Evidence map›Paper›PMID 25746747›Full record

ArticleCritical care medicine2015

Gaming hospital-level pneumonia 30-day mortality and readmission measures by legitimate changes to diagnostic coding.

Michael W Sjoding, Theodore J Iwashyna, Justin B Dimick, Colin R Cooke

Open access · greenAbstract read
In one paragraph

Article in Critical care medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
7.7field-weighted citation impact, top 2% 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

25 citing papers in PubMed, 48 citations in OpenAlex.

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  20. Impact of Policies on the Rise in Sepsis Incidence, 2000-2010.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2016
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Michael W Sjoding1Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI. 2VA Center for Clinical Management Research, Ann Arbor, MI. 3Institute for Social Research, Ann Arbor, MI. 4Department of Surgery, University of Michigan, Ann Arbor, MI. 5Center for Healthcare Outcomes and Policy, Institute for Healthcare Innovation & Policy, University of Michigan, Ann Arbor, MI.
Theodore J Iwashyna
Justin B Dimick
Colin R Cooke
University of Michigan–Ann Arbor · USAnn Arbor Center for Independent Living · US

Funding

PULMONARY CELLULAR AND MOLECULAR BIOLOGY TRAININGT32HL007749 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Robert Pickett Dickson · 1993 to 2026
$19.9M
Research BaseP30DK092926 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARY ELLEN MICHELE HEISLER, ADESUWA B OLOMU · 2011 to 2026
$10.0M
Evaluating Policies for Improving Surgical Care in the ElderlyR01AG039434 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DIMICK, JUSTIN BRIGHAM · 2011 to 2019
$2.9M
Understanding Variation in the Use of Critical Care ServicesK08HS020672 · AHRQ · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI COOKE, COLIN · 2012 to 2016
$768k
Longterm Impact of Natural Disasters on Disability and Health in Older AmericansR21AG044752 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI IWASHYNA, THEODORE J · 2013 to 2014
$428k
AHRQ HHS K08 HS020672AHRQ HHS K08HS020672NHLBI NIH HHS L30 HL090280NHLBI NIH HHS T32 HL007749NHLBI NIH HHS T32HL007749NIA NIH HHS R01 AG039434NIA NIH HHS R01AG039434NIA NIH HHS R21 AG044752NIA NIH HHS R21AG044752NIDDK NIH HHS P30 DK092926
6 · The paper itself

Abstract

objectiveRisk-standardized 30-day mortality and hospital readmission rates for pneumonia are increasingly being tied to hospital reimbursement to incentivize the delivery of high-quality care. Such measures may be susceptible to gaming by recoding patients with pneumonia to a primary diagnosis of sepsis or respiratory failure. We sought to determine the degree to which hospitals can game mortality or readmission measures and change their rankings by recoding patients with pneumonia. DESIGN AND

settingSimulated experimental study of 2,906 U.S. acute care hospitals with at least 25 admissions for pneumonia using 2009 Medicare data. PATIENTS: Elderly (age ≥ 65 yr) Medicare fee-for-service beneficiaries hospitalized with pneumonia. Patients eligible for recoding to sepsis or respiratory failure were those with a principal International Classification of Diseases, 9th Edition, Clinical Modification, discharge code for pneumonia and secondary codes for respiratory failure or acute organ dysfunction.

interventionsNone. MEASUREMENTS AND MAIN

resultsWe measured the number of hospitals that improved their pneumonia mortality or readmission rates after recoding eligible patients. When a sample of 100 hospitals with pneumonia mortality rates above the 50th percentile recoded all eligible patients to sepsis or respiratory failure, 90 hospitals (95% CI, 84-95) improved their mortality rate (mean improvement, 1.09%; 95% CI, 0.94-1.28%) and 41 hospitals dropped below the 50th percentile (95% CI, 33-52). When a sample of 100 hospitals with pneumonia readmission rates above the 50th percentile recoded all eligible patients, 66 hospitals (95% CI, 54-75) improved their readmission rate (mean improvement, 0.34%; 95% CI, 0.19-0.45%) and 15 hospitals (95% CI, 9-22) dropped below the 50th percentile.

conclusionsHospitals can improve apparent pneumonia mortality and readmission rates by recoding pneumonia patients. Centers for Medicare and Medicaid Services should consider changes to their methods used to calculate hospital-level pneumonia outcome measures to make them less susceptible to gaming.

Indexed as

International Classification of DiseasesQuality Indicators, Health CareAgedAged, 80 and overComorbidityFemaleHospital AdministrationHospital MortalityHumansMaleMedicarePatient ReadmissionPneumoniaSepsisUnited States

Identifiers

PMID25746747
PMCPMC4617210
OpenAlexW2322261368

What OpenQuestion holds

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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.