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Concordance of care processes between medical records and patient self-administered questionnaires
BACKGROUND: Despite the increasing use of medical records to measure quality of care, studies have shown that their validity is suboptimal. The objective of this study is to assess the concordance of cardiovascular care processes evaluated through medical record review and patient self-administered...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6607524/ https://www.ncbi.nlm.nih.gov/pubmed/31269902 http://dx.doi.org/10.1186/s12875-019-0979-7 |
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author | Khanji, Cynthia Schnitzer, Mireille E. Bareil, Céline Perreault, Sylvie Lalonde, Lyne |
author_facet | Khanji, Cynthia Schnitzer, Mireille E. Bareil, Céline Perreault, Sylvie Lalonde, Lyne |
author_sort | Khanji, Cynthia |
collection | PubMed |
description | BACKGROUND: Despite the increasing use of medical records to measure quality of care, studies have shown that their validity is suboptimal. The objective of this study is to assess the concordance of cardiovascular care processes evaluated through medical record review and patient self-administered questionnaires (SAQs) using ten quality indicators (TRANSIT indicators). These indicators were developed as part of a participatory research program (TRANSIT study) dedicated to TRANSforming InTerprofessional clinical practices to improve cardiovascular disease (CVD) prevention in primary care. METHODS: For every patient participating in the TRANSIT study, the compliance to each indicator (individual scores) as well as the mean compliance to all indicators of a category (subscale scores) and to the complete set of ten indicators (overall scale score) were established. Concordance between results obtained using medical records and patient SAQs was assessed by prevalence-adjusted bias-adjusted kappa (PABAK) coefficients as well as intraclass correlation coefficients (ICCs) and 95% confidence intervals (95% CI). Generalized linear mixed models (GLMM) were used to identify patients’ sociodemographic and clinical characteristics associated with agreement between the two data sources. RESULTS: The TRANSIT study was conducted in a primary care setting among patients (n = 759) with multimorbidity, at moderate (16%) and high risk (83%) of cardiovascular diseases. Quality of care, as measured by the TRANSIT indicators, varied substantially between medical records and patient SAQ. Concordance between the two data sources, as measured by ICCs (95% CI), was poor for the subscale (0.18 [0.08–0.27] to 0.46 [0.40–0.52]) and overall (0.46 [0.40–0.53]) compliance scale scores. GLMM showed that agreement was not affected by patients’ characteristics. CONCLUSIONS: In quality improvement strategies, researchers must acknowledge that care processes may not be consistently recorded in medical records. They must also be aware that the evaluation of the quality of care may vary depending on the source of information, the clinician responsible of documenting the interventions, and the domain of care. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12875-019-0979-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6607524 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-66075242019-07-12 Concordance of care processes between medical records and patient self-administered questionnaires Khanji, Cynthia Schnitzer, Mireille E. Bareil, Céline Perreault, Sylvie Lalonde, Lyne BMC Fam Pract Research Article BACKGROUND: Despite the increasing use of medical records to measure quality of care, studies have shown that their validity is suboptimal. The objective of this study is to assess the concordance of cardiovascular care processes evaluated through medical record review and patient self-administered questionnaires (SAQs) using ten quality indicators (TRANSIT indicators). These indicators were developed as part of a participatory research program (TRANSIT study) dedicated to TRANSforming InTerprofessional clinical practices to improve cardiovascular disease (CVD) prevention in primary care. METHODS: For every patient participating in the TRANSIT study, the compliance to each indicator (individual scores) as well as the mean compliance to all indicators of a category (subscale scores) and to the complete set of ten indicators (overall scale score) were established. Concordance between results obtained using medical records and patient SAQs was assessed by prevalence-adjusted bias-adjusted kappa (PABAK) coefficients as well as intraclass correlation coefficients (ICCs) and 95% confidence intervals (95% CI). Generalized linear mixed models (GLMM) were used to identify patients’ sociodemographic and clinical characteristics associated with agreement between the two data sources. RESULTS: The TRANSIT study was conducted in a primary care setting among patients (n = 759) with multimorbidity, at moderate (16%) and high risk (83%) of cardiovascular diseases. Quality of care, as measured by the TRANSIT indicators, varied substantially between medical records and patient SAQ. Concordance between the two data sources, as measured by ICCs (95% CI), was poor for the subscale (0.18 [0.08–0.27] to 0.46 [0.40–0.52]) and overall (0.46 [0.40–0.53]) compliance scale scores. GLMM showed that agreement was not affected by patients’ characteristics. CONCLUSIONS: In quality improvement strategies, researchers must acknowledge that care processes may not be consistently recorded in medical records. They must also be aware that the evaluation of the quality of care may vary depending on the source of information, the clinician responsible of documenting the interventions, and the domain of care. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12875-019-0979-7) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-03 /pmc/articles/PMC6607524/ /pubmed/31269902 http://dx.doi.org/10.1186/s12875-019-0979-7 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Khanji, Cynthia Schnitzer, Mireille E. Bareil, Céline Perreault, Sylvie Lalonde, Lyne Concordance of care processes between medical records and patient self-administered questionnaires |
title | Concordance of care processes between medical records and patient self-administered questionnaires |
title_full | Concordance of care processes between medical records and patient self-administered questionnaires |
title_fullStr | Concordance of care processes between medical records and patient self-administered questionnaires |
title_full_unstemmed | Concordance of care processes between medical records and patient self-administered questionnaires |
title_short | Concordance of care processes between medical records and patient self-administered questionnaires |
title_sort | concordance of care processes between medical records and patient self-administered questionnaires |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6607524/ https://www.ncbi.nlm.nih.gov/pubmed/31269902 http://dx.doi.org/10.1186/s12875-019-0979-7 |
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