Evidence map›Paper›PMID 27627965›Full record

ArticleJMIR mHealth and uHealth2016

User-Centered Design of a Tablet Waiting Room Tool for Complex Patients to Prioritize Discussion Topics for Primary Care Visits.

Courtney R Lyles, Andrea Altschuler, Neetu Chawla, Christine Kowalski, Deanna McQuillan, Elizabeth Bayliss, Michele Heisler, Richard W Grant

2 registry-linked trialsOpen access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 28 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 4 pooled it
5.0field-weighted citation impact, top 4% 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.

NCT02707146 nacompletednot on this map

Aligning the Visit Priorities of Complex Patients and Their Primary Care Providers

TypeinterventionalSponsorKaiser PermanenteRan2016 to 2018Enrolled750ConditionsPrimary Health Care, Quality of Health Care, Comorbidity, CommunicationArmsVisit Planner, Attention Control Pamphlet, iPad
NCT04070456 nacompletednot on this mapstarted 2019, after this paper: background citation

Addressing Social Determinants of Health to Reduce Physician Burnout

TypeinterventionalSponsorWake Forest University Health SciencesRan2019 to 2021Enrolled34ConditionsBurnout, ProfessionalArmsTablet-based SDH tool
3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 4 syntheses or guidelines pooled it, 49 citations in OpenAlex.

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  10. "You Can See the Connections": Facilitating Visualization of Care Priorities in People Living with Multiple Chronic Health Conditions.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2023
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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

8 authors at 1 institution in 1 country.

Courtney R LylesCenter for Vulnerable Populations, Division of General Internal Medicine, University of California, San Francisco, San Francisco, CA, United States. Courtney.Lyles@ucsf.edu.ORCID http://orcid.org/0000-0002-1111-8595
University of San Francisco · US

Funding

Research BaseP30DK092926 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARY ELLEN MICHELE HEISLER, ADESUWA B OLOMU · 2011 to 2026
$10.0M
Research ProjectU54CA153499 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CHEN, MOON SHAO-CHUANG, CHOW, EDWARD A. · 2010 to 2015
$6.7M
Engaging Diverse Patients in Using an Online Patient PortalR00HS022408 · AHRQ · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LYLES, COURTNEY REES · 2015 to 2017
$740k
AHRQ HHS R00 HS022408NCI NIH HHS U54 CA153499NIDDK NIH HHS P30 DK092926
6 · The paper itself

Abstract

backgroundComplex patients with multiple chronic conditions often face significant challenges communicating and coordinating with their primary care physicians. These challenges are exacerbated by the limited time allotted to primary care visits.

objectiveOur aim was to employ a user-centered design process to create a tablet tool for use by patients for visit discussion prioritization.

methodsWe employed user-centered design methods to create a tablet-based waiting room tool that enables complex patients to identify and set discussion topic priorities for their primary care visit. In an iterative design process, we completed one-on-one interviews with 40 patients and their 17 primary care providers, followed by three design sessions with a 12-patient group. We audiorecorded and transcribed all discussions and categorized major themes. In addition, we met with 15 key health communication, education, and technology leaders within our health system to further review the design and plan for broader implementation of the tool. In this paper, we present the significant changes made to the tablet tool at each phase of this design work.

resultsPatient feedback emphasized the need to make the tablet tool accessible for patients who lacked technical proficiency and to reduce the quantity and complexity of text presentation. Both patients and their providers identified specific content choices based on their personal experiences (eg, the ability to raise private or sensitive concerns) and recommended targeting new patients. Stakeholder groups provided essential input on the need to augment text with video and to create different versions of the videos to match sex and race/ethnicity of the actors with patients.

conclusionsUser-centered design in collaboration with patients, providers, and key health stakeholders led to marked evolution in the initial content, layout, and target audience for a tablet waiting room tool intended to assist complex patients with setting visit discussion priorities.

Indexed as

chronic diseasecomputers, handheldhealth communicationmedical informaticsmobile applicationsprimary health care

Identifiers

PMID27627965
PMCPMC5040865
OpenAlexW2520316485

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.