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Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study
BACKGROUND: Prescription medication use, which is common among long-term care facility (LTCF) residents, is routinely used to describe quality of care and predict health outcomes. Data sources that capture medication information, which include surveys, medical charts, administrative health databases...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4359405/ https://www.ncbi.nlm.nih.gov/pubmed/25886888 http://dx.doi.org/10.1186/s12877-015-0023-2 |
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author | Lix, Lisa M Yan, Lin Blackburn, David Hu, Nianping Schneider-Lindner, Verena Shevchuk, Yvonne Teare, Gary F |
author_facet | Lix, Lisa M Yan, Lin Blackburn, David Hu, Nianping Schneider-Lindner, Verena Shevchuk, Yvonne Teare, Gary F |
author_sort | Lix, Lisa M |
collection | PubMed |
description | BACKGROUND: Prescription medication use, which is common among long-term care facility (LTCF) residents, is routinely used to describe quality of care and predict health outcomes. Data sources that capture medication information, which include surveys, medical charts, administrative health databases, and clinical assessment records, may not collect concordant information, which can result in comparable prevalence and effect size estimates. The purpose of this research was to estimate agreement between two population-based electronic data sources for measuring use of several medication classes among LTCF residents: outpatient prescription drug administrative data and the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0. METHODS: Prescription drug and RAI-MDS data from the province of Saskatchewan, Canada (population 1.1 million) were linked for 2010/11 in this cross-sectional study. Agreement for anti-psychotic, anti-depressant, and anti-anxiety/hypnotic medication classes was examined using prevalence estimates, Cohen’s κ, and positive and negative agreement. Mixed-effects logistic regression models tested resident and facility characteristics associated with disagreement. RESULTS: The cohort was comprised of 8,866 LTCF residents. In the RAI-MDS data, prevalence of anti-psychotics was 35.7%, while for anti-depressants it was 37.9% and for hypnotics it was 27.1%. Prevalence was similar in prescription drug data for anti-psychotics and anti-depressants, but lower for hypnotics (18.0%). Cohen’s κ ranged from 0.39 to 0.85 and was highest for the first two medication classes. Diagnosis of a mood disorder and facility affiliation was associated with disagreement for hypnotics. CONCLUSIONS: Agreement between prescription drug administrative data and RAI-MDS assessment data was influenced by the type of medication class, as well as selected patient and facility characteristics. Researchers should carefully consider the purpose of their study, whether it is to capture medication that are dispensed or medications that are currently used by residents, when selecting a data source for research on LTCF populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12877-015-0023-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4359405 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43594052015-03-15 Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study Lix, Lisa M Yan, Lin Blackburn, David Hu, Nianping Schneider-Lindner, Verena Shevchuk, Yvonne Teare, Gary F BMC Geriatr Research Article BACKGROUND: Prescription medication use, which is common among long-term care facility (LTCF) residents, is routinely used to describe quality of care and predict health outcomes. Data sources that capture medication information, which include surveys, medical charts, administrative health databases, and clinical assessment records, may not collect concordant information, which can result in comparable prevalence and effect size estimates. The purpose of this research was to estimate agreement between two population-based electronic data sources for measuring use of several medication classes among LTCF residents: outpatient prescription drug administrative data and the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0. METHODS: Prescription drug and RAI-MDS data from the province of Saskatchewan, Canada (population 1.1 million) were linked for 2010/11 in this cross-sectional study. Agreement for anti-psychotic, anti-depressant, and anti-anxiety/hypnotic medication classes was examined using prevalence estimates, Cohen’s κ, and positive and negative agreement. Mixed-effects logistic regression models tested resident and facility characteristics associated with disagreement. RESULTS: The cohort was comprised of 8,866 LTCF residents. In the RAI-MDS data, prevalence of anti-psychotics was 35.7%, while for anti-depressants it was 37.9% and for hypnotics it was 27.1%. Prevalence was similar in prescription drug data for anti-psychotics and anti-depressants, but lower for hypnotics (18.0%). Cohen’s κ ranged from 0.39 to 0.85 and was highest for the first two medication classes. Diagnosis of a mood disorder and facility affiliation was associated with disagreement for hypnotics. CONCLUSIONS: Agreement between prescription drug administrative data and RAI-MDS assessment data was influenced by the type of medication class, as well as selected patient and facility characteristics. Researchers should carefully consider the purpose of their study, whether it is to capture medication that are dispensed or medications that are currently used by residents, when selecting a data source for research on LTCF populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12877-015-0023-2) contains supplementary material, which is available to authorized users. BioMed Central 2015-03-11 /pmc/articles/PMC4359405/ /pubmed/25886888 http://dx.doi.org/10.1186/s12877-015-0023-2 Text en © Lix et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Lix, Lisa M Yan, Lin Blackburn, David Hu, Nianping Schneider-Lindner, Verena Shevchuk, Yvonne Teare, Gary F Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study |
title | Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study |
title_full | Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study |
title_fullStr | Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study |
title_full_unstemmed | Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study |
title_short | Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study |
title_sort | agreement between administrative data and the resident assessment instrument minimum dataset (rai-mds) for medication use in long-term care facilities: a population-based study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4359405/ https://www.ncbi.nlm.nih.gov/pubmed/25886888 http://dx.doi.org/10.1186/s12877-015-0023-2 |
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