Evidence map›Paper›PMID 39525833›Full record

ArticleFrontiers in pediatrics2024

Digital health technology to support patient-centered shared decision making at point of care for juvenile idiopathic arthritis.

Bin Huang, Michal Kouril, Chen Chen, Nancy M Daraiseh, Kerry Ferraro, Melissa L Mannion, Hermine I Brunner, Daniel J Lovell, Esi M Morgan

Abstract read
In one paragraph

Article in Frontiers in pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Bin HuangDivision of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
Michal KourilDepartment of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH, United States.
Chen ChenDivision of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
Nancy M DaraisehDivision of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
Kerry FerraroJIA Parent, Lower Gwynedd, PA, United States.
Melissa L MannionDepartment of Pediatrics, University of Alabama at Birmingham, Birmingham, AL, United States.
Hermine I BrunnerDepartment of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH, United States.
Daniel J LovellDepartment of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH, United States.
Esi M MorganDivision of Rheumatology, Department of Pediatrics, Seattle Children's Hospital, Seattle, WA, United States.

Funding

Pediatric musculOskeletal & RheumaTology Innovation COre center (PORTICO)P30AR076316 · NIAMS · CINCINNATI CHILDRENS HOSP MED CTR · PI BRUNNER, HERMINE I · 2019 to 2023
$3.4M
NIAMS NIH HHS P30 AR076316
6 · The paper itself

Abstract

Despite availability of multiple FDA approved therapies, many children with juvenile idiopathic arthritis (JIA) suffer pain and disability due to uncontrolled disease. The term JIA includes a heterogeneous set of conditions unified by chronic inflammatory arthritis, collectively affecting 1:1,000 children. When reviewing treatment options with families the rheumatologist currently refers to the experience of the average patient in relatively small controlled clinical trials, to consensus-based treatment plans, or increasingly the choice is dictated by the formulary restrictions of insurance payers. The current paradigm for treatment selection does not incorporate real-world evidence of treatment effectiveness centered to the individual patients with whom decisions are to be made. Treatment decisions based on the evidence of the average patient are not optimized to reflect the unique clinical characteristics of an individual with JIA and their disease course, nor does it account for heterogeneous treatment effects. To guide treatment choices centered around each patient, we describe a novel concept of utilizing digital health technology to bring patient-centered information into shared decision-making discussions based on comparative effectiveness analysis of electronic health record or observational clinical registry data of patients with similar characteristics. The envisioned digital tool will organize and present data relevant to the individual patient and enable evidence-based individualized treatment decision making when used in a collaborative manner with the patient family and rheumatologist. Capabilities in digital health technology, data capturing, and analytical methodologies are ripe for this endeavor. This brings the concept of a learning health system directly to the point of care.

Indexed as

clinical decision support systemdigital health technologyjuvenile idiopathic arthritislearning network modelpersonalized medicineregistry analysisshared decision making

Identifiers

PMID39525833
PMCPMC11543470

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.