Do hospital factors impact readmissions and mortality after colorectal resections at minority-serving hospitals?

Hechenbleikner, Elizabeth M.; Zheng, Cheng; Lawrence, S; Hong, Young Ki; Shara, Nawar; Johnson, Lynt B.; Al‐Refaie, Waddah B.

doi:10.1016/j.surg.2016.08.041

Cited by 15 publications

(8 citation statements)

References 18 publications

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“… 5 In colorectal surgery, minority-serving hospitals have higher readmission rates than non-minority-serving hospitals, and patient-level factors account for 65 % of this difference. 20 These inconsistent findings may be explained by the fact that race and ethnicity are non-modifiable patient-level factors that are potential proxies for implicit bias and systemic racism and often confounded with other social risk factors.…”

Section: Discussionmentioning

confidence: 99%

Value of Ambulatory Modified Radical Mastectomy

et al. 2023

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Background Modified radical mastectomy (MRM) still is largely performed in inpatient settings. This study sought to determine the value (expenditures and complications) of ambulatory MRM. Methods Health Care Utilization Project (HCUP) state databases from 2016 were queried for patients who underwent MRM. The study examined rates of 30-day readmission for surgical-site infection (SSI) or hematoma, charges by index care setting, and predictors of 30-day readmission. Results Overall, 8090 patients underwent MRM: 5113 (63 %) inpatient and 2977 (37 %) ambulatory patients. Compared with the patients who underwent inpatient MRM, those who underwent ambulatory MRM were older (61 vs. 59 years), more often white (66 % vs. 57 %), in the lowest income quartile (28 % vs. 21 %), insured by Medicare (43 % vs. 33 %) and residents in a small metro area (6 % vs. 4 %) (all p < 0.01). Of the 5113 patients treated as inpatients, 126 (2.5 %) were readmitted, whereas 50 (1.7 %) of the ambulatory patients were readmitted ( p = 0.02). The adjusted charge for inpatient MRM without readmission was $113,878 (range, $107,355–120,402) compared with $94,463 (range, $86,021–102,907) for ambulatory MRM, and the charge for inpatient MRM requiring readmission was $159,355 (range, $147,142–171,568) compared with $139,940 (range, $125,808–154,073) for ambulatory MRM (all p < 0.01). This difference remained significant after adjustment for hospital length of stay. Adjusted logistic regression showed that the ambulatory setting was protective for readmission (odds ratio, 0.49; 95 % confidence interval, 0.35–0.70; p < 0.01). Conclusions The analyses suggest that ambulatory MRM is both safe and less expensive. The findings advocate that MRM, a last holdout of inpatient care within breast surgical oncology, can be transitioned to the ambulatory setting for appropriate patients.

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Section: Discussionmentioning

confidence: 99%

Value of Ambulatory Modified Radical Mastectomy

et al. 2023

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“…This reflects the idea that areas with higher percentages of racial and ethnic diversity tended to have lower‐performing hospitals, regardless of what specific racial or ethnic minority group predominated. While many studies of inequality in access to quality health care concentrate on the lower availability of health care, there is a growing body of literature reporting on the association between hospital quality and minority‐service hospital status across multiple health states and conditions 4,5,8,10,13,26–49 . Minority‐serving hospitals have also been shown to have lower scores for reported patient experience, despite findings that minority patients report better experiences overall 12,50,51 .…”

Section: Discussionmentioning

confidence: 99%

The geography of Medicare's hospital value‐based purchasing in relation to market demographics

McLaughlin

Boscoe²

2023

Health Services Research

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Objective To illustrate the association between the sociodemographic characteristics of hospital markets and the geographic patterns of Medicare hospital value‐based purchasing (HVBP) scores. Data Sources and Study Setting This is a secondary analysis of United States hospitals with a HVBP Total Performance Score (TPS) for 2019 in the Centers for Medicare and Medicaid Services (CMS) Hospital Compare database (4/2021 release) and American Community Survey (ACS) data for 2015–2019. Study Design This is a cross‐sectional study using spatial multivariable autoregressive models with HVBP TPS and component domain scores as dependent variables and hospital market demographics as the independent variables. Data Collection/Extraction Methods We calculated hospital market demographics using ZIP code level data from the ACS, weighted the 2019 CMS inpatient Hospital Service Area file. Principal Findings Spatial autoregressive models using eight nearest neighbors with diversity index, race and ethnicity distribution, families in poverty, unemployment, and lack of health insurance among residents ages 19–64 years provided the best model fit. Diversity index had the highest statistically significant contribution to lower TPS (ß = −12.79, p < 0.0001), followed by the percent of the population coded to “non‐Hispanic, some other race” (ß = −2.59, p < 0.0023), and the percent of families in poverty (ß = −0.26, p < 0.0001). Percent of the population was non‐Hispanic American Indian/Alaskan Native (ß = 0.35, p < 0.0001) and percent non‐Hispanic Asian (ß = 0.12, p < 0.02071) were associated with higher TPS. Lower predicted TPS was observed in large urban cities throughout the US as well as in states throughout the Southeastern US. Similar geographic patterns were observed for the predicted Patient Safety, Person and Community Engagement, and Efficiency and Cost Reduction domain scores but are not for predicted Clinical Outcomes scores. Conclusions The lower predicted scores seen in cities and in the Southeastern region potentially reflect an inherent—that is, structural—association between market sociodemographics and HVBP scores.

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“…bed size, teaching status, rural/urban location) and outcomes. 20,21 SID have also been used to describe the burden of disease, 22 evaluate disparities, 8,23 challenge measures of hospital quality, 24,25 describe inter-hospital variation, 26 and evaluate health policy initiatives, 27 including differences in implementation at the state level. 28…”

Section: Data Resource Usementioning

confidence: 99%

Data resource profile: State Inpatient Databases

Metcalfe

Zogg

Haut

et al. 2019

International Journal of Epidemiology

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Profile in a nutshell• The SIDs contain data on almost all inpatient discharges from hospitals in participating states.They were established from a range of data sources for the specific purpose of undertaking health-related research.• The first SIDs are available starting in 1990.• SID data elements vary by year and state, but typically include demographic characteristics, admission and discharge details, diagnoses and procedures, charge/cost and payment details, and outcomes such as in-hospital death. They are linkable to information contained in AHA.• Some SIDs permit longitudinal linkage so that individual patients can be tracked between hospital admissions. Patients can often also be tracked through Emergency Department visits through linkage to other state-level HCUP databases.• Access to data is swift and at reasonable reduced cost, particularly for non-profit and student researchers. Data Resource Basics ScopeThe State Inpatient Databases (SID) comprise a collection of state-specific encounter-level administrative claims from 32/50 states in the United States (US). These databases are maintained by the US Agency for Healthcare Research and Quality (AHRQ) as a part of the organization's Healthcare Cost and Utilization Project (HCUP). As part of a family of six other HCUP databases (Table 1), the SIDs represent the largest collection of longitudinal hospital care data in the US inclusive of all insurance payers (e.g. Medicare, Medicaid, private insurance, and uninsured) and all patient ages. Taken together, the SIDs capture more than 97% of all eligible hospital discharges within each state. Purpose of data collectionOriginally created as the "Agency for Health Care Policy and Research," AHRQ was established by the US Omnibus Budget Reconciliation Act of 1989 with the purpose of enhancing the "quality, appropriateness, and effectiveness of health care services […] through the establishment of a broad case of scientific research." 1 In particular, the Act required that databases be created to support healthcare research. The HCUP-family of databases were, therefore, established as a federal-stateindustry partnership sponsored by AHRQ in order to "enable research on a broad range of health policy issues, including cost and quality of health services, medical practice patterns, access to health care programs, and outcomes of treatment at the national, state, and local market levels." 2 The HCUP SIDs maintain data expressly for research purposes dating back to 1990. StructureThe SID share a common structure, although the precise list of available data elements vary slightly by state and calendar year. Differences in key variables used to link SID data are presented in Table 2.The SIDs are organised by calendar year based on the date of hospital discharge. The data for each SID

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Do hospital factors impact readmissions and mortality after colorectal resections at minority-serving hospitals?

Cited by 15 publications

References 18 publications

Value of Ambulatory Modified Radical Mastectomy

Value of Ambulatory Modified Radical Mastectomy

The geography of Medicare's hospital value‐based purchasing in relation to market demographics

Data resource profile: State Inpatient Databases

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