The Impact of Interhospital Competition on Treatment Strategy and Outcomes for Unruptured Intracranial Aneurysms

Association of Hospital Market Competition with Outcomes of Complex Cancer Surgery

BACKGROUND

The association of hospital market competition, financial costs, and quality of oncologic care has not been well-defined. This study sought to evaluate variations in patient outcomes and financial expenditures after complex cancer surgery across high- and low-competition markets.

METHODS

Medicare 100% Standard Analytic Files were used to identify patients with lung, esophageal, gastric, hepatopancreaticobiliary, or colorectal cancer who underwent surgical resection between 2018 and 2021. Data were merged with the annual hospital survey database, and the hospital market Herfindahl-Hirschman index was used to categorize hospitals into low- and high-concentration markets. Multi-level, multivariable regression models adjusting for patient characteristics (i.e., age, sex, comorbidities, and social vulnerability), year of procedure, and hospital factors (i.e., case volume, nurse-bed ratio, and teaching status) were used to assess the association between hospital market competition and outcomes.

RESULTS

Among 117,641 beneficiaries who underwent complex oncologic surgery, the mean age was 73.8 ± 6.1 years, and approximately one-half of the cohort was male (n = 56,243, 47.8%). Overall, 63.8% (n = 75,041) of the patients underwent care within a high-competition market. Notably, there was marked geographic variation relative to market competition. High versus low market-competition hospitals were more likely to be in high social vulnerability areas (35.1 vs 27.5%; p < 0.001), as well as care for racial/ethnic minority individuals (13.8 vs 7.7%; p < 0.001), and patients with more comorbidities (≥ 2 Elixhauser comorbidities: 63.1 vs 61.1%; p < 0.001). In the multivariable analysis, treatment at hospitals in high- versus low-competition markets was associated with lower odds of achieving a textbook outcome (odds ratio, 0.95; 95% confidence interval, 0.91-0.99; p = 0.009). Patients at high-competition hospitals had greater mean index hospitalization costs ($19,462.2 [16211.9] vs $18,844.7 [14994.7]) and 90-day post-discharge costs ($7807.8 [15431.3] vs $7332.8 [14038.2]) (both p < 0.001) than individuals at low-competition hospitals.

CONCLUSIONS

Hospital market competition was associated with poor achievement of an optimal postoperative outcome and greater hospitalization costs.

Heterogeneous effects of hospital competition on inpatient quality: an analysis of five common diseases in China

BACKGROUND

Many countries has introduced pro-competition policies in the delivery of healthcare to improve medical quality, including China. With the increasing intensity of competition in China's healthcare market, there are rising concerns among policymakers about the impact of hospital competition on quality. This study investigated heterogeneous effects of hospital competition on inpatient quality.

METHODS

We analyzed the inpatient discharge dataset and selected chronic obstructive pulmonary disease (COPD), ischemic stroke, pneumonia, hemorrhagic stroke, and acute myocardial infarction (AMI) as representative diseases. A total of 561,429 patients in Sichuan Province in 2017 and 2019 were included. The outcomes of interest were in-hospital mortality and 30-day unplanned readmissions. The Herfindahl-Hirschman Index was calculated using predicted patient flows to measure hospital competition. To address the spatial correlations of hospitals and the structure of the dataset, the multiple membership multiple classification model was employed for analysis.

RESULTS

Amid intensifying competition in the hospital market, our study discerned no marked statistical variance in the risk of inpatient quality across most diseases examined. Amplified competition exhibited a positive correlation with heightened in-hospital mortality for both COPD and pneumonia patients. Elevated competition escalated the risk of 30-day unplanned readmissions for COPD patients, while inversely affecting the risk for AMI patients.

CONCLUSIONS

There is the heterogeneous impact of hospital competition on quality across various diseases in China. Policymakers who intend to leverage hospital competition as a tool to enhance healthcare quality must be cognizant of the possible influences of it.

Outcomes for High-Risk Surgical Procedures Across High- and Low-Competition Hospital Markets

Importance

Maintaining competition among hospitals is increasingly seen as important to achieving high-quality outcomes. Whether or not there is an association between hospital market competition and outcomes after high-risk surgery is unknown.

Objective

To evaluate whether there is an association between hospital market competition and outcomes after high-risk surgery.

Design, Setting, and Participants

We performed a retrospective study of Medicare beneficiaries who received care in US hospitals. Participants were 65 years and older who electively underwent 1 of 10 high-risk surgical procedures from 2015 to 2018: carotid endarterectomy, mitral valve repair, open aortic aneurysm repair, lung resection, esophagectomy, pancreatectomy, rectal resection, hip replacement, knee replacement, and bariatric surgery. Hospitals were categorized into high-competition and low-competition markets based on the hospital market Herfindahl-Hirschman index. Comparisons of 30-day mortality and 30-day readmissions were risk-adjusted using a multivariate logistic regression model adjusting for patient factors (age, sex, comorbidities, and dual eligibility), year of procedure, and hospital characteristics (nurse ratio and teaching status). Data were analyzed from May 2022 to March 2023.

Main Outcomes and Measures

Thirty-day postoperative mortality and readmissions.

Results

A total of 2 242 438 Medicare beneficiaries were included in the study. The mean (SD) age of the cohort was 74.1 (6.4) years, 1 328 946 were women (59.3%), and 913 492 were men (40.7%). When examined by procedure, compared with low-competition hospitals, high-competition market hospitals demonstrated higher 30-day mortality for 2 of 10 procedures (mitral valve repair: odds ratio [OR], 1.11; 95% CI, 1.07-1.14; and carotid endarterectomy: OR, 1.06; 95% CI, 1.03-1.09) and no difference for 5 of 10 procedures (open aortic aneurysm repair, bariatric surgery, esophagectomy, knee replacement, and hip replacement; ranging from OR, 0.97; 95% CI, 0.94-1.00, for hip replacement to OR, 1.09; 95% CI, 0.94-1.26, for bariatric surgery). High-competition hospitals also demonstrated 30-day readmissions that were higher for 5 of 10 procedures (open aortic aneurysm repair, knee replacement, mitral valve repair, rectal resection, and carotid endarterectomy; ranging from OR, 1.01; 95% CI, 1.00-1.02, for knee replacement to OR, 1.05; 95% CI, 1.02-1.08, for rectal resection) and no difference for 3 procedures (bariatric surgery: OR, 1.03; 95% CI, 0.99-1.07; esophagectomy: OR, 1.02; 95% CI, 0.99-1.06; and pancreatectomy: OR, 1.00; 95% CI, 0.99-1.01). Hospitals in high-competition compared with low-competition markets cared for patients who were older (mean [SD] age of 74.4 [6.6] years vs 74.0 [6.2] years, respectively; P < .001), were more likely to be racial and ethnic minority individuals (77 322/450 404 [17.3%] vs 23 328/444 900 [5.6%], respectively; P < .001), and had more comorbidities (≥2 Elixhauser comorbidities, 302 415/450 404 [67.1%] vs 284 355/444 900 [63.9%], respectively; P < .001).

Conclusions and Relevance

This study found that hospital market competition was not consistently associated with improved outcomes after high-risk surgery. Efforts to maintain hospital market competition may not achieve better postoperative outcomes.

Predicting access to postoperative treatment after glioblastoma resection: an analysis of neighborhood-level disadvantage using the Area Deprivation Index (ADI)

PURPOSE

Social determinants of health (SDoH)-socioeconomic and environmental factors-impact outcomes. The Area Deprivation Index (ADI), a composite of seventeen SDoH factors, has been correlated with poorer outcomes. We aimed to compare outcomes and treatment access for glioblastoma, a universally fatal malignant brain tumor, in patients more (ADI 34-100%) versus less disadvantaged (ADI 0-33%).

METHODS

A 5-year retrospective study of Rhode Island Hospital and Mayo Clinic databases was conducted from 2012 to 2017 for patients ≥ 18 years with glioblastoma. Patient addresses were matched to ADI percentiles and grouped into more (top 66% ADI) and less disadvantaged. Adjusted multivariable regressions were used to compare outcomes between groups.

RESULTS

A total of 434 patients met inclusion; 92.9% were insured, 56.2% were more disadvantaged (n = 244), and the more disadvantaged cohort was younger on average (62 years). After adjustment, the more disadvantaged group had decreased odds of receiving gross total resection (adjusted odds ratio (aOR) 0.43, 95% CI [0.27-0.68]; p < 0.001). This cohort also had decreased odds of undergoing chemotherapy (aOR 0.51[0.26-0.98]), radiation (aOR 0.39[0.20-0.77]), chemoradiation (aOR 0.42[0.23-0.77]), tumor-treating fields (aOR 0.39[0.16-0.93]), and clinical trial participation (aOR 0.47[0.25-0.91]). No differences in length of survival or postoperative Karnofsky Performance Status Scale were observed.

CONCLUSION

More disadvantaged glioblastoma patients had decreased odds of receiving gross total resection. They also exhibited decreased odds of receiving standard of care like chemoradiation as well as participating in a clinical trial, compared to the less disadvantaged group. More research is needed to identify modifiable SDoH barriers to post-operative treatment in disadvantaged patients with glioblastoma.

The National Inpatient Sample: A Primer for Neurosurgical Big Data Research and Systematic Review

OBJECTIVE

The National Inpatient Sample - the largest all-payer inpatient database in the United States - is an important instrument for big data analysis of neurosurgical inquiries. However, earlier research has determined that many NIS studies are limited by common methodological pitfalls. In this study, we provide the first primer of NIS methodological procedures in the setting of neurosurgical research and review all published neurosurgical studies utilizing the NIS.

METHODS

We designed a protocol for neurosurgical big data research using the NIS, based on the authors' subject matter expertise, NIS documentation, and input and verification from the Healthcare Cost and Utilization Project. We subsequently used a comprehensive search strategy to identify all neurosurgical studies utilizing the NIS in the PubMed and MEDLINE, Embase, and Web of Science databases from inception to August 2021. Studies underwent qualitative categorization (years of the NIS studied, neurosurgical subspecialty, age group, and thematic focus of study objective) and analysis of longitudinal trends.

RESULTS

We identified a canonical, four-step protocol for NIS analysis: study population selection, defining additional clinical variables, identification and coding of outcomes, and statistical analysis. Methodological nuances discussed include identifying neurosurgery-specific admissions, addressing missing data, calculating additional severity and hospital-specific metrics, coding perioperative complications, and applying survey weights to make nationwide estimates. Inherent database limitations and common pitfalls of NIS studies discussed include lack of disease process-specific variables and data following the index admission, inability to calculate certain hospital-specific variables after 2011, performing state-level analyses, conflating hospitalization charges and costs, and not following proper statistical methodology for performing survey-weighted regression. In a systematic review, we identified 647 neurosurgical studies utilizing the NIS. While almost 60% of studies were published after 2015, <10% of studies analyzed NIS data after 2015. The average sample size of studies was 507,352 patients (standard deviation=2,739,900). Most studies analyzed cranial procedures (58.1%) and adults (68.1%). The most prevalent topic areas analyzed were surgical outcome trends (35.7%) and health policy and economics (17.8%), while patient disparities (9.4%) and surgeon or hospital volume (6.6%) were the least studied.

CONCLUSIONS

We present a standardized methodology to analyze the NIS, systematically review the state of the NIS neurosurgical literature, suggest potential future directions for neurosurgical big data inquiries, and outline recommendations to improve the design of future neurosurgical data instruments.