Evidence map›Paper›PMID 36626501›Full record

ArticleMedicine2022

Comparative analysis of potentially inappropriate medication use in long-term care facility residents and community-dwelling elders: A matched cohort study.

Yumin Lee, Suhyun Jang, Hee-Jin Kang, Sunmee Jang

Abstract read
In one paragraph

Article in Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

4 authors.

Yumin LeeCollege of Pharmacy and Gachon Institute of Pharmaceutical Sciences, Gachon University, Incheon, Republic of Korea.ORCID 0000-0001-6479-5306
Suhyun Jang
Hee-Jin Kang
Sunmee Jang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the population of the elderly in long-term care facilities has grown, the number of users of potentially inappropriate medication (PIM) is also increasing. With this study, we aimed to investigate the pattern of PIM usage and related factors among the elderly receiving long-term care services. Using the South Korean National Health Insurance Service Elderly Cohort Database, we conducted a retrospective matched cohort study. Elderly residents (n = 1980) in long-term care facilities in 2013 were selected and matched 1:1 with elderly persons living in the community applying propensity score method. The matching variables were sex, age, health insurance type, long-term care grade, Charlson's Comorbidity Index score, presence of dementia, cerebrovascular disease, or Parkinson's disease, and number of drugs prescribed. PIM use was assessed according to Beers criteria 2019. The prevalence of PIM was found to be higher among the elderly in long-term care facilities (86.77%) than among community-dwelling individuals (75.35%). Logistic regression showed that long-term care facility residents were 1.84 odds more likely to use PIM than community-dwelling older adults. We also confirmed that the average number of medications taken per day and the number of outpatient visits were the major influencing factors affecting PIM prescriptions. In addition, elders living in long-term care facilities were prescribed more PIM drugs acting on the central nervous system than community-dwelling older adults. The results of this study show that among those receiving long-term care services, older people in long-term care facilities use PIM more than do the elderly living at home. Medication management programs need to be developed to reduce the use of PIM in long-term care facilities.

Indexed as

Independent LivingPotentially Inappropriate Medication ListAgedCohort StudiesHumansInappropriate PrescribingLong-Term CareRetrospective Studies

Identifiers

PMID36626501
PMCPMC9750672

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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.