Evidence map›Paper›PMID 40916113›Full record

ArticleHome healthcare now

A Pharmacist-Led Quality Improvement Project to Optimize Medication Evaluation and Reconciliation in Home Healthcare.

Jeffrey A Clark, Kimberly C McKeirnan, Brian J Gates

Abstract read
In one paragraph

Article in Home healthcare now. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Jeffrey A Clark
Kimberly C McKeirnan
Brian J Gates

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medication reconciliation was adopted as a National Patient Safety Goal by the Joint Commission in 2005 and is now standard practice across care settings. More recently, the concept of medication optimization has gained attention, recognizing that safe medication use requires more than reconciliation alone. Home healthcare (HHC) is one setting with a critical need for medication optimization. This work describes a pharmacist-led interdisciplinary team (IDT) effort to reduce hospitalization rates at Providence VNA Home Health by improving medication reconciliation, evaluation, and prescriber communication. The IDT developed a tool and a 1-hour training with operational definitions and scenarios for reconciliation and documentation, along with a separate training focused on medication evaluation. To assess training effectiveness, the primary outcome was to reduce 30-day hospitalizations among high-risk heart failure patients to below 12%. This outcome was met and sustained for 8 weeks post-implementation. A secondary goal-reducing 30-day rehospitalizations per Strategic Healthcare Programs (SHP)-was also met and sustained from April to December 2020. This quality improvement project demonstrated that enhancing medication reconciliation and evaluation in high-risk patients reduces hospitalizations. Reconciliation may be especially important in patients with two or more self-reported unreconciled medications in the EHR, which may signal suboptimal medication evaluation. Addressing the challenges HHC clinicians face in optimizing medications and reinforcing best practices can improve outcomes. Pharmacists play a key role in interdisciplinary teams in HHC, given the complexity of medications and their impact on quality measures.

Indexed as

Home Care ServicesMedication ReconciliationPharmacistsQuality ImprovementAgedFemaleHospitalizationHumansMaleMedication ErrorsPatient Care Team

Identifiers

PMID40916113
PMCPMC12412458

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.