Evidence map›Paper›PMID 27261414›Full record

ArticleJournal of the American College of Surgeons2016

Vulnerable Hospitals and Cancer Surgery Readmissions: Insights into the Unintended Consequences of the Patient Protection and Affordable Care Act.

Young Hong, Chaoyi Zheng, Elizabeth Hechenbleikner, Lynt B Johnson, Nawar Shara, Waddah B Al-Refaie

Abstract read
In one paragraph

Article in Journal of the American College of Surgeons, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Readmissions after colorectal surgery: not all are equal.International journal of colorectal disease · 2018
    Article
  4. Review
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Young HongDepartment of Surgery, MedStar Georgetown University Hospital, Washington, DC.
Chaoyi ZhengDepartment of Surgery, MedStar Georgetown University Hospital, Washington, DC.
Elizabeth HechenbleiknerDepartment of Surgery, MedStar Georgetown University Hospital, Washington, DC.
Lynt B JohnsonDepartment of Surgery, MedStar Georgetown University Hospital, Washington, DC.
Nawar SharaMedStar Health Research Institute, Washington, DC.
Waddah B Al-RefaieDepartment of Surgery, MedStar Georgetown University Hospital, Washington, DC; MedStar Health Research Institute, Washington, DC; MedStar-Georgetown Surgical Outcomes Research Center, Washington, DC; Georgetown Lombardi Comprehensive Cancer Center, Washington, DC. Electronic address: wba6@georgetown.edu.

Funding

Maternal Morbidity and Mortality: Risk Factors, Early Detection and Personalized InterventionUL1TR001409 · NCATS · GEORGETOWN UNIVERSITY · PI GONDRE-LEWIS, MARJORIE C, MELLMAN, THOMAS A · 2015 to 2024
$37.8M
Kidney and Cardiovascular Disease in American IndiansF32DK075204 · NIDDK · MEDSTAR HEALTH RESEARCH INSTITUTE · PI SHARA, NAWAR · 2006 to 2007
$73k
NCATS NIH HHS UL1 TR001409NIDDK NIH HHS F32 DK075204
6 · The paper itself

Abstract

backgroundPenalties from the Hospital Readmission Reduction Program can push financially strained, vulnerable patient-serving hospitals into additional hardship. In this study, we quantified the association between vulnerable hospitals and readmissions and examined the respective contributions of patient- and hospital-related factors.

methodsA total of 110,857 patients who underwent major cancer operations were identified from the 2004-2011 State Inpatient Database of California. Vulnerable hospitals were defined as either self-identified safety net hospitals (SNHs) or hospitals with a high percentage of Medicaid patients (high Medicaid hospitals [HMHs]). We used multivariable logistic regression to determine the association between vulnerable hospitals and readmission. Patient and hospital contributions to the elevation in odds of readmission were assessed by comparing estimates from models with different subsets of predictors.

resultsOf the 355 hospitals, 13 were SNHs and 31 were HMHs. After adjusting for Hospital Readmission Reduction Program variables, SNHs had higher 30-day (odds ratio [OR] = 1.32; 95% CI, 1.18-1.47), 90-day (OR = 1.28; 95% CI, 1.18-1.38), and repeated readmissions (OR = 1.33; 95% CI, 1.18-1.49); HMHs also had higher 30-day (OR = 1.18; 95% CI, 1.05-1.32), 90-day (OR = 1.28; 95% CI, 1.16-1.42), and repeated readmissions (OR = 1.24; 95% CI, 1.01-1.54). Compared with patient characteristics, hospital factors accounted for a larger proportion of the increase in odds of readmission among SNHs (60% to 93% vs 24% to 39%), but a smaller proportion among HMHs (9% to 15% vs 60% to 115%).

conclusionsVulnerable status of hospitals is associated with higher readmission rates after major cancer surgery. These findings reinforce the call to account for socioeconomic variables in risk adjustments for hospitals who serve a disproportionate share of disadvantaged patients.

Indexed as

Patient Protection and Affordable Care ActAdolescentAdultAgedAged, 80 and overCaliforniaDatabases, FactualFemaleHumansLogistic ModelsMaleMedicaidMiddle AgedNeoplasmsPatient ReadmissionQuality Indicators, Health Care

Identifiers

PMID27261414
PMCPMC5266542

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.