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The Development and Use of an EHR-Linked Database for Glomerular Disease Research and Quality Initiatives

BACKGROUND AND OBJECTIVE: The use of electronic health record (EHR) data can facilitate efficient research and quality initiatives. The imprecision of ICD-10 codes for kidney diagnoses has been an obstacle to discrete data-defined diagnoses in the EHR. This manuscript describes the Kidney Research N...

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Autores principales: Eikstadt, Richard N., Desmond, Hailey E., Lindner, Clare, Chen, Liz Yao, Courtlandt, Cheryl D., Massengill, Susan F., Kamil, Elaine S., Lafayette, Richard, Pesenson, Anne, Elliott, Matthew, Gipson, Patrick E., Gipson, Debbie S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: S. Karger AG 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9677745/
https://www.ncbi.nlm.nih.gov/pubmed/36751383
http://dx.doi.org/10.1159/000518187
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author Eikstadt, Richard N.
Desmond, Hailey E.
Lindner, Clare
Chen, Liz Yao
Courtlandt, Cheryl D.
Massengill, Susan F.
Kamil, Elaine S.
Lafayette, Richard
Pesenson, Anne
Elliott, Matthew
Gipson, Patrick E.
Gipson, Debbie S.
author_facet Eikstadt, Richard N.
Desmond, Hailey E.
Lindner, Clare
Chen, Liz Yao
Courtlandt, Cheryl D.
Massengill, Susan F.
Kamil, Elaine S.
Lafayette, Richard
Pesenson, Anne
Elliott, Matthew
Gipson, Patrick E.
Gipson, Debbie S.
author_sort Eikstadt, Richard N.
collection PubMed
description BACKGROUND AND OBJECTIVE: The use of electronic health record (EHR) data can facilitate efficient research and quality initiatives. The imprecision of ICD-10 codes for kidney diagnoses has been an obstacle to discrete data-defined diagnoses in the EHR. This manuscript describes the Kidney Research Network (KRN) registry and database that provide an example of a prospective, real-world data glomerular disease registry for research and quality initiatives. METHODS: KRN is a multicenter collaboration of patients, physicians, and scientists across diverse health-care settings with a focus on improving treatment options and outcomes for patients with glomerular disease. The registry and data warehouse amasses retrospective and prospective data including EHR, active research study, completed clinical trials, patient reported outcomes, and other relevant data. Following consent, participating sites enter the patient into KRN and provide a physician-confirmed primary kidney diagnosis. Kidney biopsy reports are redacted and uploaded. Site programmers extract local EHR data including demographics, insurance type, zip code, diagnoses, encounters, laboratories, procedures, medications, dialysis/transplant status, vitals, and vital status monthly. Participating sites transform data to conform to a common data model prior to submitting to the Data Analysis and Coordinating Center (DACC). The DACC stores and reviews each site's EHR data for quality before loading into the KRN database. RESULTS: As of January 2021, 1,192 patients have enrolled in the registry. The database has been utilized for research, clinical trial design, clinical trial end point validation, and supported quality initiatives. The data also support a dashboard allowing enrolling sites to assist with clinical trial enrollment and population health initiatives. CONCLUSION: A multicenter registry using EHR data, following physician- and biopsy-confirmed glomerular disease diagnosis, can be established and used effectively for research and quality initiatives. This design provides an example which may be readily replicated for other rare or common disease endeavors.
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spelling pubmed-96777452023-02-06 The Development and Use of an EHR-Linked Database for Glomerular Disease Research and Quality Initiatives Eikstadt, Richard N. Desmond, Hailey E. Lindner, Clare Chen, Liz Yao Courtlandt, Cheryl D. Massengill, Susan F. Kamil, Elaine S. Lafayette, Richard Pesenson, Anne Elliott, Matthew Gipson, Patrick E. Gipson, Debbie S. Glomerular Dis Research Article BACKGROUND AND OBJECTIVE: The use of electronic health record (EHR) data can facilitate efficient research and quality initiatives. The imprecision of ICD-10 codes for kidney diagnoses has been an obstacle to discrete data-defined diagnoses in the EHR. This manuscript describes the Kidney Research Network (KRN) registry and database that provide an example of a prospective, real-world data glomerular disease registry for research and quality initiatives. METHODS: KRN is a multicenter collaboration of patients, physicians, and scientists across diverse health-care settings with a focus on improving treatment options and outcomes for patients with glomerular disease. The registry and data warehouse amasses retrospective and prospective data including EHR, active research study, completed clinical trials, patient reported outcomes, and other relevant data. Following consent, participating sites enter the patient into KRN and provide a physician-confirmed primary kidney diagnosis. Kidney biopsy reports are redacted and uploaded. Site programmers extract local EHR data including demographics, insurance type, zip code, diagnoses, encounters, laboratories, procedures, medications, dialysis/transplant status, vitals, and vital status monthly. Participating sites transform data to conform to a common data model prior to submitting to the Data Analysis and Coordinating Center (DACC). The DACC stores and reviews each site's EHR data for quality before loading into the KRN database. RESULTS: As of January 2021, 1,192 patients have enrolled in the registry. The database has been utilized for research, clinical trial design, clinical trial end point validation, and supported quality initiatives. The data also support a dashboard allowing enrolling sites to assist with clinical trial enrollment and population health initiatives. CONCLUSION: A multicenter registry using EHR data, following physician- and biopsy-confirmed glomerular disease diagnosis, can be established and used effectively for research and quality initiatives. This design provides an example which may be readily replicated for other rare or common disease endeavors. S. Karger AG 2021-07-05 /pmc/articles/PMC9677745/ /pubmed/36751383 http://dx.doi.org/10.1159/000518187 Text en Copyright © 2021 by The Author(s) Published by S. Karger AG, Basel https://creativecommons.org/licenses/by-nc/4.0/This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC). Usage and distribution for commercial purposes requires written permission.
spellingShingle Research Article
Eikstadt, Richard N.
Desmond, Hailey E.
Lindner, Clare
Chen, Liz Yao
Courtlandt, Cheryl D.
Massengill, Susan F.
Kamil, Elaine S.
Lafayette, Richard
Pesenson, Anne
Elliott, Matthew
Gipson, Patrick E.
Gipson, Debbie S.
The Development and Use of an EHR-Linked Database for Glomerular Disease Research and Quality Initiatives
title The Development and Use of an EHR-Linked Database for Glomerular Disease Research and Quality Initiatives
title_full The Development and Use of an EHR-Linked Database for Glomerular Disease Research and Quality Initiatives
title_fullStr The Development and Use of an EHR-Linked Database for Glomerular Disease Research and Quality Initiatives
title_full_unstemmed The Development and Use of an EHR-Linked Database for Glomerular Disease Research and Quality Initiatives
title_short The Development and Use of an EHR-Linked Database for Glomerular Disease Research and Quality Initiatives
title_sort development and use of an ehr-linked database for glomerular disease research and quality initiatives
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9677745/
https://www.ncbi.nlm.nih.gov/pubmed/36751383
http://dx.doi.org/10.1159/000518187
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