Community social vulnerability and the 340B Drug Pricing Program: Evaluating predictors of 340B participation among critical access hospital.

PURPOSE: The federal 340B Drug Pricing Program allows eligible hospitals, including critical access hospitals (CAHs), to obtain outpatient drugs at a discounted rate. CAHs likely benefit from 340B participation because they are often under-resourced and serve at-risk patient populations. The objective of this study was to understand predictors of 340B program participation among CAHs, and how participation varies with community-level social vulnerability. METHODS: We used a cross-sectional study design to assess the relationship between 340B participation in 2019 and community vulnerability status using 2018 data from the CDC's social vulnerability index (SVI) among acute care CAHs. Analyses used linear probability models adjusted for hospital-level characteristics. FINDINGS: In bivariate analyses, CAHs participating in the 340B program had lower overall social vulnerability scores, relative to nonparticipating, eligible, and ineligible CAHs, respectively (43.8 vs. 48.7 vs. 64.7, p < 0.10). In adjusted regression models, greater community vulnerability rankings due to socioeconomic status (-0.129, p < 0.05) and minority status and language (-0.092, p < 0.05) were associated with decreased 340B participation. Higher hospital operating margin was associated with increased 340B participation (0.163, p < 0.05). Although the number of for-profit CAHs ineligible for 340B was small, they had the highest community-level social vulnerability score and lowest hospital operating margin on average. CONCLUSIONS: CAHs located in areas of high community vulnerability are less likely to participate in the 340B program. Some vulnerable patient populations served by CAHs may be excluded from 340B program benefits.

Hospital Finances During the First Two Years of the COVID-19 Pandemic: Evidence From Washington State Hospitals.

The COVID-19 pandemic created a broad array of challenges for hospitals. These challenges included restrictions on admissions and procedures, patient surges, rising costs of labor and supplies, and a disparate impact on already disadvantaged populations. Many of these intersecting challenges put pressure on hospitals' finances. There was concern that financial pressure would be particularly acute for hospitals serving vulnerable populations, including safety-net (SN) hospitals and critical access hospitals (CAHs). Using data from hospitals in Washington State, we examined changes in operating margins for SN hospitals, CAHs, and other acute care hospitals in 2020 and 2021. We found that the operating margins for all three categories of hospitals fell from 2019 to 2020, with SNs and CAHs sustaining the largest declines. During 2021, operating margins improved for all three hospital categories but SN operating margins still remained negative. Both changes in revenue and changes in expenses contributed to observed changes in operating margins. Our study is one of the first to describe how the financial effects of COVID-19 differed for SNs, CAHs, and other acute care hospitals over the first two years of the pandemic. Our results highlight the continuing financial vulnerability of SNs and demonstrate how the factors that contribute to profitability can shift over time.

The Impact of Palliative Medicine Consultation on Readmission Rates and Hospital Costs in Surgical Patients Requiring Prolonged Mechanical Ventilation.

BACKGROUND: The use of palliative care for critically ill hospitalized patients has expanded. However, it is still underutilized in surgical specialties. Postsurgical patients requiring prolonged mechanical ventilation have increased mortality and costs of care; outcomes from adding palliative care services to this population have been poorly investigated. The objective of this study was to determine the impact of palliative medicine consultation on readmission rates and hospitalization costs in postsurgical patients requiring prolonged mechanical ventilation. METHODS: The Nationwide Readmissions Database was queried for adults (> 18 years) between the years 2010 and 2014 who underwent a major operation (Healthcare Cost and Utilization Project [HCUP] data element ORPROC = 1), required mechanical ventilation for ≥ 96 consecutive hours (ICD-9-CM V46.1), and survived until discharge. Among these, patients who received a palliative medicine consultation during hospitalization were identified using the ICD-9-CM diagnosis code V66.7. RESULTS: Of 53,450 included patients, 3.4% received a palliative care consultation. Compared to patients who did not receive a palliative care consultation, patients who did receive a consultation had a lower readmission rate (14.8% vs. 24.8%, p < 0.001) and lower average cost of hospitalization during the initial admission ($109,007 vs. $124,218, p < 0.001), findings that persisted after multivariable logistic regression. CONCLUSION: Utilization of palliative care in surgical patients remains low. Palliative care consultation in postsurgical patients requiring prolonged mechanical ventilation was associated with lower cost and rate of readmission. Further work is needed to integrate palliative care services with surgical care.

Variations in Cost and Readmissions of Patients in the Bundled Payment for Care Improvement Bundle for Hip and Femur Fractures.

INTRODUCTION: The Bundled Payment for Care Improvement (BPCI) for hip and femur fractures is an effort to increase care quality and coordination at a lower cost. The bundle includes all patients undergoing an operative fixation of a hip or femur fracture (diagnosis-related group codes 480-482). This study aims to investigate variance in the hospital cost and readmission rates for patients within the bundle. MATERIALS AND METHODS: The study is a retrospective analysis of patients ≥65 years old billed for a diagnosis-related groups 480-482 in 2016 in the National Readmission Database. Cost of admission and length of stay were compared between patients who were or were not readmitted. Regression analysis was used to determine the effects of the primary procedure code and anatomical location of the femur fracture on costs, length of stay, and readmission rates. RESULTS: Patients that were readmitted within 90 days of surgery had an increased cost on initial admission ($18,427 vs $16,844, P < .0001), and an increased length of stay (6.24 vs 5.42, P < .0001). When stratified by procedure, patients varied in readmission rates (20.7% vs 19.6% vs 21.8%), initial cost, and length of stay (LOS). Stratification by anatomical location also led to variation in readmission rates (20.7% vs 18.3% vs 20.6%), initial cost, and LOS. CONCLUSION: The hip and femur fractures bundle includes a great number of procedures with variance in cost, readmission, and length of stay. This amount of variation may make standardization difficult and may put the hospital at potential financial risk.

Financial Performance of Hospitals in the Appalachian Region Under the Hospital Readmissions Reduction Program and Hospital Value-Based Purchasing Program.

PURPOSE: The Hospital Readmission and Reduction Program (HRRP) and Hospital Value-Based Purchasing Program (HVBP) propose to improve quality of patient care by either rewarding or penalizing hospitals through inpatient reimbursement. This study analyzes the effect of both programs on profitability of hospitals located in the Appalachian Region (AR) compared to hospitals in Appalachian states and the rest of the United States. METHODS: This study used a retrospective research design with a longitudinal unbalanced panel dataset from 2008 to 2015. Hospitals participating in both HRRP and HVBP during this time frame were included in the study. A difference-in-difference model with hospital-level fixed effects, controlling for hospital and market characteristics, was used to determine effects of both programs on profitability of hospitals serving the AR, Appalachian states, and the rest of the United States. FINDINGS: After implementation of HRRP and HVBP, only hospitals located in Appalachian states experienced a significant decrease in operating margin (-1.14 percentage points). Unexpectedly, during the same time period, total margin increased significantly for hospitals located in the AR (1.05 percentage points), Appalachian states (1.71 percentage points), and the rest of the United States (2.38 percentage points). CONCLUSIONS: HRRP and HVBP financially incentivize hospitals to focus efforts on improving patient care. The programs may not have the anticipated results. Increases in total margin for all hospitals during the study period indicate access to nonpatient revenues, offsetting the financial penalties from both programs. This revenue source may undermine the program's objectives of delivering value and achieving quality outcomes.

The Effect of the Magnet Recognition Signal on Hospital Financial Performance.

EXECUTIVE SUMMARY: The objective of this study was to investigate the effect of the Magnet Recognition (MR) signal on hospital financial performance. MR is a quality designation granted by the American Nurses Credentialing Center (ANCC). Growing evidence shows that MR hospitals are associated with various interrelated positive outcomes that have been theorized to affect hospital financial performance.In this study, which covered the period from 2000 to 2010, we applied a pre-post research design using a longitudinal, unbalanced panel of MR hospitals and hospitals that had never received MR designation located in urban areas in the United States. We obtained data for this analysis from Medicare's Hospital Cost Report Information System, the American Hospital Association Annual Survey Database, the Health Resources & Services Administration's Area Resource File, and the ANCC website. Propensity score matching was used to construct the final study sample. We then applied a difference-in-difference model with hospital fixed effects to the matched hospital sample to test the effect of the MR signal, while controlling for both hospital and market characteristics.According to signaling theory, signals aim to reduce the imbalance of information between two parties, such as patients and providers. The MR signal was found to have a significant positive effect on hospital financial performance. These findings support claims in the literature that the nonfinancial benefits resulting from MR lead to improved financial performance. In the current healthcare environment in which reimbursement is increasingly tied to delivery of quality care, healthcare executives may be encouraged to pursue MR to help hospitals maintain their financial viability while improving quality of care.

Major traumatic brain injury: time to tertiary care and the impact of a clinical guideline.

BACKGROUND: To achieve timely access to neurosurgical care for adult brain-injured patients, a Head Injury Guideline was implemented to standardize the emergency department evaluation and management of these patients. The goals of this study were to document times to neurosurgical care for patients with major traumatic brain injury presenting to a Provincial emergency room and to evaluate the impact of the Guideline on timely access to definitive care. METHODS: Data collected prospectively and stored in the Nova Scotia Trauma Registry and the Emergency Health Services Communications and Dispatch Centre database were analyzed for patients with head abbreviated injury scale score (AIS)≥3. Several time intervals from admission to a referring hospital to access to tertiary care were determined and compared for the periods before Guideline implementation, the implementation phase, and after implementation. RESULTS: The time elapsed before calling the provincial Trauma Hotline was not statistically different after Guideline implementation for polytrauma patients with head AIS score≥3 (n=388) during the preimplementation (2:34±1:30; median time in hours:minutes±standard deviation), implementation (1:57±2:33) and postimplementation (2:31±4:06) periods. Subset group analysis of patients with isolated head injuries AIS score≥3 (n=99) also showed no statistical difference in preimplementation (1:51±1:42), implementation (2:49±2:57), and postimplementation (3:10±4:58) times. Examination of overall time to tertiary care revealed prolonged transfer times and that the Guideline had no influence on either the polytrauma patient group (preimplementation, 4:20±1:41; implementation, 5:01±2:55; and postimplementation 4:46±4:22) or those with isolated head injuries (preimplementation, 3:39±1:47; implementation, 6:06±4:00; and postimplementation, 5:13±4:59). CONCLUSIONS: Times to tertiary care are lengthy and have not been reduced by Guideline implementation. System changes beyond Guideline implementation are required to provide timely access to tertiary care for patients with major head injury.