Evidence map›Paper›PMID 28815131›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2017

Integrating Medication Alert Data into a Clinical Data Repository to Enable Retrospective Study of Drug Interaction Alerts in Clinical Practice.

Mei Liu, Brittany L Melton, Gregory Ator, Lemuel R Waitman

Open access · greenAbstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 14% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

4 authors at 2 institutions in 1 country.

Mei LiuUniversity of Kansas Medical Center, Department of Internal Medicine, Division of Medical Informatics, Kansas City, KS.
Brittany L MeltonThe University of Kansas, School of Pharmacy, Lawrence, KS.
Gregory AtorUniversity of Kansas Medical Center, Department of Otolaryngology, Kansas City, KS.
Lemuel R WaitmanUniversity of Kansas Medical Center, Department of Internal Medicine, Division of Medical Informatics, Kansas City, KS.
University of Kansas Medical Center · USUniversity of Kansas · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current clinical data repositories primarily extract data from multiple administrative and electronic medical record (EMR) data resources (e.g., hospital and physician billing records) containing specific patient-level data including demographics, medications, laboratory results, diagnoses, and procedure codes. It overlooks the importance of EMR system-level data (e.g., medication alerts that are routinely used by physicians, nurses, and pharmacists for decision support) for the surveillance of EMR decision support tools. These medication alerts are a significant source of information for providers, to minimize avoidable adverse drug events. This study describes the integration of medication alert data into an i2b2-based clinical data repository to support the investigation of clinical events occurring around patients with anticoagulation treatment that triggered drug-drug interaction alerts. The integration of medication alerts allows us to repurpose the clinical and translational research infrastructure to conduct retrospective effectiveness surveillance of clinical decision support tools.

Identifiers

PMID28815131
PMCPMC5543377
OpenAlexW2787782119

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.