Evidence map›Paper›PMID 31782128›Full record

ArticleDrugs & aging2020

Reducing Inappropriate Drug Use in Older Patients by Use of Clinical Decision Support in Community Pharmacy: A Mixed-Methods Evaluation.

Linda G M Mulder-Wildemors, Mette Heringa, Annemieke Floor-Schreudering, Paul A F Jansen, Marcel L Bouvy

Open access · greenAbstract read
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In one paragraph

Article in Drugs & aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 17% 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.

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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
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  9. Clinical decision support systems in community pharmacies: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023
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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

5 authors at 3 institutions in 1 country.

Linda G M Mulder-WildemorsSIR Institute for Pharmacy Practice and Policy, Theda Mansholtstraat 5B, 2331 JE, Leiden, The Netherlands. l.mulder@sirstevenshof.nl.ORCID http://orcid.org/0000-0001-6301-5443
Mette HeringaSIR Institute for Pharmacy Practice and Policy, Theda Mansholtstraat 5B, 2331 JE, Leiden, The Netherlands.
Annemieke Floor-SchreuderingSIR Institute for Pharmacy Practice and Policy, Theda Mansholtstraat 5B, 2331 JE, Leiden, The Netherlands.
Paul A F JansenDepartment of Geriatric Medicine and Expertise Centre Pharmacotherapy in Old Persons, University Medical Centre Utrecht, Utrecht, The Netherlands.
Marcel L BouvySIR Institute for Pharmacy Practice and Policy, Theda Mansholtstraat 5B, 2331 JE, Leiden, The Netherlands.
Utrecht University · NLSIR Institute for Pharmacy Practice and Policy · NLUniversity Medical Center Utrecht · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionOlder people are prone to drug-related harm. Clinical decision support systems (CDSSs) in community pharmacies may improve appropriate prescribing in this population.

objectiveThis study investigated (persistent) drug therapy changes and its determinants to reduce potentially inappropriate medication (PIM) in older patients based on CDSS alerts and to investigate barriers and facilitators for implementation of drug therapy changes based on these CDSS alerts.

methodsFive clinical decision rules based on national guidelines for inappropriate drugs in older patients were incorporated in a web-based CDSS in 31 community pharmacies between February and April 2017. The CDSS generated alerts for patients aged > 70 years who had prescriptions for one of the following drugs: alprazolam, amitriptyline, barnidipine, duloxetine, fluoxetine, trazodone, quetiapine and olanzapine. The registered alert management data and medication dispensing histories were analysed to find potential determinants of persistent drug therapy changes. Ten pharmacists were interviewed about the barriers and facilitators for implementing drug therapy changes based on CDSS alerts. An inductive thematic analysis of the transcripts was performed.

resultsThe pharmacists recorded the management of 1810 of the 2589 generated alerts, and 158 (8.7%) alerts were associated with a persistent drug therapy change. A logistic regression analysis found that the drug triggering the alert and the type of prescription [first dispensing vs. repeat; odds ratio 2.1 (95% confidence interval 1.4-3.2)] were significantly associated with persistent drug therapy changes. No association was found between persistent changes and age, sex, number of medicines in use, or recent clinical medication review. Analysis of the interviews revealed nine barriers and facilitators associated with drug therapy change.

conclusionWhen community pharmacists implemented CDSS alerts to reduce inappropriate drug use in older patients, they registered a persistent drug therapy change in 8.7% of the cases. Alerts triggered by a first prescription were two times more likely to be associated with a persistent drug therapy change than alerts triggered by repeat prescriptions. This study found that clinical rules can be used to detect inappropriate drug use in older patients and that drug therapy can change based on the alerts. This suggests that CDSS alerts are a useful tool for implementing guidelines on PIM in older patients in daily practice.

Indexed as

Decision Support Systems, ClinicalPotentially Inappropriate Medication ListAgedAged, 80 and overDrug-Related Side Effects and Adverse ReactionsFemaleHumansInappropriate PrescribingMaleMiddle AgedNetherlandsPharmaciesPharmacists

Identifiers

PMID31782128
OpenAlexW2991584847

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.