Evidence map›Paper›PMID 35776499›Full record

ArticleJMIR formative research2022

Exploring a Need for a Cardiometabolic Disease Staging System as a Computerized Clinical Decision Support Tool: Qualitative Study.

Aizhan Karabukayeva, Jami L Anderson, Allyson G Hall, Sue S Feldman, Tapan Mehta

Abstract read
In one paragraph

Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Aizhan Karabukayeva *Department of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID https://orcid.org/0000-0003-2976-4277
Jami L Anderson *Department of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID https://orcid.org/0000-0001-9203-765X
Allyson G Hall *Department of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID https://orcid.org/0000-0002-4945-9184
Sue S Feldman *Department of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID https://orcid.org/0000-0002-1173-3993
Tapan Mehta *Department of Family and Community Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID https://orcid.org/0000-0002-2016-2344

Funding

University of Alabama at Birmingham's Diabetes Research CenterP30DK079626 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI BARBARA A GOWER · 2013 to 2026
$19.5M
NIDDK NIH HHS P30 DK079626
6 · The paper itself

Abstract

backgroundAlthough cardiometabolic diseases are leading causes of morbidity and mortality in the United States, computerized tools for risk assessment of cardiometabolic disease are rarely integral components of primary care practice. Embedding cardiometabolic disease staging systems (CMDS) into computerized clinical decision support systems (CDSS) may assist with identifying and treating patients at greatest risk for developing cardiometabolic disease.

objectiveThis study aimed to explore the current approach to medical management of obesity and the need for CMDS designed to aid medical management of people living with obesity, at risk of being obese, or diabetic at the point of care.

methodsUsing a general inductive approach, this qualitative research study was guided by an interpretive epistemology. The method included semistructured, in-depth interviews with primary care providers (PCPs) from university-based community health clinics. The literature informed the interview protocol and included questions on PCPs' experiences and the need for a tool to improve their ability to manage and prevent complications from overweight and obesity.

resultsPCPs (N=10) described their current approaches and emphasized behavioral treatments consisting of combined diet, physical activity, and behavior therapy as the first line of treatment for people who were overweight or obese. Results suggest that beneficial features of CDSS include (1) clinically relevant and customizable support, (2) provision of a comprehensive medical summary with trends, (3) availability of patient education materials and community resources, and (4) simplicity and ease of navigation.

conclusionsImplementation of a CMDS via a CDSS could enable PCPs to conduct comprehensive cardiometabolic disease risk assessments, supporting clinical management of overweight, obesity, and diabetes. Results from this study provide unique insights to developers and researchers by identifying areas for design optimization, improved end user experience, and successful adoption of the CDSS.

Indexed as

cardiometabolic diseasecardiometabolic disease staging systemclinical decision support systemmedical managementobesityoverweightprimary carerisk assessment

Identifiers

PMID35776499
PMCPMC9288101

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LicenceCC BY
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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.