Evidence map›Paper›PMID 39764426›Full record

ArticleFrontiers in health services2024

The association of workforce configurations with length of stay and charges in hospitalized patients with congestive heart failure.

Tremaine B Williams, Alisha Crump, Pearman Parker, Maryam Y Garza, Emel Seker, Taren Massey Swindle, Taiquitha Robins, Adrian Price, Kevin Wayne Sexton

Abstract read
In one paragraph

Article in Frontiers in health services, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
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.

Tremaine B WilliamsDepartment of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Alisha CrumpDepartment of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Pearman ParkerCollege of Nursing, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Maryam Y GarzaDepartment of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Emel SekerDepartment of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Taren Massey SwindleDepartment of Family and Preventive Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Taiquitha RobinsDepartment of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
Adrian PriceRisc.ai, Little Rock, AR, United States.
Kevin Wayne SextonDepartment of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States.

Funding

Equitable Standards of Care Delivery in Team-based Risk Stratification of African Americans with Congestive Heart FailureR21NR021063 · NINR · UNIV OF ARKANSAS FOR MED SCIS · PI WILLIAMS, TREMAINE · 2024 to 2024
$407k
NINR NIH HHS R21 NR021063
6 · The paper itself

Abstract

Introduction: Clinicians are the conduits of high-quality care delivery. Clinicians have driven advancements in pharmacotherapeutics, devices, and related interventions and improved morbidity and mortality in patients with congestive heart failure over the past decade. Yet, the management of congestive heart failure has become extraordinarily complex and has fueled recommendations from the American Heart Association and the American College of Cardiology to optimize the composition of the care team to reduce the health, economic, and the health system burden of high lengths of stay and hospital charges. Therefore, the purpose of this study was to identify the extent to which specific care team configurations were associated with high length of stay and high-charge hospitalizations of patients with congestive heart failure. Methods: This study performed a retrospective analysis of data extracted from the electronic health records of 3,099 patients and their hospitalizations from the Arkansas Clinical Data Repository. The data was analyzed using binomial logistic regression in which adjusted odds ratios reflected the association of specific care team configurations (i.e., combination of care roles) with length of stay and hospital charges. Results: Team configurations that included a nurse practitioner, registered nurse, care manager, and social worker were generally above the median length of stay and median charges when compared to team configurations that did not collectively include all of these roles. Patients with larger configurations (i.e., four or more different care roles) had higher length of stays and charges than smaller configurations (i.e., two to three different care roles). The results also validated the Van Walraven Elixhauser Comorbidity Score by finding that its quartiles were associated with length of stay and charges, an indicator of care demand based on patient morbidity. Conclusions: Cardiologists, alone, cannot shoulder the burden of improving patient outcomes. Care team configuration data within electronic health record systems of hospitals could be an effective method of isolating and tracking high-risk patients. Registered nurses may be particularly effective in advancing real-time risk stratification by applying the Van Walraven Elixhauser Comorbidity Score at the point of care, improving the ability of health systems to match care demand with workforce availability.

Indexed as

care deliverycare team compositioncongestive heart failureelectronic health recordelixhauser indexrisk stratification

Identifiers

PMID39764426
PMCPMC11702897

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.