Evidence map›Paper›PMID 35522472›Full record

ArticleJMIR human factors2022

Enhancing Clinical Information Display to Improve Patient Encounters: Human-Centered Design and Evaluation of the Parkinson Disease-BRIDGE Platform.

Ethan G Brown, Erica Schleimer, Ian O Bledsoe, William Rowles, Nicolette A Miller, Stephan J Sanders, Katherine P Rankin, Jill L Ostrem, Caroline M Tanner, Riley Bove

Abstract 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 8 papers.

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

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Actionable Wearables Data for the Neurology Clinic: A Proof-of-Concept Tool.Annals of clinical and translational neurology · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
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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

10 authors.

Ethan G BrownUniversity of California San Francisco Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0001-9744-8562
Erica SchleimerUniversity of California San Francisco Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0001-5040-6306
Ian O BledsoeUniversity of California San Francisco Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0001-8885-8148
William RowlesUniversity of California San Francisco Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0002-5613-0483
Nicolette A MillerUniversity of California San Francisco Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0001-8987-4908
Stephan J SandersDepartment of Psychiatry, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0001-9112-5148
Katherine P RankinUniversity of California San Francisco Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0002-3611-0848
Jill L OstremUniversity of California San Francisco Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0001-7018-9521
Caroline M TannerUniversity of California San Francisco Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0002-3775-5082
Riley BoveUniversity of California San Francisco Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0002-2034-8800

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPeople with Parkinson disease (PD) have a variety of complex medical problems that require detailed review at each clinical encounter for appropriate management. Care of other complex conditions has benefited from digital health solutions that efficiently integrate disparate clinical information. Although various digital approaches have been developed for research and care in PD, no digital solution to personalize and improve communication in a clinical encounter is readily available.

objectiveWe intend to improve the efficacy and efficiency of clinical encounters with people with PD through the development of a platform (PD-BRIDGE) with personalized clinical information from the electronic health record (EHR) and patient-reported outcome (PRO) data.

methodsUsing human-centered design (HCD) processes, we engaged clinician and patient stakeholders in developing PD-BRIDGE through three phases: an inspiration phase involving focus groups and discussions with people having PD, an ideation phase generating preliminary mock-ups for feedback, and an implementation phase testing the platform. To qualitatively evaluate the platform, movement disorders neurologists and people with PD were sent questionnaires asking about the technical validity, usability, and clinical relevance of PD-BRIDGE after their encounter.

resultsThe HCD process led to a platform with 4 modules. Among these, 3 modules that pulled data from the EHR include a longitudinal module showing motor ratings over time, a display module showing the most recently collected clinical rating scales, and another display module showing relevant laboratory values and diagnoses; the fourth module displays motor symptom fluctuation based on an at-home diary. In the implementation phase, PD-BRIDGE was used in 17 clinical encounters for patients cared for by 1 of 11 movement disorders neurologists. Most patients felt that PD-BRIDGE facilitated communication with their clinician (n=14, 83%) and helped them understand their disease trajectory (n=11, 65%) and their clinician's recommendations (n=11, 65%). Neurologists felt that PD-BRIDGE improved their ability to understand the patients' disease course (n=13, 75% of encounters), supported clinical care recommendations (n=15, 87%), and helped them communicate with their patients (n=14, 81%). In terms of improvements, neurologists noted that data in PD-BRIDGE were not exhaustive in 62% (n=11) of the encounters.

conclusionsIntegrating clinically relevant information from EHR and PRO data into a visually efficient platform (PD-BRIDGE) can facilitate clinical encounters with people with PD. Developing new modules with more disparate information could improve these complex encounters even further.

Indexed as

digital healthhuman-centered designParkinson diseasepersonal health recordvisualization in eHealth

Identifiers

PMID35522472
PMCPMC9123539

What OpenQuestion holds

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LicenceCC BY
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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.