Evidence map›Paper›PMID 29051001›Full record

ArticleUrology2018

Episode-based Payment Variation for Urologic Cancer Surgery.

Chad Ellimoottil, Jonathan Li, Zaojun Ye, James M Dupree, Hye Sung Min, Deborah Kaye, Lindsey A Herrel, David C Miller

Open access · greenAbstract read
In one paragraph

Article in Urology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
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

8 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
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  5. Review
  6. Cardiac Rehabilitation Use After Percutaneous Coronary Intervention.Journal of the American College of Cardiology · 2019
    Article
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  8. Observational
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Chad EllimoottilInstitute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan; Dow Division of Health Services Research, Department of Urology, Ann Arbor, Michigan. Electronic address: cellimoo@med.umich.edu.
Jonathan LiInstitute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan; Dow Division of Health Services Research, Department of Urology, Ann Arbor, Michigan.
Zaojun YeInstitute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan; Dow Division of Health Services Research, Department of Urology, Ann Arbor, Michigan.
James M DupreeInstitute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan; Dow Division of Health Services Research, Department of Urology, Ann Arbor, Michigan.
Hye Sung MinInstitute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan; Dow Division of Health Services Research, Department of Urology, Ann Arbor, Michigan.
Deborah KayeInstitute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan; Dow Division of Health Services Research, Department of Urology, Ann Arbor, Michigan.
Lindsey A HerrelInstitute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan; Dow Division of Health Services Research, Department of Urology, Ann Arbor, Michigan.
David C MillerInstitute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, Michigan; Dow Division of Health Services Research, Department of Urology, Ann Arbor, Michigan.
University of Michigan · US

Funding

Understanding optimal delivery systems for cancer careR01CA174768 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MILLER, DAVID C · 2014 to 2018
$2.0M
Variation in surgical care for early-stage kidney cancerF32CA123819 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI MILLER, DAVID C · 2006 to 2006
$58k
AHRQ HHS K08 HS018346NCI NIH HHS F32 CA123819NCI NIH HHS R01 CA174768
6 · The paper itself

Abstract

objectiveTo investigate payment variation for 3 common urologic cancer surgeries and evaluate the potential for applying bundled payment programs to these procedures.

methodsUsing 2008-2011 Surveillance, Epidemiology, and End Results-Medicare linked data, we identified all beneficiaries aged greater than 65 years who underwent cystectomy, prostatectomy, or nephrectomy for cancer. Total episode payments were determined by aggregating hospital, professional, and post-acute care claims from the index surgical hospitalization through 90 days post discharge. Total episode payments were then compared to examine hospital level-variation within each procedure type and the specific payment components (ie, index hospitalization, professional, readmission, and post-acute care) driving spending variation.

resultsNinety-day episodes of care were identified for 1849 cystectomies, 8770 prostatectomies, and 4304 nephrectomies. We observed wide variation in mean episode payments for all 3 conditions (cystectomy mean $35,102: range $24,112-$57,238, prostatectomy mean $10,803: range $8,816-$17,877, nephrectomy mean $17,475: range $11,681-$26,711). Majority of payment variation was attributable to index hospitalization and post-acute care for cystectomy and nephrectomy and professional payments for prostatectomy. The most expensive hospitals by procedure each demonstrated a unique opportunity for spending reduction due to individual differences in component payment patterns between hospitals.

conclusionNinety-day episode payments for urologic cancer surgery vary widely across hospitals in the United States. The key drivers of this payment variation differ for individual procedures and hospitals. Accordingly, hospitals will need individualized data and clinical re-design strategies to succeed with implementation of episode-based payment models for urologic cancer care.

Indexed as

Episode of CareReimbursement MechanismsAgedAged, 80 and overCystectomyHumansNephrectomyProstatectomyUrologic Neoplasms

Identifiers

PMID29051001
PMCPMC7437608
OpenAlexW2765970950

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.