Evidence map›Paper›PMID 32215894›Full record

ArticleApplied clinical informatics2020

Impact of Patient Census and Admission Mortality on Pediatric Intensive Care Unit Attending Electronic Health Record Activity: A Preliminary Study.

Conrad Krawiec, Christy Stetter, Lan Kong, Paul Haidet

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. Measuring Documentation Burden in Healthcare.Journal of general internal medicine · 2024
    Pooled it
  2. Article
  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.

Conrad KrawiecPediatric Critical Care Medicine, Department of Pediatrics, Penn State Milton S. Hershey Medical Center, Penn State Hershey College of Medicine, Penn State Hershey Children's Hospital, Hershey, Pennsylvania, United States.
Christy StetterDepartment of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, Pennsylvania, United States.
Lan KongDepartment of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, Pennsylvania, United States.
Paul HaidetOffice for Scholarship in Learning and Education Research, Pennsylvania State University College of Medicine, Hershey, Pennsylvania, United States.

Funding

Penn State Clinical and Translational Science InstituteUL1TR002014 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI KRASCHNEWSKI, JENNIFER L. · 2016 to 2025
$33.7M
Penn State Clinical and Translational Science InstituteUL1TR000127 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI SINOWAY, LAWRENCE I · 2012 to 2015
$17.1M
NCATS NIH HHS UL1 TR000127NCATS NIH HHS UL1 TR002014
6 · The paper itself

Abstract

backgroundPhysicians may spend a significant amount of time using the electronic health record (EHR), but this is understudied in the pediatric intensive care unit (PICU). The objective of this study is to quantify PICU attending physician EHR usage and determine its association with patient census and mortality scores.

methodsDuring the year 2016, total EHR, chart review, and documentation times of 7 PICU physicians were collected retrospectively utilizing an EHR-embedded time tracking software package. We examined associations between documentation times and patient census and maximum admission mortality scores. Odds ratios (ORs) are reported per 1-unit increase in patient census and mortality scores.

resultsOverall, total daily EHR usage time (median time [hh:mm] [25th, 75th percentile]) was 2:10 (1:31, 3:08). For all hours (8 a.m.-8 a.m.), no strong association was noted between total EHR time, chart review, and documentation times and patient census, Pediatric Index of Mortality 2 (PIM2), or Pediatric Risk of Mortality 3 (PRISM3) scores. For regular hours (8 a.m.-7 p.m.), no strong association was noted between total EHR, chart review, and documentation times and patient census, PIM2, or PRISM3 scores. When patient census was higher, the odds of EHR after-hour usage (7 p.m.-8 a.m.) was higher (OR 1.262 [1.135, 1.403],

conclusionWe performed a novel evaluation of physician EHR workflow in our PICU. Our pediatric critical care physicians spend approximately 2 hours (out of an expected 10-hour shift) each service day using the EHR, but there was no strong or consistent association between EHR usage and patient census or mortality scores. Future larger scale studies are needed to ensure validity of these results.

Indexed as

MortalityElectronic Health RecordsHumansIntensive Care Units, PediatricPatient AdmissionTime FactorsWorkflow

Identifiers

PMID32215894
PMCPMC7096317

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.