Evidence map›Paper›PMID 25886888›Full record

ArticleBMC geriatrics2015

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.

Lisa M Lix, Lin Yan, David Blackburn, Nianping Hu, Verena Schneider-Lindner, Yvonne Shevchuk, Gary F Teare

Abstract read
In one paragraph

Article in BMC geriatrics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. National assessment of frailty impact on endovascular mechanical thrombectomy for minor to moderately severe large vessel occlusions per NIHSS.Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Lisa M LixUniversity of Manitoba, Winnipeg, MB, Canada. lisa.lix@umanitoba.ca.
Lin YanUniversity of Manitoba, Winnipeg, MB, Canada. lin.yan@umanitoba.ca.
David BlackburnUniversity of Saskatchewan, Saskatoon, SK, Canada. d.blackburn@usask.ca.
Nianping HuHealth Quality Council, Saskatoon, SK, Canada. nhu@hqc.sk.ca.
Verena Schneider-LindnerMedical Faculty Mannheim, Heidelberg University, Heidelberg, Germany. Verena.Schneider-Lindner@medma.uni-heidelberg.de.
Yvonne ShevchukUniversity of Saskatchewan, Saskatoon, SK, Canada. yvonne.shevchuk@usask.ca.
Gary F TeareUniversity of Saskatchewan, Saskatoon, SK, Canada. gteare@hqc.sk.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrescription 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.

methodsPrescription 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.

resultsThe 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.

conclusionsAgreement 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.

Indexed as

Drug UtilizationNursing HomesAgedAged, 80 and overCanadaCross-Sectional StudiesHumansLong-Term CarePrevalencePsychotropic DrugsSurveys and QuestionnairesPsychotropic Drugs

Identifiers

PMID25886888
PMCPMC4359405

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.