Evidence map›Paper›PMID 30667607›Full record

ArticleThe American journal of managed care2019

Inpatient electronic health record maintenance from 2010 to 2015.

Vincent X Liu, Nimah Haq, Ignatius C Chan, Brian Hoberman

Abstract read
In one paragraph

Article in The American journal of managed care, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. 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.

Vincent X LiuKaiser Permanente Division of Research, 2000 Broadway, Oakland, CA 95070. Email: Vincent.x.liu@kp.org.
Nimah Haq
Ignatius C Chan
Brian Hoberman

Funding

Identifying pre-sepsis opportunities for early, targeted intervention - Equipment SupplementR35GM128672 · NIGMS · KAISER FOUNDATION RESEARCH INSTITUTE · PI Vincent Liu · 2018 to 2026
$4.3M
Data-driven Precision medicine in sepsisK23GM112018 · NIGMS · KAISER FOUNDATION RESEARCH INSTITUTE · PI LIU, VINCENT · 2014 to 2017
$768k
NIGMS NIH HHS K23 GM112018NIGMS NIH HHS R35 GM128672
6 · The paper itself

Abstract

objectivesTo describe the scale and scope of inpatient electronic health record (EHR) maintenance following initial implementation. STUDY

designA retrospective study reviewing EHR change documentation within an integrated healthcare delivery system that has 21 hospitals.

methodsBetween 2010 and 2015, we identified and categorized all significant changes made to the inpatient EHR, as documented within monthly EHR communication updates. We categorized EHR changes as updates to existing functionality or upgrades to new functionality. We grouped changes within larger functional domains as orders, alerts and customization, surgical and emergency department (ED), data review, reports and health information management, and other. We also identified the clinical areas and user roles targeted by these changes.

resultsOver a 6-year period, 5551 unique changes were made to the inpatient EHR, with a median of 72 changes per month. Changes most frequently targeted orders (44.7% of 2190 change documents) and order sets (29.9% of documents). In total, changes affected 135 EHR functions. A total of 151 unique user roles were affected by these changes, with the most frequent roles including nurses (30.6%), physicians (26.6%), and other clinical staff (22.7%). The clinical areas most targeted by changes included surgical areas and the ED.

conclusionsOver 6 years, EHR maintenance for clinical functionality was substantial and varied with pervasive impacts, requiring persistent attention, diverse expertise, and interdisciplinary collaboration.

Indexed as

InpatientsDelivery of Health Care, IntegratedElectronic Health RecordsHumansRetrospective Studies

Identifiers

PMID30667607
PMCPMC6596284

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Registered trials

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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.