Evidence map›Paper›PMID 35521024›Full record

ArticleHospital pharmacy2022

Real-Time Risk Tool for Pharmacy Interventions.

Hanh L Nguyen, Kristin S Alvarez, Boryana Manz, Arun Nethi, Varun Sharma, Venkatraghavan Sundaram, Manjula Julka

Open access · bronzeAbstract read
In one paragraph

Article in Hospital pharmacy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
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.

Hanh L NguyenParkland Health and Hospital System, Dallas, TX, USA.ORCID https://orcid.org/0000-0003-4154-9561
Kristin S AlvarezParkland Health and Hospital System, Dallas, TX, USA.
Boryana ManzParkland Center for Clinical Innovation, Dallas, TX, USA.
Arun NethiParkland Center for Clinical Innovation, Dallas, TX, USA.
Varun SharmaParkland Health and Hospital System, Dallas, TX, USA.
Venkatraghavan SundaramParkland Center for Clinical Innovation, Dallas, TX, USA.
Manjula JulkaParkland Center for Clinical Innovation, Dallas, TX, USA.
Parkland Center For Clinical Innovation · USParkland Health & Hospital System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Adverse drug events (ADEs) result in excess hospitalizations. Thorough admission medication histories (AMHs) may prevent ADEs; however, the resources required oftentimes outweigh what is available in large hospital settings. Previous risk prediction models embedded into the Electronic Medical Record (EMR) have been used at hospitals to aid in targeting delivery of scarce resources. Objective: To determine if an AMH scoring tool used to allocate resources can decrease 30-day hospital readmissions. Design Setting and Participants: Propensity-matched cohort study, Medicine/Surgery patients in large academic safety-net hospital. Intervention or Exposure: Pharmacy-conducted AMHs identified by risk model versus standard of care AMH. Main Outcomes and Measures: A total of 30-day hospital readmissions and inpatient ADE prevention. Results: The model screened 87 240 hospitalizations between June 2017 and June 2019 and 4027 patients per group were included. There were significantly less 30 day readmissions among high-risk identified patients that received a pharmacy-conducted AMH compared to controls (11% vs 15%; Conclusions: A risk tool embedded into the EMR can be used to identify patients whom pharmacy teams can easily target for AMHs. This study showed significant reductions in readmissions for patients identified as high-risk. However, the same benefit in readmissions was not seen in those identified at low-risk, which supports allocating resources to those that will benefit the most.

Indexed as

adverse drug reactionsclinical pharmacy servicesmedication safetymedication therapy managementmonitoring drug therapytechnicians

Identifiers

PMID35521024
PMCPMC9065517
OpenAlexW3107824035

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.