Houston Methodist cardiovascular learning health system (CVD-LHS) registry: Methods for development and implementation of an automated electronic medical record-based registry using an informatics framework approach
Objectives: To investigate the potential value and feasibility of creating a listing system-wide registry of patients with at-risk and established Atherosclerotic Cardiovascular Disease (ASCVD) within a large healthcare system using automated data extraction methods to systematically identify burden...
| Autores: | , , , , , , , , , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Pompeu Fabra |
| Repositorio: | Repositorio Digital de la UPF |
| OAI Identifier: | oai:repositori.upf.edu:10230/69626 |
| Acceso en línea: | http://hdl.handle.net/10230/69626 http://dx.doi.org/10.1016/j.ajpc.2024.100678 |
| Access Level: | acceso abierto |
| Palabra clave: | Cardiovascular research Electronic medical records Health outcomes-process assessment Information retrieval-warehousing Patient registries Population health |
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Houston Methodist cardiovascular learning health system (CVD-LHS) registry: Methods for development and implementation of an automated electronic medical record-based registry using an informatics framework approachNasir, KhurramGullapelli, RakeshNicolas, Juan C.Bose, BudhadityaNwana, NwabunieButt, Sara AyazShahid, IzzaCainzos-Achirica, MiguelPatel, KershawBhimaraj, ArvindJaved, ZulqarnainAndrieni, JuliaAl-Kindi, SadeerJones, Stephen L.Zoghbi, William A.Cardiovascular researchElectronic medical recordsHealth outcomes-process assessmentInformation retrieval-warehousingPatient registriesPopulation healthObjectives: To investigate the potential value and feasibility of creating a listing system-wide registry of patients with at-risk and established Atherosclerotic Cardiovascular Disease (ASCVD) within a large healthcare system using automated data extraction methods to systematically identify burden, determinants, and the spectrum of at-risk patients to inform population health management. Additionally, the Houston Methodist Cardiovascular Disease Learning Health System (HM CVD-LHS) registry intends to create high-quality data-driven analytical insights to assess, track, and promote cardiovascular research and care. Methods: We conducted a retrospective multi-center, cohort analysis of adult patients who were seen in the outpatient settings of a large healthcare system between June 2016 - December 2022 to create an EMR-based registry. A common framework was developed to automatically extract clinical data from the EMR and then integrate it with the social determinants of health information retrieved from external sources. Microsoft's SQL Server Management Studio was used for creating multiple Extract-Transform-Load scripts and stored procedures for collecting, cleaning, storing, monitoring, reviewing, auto-updating, validating, and reporting the data based on the registry goals. Results: A real-time, programmatically deidentified, auto-updated EMR-based HM CVD-LHS registry was developed with ∼450 variables stored in multiple tables each containing information related to patient's demographics, encounters, diagnoses, vitals, labs, medication use, and comorbidities. Out of 1,171,768 adult individuals in the registry, 113,022 (9.6%) ASCVD patients were identified between June 2016 and December 2022 (mean age was 69.2 ± 12.2 years, with 55% Men and 15% Black individuals). Further, multi-level groupings of patients with laboratory test results and medication use have been analyzed for evaluating the outcomes of interest. Conclusions: HM CVD-LHS registry database was developed successfully providing the listing registry of patients with established ASCVD and those at risk. This approach empowers knowledge inference and provides support for efforts to move away from manual patient chart abstraction by suggesting that a common registry framework with a concurrent design of data collection tools and reporting rapidly extracting useful structured clinical data from EMRs for creating patient or specialty population registries.Elsevier202520252024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/69626http://dx.doi.org/10.1016/j.ajpc.2024.100678reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésAm J Prev Cardiol. 2024 Apr 30;18:100678© 2024 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/696262026-06-12T07:21:37Z |
| dc.title.none.fl_str_mv |
Houston Methodist cardiovascular learning health system (CVD-LHS) registry: Methods for development and implementation of an automated electronic medical record-based registry using an informatics framework approach |
| title |
Houston Methodist cardiovascular learning health system (CVD-LHS) registry: Methods for development and implementation of an automated electronic medical record-based registry using an informatics framework approach |
| spellingShingle |
Houston Methodist cardiovascular learning health system (CVD-LHS) registry: Methods for development and implementation of an automated electronic medical record-based registry using an informatics framework approach Nasir, Khurram Cardiovascular research Electronic medical records Health outcomes-process assessment Information retrieval-warehousing Patient registries Population health |
| title_short |
Houston Methodist cardiovascular learning health system (CVD-LHS) registry: Methods for development and implementation of an automated electronic medical record-based registry using an informatics framework approach |
| title_full |
Houston Methodist cardiovascular learning health system (CVD-LHS) registry: Methods for development and implementation of an automated electronic medical record-based registry using an informatics framework approach |
| title_fullStr |
Houston Methodist cardiovascular learning health system (CVD-LHS) registry: Methods for development and implementation of an automated electronic medical record-based registry using an informatics framework approach |
| title_full_unstemmed |
Houston Methodist cardiovascular learning health system (CVD-LHS) registry: Methods for development and implementation of an automated electronic medical record-based registry using an informatics framework approach |
| title_sort |
Houston Methodist cardiovascular learning health system (CVD-LHS) registry: Methods for development and implementation of an automated electronic medical record-based registry using an informatics framework approach |
| dc.creator.none.fl_str_mv |
Nasir, Khurram Gullapelli, Rakesh Nicolas, Juan C. Bose, Budhaditya Nwana, Nwabunie Butt, Sara Ayaz Shahid, Izza Cainzos-Achirica, Miguel Patel, Kershaw Bhimaraj, Arvind Javed, Zulqarnain Andrieni, Julia Al-Kindi, Sadeer Jones, Stephen L. Zoghbi, William A. |
| author |
Nasir, Khurram |
| author_facet |
Nasir, Khurram Gullapelli, Rakesh Nicolas, Juan C. Bose, Budhaditya Nwana, Nwabunie Butt, Sara Ayaz Shahid, Izza Cainzos-Achirica, Miguel Patel, Kershaw Bhimaraj, Arvind Javed, Zulqarnain Andrieni, Julia Al-Kindi, Sadeer Jones, Stephen L. Zoghbi, William A. |
| author_role |
author |
| author2 |
Gullapelli, Rakesh Nicolas, Juan C. Bose, Budhaditya Nwana, Nwabunie Butt, Sara Ayaz Shahid, Izza Cainzos-Achirica, Miguel Patel, Kershaw Bhimaraj, Arvind Javed, Zulqarnain Andrieni, Julia Al-Kindi, Sadeer Jones, Stephen L. Zoghbi, William A. |
| author2_role |
author author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
Cardiovascular research Electronic medical records Health outcomes-process assessment Information retrieval-warehousing Patient registries Population health |
| topic |
Cardiovascular research Electronic medical records Health outcomes-process assessment Information retrieval-warehousing Patient registries Population health |
| description |
Objectives: To investigate the potential value and feasibility of creating a listing system-wide registry of patients with at-risk and established Atherosclerotic Cardiovascular Disease (ASCVD) within a large healthcare system using automated data extraction methods to systematically identify burden, determinants, and the spectrum of at-risk patients to inform population health management. Additionally, the Houston Methodist Cardiovascular Disease Learning Health System (HM CVD-LHS) registry intends to create high-quality data-driven analytical insights to assess, track, and promote cardiovascular research and care. Methods: We conducted a retrospective multi-center, cohort analysis of adult patients who were seen in the outpatient settings of a large healthcare system between June 2016 - December 2022 to create an EMR-based registry. A common framework was developed to automatically extract clinical data from the EMR and then integrate it with the social determinants of health information retrieved from external sources. Microsoft's SQL Server Management Studio was used for creating multiple Extract-Transform-Load scripts and stored procedures for collecting, cleaning, storing, monitoring, reviewing, auto-updating, validating, and reporting the data based on the registry goals. Results: A real-time, programmatically deidentified, auto-updated EMR-based HM CVD-LHS registry was developed with ∼450 variables stored in multiple tables each containing information related to patient's demographics, encounters, diagnoses, vitals, labs, medication use, and comorbidities. Out of 1,171,768 adult individuals in the registry, 113,022 (9.6%) ASCVD patients were identified between June 2016 and December 2022 (mean age was 69.2 ± 12.2 years, with 55% Men and 15% Black individuals). Further, multi-level groupings of patients with laboratory test results and medication use have been analyzed for evaluating the outcomes of interest. Conclusions: HM CVD-LHS registry database was developed successfully providing the listing registry of patients with established ASCVD and those at risk. This approach empowers knowledge inference and provides support for efforts to move away from manual patient chart abstraction by suggesting that a common registry framework with a concurrent design of data collection tools and reporting rapidly extracting useful structured clinical data from EMRs for creating patient or specialty population registries. |
| publishDate |
2024 |
| dc.date.none.fl_str_mv |
2024 2025 2025 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://hdl.handle.net/10230/69626 http://dx.doi.org/10.1016/j.ajpc.2024.100678 |
| url |
http://hdl.handle.net/10230/69626 http://dx.doi.org/10.1016/j.ajpc.2024.100678 |
| dc.language.none.fl_str_mv |
Inglés |
| language_invalid_str_mv |
Inglés |
| dc.relation.none.fl_str_mv |
Am J Prev Cardiol. 2024 Apr 30;18:100678 |
| dc.rights.none.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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openAccess |
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application/pdf application/pdf |
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Elsevier |
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Elsevier |
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reponame:Repositorio Digital de la UPF instname:Universitat Pompeu Fabra |
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Universitat Pompeu Fabra |
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Repositorio Digital de la UPF |
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