Evidence map›Paper›PMID 38802865›Full record

ArticleBMC medical informatics and decision making2024

Using the technology acceptance model to assess clinician perceptions and experiences with a rheumatoid arthritis outcomes dashboard: qualitative study.

Catherine Nasrallah, Cherish Wilson, Alicia Hamblin, Cammie Young, Lindsay Jacobsohn, Mary C Nakamura, Andrew Gross, Mehrdad Matloubian, Judith Ashouri, Jinoos Yazdany and 1 more

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In one paragraph

Article in BMC medical informatics and decision making, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Review
  5. Article
  6. Article
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  8. 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

11 authors.

Catherine NasrallahDivision of Rheumatology, Department of Medicine, University of California, San Francisco, CA, USA.
Cherish WilsonDivision of Rheumatology, Department of Medicine, University of California, San Francisco, CA, USA.
Alicia HamblinDivision of Rheumatology, Department of Medicine, University of California, San Francisco, CA, USA.
Cammie YoungDivision of Rheumatology, Department of Medicine, University of California, San Francisco, CA, USA.
Lindsay JacobsohnDivision of Rheumatology, Department of Medicine, University of California, San Francisco, CA, USA.
Mary C NakamuraDivision of Rheumatology, Department of Medicine, University of California, San Francisco, CA, USA.
Andrew GrossDivision of Rheumatology, Department of Medicine, University of California, San Francisco, CA, USA.
Mehrdad MatloubianDivision of Rheumatology, Department of Medicine, University of California, San Francisco, CA, USA.
Judith AshouriDivision of Rheumatology, Department of Medicine, University of California, San Francisco, CA, USA.
Jinoos YazdanyDivision of Rheumatology, Department of Medicine, University of California, San Francisco, CA, USA.
Gabriela SchmajukDivision of Rheumatology, Department of Medicine, University of California, San Francisco, CA, USA. gabriela.schmajuk@ucsf.edu.

Funding

RESOURCE-BASED CENTER FOR THE ADVANCEMENT OF PRECISION MEDICINE IN RHEUMATOLOGYP30AR070155 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Mary C Nakamura · 2016 to 2026
$8.2M
Advancing Quality and Outcomes Measurement in RheumatologyK24AR074534 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Jinoos Yazdany · 2019 to 2026
$1.5M
AHRQ HHS R01 HS025405NIAMS NIH HHS K24 AR074534NIAMS NIH HHS P30 AR070155
6 · The paper itself

Abstract

backgroundImproving shared decision-making using a treat-to-target approach, including the use of clinical outcome measures, is important to providing high quality care for rheumatoid arthritis (RA). We developed an Electronic Health Record (EHR) integrated, patient-facing sidecar dashboard application that displays RA outcomes, medications, and lab results for use during clinical visits ("RA PRO dashboard"). The purpose of this study was to assess clinician perceptions and experiences using the dashboard in a university rheumatology clinic.

methodsWe conducted focus group (FG) discussions with clinicians who had access to the dashboard as part of a randomized, stepped-wedge pragmatic trial. FGs explored clinician perceptions towards the usability, acceptability, and usefulness of the dashboard. FG data were analyzed thematically using deductive and inductive techniques; generated themes were categorized into the domains of the Technology Acceptance Model (TAM).

results3 FG discussions were conducted with a total of 13 clinicians. Overall, clinicians were enthusiastic about the dashboard and expressed the usefulness of visualizing RA outcome trajectories in a graphical format for motivating patients, enhancing patient understanding of their RA outcomes, and improving communication about medications. Major themes that emerged from the FG analysis as barriers to using the dashboard included inconsistent collection of RA outcomes leading to sparse data in the dashboard and concerns about explaining RA outcomes, especially to patients with fibromyalgia. Other challenges included time constraints and technical difficulties refreshing the dashboard to display real-time data. Methods for integrating the dashboard into the visit varied: some clinicians used the dashboard at the beginning of the visit as they documented RA outcomes; others used it at the end to justify changes to therapy; and a few shared it only with stable patients.

conclusionsThe study provides valuable insights into clinicians' perceptions and experiences with the RA PRO dashboard. The dashboard showed promise in enhancing patient-clinician communication, shared decision-making, and overall acceptance among clinicians. Addressing challenges related to data collection, education, and tailoring dashboard use to specific patient populations will be crucial for maximizing its potential impact on RA care. Further research and ongoing improvements in dashboard design and implementation are warranted to ensure its successful integration into routine clinical practice.

Indexed as

Arthritis, RheumatoidAttitude of Health PersonnelElectronic Health RecordsFocus GroupsQualitative ResearchAdultDecision Making, SharedFemaleHumansMaleMiddle AgedOutcome Assessment, Health CareClinicianDashboardDisease ActivityFocus GroupPatient reported outcomesPerceptionsPhysical functionQualitative researchRheumatoid arthritisTechnology Acceptance Model

Identifiers

PMID38802865
PMCPMC11129391

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.