Evidence map›Paper›PMID 38028731›Full record

ArticleJAMIA open2023

Implementation and evaluation of an electronic health record-integrated app for postpartum monitoring of hypertensive disorders of pregnancy using patient-contributed data collection.

Prashila Dullabh, Krysta K Heaney-Huls, Andrew B Chiao, Melissa G Callaham, Priyanka Desai, Nicole A Gauthreaux, Nitu Kashyap, David F Lobach, Aziz Boxwala

Open access · goldAbstract readCase Reports
In one paragraph

Article in JAMIA open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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

9 authors at 2 institutions in 1 country.

Prashila DullabhHealth Sciences Department, NORC at the University of Chicago, Bethesda, MD 20814, United States.
Krysta K Heaney-HulsHealth Sciences Department, NORC at the University of Chicago, Bethesda, MD 20814, United States.
Andrew B ChiaoHealth Sciences Department, NORC at the University of Chicago, Bethesda, MD 20814, United States.ORCID https://orcid.org/0000-0002-8116-4546
Melissa G CallahamHealth Sciences Department, NORC at the University of Chicago, Bethesda, MD 20814, United States.
Priyanka DesaiHealth Sciences Department, NORC at the University of Chicago, Bethesda, MD 20814, United States.ORCID https://orcid.org/0000-0002-1573-4790
Nicole A GauthreauxHealth Sciences Department, NORC at the University of Chicago, Bethesda, MD 20814, United States.ORCID https://orcid.org/0000-0001-5743-0640
Nitu KashyapDepartment of Medicine,Yale New Haven Health, New Haven, CT 06510, United States.
David F LobachElimu Informatics, El Cerrito, CA 94530, United States.
Aziz BoxwalaElimu Informatics, El Cerrito, CA 94530, United States.
University of Chicago · USYale New Haven Health System · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Remote monitoring of women experiencing hypertensive disorders of pregnancy (HDP) can provide timely life-saving data, particularly if these data are integrated into existing patient and clinical workflows. This pilot intervention of a smartphone application (app) for postpartum monitoring of hypertensive disorders integrates patient-contributed data into electronic health records (EHRs) to support monitoring and clinical decision-making. Results from the evaluation of the pilot highlight the resources needed when implementing the app, challenges for integrating an app into the EHR, and the usability and utility of the HDP monitoring app for patient and clinician users. The implementation team's key observations included the importance of a local clinical champion, more robust patient involvement and support for the remote patient monitoring program, an impetus for EHR developers to adopt data integration standards, and a need to expand the capabilities of the standards to support interventions using patient-contributed data.

Indexed as

clinical decision support systemspatient centered carepatient-generated health datawomen’s health

Identifiers

PMID38028731
PMCPMC10646567
OpenAlexW4388711332

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.