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Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers
OBJECTIVE: Electronic health record (EHR)-based shared decision-making (SDM) and clinical decision support (CDS) systems can improve cardiovascular disease (CVD) care quality and risk factor management. Use of the CV Wizard system showed a beneficial effect on high-risk community health center (CHC)...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10005607/ https://www.ncbi.nlm.nih.gov/pubmed/36909848 http://dx.doi.org/10.1093/jamiaopen/ooad012 |
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author | Hauschildt, Jennifer Lyon-Scott, Kristin Sheppler, Christina R Larson, Annie E McMullen, Carmit Boston, David O’Connor, Patrick J Sperl-Hillen, JoAnn M Gold, Rachel |
author_facet | Hauschildt, Jennifer Lyon-Scott, Kristin Sheppler, Christina R Larson, Annie E McMullen, Carmit Boston, David O’Connor, Patrick J Sperl-Hillen, JoAnn M Gold, Rachel |
author_sort | Hauschildt, Jennifer |
collection | PubMed |
description | OBJECTIVE: Electronic health record (EHR)-based shared decision-making (SDM) and clinical decision support (CDS) systems can improve cardiovascular disease (CVD) care quality and risk factor management. Use of the CV Wizard system showed a beneficial effect on high-risk community health center (CHC) patients’ CVD risk within an effectiveness trial, but system adoption was low overall. We assessed which multi-level characteristics were associated with system use. MATERIALS AND METHODS: Analyses included 80 195 encounters with 17 931 patients with high CVD risk and/or uncontrolled risk factors at 42 clinics in September 2018–March 2020. Data came from the CV Wizard repository and EHR data, and a survey of 44 clinic providers. Adjusted, mixed-effects multivariate Poisson regression analyses assessed factors associated with system use. We included clinic- and provider-level clustering as random effects to account for nested data. RESULTS: Likelihood of system use was significantly higher in encounters with patients with higher CVD risk and at longer encounters, and lower when providers were >10 minutes behind schedule, among other factors. Survey participants reported generally high satisfaction with the system but were less likely to use it when there were time constraints or when rooming staff did not print the system output for the provider. DISCUSSION: CHC providers prioritize using this system for patients with the greatest CVD risk, when time permits, and when rooming staff make the information readily available. CHCs’ financial constraints create substantial challenges to addressing barriers to improved system use, with health equity implications. CONCLUSION: Research is needed on improving SDM and CDS adoption in CHCs. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03001713, https://clinicaltrials.gov/ |
format | Online Article Text |
id | pubmed-10005607 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-100056072023-03-11 Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers Hauschildt, Jennifer Lyon-Scott, Kristin Sheppler, Christina R Larson, Annie E McMullen, Carmit Boston, David O’Connor, Patrick J Sperl-Hillen, JoAnn M Gold, Rachel JAMIA Open Research and Applications OBJECTIVE: Electronic health record (EHR)-based shared decision-making (SDM) and clinical decision support (CDS) systems can improve cardiovascular disease (CVD) care quality and risk factor management. Use of the CV Wizard system showed a beneficial effect on high-risk community health center (CHC) patients’ CVD risk within an effectiveness trial, but system adoption was low overall. We assessed which multi-level characteristics were associated with system use. MATERIALS AND METHODS: Analyses included 80 195 encounters with 17 931 patients with high CVD risk and/or uncontrolled risk factors at 42 clinics in September 2018–March 2020. Data came from the CV Wizard repository and EHR data, and a survey of 44 clinic providers. Adjusted, mixed-effects multivariate Poisson regression analyses assessed factors associated with system use. We included clinic- and provider-level clustering as random effects to account for nested data. RESULTS: Likelihood of system use was significantly higher in encounters with patients with higher CVD risk and at longer encounters, and lower when providers were >10 minutes behind schedule, among other factors. Survey participants reported generally high satisfaction with the system but were less likely to use it when there were time constraints or when rooming staff did not print the system output for the provider. DISCUSSION: CHC providers prioritize using this system for patients with the greatest CVD risk, when time permits, and when rooming staff make the information readily available. CHCs’ financial constraints create substantial challenges to addressing barriers to improved system use, with health equity implications. CONCLUSION: Research is needed on improving SDM and CDS adoption in CHCs. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03001713, https://clinicaltrials.gov/ Oxford University Press 2023-03-10 /pmc/articles/PMC10005607/ /pubmed/36909848 http://dx.doi.org/10.1093/jamiaopen/ooad012 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research and Applications Hauschildt, Jennifer Lyon-Scott, Kristin Sheppler, Christina R Larson, Annie E McMullen, Carmit Boston, David O’Connor, Patrick J Sperl-Hillen, JoAnn M Gold, Rachel Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers |
title | Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers |
title_full | Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers |
title_fullStr | Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers |
title_full_unstemmed | Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers |
title_short | Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers |
title_sort | adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers |
topic | Research and Applications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10005607/ https://www.ncbi.nlm.nih.gov/pubmed/36909848 http://dx.doi.org/10.1093/jamiaopen/ooad012 |
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