI, 8813-9857; 6.0%) resulted in in-hospital mortality. Variables associated with higher odds of OI-related hospitalizations (compared to without an OI) included younger age, male sex, non-White race/ethnicity, and being uninsured (all likelihood ratio [LR] P < .001). Higher OI-related mortality was associated with older age (LR P < .001), male sex (LR P = .001), Hispanic race/ethnicity (LR P < .001), and being uninsured (LR P = .009). The OI-related hospitalization rate fell from 2725.3 (95% CI, 2266.9-3183.7) per 100 000 PWH in 2011 to 1647.3 (95% CI, 1492.5-1802.1) in 2018 (P < .001), but the proportion of hospitalizations with mortality was stable (5.9% in 2011 and 2018). Our findings indicate an ongoing need for continued funding of HIV testing, health insurance for all PWH, OI screening initiatives, review of current prophylaxis guidelines, and recruitment of more HIV clinicians.

Abstract 24: Differences in Door to Needle and Door In Door Out Times for Tenecteplase vs Alteplase in Acute Ischemic Stroke: Findings From Get With the Guidelines Stroke

Introduction: Tenecteplase (TNK) has arisen as an alternative to alteplase (ALT) for emergent treatment of acute ischemic stroke. Shorter times to prepare and administer TNK raises the possibility that TNK use leads to faster treatment and transfer times. Hypothesis: We hypothesized that treatment with TNK is associated with shorter door-to-needle (DTN) and door-in-door-out (DIDO) times. Methods: Using the US Get With The Guidelines-Stroke registry, we performed a retrospective, observational cohort study of consecutive patients treated with either TNK or ALT between July 1, 2020 and June 30, 2022. The exposure was treatment with TNK vs ALT. The primary endpoints were DTN and DIDO. We fit generalized linear mixed models to determine the association between TNK (vs ALT) and endpoints after adjustment for key demographic, clinical, and hospital-level variables. A secondary analysis compared changes in DTN among hospitals that switched to TNK in 2021 with at least 10 cases per year pre and post switch. Results: From 2092 sites, 133,228 patients received intravenous thrombolysis. Among the 13,988 (10%) treated with TNK, median age was 70 yrs, median NIHSS 7, 47% female, 21% received endovascular thrombectomy (EVT), and 9% were transferred from the hospital emergency department after receiving lytic. Among 119,240 (90%) treated with ALT, median age was 69 yrs, median NIHSS 7, 48% female; 17% received EVT, and 12% were transferred after lytic. In the primary DTN analysis, time to treatment was shorter with TNK, with mean 47.0 vs 52.7 minutes and DTN ≤60 mins in 77.5% vs 70.7% (TABLE). In the primary DIDO analysis, time to departure was shorter with TNK, 108.3 vs 114.1 minutes. In centers that changed from ALT to TNK during this period DTN times were significantly lower after switching. Conclusions: In this largest study of TNK vs ALT workflow time intervals in ischemic stroke using population-based data, TNK use was associated with more favorable DTN and DIDO times relative to ALT use.

Abstract 5: National Institutes of Health Stroke Scale Reporting in Administrative Claims Data: Incomplete and Biased Reporting in the First Three Years

Background: Since 2016, hospitals have been able to document International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes for National Institutes of Health Stroke Scale (NIHSS). As of 2023, Center for Medicare &amp; Medicaid Services uses NIHSS as a risk adjustment variable. We assessed associations between patient- and hospital-level variables and contemporary NIHSS reporting using Medicare datasets. Methods: Retrospective cross-sectional analysis of acute ischemic stroke (AIS) admissions from October 1, 2016-December 31, 2019 using de-identified, national 100% inpatient Medicare datasets. Index AIS admissions were identified using the ICD-10-CM code of I63.x. Demographic information, medical comorbidities, hospital characteristics, and NIHSS were abstracted. Medicare and Mount Sinai Health System registry data were linked using a matching algorithm. We calculated documentation of NIHSS at the patient and hospital level, predictors of NIHSS documentation, change over time, and concordance with local registry data. Results: There were 770104 index AIS admissions. NIHSS was documented in 40.1% of AIS admissions and by 62.5% of hospitals. Hospitals documenting ≥1 NIHSS were more commonly teaching hospitals, in metropolitan areas, stroke certified, higher-volume, and had ICU availability. Adjusted odds of documentation were lower for patients of black race compared to white and with inpatient mortality, increasing Charlson comorbidity score, discharge home, and treatment in non-metropolitan areas. NIHSS was documented for 52.9% of Medicare cases even though it was documented in 93.1% of registry cases, and 74.7% of Medicare NIHSS scores equaled registry admission NIHSS. Conclusions: Hospitals face financial implications for risk-standardized mortality rate adjustment, and administrative data play an increasingly important in stroke health services and outcomes research. Yet, missing ICD-10-CM NIHSS data remains widespread three years after introduction of the ICD-10-CM NIHSS code, and there are systematic differences in reporting at the patient and hospital levels.

The Evaluation of Hospitalist Care for Patients with Aspiration Pneumonia Using Risk-adjusted Performance Indicators Developed from a Nationwide Inpatient Database.

Background High-quality evidence proving the superiority of hospitalist services is lacking. We developed risk-adjusted performance indicators from a multilevel prediction model using a nationwide inpatient database to evaluate hospitalist medical care for patients with aspiration pneumonia. Methods We extracted cases diagnosed with aspiration pneumonia between 2014 and 2021 from the Diagnosis Procedure Combination (DPC) database. Hospital-level risk-adjusted performance indicators were the observed-to-expected ratio of the following outcomes using a multilevel prediction model containing both patient- and hospital-level variables: death or transfer in poor condition within 30 days (poor outcome), in-hospital death within 30 days, and discharges within the 25th and 50th percentiles for length of stay defined by the DPC system. Using the predicted numbers of each outcome without random intercept as denominators of both indicators, the numerators of Indicator 1 were observed numbers of each outcome, while those in Indicator 2 were "smoothed" predicted numbers of outcomes estimated by the fitted model with random intercept. The ratio of the number of outcomes for each hospital to the mean number of outcomes among participating hospitals was used as a reference. We applied these indicators to Takatsuki General Hospital (TGH) as a working example. Results A total of 526,245 patients were analyzed. Compared with indicator 1, indicator 2 showed greater stability in the mean ratio and bootstrapping confidence interval (CI). Indicator 2 of poor outcome and discharges within the 25th percentile in 2017 at TGH were 1.110 (95% CI 0.784-1.375) and 1.458 (95% CI 1.272-1.597), respectively. Conclusions Utilizing a nationwide inpatient database, we developed risk-adjusted performance indicators using a multilevel prediction model to evaluate hospitalist medical care for patients with aspiration pneumonia. Given the reliable results shown in the working example, these indicators have potential benefits for the accurate evaluation of the quality of medical care.

Trends in utilisation of palliative care services in COVID-19 patients and their impact on hospital resources in the USA: insights from the national inpatient sample

ObjectivesPoor prognosis and lack of effective therapeutic options have made palliative care an integral part of the management of severe COVID-19. However, clinical studies on the role of palliative care...

Treatment of Acute Traumatic Central Cord Syndrome: A Study of North American Trauma Centers.

Central cord syndrome (CCS) is expected to become the most common traumatic spinal cord injury, yet its optimal management remains unclear. This study aimed to evaluate variability in nonoperative vs operative treatment for CCS between trauma centers in the American College of Surgeons Trauma Quality Improvement Program, identify patient- and hospital-level factors associated with treatment, and determine the association of treatment with outcomes. Adults with CCS were identified from the Trauma Quality Improvement Program database (2014-2016). Mixed-effects modeling with a random intercept for trauma centers was used to examine the adjusted association of patient- and hospital-level variables with nonoperative treatment. The random-effects output of the model assessed the risk-adjusted variability in nonoperative treatment across centers. Outlier hospitals were identified, and the median odds ratio was calculated. The adjusted effect of nonoperative treatment on mortality, morbidity, and hospital length of stay (LOS) was examined at the patient and hospital level by mixed-effects regression. Three thousand, nine hundred twenty-eight patients across 255 centers were eligible; of these, 1523 (38.8%) were treated nonoperatively. Older age, noncommercial insurance (odds ratio [OR] 1.26, 95% CI 1.08-1.48, P = .004), absence of fracture (OR 0.58, 95% CI 0.49-0.68, P < .001), severe head injury (OR 1.41, 95% CI 1.09-1.82, P = .008), and comatose presentation (1.82, 95% CI 1.15-2.89, P = .011) were associated with nonoperative treatment. Twenty-eight hospitals were outliers, and the median odds ratio was 2.02. Patients receiving nonoperative treatment had shorter LOS (mean difference -4.65 days). Nonoperative treatment was associated with lesser in-hospital morbidity (OR 0.49, 95% CI 0.37-0.63, P < .001) at the patient level. There was no difference in mortality. Operative decision-making for CCS is influenced by patient factors. There remains substantial variability between trauma centers not explained by case-mix differences. Nonoperative treatment was associated with shorter hospital LOS and lesser inpatient morbidity.

Measuring the effects of electronic government services and corrupt practices on information exchange: a comparison of public and private hospitals

PurposeHealth Information Exchange (HIE) is essential for the efficient and cost-effective delivery of health-care services. The provider’s administrative structure and external environment can substantially influence adopting technologies involving inter-organizational linkages, such as HIE. Using the theoretical lens of institutional theory, this study aims to compare how public and private hospitals' engagement in HIE is influenced by corruption and government online services or e-government usage.Design/methodology/approachThe study uses the positivist research design of secondary data analysis to test the six hypotheses proposed. Data from multiple third-party reliable sources, including the European Commission and World Bank, are combined into the final dataset consisting of observations from 1,442 hospitals across 30 countries in Europe. A multilevel modeling approach is used to associate country and hospital-level variables and test the hypothesis.FindingsThe study finds that, on average, a 10% increase in corruption leads to a 6.3% decrease, while a 10% increase in e-government leads to a 7% increase in the probability of HIE engagement for a hospital. The negative impact of corruption on average is 18% more in public than private hospitals, while the positive impact of e-government is 75% stronger in public in comparison to private hospitals. The study also finds that HIE engagements in health systems with predominantly public hospitals are more sensitive to corruption and e-government.Originality/valueTo the best of the authors’ knowledge, the study is one of the first to use the institutional view to test the influence of government actions and public providers' concentration on HIE engagement. The comparison of public and private institutions enriches our understanding of promoters and inhibitors of HIE.