Evidence map›Paper›PMID 34587114›Full record

ArticleJMIR research protocols2022

Reducing Delays in Diagnosing Primary Immunodeficiency Through the Development and Implementation of a Clinical Decision Support Tool: Protocol for a Quality Improvement Project.

Bharat Kumar, Samuel Zetumer, Melissa Swee, Ellen L Keyser Endelman, Manish Suneja, Benjamin Davis

Open access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2022. 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
0.6field-weighted citation impact, top 37% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Development of a primary care screening algorithm for the early detection of patients at risk of primary antibody deficiency.Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2023
    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

6 authors at 2 institutions in 1 country.

Bharat KumarDivision of Immunology, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, IA, United States.ORCID https://orcid.org/0000-0002-4245-521X
Samuel ZetumerDepartment of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, IA, United States.ORCID https://orcid.org/0000-0002-6045-208X
Melissa SweeDivision of Nephrology, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, IA, United States.ORCID https://orcid.org/0000-0002-1591-0862
Ellen L Keyser EndelmanChicago Theological Seminary, University of Chicago, Chicago, IL, United States.ORCID https://orcid.org/0000-0002-6982-2585
Manish SunejaDepartment of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, IA, United States.ORCID https://orcid.org/0000-0002-1613-8456
Benjamin DavisDivision of Immunology, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, IA, United States.ORCID https://orcid.org/0000-0003-2108-8059
University of Iowa · USChicago Theological Seminary · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrimary immunodeficiencies (PIs) are a set of heterogeneous chronic disorders characterized by immune dysfunction. They are diagnostically challenging because of their clinical heterogeneity, knowledge gaps among primary care physicians, and continuing shortages of clinically trained immunologists. As a result, patients with undiagnosed PIs are at increased risk for recurrent infections, cancers, and autoimmune diseases.

objectiveThe aim of this research is to develop and implement a clinical decision support (CDS) tool for the identification of underlying PIs.

methodsWe will develop and implement a CDS tool for the identification of underlying PIs among patients who receive primary care through a health care provider at the University of Iowa Hospitals and Clinics. The CDS tool will function through an algorithm that is based on the Immune Deficiency Foundation's 10 Warning Signs for Primary Immunodeficiency. Over the course of a year, we will use Lean Six Sigma principles and the Define, Measure, Analyze, Improve, and Control (DMAIC) framework to guide the project. The primary measure is the number of newly diagnosed PI patients per month. Secondary measures include the following: (1) the number of new patients identified by the CDS as being at high risk for PI, (2) the number of new PI cases in which immunoglobulin replacement or rotating antibiotics are started, (3) the cost of evaluation of each patient identified by the CDS tool as being at high risk for PIs, (4) the number of new consults not diagnosed with a PI, and (5) patient satisfaction with the process of referral to the Immunology Clinic.

resultsThis study was determined to not be Human Subjects Research by the Institutional Review Board at the University of Iowa. Data collection will begin in August 2021.

conclusionsThe development and implementation of a CDS tool is a promising approach to identifying patients with underlying PI. This protocol assesses whether such an approach will be able to achieve its objective of reducing diagnostic delays. The disciplined approach, using Lean Six Sigma and the DMAIC framework, will guide implementation to maximize opportunities for a successful intervention that meets the study's goals and objectives as well as to allow for replication and adaptation of these methods at other sites. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/32635.

Indexed as

clinical decision supportdiagnostic decision-makingimmunology

Identifiers

PMID34587114
PMCPMC8767470
OpenAlexW3198568370

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.