Evidence map›Paper›PMID 33148237›Full record

ArticleBMC medical informatics and decision making2020

Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury.

Megan Howarth, Meha Bhatt, Eleanor Benterud, Anna Wolska, Evan Minty, Kyoo-Yoon Choi, Andrea Devrome, Tyrone G Harrison, Barry Baylis, Elijah Dixon and 3 more

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

13 authors.

Megan HowarthDepartment of Medicine, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
Meha BhattDepartment of Medicine, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
Eleanor BenterudDepartment of Medicine, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
Anna WolskaAlberta Health Services, Calgary, AB, Canada.
Evan MintyDepartment of Medicine, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
Kyoo-Yoon ChoiDepartment of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Andrea DevromeDepartment of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Tyrone G HarrisonDepartment of Medicine, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
Barry BaylisDepartment of Medicine, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada.
Elijah DixonDepartment of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Indraneel DattaDepartment of Surgery, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Neesh PannuDepartment of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada.
Matthew T JamesDepartment of Medicine, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada. mjames@ucalgary.ca.ORCID 0000-0002-1876-3917

Funding

CIHR FDN143240
6 · The paper itself

Abstract

backgroundAcute kidney injury (AKI) is common in hospitalized patients and is associated with poor patient outcomes and high costs of care. The implementation of clinical decision support tools within electronic medical record (EMR) could improve AKI care and outcomes. While clinical decision support tools have the potential to enhance recognition and management of AKI, there is limited description in the literature of how these tools were developed and whether they meet end-user expectations.

methodsWe developed and evaluated the content, acceptability, and usability of electronic clinical decision support tools for AKI care. Multi-component tools were developed within a hospital EMR (Sunrise Clinical Manager™, Allscripts Healthcare Solutions Inc.) currently deployed in Calgary, Alberta, and included: AKI stage alerts, AKI adverse medication warnings, AKI clinical summary dashboard, and an AKI order set. The clinical decision support was developed for use by multiple healthcare providers at the time and point of care on general medical and surgical units. Functional and usability testing for the alerts and clinical summary dashboard was conducted via in-person evaluation sessions, interviews, and surveys of care providers. Formal user acceptance testing with clinical end-users, including physicians and nursing staff, was conducted to evaluate the AKI order set.

resultsConsiderations for appropriate deployment of both non-disruptive and interruptive functions was important to gain acceptability by clinicians. Functional testing and usability surveys for the alerts and clinical summary dashboard indicated that the tools were operating as desired and 74% (17/23) of surveyed healthcare providers reported that these tools were easy to use and could be learned quickly. Over three-quarters of providers (18/23) reported that they would utilize the tools in their practice. Three-quarters of the participants (13/17) in user acceptance testing agreed that recommendations within the order set were useful. Overall, 88% (15/17) believed that the order set would improve the care and management of AKI patients.

conclusionsDevelopment and testing of EMR-based decision support tools for AKI with clinicians led to high acceptance by clinical end-users. Subsequent implementation within clinical environments will require end-user education and engagement in system-level initiatives to use the tools to improve care.

Indexed as

Decision Support Systems, ClinicalElectronic Health RecordsAcute Kidney InjuryAlbertaFemaleHospitalsHumansMaleAcute kidney injuryClinical decision supportElectronic medical record

Identifiers

PMID33148237
PMCPMC7640650

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.