Evidence map›Paper›PMID 37817606›Full record

ArticleJournal of preventive medicine and public health = Yebang Uihakhoe chi2023

Multilevel Analysis of the Relationship Between Prescribing Institutions and Medication Adherence Among Patients With Hypertension and Diabetes in Korea.

Haryeom Ghang, Juhyang Lee

Open access · goldAbstract read
In one paragraph

Article in Journal of preventive medicine and public health = Yebang Uihakhoe chi, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 26% of its field
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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Haryeom GhangHealth Insurance Research Institute, National Health Insurance Service, Wonju, Korea.
Juhyang LeeHealth Insurance Research Institute, National Health Insurance Service, Wonju, Korea.
Seoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study investigated the relationship between prescribing institutions and medication adherence among patients newly diagnosed with hypertension and diabetes.

methodsThis study investigated patients with new prescriptions for hypertension and diabetes in Korea in 2019 with using data collected from general health screenings. A multilevel logistic regression model was applied to explore the relationship between patients' first prescribing institution and their medication adherence, defined as a medication possession ratio (MPR) over 80%.

resultsThe overall adherence rates were 53.7% and 56.0% among patients with hypertension and diabetes, respectively. The intraclass correlation coefficients were 13.2% for hypertension and 13.8% for diabetes (p<0.001), implying that the first prescribing institution had a significant role in medication adherence. With clinics as the reference group, all other types of hospitals showed an odds ratio (OR) less than 1.00, with the lowest for tertiary hospitals (OR, 0.30 for hypertension; 0.45 for diabetes), and the next lowest in health screening specialized clinics (OR, 0.51 for hypertension; 0.46 for diabetes). Among individual-level variables, female sex, older age, higher insurance premium level, and residing in cities were positively associated with adherence in both the hypertension and diabetes samples.

conclusionsThis study showed that the prescribing institution had a significant relationship with medication adherence. When the first prescribing institution was a clinic, newly diagnosed patients were more likely to adhere to their medication. These results highlight the important role played by primary care institutions in managing mild chronic diseases.

Indexed as

Diabetes MellitusHypertensionFemaleHumansMedication AdherenceMultilevel AnalysisRepublic of KoreaRetrospective StudiesDiabetes mellitusHypertensionMass screeningMedication adherence

Identifiers

PMID37817606
PMCPMC10704073
OpenAlexW4387515967

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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.