Evidence map›Paper›PMID 35549672›Full record

ArticleBMC geriatrics2022

Improving individualized prescription in patients with multimorbidity through medication review.

Núria Molist-Brunet, Daniel Sevilla-Sánchez, Emma Puigoriol-Juvanteny, Matilde Barneto-Soto, Javier González-Bueno, Joan Espaulella-Panicot

Open access · goldAbstract read
In one paragraph

Article in BMC geriatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
4.0field-weighted citation impact, top 5% 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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 32 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

6 authors at 1 institution in 1 country.

Núria Molist-BrunetDepartment of Geriatrics, Hospital Universitari de La Santa Creu de Vic, Vic, Spain. nmolist@gmail.com.ORCID 0000-0003-0138-6278
Daniel Sevilla-SánchezCentral Catalonia Chronicity Research Group (C3RG), Centre for Health and Social Care Research (CESS), University of Vic - Central University of Catalonia (UVIC-UCC), Vic, Barcelona, Spain.ORCID 0000-0003-2993-6200
Emma Puigoriol-JuvantenyDepartment of Geriatrics, Hospital Universitari de La Santa Creu de Vic, Vic, Spain.ORCID 0000-0002-5510-2480
Matilde Barneto-SotoDepartment of Geriatrics, Hospital Universitari de La Santa Creu de Vic, Vic, Spain.ORCID 0000-0003-2601-469X
Javier González-BuenoCentral Catalonia Chronicity Research Group (C3RG), Centre for Health and Social Care Research (CESS), University of Vic - Central University of Catalonia (UVIC-UCC), Vic, Barcelona, Spain.ORCID 0000-0003-2474-5413
Joan Espaulella-PanicotDepartment of Geriatrics, Hospital Universitari de La Santa Creu de Vic, Vic, Spain.ORCID 0000-0002-7057-0901
Universitat de Vic - Universitat Central de Catalunya · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOlder patients tend to have multimorbidity, represented by multiple chronic diseases or geriatric conditions, which leads to a growing number of prescribed medications. As a result, pharmacological prescription has become a major concern because of the increased difficulties to ensure appropriate prescription in older adults. The study's main objectives were to characterize a cohort of older adults with multimorbidity, carry out a medication review and compare the pharmacological data before and after the medication review globally and according to the frailty index.

methodsThis was a quasi-experimental (uncontrolled pre-post) study with a cohort of patients ≥ 65 years old with multimorbidity. Data were collected from June 2019 to October 2020. Variables assessed included demographic, clinical, and pharmacological data, degree of frailty (Frail-VIG index), medication regimen complexity index, anticholinergic and or sedative burden index, and monthly drug expenditure. Finally, a medication review was carried out by an interdisciplinary team (primary care team and a consultant team with a geriatrician and a clinical pharmacist) by applying the Patient-Centered Prescription model to align the treatment with care goals.

resultsFour hundred twenty-eight patients were recruited [66.6% women; mean age 85.5 (SD 7.67)]. The mean frail index was 0.39 (SD 0.13), corresponding with moderate frailty. Up to 90% of patients presented at least one inappropriate prescription, and the mean of inappropriate prescriptions per patient was 3.14 (SD 2.27). At the three-month follow-up [mortality of 17.7% (n = 76)], the mean chronic medications per patient decreased by 17.96%, varying from 8.13 (SD 3.87) to 6.67 (SD 3.72) (p < 0.001). The medication regimen complexity index decreased by 19.03%, from 31.0 (SD 16.2) to 25.1 (SD 15.1), and the drug burden index mean decreased by 8.40%, from 1.19 (SD 0.82) to 1.09 (SD 0.82) (p < 0.001). A decrease in polypharmacy, medication regimen complexity index, and drug burden index was more frequent among frail patients, especially those with severe frailty (p < 0.001).

conclusionsAn individualized medication review in frail older patients, applying the Patient-Centered Prescription model, decreases pharmacological parameters related to adverse drug effects, such as polypharmacy, therapeutical complexity, and anticholinergic and, or sedative burden. The benefits are for patients with frailty.

Indexed as

FrailtyMultimorbidityAgedAged, 80 and overCholinergic AntagonistsFemaleHumansHypnotics and SedativesMaleMedication ReviewPolypharmacyPrescriptionsCholinergic AntagonistsHypnotics and SedativesInappropriate prescriptionMedication reviewPolypharmacy

Identifiers

PMID35549672
PMCPMC9096338
OpenAlexW4280561003

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.