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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
S. Karger AG
2021
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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. |
format | Online Article Text |
id | pubmed-9677745 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | S. Karger AG |
record_format | MEDLINE/PubMed |
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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