Evidence map›Paper›PMID 35788103›Full record

ArticleJMIR human factors2022

Automated Decision Support For Community Mental Health Services Using National Electronic Health Records: Qualitative Implementation Case Study.

Yasmin van Kasteren, Jörg Strobel, Tarun Bastiampillai, Ecushla Linedale, Niranjan Bidargaddi

Open access · goldAbstract read
In one paragraph

Article in JMIR human factors, 2022. 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
0.9field-weighted citation impact, top 28% 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, 6 citations in OpenAlex.

  1. Article
  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

5 authors at 2 institutions in 1 country.

Yasmin van KasterenFlinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, Australia.ORCID https://orcid.org/0000-0002-8905-5934
Jörg StrobelBarossa Fleurieu Adelaide Hills Local Health Network, South Australia, Australia.ORCID https://orcid.org/0000-0003-4077-9269
Tarun BastiampillaiFlinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, Australia.ORCID https://orcid.org/0000-0002-6931-2913
Ecushla LinedaleHealth Translation SA, South Australian Health and Medical Research Institute, Adelaide, Australia.ORCID https://orcid.org/0000-0002-8635-6731
Niranjan BidargaddiFlinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Adelaide, Australia.ORCID https://orcid.org/0000-0003-2868-9260
Flinders University · AUSouth Australian Health and Medical Research Institute · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA high proportion of patients with severe mental illness relapse due to nonadherence to psychotropic medication. In this paper, we use the normalization process theory (NPT) to describe the implementation of a web-based clinical decision support system (CDSS) for Community Mental Health Services (CMHS) called Actionable Intime Insights or AI

objectiveOur objective is to evaluate the pilot implementation of the AI

methodsThe NPT and participatory action framework were used to both explore and support implementation. Qualitative data were collected over the course of the 14-month implementation, in which researchers were active participants. Data were analyzed and coded using the NPT framework. Qualitative data included discussions, meetings, and work products, including emails and documents.

resultsThis study explores the barriers and enablers of implementing a CDSS to support early intervention within CMHS using Medicare data from Australia's national electronic record system, My Health Record (MyHR). The implementation was a series of ongoing negotiations, which resulted in a staged implementation with compromises on both sides. Clinicians were initially hesitant about using a CDSS based on MyHR data and expressed concerns about the changes to their work practice required to support early intervention. Substantial workarounds were required to move the implementation forward. This pilot implementation allowed us to better understand the challenges of implementation and the resources and support required to implement and sustain a model of care based on automated alerts to support early intervention.

conclusionsThe use of decision support based on electronic health records is growing, and while implementation is challenging, the potential benefits of early intervention to prevent relapse and hospitalization and ensure increased efficiency of the health care system are worth pursuing.

Indexed as

adherencealgorithmalgorithmsautomated alertautomated alertscomputerised clinical decision systemdecision supportdecision systemeHealthEHRelectronic health recordshealth recordimplementationmedicationmedication adherencemental healthmental illnessmonitoringnonadherencenormalization process theoryparticipatory action frameworkpsychotropicpsychotropic medicationweb-based

Identifiers

PMID35788103
PMCPMC9297136
OpenAlexW4226149114

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.