Evidence map›Paper›PMID 29035176›Full record

ArticleThe Permanente journal2017

Comparing Hospital Processes and Outcomes in California Medicare Beneficiaries: Simulation Prompts Reconsideration.

Gabriel J Escobar, Jennifer M Baker, Benjamin J Turk, David Draper, Vincent Liu, Patricia Kipnis

Abstract readComparative Study
In one paragraph

Article in The Permanente journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Gabriel J EscobarRegional Director for Hospital Operations Research for The Permanente Medical Group, Inc, at the Division of Research in Oakland, CA. gabriel.escobar@kp.org.
Jennifer M BakerPublic Health Program Specialist for Contra Costa Public Health Clinic Services in Martinez, CA. calhounjennifer1@gmail.com.
Benjamin J TurkData Analyst for the Division of Research in Oakland, CA. benjamin.j.turk@kp.org.
David DraperProfessor of Applied Mathematics and Statistics at the University of California, Santa Cruz. draper@soe.ucsc.edu.
Vincent LiuRegional Director for Hospital Advanced Analytics for The Permanente Medical Group, Inc, at the Division of Research in Oakland, CA. vincent.x.liu@kp.org.
Patricia KipnisPrincipal Statistician for Decision Support at Kaiser Foundation Health Plan. patricia.kipnis@kp.org.

Funding

Data-driven Precision medicine in sepsisK23GM112018 · NIGMS · KAISER FOUNDATION RESEARCH INSTITUTE · PI LIU, VINCENT · 2014 to 2017
$768k
NIGMS NIH HHS K23 GM112018
6 · The paper itself

Abstract

introductionThis article is not a traditional research report. It describes how conducting a specific set of benchmarking analyses led us to broader reflections on hospital benchmarking. We reexamined an issue that has received far less attention from researchers than in the past: How variations in the hospital admission threshold might affect hospital rankings. Considering this threshold made us reconsider what benchmarking is and what future benchmarking studies might be like. Although we recognize that some of our assertions are speculative, they are based on our reading of the literature and previous and ongoing data analyses being conducted in our research unit. We describe the benchmarking analyses that led to these reflections.

objectivesThe Centers for Medicare and Medicaid Services' Hospital Compare Web site includes data on fee-for-service Medicare beneficiaries but does not control for severity of illness, which requires physiologic data now available in most electronic medical records.To address this limitation, we compared hospital processes and outcomes among Kaiser Permanente Northern California's (KPNC) Medicare Advantage beneficiaries and non-KPNC California Medicare beneficiaries between 2009 and 2010.

methodsWe assigned a simulated severity of illness measure to each record and explored the effect of having the additional information on outcomes.

resultsWe found that if the admission severity of illness in non-KPNC hospitals increased, KPNC hospitals' mortality performance would appear worse; conversely, if admission severity at non-KPNC hospitals' decreased, KPNC hospitals' performance would appear better.

conclusionFuture hospital benchmarking should consider the impact of variation in admission thresholds.

Indexed as

AgedAged, 80 and overBenchmarkingCaliforniaFemaleHumansMaleMedically UninsuredMedicareMortalityPatient AdmissionQuality of Health CareUnited States

Identifiers

PMID29035176
PMCPMC5638630

What OpenQuestion holds

Textmetadata
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.