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

BACKGROUND: Primary 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 imm...

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Autores principales: Kumar, Bharat, Zetumer, Samuel, Swee, Melissa, Endelman, Ellen L Keyser, Suneja, Manish, Davis, Benjamin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8767470/
https://www.ncbi.nlm.nih.gov/pubmed/34587114
http://dx.doi.org/10.2196/32635
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author Kumar, Bharat
Zetumer, Samuel
Swee, Melissa
Endelman, Ellen L Keyser
Suneja, Manish
Davis, Benjamin
author_facet Kumar, Bharat
Zetumer, Samuel
Swee, Melissa
Endelman, Ellen L Keyser
Suneja, Manish
Davis, Benjamin
author_sort Kumar, Bharat
collection PubMed
description BACKGROUND: Primary 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. OBJECTIVE: The aim of this research is to develop and implement a clinical decision support (CDS) tool for the identification of underlying PIs. METHODS: We 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. RESULTS: This 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. CONCLUSIONS: The 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
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spelling pubmed-87674702022-02-03 Reducing Delays in Diagnosing Primary Immunodeficiency Through the Development and Implementation of a Clinical Decision Support Tool: Protocol for a Quality Improvement Project Kumar, Bharat Zetumer, Samuel Swee, Melissa Endelman, Ellen L Keyser Suneja, Manish Davis, Benjamin JMIR Res Protoc Protocol BACKGROUND: Primary 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. OBJECTIVE: The aim of this research is to develop and implement a clinical decision support (CDS) tool for the identification of underlying PIs. METHODS: We 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. RESULTS: This 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. CONCLUSIONS: The 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 JMIR Publications 2022-01-04 /pmc/articles/PMC8767470/ /pubmed/34587114 http://dx.doi.org/10.2196/32635 Text en ©Bharat Kumar, Samuel Zetumer, Melissa Swee, Ellen L Keyser Endelman, Manish Suneja, Benjamin Davis. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 04.01.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included.
spellingShingle Protocol
Kumar, Bharat
Zetumer, Samuel
Swee, Melissa
Endelman, Ellen L Keyser
Suneja, Manish
Davis, Benjamin
Reducing Delays in Diagnosing Primary Immunodeficiency Through the Development and Implementation of a Clinical Decision Support Tool: Protocol for a Quality Improvement Project
title Reducing Delays in Diagnosing Primary Immunodeficiency Through the Development and Implementation of a Clinical Decision Support Tool: Protocol for a Quality Improvement Project
title_full Reducing Delays in Diagnosing Primary Immunodeficiency Through the Development and Implementation of a Clinical Decision Support Tool: Protocol for a Quality Improvement Project
title_fullStr Reducing Delays in Diagnosing Primary Immunodeficiency Through the Development and Implementation of a Clinical Decision Support Tool: Protocol for a Quality Improvement Project
title_full_unstemmed Reducing Delays in Diagnosing Primary Immunodeficiency Through the Development and Implementation of a Clinical Decision Support Tool: Protocol for a Quality Improvement Project
title_short Reducing Delays in Diagnosing Primary Immunodeficiency Through the Development and Implementation of a Clinical Decision Support Tool: Protocol for a Quality Improvement Project
title_sort reducing delays in diagnosing primary immunodeficiency through the development and implementation of a clinical decision support tool: protocol for a quality improvement project
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8767470/
https://www.ncbi.nlm.nih.gov/pubmed/34587114
http://dx.doi.org/10.2196/32635
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