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Modernization of a Large Spinal Cord Injuries and Disorders Registry: The Veterans Administration Experience
Since the 1990s, Veterans Health Administration (VHA) has maintained a registry of Veterans with Spinal Cord Injuries and Disorders (SCI/Ds) to guide clinical care, policy, and research. Historically, methods for collecting and recording data for the VHA SCI/D Registry (VSR) have required significan...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9761267/ https://www.ncbi.nlm.nih.gov/pubmed/36545529 http://dx.doi.org/10.1016/j.arrct.2022.100237 |
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author | Sippel, Jennifer L. Daly, Jennifer E. Poggensee, Linda Ristau, Kim D. Eberhart, Adam C. Tam, Katharine Evans, Charlesnika T. Lancaster, Betsy Wickremasinghe, I. Manosha Burns, Stephen P. Goldstein, Barry Smith, Bridget M. |
author_facet | Sippel, Jennifer L. Daly, Jennifer E. Poggensee, Linda Ristau, Kim D. Eberhart, Adam C. Tam, Katharine Evans, Charlesnika T. Lancaster, Betsy Wickremasinghe, I. Manosha Burns, Stephen P. Goldstein, Barry Smith, Bridget M. |
author_sort | Sippel, Jennifer L. |
collection | PubMed |
description | Since the 1990s, Veterans Health Administration (VHA) has maintained a registry of Veterans with Spinal Cord Injuries and Disorders (SCI/Ds) to guide clinical care, policy, and research. Historically, methods for collecting and recording data for the VHA SCI/D Registry (VSR) have required significant time, cost, and staffing to maintain, were susceptible to missing data, and caused delays in aggregation and reporting. Each subsequent data collection method was aimed at improving these issues over the last several decades. This paper describes the development and validation of a case-finding and data-capture algorithm that uses primary clinical data, including diagnoses and utilization across 9 million VHA electronic medical records, to create a comprehensive registry of living and deceased Veterans seen for SCI/D services since 2012. A multi-step process was used to develop and validate a computer algorithm to create a comprehensive registry of Veterans with SCI/D whose records are maintained in the enterprise wide VHA Corporate Data Warehouse. Chart reviews and validity checks were used to validate the accuracy of cases that were identified using the new algorithm. An initial cohort of 28,202 living and deceased Veterans with SCI/D who were enrolled in VHA care from 10/1/2012 through 9/30/2017 was validated. Tables, reports, and charts using VSR data were developed to provide operational tools to study, predict, and improve targeted management and care for Veterans with SCI/Ds. The modernized VSR includes data on diagnoses, qualifying fiscal year, recent utilization, demographics, injury, and impairment for 38,022 Veterans as of 11/2/2022. This establishes the VSR as one of the largest ongoing longitudinal SCI/D datasets in North America and provides operational reports for VHA population health management and evidence-based rehabilitation. The VSR also comprises one of the only registries for individuals with non-traumatic SCI/Ds and holds potential to advance research and treatment for multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and other motor neuron disorders with spinal cord involvement. Selected trends in VSR data indicate possible differences in the future lifelong care needs of Veterans with SCI/Ds. Future collaborative research using the VSR offers opportunities to contribute to knowledge and improve health care for people living with SCI/Ds. |
format | Online Article Text |
id | pubmed-9761267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-97612672022-12-20 Modernization of a Large Spinal Cord Injuries and Disorders Registry: The Veterans Administration Experience Sippel, Jennifer L. Daly, Jennifer E. Poggensee, Linda Ristau, Kim D. Eberhart, Adam C. Tam, Katharine Evans, Charlesnika T. Lancaster, Betsy Wickremasinghe, I. Manosha Burns, Stephen P. Goldstein, Barry Smith, Bridget M. Arch Rehabil Res Clin Transl Special Communication Since the 1990s, Veterans Health Administration (VHA) has maintained a registry of Veterans with Spinal Cord Injuries and Disorders (SCI/Ds) to guide clinical care, policy, and research. Historically, methods for collecting and recording data for the VHA SCI/D Registry (VSR) have required significant time, cost, and staffing to maintain, were susceptible to missing data, and caused delays in aggregation and reporting. Each subsequent data collection method was aimed at improving these issues over the last several decades. This paper describes the development and validation of a case-finding and data-capture algorithm that uses primary clinical data, including diagnoses and utilization across 9 million VHA electronic medical records, to create a comprehensive registry of living and deceased Veterans seen for SCI/D services since 2012. A multi-step process was used to develop and validate a computer algorithm to create a comprehensive registry of Veterans with SCI/D whose records are maintained in the enterprise wide VHA Corporate Data Warehouse. Chart reviews and validity checks were used to validate the accuracy of cases that were identified using the new algorithm. An initial cohort of 28,202 living and deceased Veterans with SCI/D who were enrolled in VHA care from 10/1/2012 through 9/30/2017 was validated. Tables, reports, and charts using VSR data were developed to provide operational tools to study, predict, and improve targeted management and care for Veterans with SCI/Ds. The modernized VSR includes data on diagnoses, qualifying fiscal year, recent utilization, demographics, injury, and impairment for 38,022 Veterans as of 11/2/2022. This establishes the VSR as one of the largest ongoing longitudinal SCI/D datasets in North America and provides operational reports for VHA population health management and evidence-based rehabilitation. The VSR also comprises one of the only registries for individuals with non-traumatic SCI/Ds and holds potential to advance research and treatment for multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and other motor neuron disorders with spinal cord involvement. Selected trends in VSR data indicate possible differences in the future lifelong care needs of Veterans with SCI/Ds. Future collaborative research using the VSR offers opportunities to contribute to knowledge and improve health care for people living with SCI/Ds. Elsevier 2022-10-17 /pmc/articles/PMC9761267/ /pubmed/36545529 http://dx.doi.org/10.1016/j.arrct.2022.100237 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Special Communication Sippel, Jennifer L. Daly, Jennifer E. Poggensee, Linda Ristau, Kim D. Eberhart, Adam C. Tam, Katharine Evans, Charlesnika T. Lancaster, Betsy Wickremasinghe, I. Manosha Burns, Stephen P. Goldstein, Barry Smith, Bridget M. Modernization of a Large Spinal Cord Injuries and Disorders Registry: The Veterans Administration Experience |
title | Modernization of a Large Spinal Cord Injuries and Disorders Registry: The Veterans Administration Experience |
title_full | Modernization of a Large Spinal Cord Injuries and Disorders Registry: The Veterans Administration Experience |
title_fullStr | Modernization of a Large Spinal Cord Injuries and Disorders Registry: The Veterans Administration Experience |
title_full_unstemmed | Modernization of a Large Spinal Cord Injuries and Disorders Registry: The Veterans Administration Experience |
title_short | Modernization of a Large Spinal Cord Injuries and Disorders Registry: The Veterans Administration Experience |
title_sort | modernization of a large spinal cord injuries and disorders registry: the veterans administration experience |
topic | Special Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9761267/ https://www.ncbi.nlm.nih.gov/pubmed/36545529 http://dx.doi.org/10.1016/j.arrct.2022.100237 |
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