Evidence map›Paper›PMID 38771944›Full record

ArticleAnnals of surgery2025

Unplanned Surgery in Dually Eligible Beneficiaries for Conditions that Should Be Treated Electively.

Shukri H A Dualeh, Sidra N Bonner, Nicholas J Kunnath, Andrew M Ibrahim

Abstract read
In one paragraph

Article in Annals of surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Shukri H A DualehUniversity of Michigan, Department of Surgery, Ann Arbor, MI.
Sidra N BonnerUniversity of Michigan, Department of Surgery, Ann Arbor, MI.
Nicholas J KunnathUniversity of Michigan, Center for Healthcare Outcomes and Policy, Institute for Healthcare Policy and Innovation, Ann Arbor, MI.
Andrew M IbrahimUniversity of Michigan, Department of Surgery, Ann Arbor, MI.

Funding

Physician Scientist Training in Age-Related DiseasesT32AG062403 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MIN, LILLIAN CHIANG, MODY, LONA · 2020 to 2025
$2.7M
Insurance Coverage and Workforce Incentives to Improve Access to Surgical CareR01DK137466 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Andrew Mounir Ibrahim, Jonathan William Scott · 2023 to 2026
$1.5M
AHRQ HHS R01 HS028606AHRQ HHS R18 HS028963NIA NIH HHS L30 AG084074NIA NIH HHS T32 AG062403NIDDK NIH HHS R01 DK137466
6 · The paper itself

Abstract

objectiveTo evaluate the rate of unplanned surgery among dually eligible beneficiaries for surgical conditions that should be treated electively. SUMMARY BACKGROUND DATA: Access-sensitive surgical conditions (eg, abdominal aortic aneurysm repair, colectomy for colon cancer, and ventral hernia repair) are ideally treated with elective surgery, but when left untreated have a natural history leading to unplanned surgery. Dually eligible beneficiaries may face systematic barriers to accessing surgical care.

methodsCross-sectional retrospective study of all beneficiaries who were eligible for both Medicare and Medicaid and underwent surgery for an access-sensitive surgical condition between 2016 and 2020. We compared the rate of unplanned surgery as well as 30-day mortality, complications, and readmissions for dually eligible versus non-dually eligible beneficiaries. Gender, age, race/ethnicity, comorbidities, teaching status, nursing ratio, hospital region and bed size, and surgery year were included in the risk-adjustment model.

resultsOut of 853,500 beneficiaries, 118,812 were dually eligible, with an average age (SD) of 75.2(7.7) years. Compared with nondually eligible beneficiaries, dually eligible beneficiaries had higher rates of unplanned surgery for access-sensitive surgical conditions (45.1% vs. 31.8%, P <0.001), 30-day mortality (2.9% vs. 2.6%, aOR=1.10 (1.07-1.14), P <0.001), complications (23.6% vs. 20.1%, aOR=1.23 (1.20-1.25), P <0.001), and 30-day readmissions (15.5% vs. 12.9%, aOR=1.24 (1.22-1.27), P <0.001). These differences narrowed significantly when evaluating elective procedures only.

conclusionsDually eligible beneficiaries were more likely to undergo unplanned surgery for access-sensitive surgical conditions, leading to worse rates of mortality, complications, and readmissions. Our findings suggest that improving rates of elective surgery for these conditions represents an actionable target to narrow the difference in postoperative outcomes between dually eligible and non-dually eligible beneficiaries.

Indexed as

Elective Surgical ProceduresHealth Services AccessibilityMedicaidMedicareAgedAged, 80 and overCross-Sectional StudiesFemaleHumansMalePatient ReadmissionPostoperative ComplicationsRetrospective StudiesUnited Statesaccess-sensitive surgical conditionsdually eligible beneficiariesunplanned surgery

Identifiers

PMID38771944
PMCPMC11579254

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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.