Evidence map›Paper›PMID 30585296›Full record

ArticleInternational journal of clinical pharmacy2019

Assessment tool for hospital admissions related to medications: development and validation in older patients.

Thomas G H Kempen, Mariann Hedström, Hanna Olsson, Amanda Johansson, Sara Ottosson, Yousif Al-Sammak, Ulrika Gillespie

2 registry-linked trialsOpen access · hybridAbstract read
In one paragraph

Article in International journal of clinical pharmacy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
1.1field-weighted citation impact, top 23% 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

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.

NCT02999412 nacompletednot on this map

Medication Reviews Bridging Healthcare: a Cluster-randomised Crossover Trial to Study the Effects of Hospital-initiated Comprehensive Medication Reviews, Including Active Follow-up, on Elderly Patients' Healthcare Utilisation

TypeinterventionalSponsorUppsala County Council, SwedenRan2017 to 2020Enrolled2,637ConditionsMedication ReviewArmsComprehensive medication review, Comprehensive medication review with active follow-up, Usual Care
NCT07282379 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

Detection of isar-flagged at-risk medication in the emergency department (disarmed)

TypeobservationalSponsorPharmacie des Hopitaux de l'Est LemaniqueRan2026 to 2026Enrolled300ConditionsFrailty, Emergency Department Visit, Elderly, Drug Drug InteractionArmsPharmaceutical analysis based on the Electronic Patient Record
3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 citations in OpenAlex.

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  18. Drug-Related Hospital AdmissionsFrontiers in pharmacology · 2022
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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 at 2 institutions in 1 country.

Thomas G H KempenHospital Pharmacy Department, Uppsala University Hospital, Uppsala, Sweden.
Mariann HedströmDepartment of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden.
Hanna OlssonDepartment of Medical Sciences, Uppsala University, Uppsala, Sweden.
Amanda JohanssonDepartment of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Sara OttossonDepartment of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Yousif Al-SammakDepartment of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Ulrika GillespieHospital Pharmacy Department, Uppsala University Hospital, Uppsala, Sweden. Ulrika.Gillespie@akademiska.se.ORCID http://orcid.org/0000-0003-2181-4719
Uppsala University · SEUppsala University Hospital · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Medication-related hospital admissions (MRAs) are frequently used to measure outcomes in studies involving medication reviews. The process of identifying MRAs is subjective and time-consuming, and practical, validated alternatives are required. Objective The aim of this study was to develop and validate a practical tool to identify MRAs. Setting Uppsala University Hospital, Sweden. Method We reviewed existing literature on methods to identify MRAs. The tool AT-HARM10 was developed using an iterative process including content validity and feasibility testing. The tool's inter-rater reliability (IRR) and criterion-related validity (CRV) were assessed: four pairs of either final-year undergraduate or postgraduate pharmacy students applied the tool to one of two batches of 50 older patients' hospital admissions. Assessment of the same 100 admissions by two experienced clinicians acted as gold standard. Main outcome measure Cohen's and Fleiss' kappa for IRR, and sensitivity, specificity, and positive and negative predictive value for CRV. Results AT-HARM10 consists of ten closed questions to distinguish between admissions that are unlikely to be and those that are possibly medication-related. The IRR was moderate to substantial (Cohen's kappa values were 0.45-0.75 and Fleiss' kappa values were 0.46 and 0.58). The sensitivity and specificity values were 70/86% and 74/70%, positive and negative predictive values were 73/74% and 71/83% respectively. Both AT-HARM10 and the gold standard identified approximately 50% of the admissions as MRAs. Conclusion AT-HARM10 has been developed as a practical tool to identify MRAs and the tool is valid for use in older patients by final-year undergraduate and postgraduate pharmacy students.

Indexed as

AgedAged, 80 and overDrug-Related Side Effects and Adverse ReactionsFemaleHumansMaleMiddle AgedPatient AdmissionReproducibility of ResultsSurveys and QuestionnairesSwedenAssessment toolDrug-related problemsElderlyHospital admissionsMedication-related admissionsSweden

Identifiers

PMID30585296
PMCPMC6394508
OpenAlexW2906204699

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.