Evidence map›Paper›PMID 29117319›Full record

ArticleJAMA cardiology2017

Role of Hospital Volumes in Identifying Low-Performing and High-Performing Aortic and Mitral Valve Surgical Centers in the United States.

Rohan Khera, Ambarish Pandey, Thomas Koshy, Colby Ayers, Brahmajee K Nallamothu, Sandeep R Das, Mark H Drazner, Michael E Jessen, Ajay J Kirtane, Timothy J Gardner and 3 more

Open access · bronzeAbstract read
In one paragraph

Article in JAMA cardiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
4.8field-weighted citation impact, top 4% 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

7 citing papers in PubMed, 52 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Cardiac surgery 2017 reviewed.Clinical research in cardiology : official journal of the German Cardiac Society · 2018
    Review
  7. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 5 institutions in 1 country.

Rohan KheraDivision of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas.
Ambarish PandeyDivision of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas.
Thomas KoshyDivision of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas.
Colby AyersDivision of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas.
Brahmajee K NallamothuDivision of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor.
Sandeep R DasDivision of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas.
Mark H DraznerDivision of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas.
Michael E JessenDepartment of Cardiovascular and Thoracic Surgery, University of Texas Southwestern Medical Center, Dallas.
Ajay J KirtaneDivision of Cardiology, Department of Medicine, Columbia University Medical Center, New York, New York.
Timothy J GardnerCenter for Heart & Vascular Health, Christiana Care Health System, Wilmington, Delaware.
James A de LemosDivision of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas.
Deepak L BhattBrigham and Women's Hospital Heart & Vascular Center, Harvard Medical School, Boston, Massachusetts.
Dharam J KumbhaniDivision of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas.
The University of Texas Southwestern Medical Center · USChristiana Care Health System · USColumbia University Irving Medical Center · USHarvard University · USMichigan Medicine · US

Funding

UT Southwestern Center for Translational Medicine (UL1/KL2/TL1)UL1TR001105 · NCATS · UT SOUTHWESTERN MEDICAL CENTER · PI TOTO, ROBERT DANIEL · 2013 to 2017
$24.5M
NCATS NIH HHS UL1 TR001105
6 · The paper itself

Abstract

Importance: Identifying high-performing surgical valve centers with the best surgical outcomes is challenging. Hospital surgical volume is a frequently used surrogate for outcomes. However, its ability to distinguish low-performing and high-performing hospitals remains unknown. Objective: To examine the association of hospital procedure volume with hospital performance for aortic and mitral valve (MV) surgical procedures. Design, Setting, and Participants: Within an all-payer nationally representative data set of inpatient hospitalizations, this study identified 682 unique hospitals performing surgical aortic valve replacement (SAVR) and MV replacement and repair with or without coronary artery bypass grafting (CABG) between 2007 and 2011. Procedural outcomes were further assessed for a 10-year period (2005-2014) to assess representativeness of study period. Main Outcomes and Measures: In-hospital risk-standardized mortality rate (RSMR) calculated using hierarchical models and an empirical bayesian approach with volume-based shrinkage that allowed for reliability adjustment. Results: At 682 US hospitals, 70 295 SAVR, 19 913 MV replacement, and 17 037 MV repair procedures were performed between 2007 and 2011, with a median annual volume of 43 (interquartile range [IQR], 23-76) SAVR, 13 (IQR, 6-22) MV replacement, and 9 (IQR, 4-19) MV repair procedures. Of 225 SAVR hospitals in the highest-volume tertile, 34.7% and 36.0% were in the highest-RSMR tertile for SAVR + CABG and isolated SAVR procedures, respectively, while 21.5% and 17.5% of the 228 SAVR hospitals in the lowest-volume tertile were in the lowest respective RSMR tertile. Similarly, 36.8% and 43.5% of hospitals in the highest tertile of volume for MV replacement and repair, respectively, were in the corresponding highest-RSMR tertile, and 17.4% and 11.2% of the low-volume hospitals were in the lowest-RSMR tertile for MV replacement and repair, respectively. There was limited correlation between outcomes for SAVR and MV procedures at an institution. If solely volume-based tertiles were used to categorize hospitals for quality, 44.7% of all valve hospitals would be misclassified (as either low performing or high performing) when assessing performance based on tertiles of RSMR. Conclusions and Relevance: Hospital procedure volume alone frequently misclassifies hospital performance with regard to risk-standardized outcomes after aortic and MV surgical procedures. Valve surgery quality improvement endeavors should focus on a more comprehensive assessment that includes risk-adjusted outcomes rather than hospital volume alone.

Indexed as

Heart Valve Prosthesis ImplantationHospital MortalityMitral Valve AnnuloplastyQuality of Health CareAgedAged, 80 and overAortic ValveBayes TheoremCoronary Artery BypassDatabases, FactualFemaleHospital Bed CapacityHospitals, High-VolumeHospitals, Low-VolumeHospitals, TeachingHumans

Identifiers

PMID29117319
PMCPMC5815001
OpenAlexW2767545182

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.