Evidence map›Paper›PMID 38094672›Full record

ArticleThe journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG2023

Pharmacist Metrics in the Pediatric Intensive Care Unit: an Exploration of the Medication Regimen Complexity-Intensive Care Unit (MRC-ICU) Score.

Swaminathan Kandaswamy, Thomas E Dawson, Whitney H Moore, Katherine Howell, Jonathan Beus, Olutola Adu, Andrea Sikora

Open access · bronzeAbstract read
In one paragraph

Article in The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG, 2023. 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
0.3field-weighted citation impact, top 35% 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, 1 citations in OpenAlex.

  1. Observational
  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 4 institutions in 1 country.

Swaminathan KandaswamyDepartment of Pediatrics (SK), Emory University School of Medicine, Atlanta, GA.
Thomas E DawsonDivision of IS&T (TED, KH, JB), Children's Healthcare of Atlanta, Atlanta, GA.
Whitney H MooreWolfson Children's Hospital/Baptist Health (WHM), Jacksonville, FL.
Katherine HowellDivision of IS&T (TED, KH, JB), Children's Healthcare of Atlanta, Atlanta, GA.
Jonathan BeusDivision of IS&T (TED, KH, JB), Children's Healthcare of Atlanta, Atlanta, GA.
Olutola AduDivision of Pharmacy (OA) Children's Healthcare of Atlanta, Atlanta, GA.
Andrea SikoraCollege of Pharmacy (AS), University of Georgia, Athens, GA.
Children's Healthcare of Atlanta · USEmory University · USUniversity of Georgia · USWolfson Children's Hospital · US

Funding

Artificial intelligence-based health IT tools to optimize critical care pharmacist resources through adverse drug event predictionR01HS029009 · AHRQ · UNIVERSITY OF GEORGIA · PI Andrea Sikora · 2022 to 2026
$1.8M
Machine learning validation of medication regimen complexity for critical care pharmacist resource predictionR21HS028485 · AHRQ · UNIVERSITY OF GEORGIA · PI SIKORA, ANDREA · 2022 to 2023
$294k
AHRQ HHS R01 HS029009AHRQ HHS R21 HS028485
6 · The paper itself

Abstract

introductionThe medication regimen complexity-intensive care unit (MRC-ICU) score has been developed and validated as an objective predictive metric for patient outcomes and pharmacist workload in the adult critically ill population. The purpose of this study was to explore the MRC-ICU and other workload metrics in the pediatric ICU (PICU).

methodsThis study was a retrospective cohort of pediatric ICU patients admitted to a single institution -between February 2, 2022 - August 2, 2022. Two scores were calculated, including the MRC-ICU and the pediatric Daily Monitoring System (pDMS). Data were extracted from the electronic health record. The primary outcome was the correlation of the MRC-ICU to mortality, as measured by Pearson -correlation -coefficient. Additionally, the correlation of MRC-ICU to number of orders was evaluated. Secondary -analyses explored the correlation of the MRC-ICU with pDMS and with hospital and ICU length of stay.

resultsA total of 2,232 patients were included comprising 2,405 encounters. The average age was 6.9 years (standard deviation [SD] 6.3 years). The average MRC-ICU score was 3.0 (SD 3.8). For the primary outcome, MRC-ICU was significantly positively correlated to mortality (0.22 95% confidence interval [CI 0.18 - 0.26]), p<0.05. Additionally, MRC-ICU was significantly positively correlated to ICU length of stay (0.38 [CI 0.34 - 0.41]), p<0.05. The correlation between the MRC-ICU and pDMS was (0.72 [CI 0.70 - 0.73]), p<0.05.

conclusionIn this pilot study, MRC-ICU demonstrated an association with existing prioritization metrics and with mortality and length of ICU stay in PICU population. Further, larger scale studies are required.

Indexed as

critical careinformaticsmedication regimen complexitypediatricspharmacistspharmacy

Identifiers

PMID38094672
PMCPMC10715388
OpenAlexW4389609949

What OpenQuestion holds

Textmetadata
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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.