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Record W4393965931 · doi:10.1016/j.xkme.2024.100810

Medication Deprescribing in Patients Receiving Hemodialysis: A Prospective Controlled Quality Improvement Study

2024· article· en· W4393965931 on OpenAlex
Émilie Bortolussi‐Courval, Tiina Podymow, Marisa Battistella, Emilie Trinh, Thomas A. Mavrakanas, Lisa McCarthy, Joseph Moryousef, Ryan Hanula, Jean‐François Huon, Rita S. Suri, Todd C. Lee, Emily G. McDonald

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueKidney Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsUniversity of TorontoMcGill University Health CentreMcGill University
FundersMcGill University Health CentreMcGill University
KeywordsDeprescribingPolypharmacyMedicineClinical pharmacyEmergency medicineDialysisIntensive care medicinePharmacyInternal medicineNursing

Abstract

fetched live from OpenAlex

Rationale & ObjectivePatients treated with dialysis are commonly prescribed multiple medications (polypharmacy), including some potentially inappropriate medications (PIMs). PIMs are associated with an increased risk of medication harm (eg, falls, fractures, hospitalization). Deprescribing is a solution that proposes to stop, reduce, or switch medications to a safer alternative. Although deprescribing pairs well with routine medication reviews, it can be complex and time-consuming. Whether clinical decision support improves the process and increases deprescribing for patients treated with dialysis is unknown. This study aimed to test the efficacy of the clinical decision support software MedSafer at increasing deprescribing for patients treated with dialysis.Study DesignProspective controlled quality improvement study with a contemporaneous control.Setting & ParticipantsPatients prescribed ≥5 medications in 2 outpatient dialysis units in Montréal, Canada.ExposuresPatient health data from the electronic medical record were input into the MedSafer web-based portal to generate reports listing candidate PIMs for deprescribing. At the time of a planned biannual medication review (usual care), treating nephrologists in the intervention unit additionally received deprescribing reports, and patients received EMPOWER brochures containing safety information on PIMs they were prescribed. In the control unit, patients received usual care alone.Analytical ApproachThe proportion of patients with ≥1 PIMs deprescribed was compared between the intervention and control units following a planned medication review to determine the effect of using MedSafer. The absolute risk difference with 95% CI and number needed to treat were calculated.ResultsIn total, 195 patients were included (127, control unit; 68, intervention unit); the mean age was 64.8 ± 15.9 (SD), and 36.9% were women. The proportion of patients with ≥1 PIMs deprescribed in the control unit was 3.1% (4/127) vs 39.7% (27/68) in the intervention unit (absolute risk difference, 36.6%; 95% CI, 24.5%-48.6%; P < 0.0001; number needed to treat = 3).LimitationsThis was a single-center nonrandomized study with a type 1 error risk. Deprescribing durability was not assessed, and the study was not powered to reduce adverse drug events.ConclusionsDeprescribing clinical decision support and patient EMPOWER brochures provided during medication reviews could be an effective and scalable intervention to address PIMs in the dialysis population. A confirmatory randomized controlled trial is needed.RegistrationNCT05585268.Plain-Language SummaryPatients treated with dialysis are commonly prescribed multiple medications, some of which are potentially inappropriate medications (PIMs). PIMs can increase a patient’s pill burden and are associated with an increased risk of harm (some examples include falls, fractures, and hospitalization). Deprescribing is a proposed solution that aims to highlight medications that can be stopped, reduced, or switched to a safer option, under supervision of a health care provider. We aimed to determine if a quality improvement intervention in the dialysis unit could increase deprescribing compared to usual care. The study took place in 2 outpatient hemodialysis units where usual care involves nurses and nephrologists performing medication reviews twice a year. The intervention was a deprescribing report that was generated with the help of a software tool called MedSafer, along with brochures for patients with information on PIMs they were taking. In the intervention unit, we increased the number of patients who had a medication safely deprescribed by 36.6% more than on the control unit. Although the study was small, a future larger study in dialysis patients might show that a computer software such as MedSafer can prevent harmful complications from taking too many medications. Patients treated with dialysis are commonly prescribed multiple medications (polypharmacy), including some potentially inappropriate medications (PIMs). PIMs are associated with an increased risk of medication harm (eg, falls, fractures, hospitalization). Deprescribing is a solution that proposes to stop, reduce, or switch medications to a safer alternative. Although deprescribing pairs well with routine medication reviews, it can be complex and time-consuming. Whether clinical decision support improves the process and increases deprescribing for patients treated with dialysis is unknown. This study aimed to test the efficacy of the clinical decision support software MedSafer at increasing deprescribing for patients treated with dialysis. Prospective controlled quality improvement study with a contemporaneous control. Patients prescribed ≥5 medications in 2 outpatient dialysis units in Montréal, Canada. Patient health data from the electronic medical record were input into the MedSafer web-based portal to generate reports listing candidate PIMs for deprescribing. At the time of a planned biannual medication review (usual care), treating nephrologists in the intervention unit additionally received deprescribing reports, and patients received EMPOWER brochures containing safety information on PIMs they were prescribed. In the control unit, patients received usual care alone. The proportion of patients with ≥1 PIMs deprescribed was compared between the intervention and control units following a planned medication review to determine the effect of using MedSafer. The absolute risk difference with 95% CI and number needed to treat were calculated. In total, 195 patients were included (127, control unit; 68, intervention unit); the mean age was 64.8 ± 15.9 (SD), and 36.9% were women. The proportion of patients with ≥1 PIMs deprescribed in the control unit was 3.1% (4/127) vs 39.7% (27/68) in the intervention unit (absolute risk difference, 36.6%; 95% CI, 24.5%-48.6%; P < 0.0001; number needed to treat = 3). This was a single-center nonrandomized study with a type 1 error risk. Deprescribing durability was not assessed, and the study was not powered to reduce adverse drug events. Deprescribing clinical decision support and patient EMPOWER brochures provided during medication reviews could be an effective and scalable intervention to address PIMs in the dialysis population. A confirmatory randomized controlled trial is needed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.078
GPT teacher head0.416
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it