Evidence map›Paper›PMID 31837990›Full record

ReviewJoint Commission journal on quality and patient safety2020

What Are the Determinants of Health System Performance? Findings from the Literature and a Technical Expert Panel.

M Susan Ridgely, Sangeeta C Ahluwalia, Ashlyn Tom, Mary E Vaiana, Aneesa Motala, Marissa Silverman, Alice Kim, Cheryl L Damberg, Paul G Shekelle

Abstract readReview
In one paragraph

Review in Joint Commission journal on quality and patient safety, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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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

9 authors.

M Susan Ridgely
Sangeeta C Ahluwalia
Ashlyn Tom
Mary E Vaiana
Aneesa Motala
Marissa Silverman
Alice Kim
Cheryl L Damberg
Paul G Shekelle

Funding

AHRQ HHS U19 HS024067
6 · The paper itself

Abstract

backgroundThe US health care system is the most expensive in the world, but it lags behind many other industrialized nations on multiple measures of effectiveness and quality. This poor performance may have played a role in the push to incentivize health care organizations to achieve high performance over a range of domains. Research is needed to understand the determinants of health system performance.

methodsTo identify key attributes of health systems associated with performance, a literature review was conducted. The characteristics identified were compiled into a Web-based rating instrument for use with a Technical Expert Panel composed of leaders in health systems and health services research. A modified Delphi process was initiated using three rounds to develop group consensus.

resultsThe expert panel reached consensus on nine broad areas important to health system performance. Panelists also rated which specific attributes within those domains were predictive of performance. Panelists tended to rate the kind of characteristics used in past research (such as size, ownership, and profit status) as only somewhat or not at all important, while rating aspects of culture, leadership, and business execution as very important.

conclusionThere is limited empirical evidence and understanding of factors associated with health system performance. This study illustrates the value of using a modified Delphi process to bring experiential evidence to the task. These findings may help researchers refine their data collection efforts, policy makers craft better policies to incentivize high performance, and health leaders build better systems.

Indexed as

Delivery of Health CareHealth Services ResearchConsensusDelphi TechniqueHumansLeadership

Identifiers

PMID31837990
PMCPMC8606307

What OpenQuestion holds

Textmetadata
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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.