Evidence map›Paper›PMID 32162288›Full record

ArticleApplied clinical informatics2020

The Impact of Changes to an Electronic Admission Order Set on Prescribing and Clinical Outcomes in the Intensive Care Unit.

Ellen T Muniga, Todd A Walroth, Natalie C Washburn

Abstract read
In one paragraph

Article in Applied clinical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
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.

Ellen T MunigaDepartment of Pharmacy, Bronson Methodist Hospital, Kalamazoo, Michigan, United States.
Todd A WalrothDepartment of Pharmacy, Eskenazi Health, Indianapolis, Indiana, United States.
Natalie C WashburnDepartment of Pharmacy, Bronson Methodist Hospital, Kalamazoo, Michigan, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImplementation of disease-specific order sets has improved compliance with standards of care for a variety of diseases. Evidence of the impact admission order sets can have on care is limited.

objectiveThe main purpose of this article is to evaluate the impact of changes made to an electronic critical care admission order set on provider prescribing patterns and clinical outcomes.

methodsA retrospective, observational before-and-after exploratory study was performed on adult patients admitted to the medical intensive care unit using the Inpatient Critical Care Admission Order Set. The primary outcome measure was the percentage change in the number of orders for scheduled acetaminophen, a histamine-2 receptor antagonist (H2RA), and lactated ringers at admission before implementation of the revised order set compared with after implementation. Secondary outcomes assessed clinical impact of changes made to the order set.

resultsThe addition of a different dosing strategy for a medication already available on the order set (scheduled acetaminophen vs. as needed acetaminophen) had no impact on physician prescribing (0 vs. 0%,

conclusionMaking changes to an admission order set can impact provider prescribing patterns. The type of change made to the order set, in addition to the specific medication changed, may have an effect on how influential the changes are on prescribing patterns.

Indexed as

Medical Order Entry SystemsDrug PrescriptionsFemaleHumansIntensive Care UnitsMaleMiddle AgedPatient Admission

Identifiers

PMID32162288
PMCPMC7065977

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.