Evidence map›Paper›PMID 32811489›Full record

ArticleBMC medical informatics and decision making2020

Home blood pressure data visualization for the management of hypertension: designing for patient and physician information needs.

Richelle J Koopman, Shannon M Canfield, Jeffery L Belden, Pete Wegier, Victoria A Shaffer, K D Valentine, Akshay Jain, Linsey M Steege, Sonal J Patil, Mihail Popescu and 1 more

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

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

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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

11 authors.

Richelle J KoopmanDepartment of Family & Community Medicine, University of Missouri-Columbia, Columbia, MO, USA. koopmanr@health.missouri.edu.ORCID 0000-0002-0662-2391
Shannon M CanfieldDepartment of Family & Community Medicine, University of Missouri-Columbia, Columbia, MO, USA.
Jeffery L BeldenDepartment of Family & Community Medicine, University of Missouri-Columbia, Columbia, MO, USA.
Pete WegierDepartment of Family & Community Medicine, University of Toronto, Toronto, Ontario, Canada.
Victoria A ShafferDepartment of Psychological Sciences, University of Missouri-Columbia, Columbia, MO, USA.
K D ValentineHealth Decision Sciences Center, Massachusetts General Hospital, Boston, MA, USA.
Akshay JainDepartment of Electrical & Computer Engineering, University of Missouri-Columbia, Columbia, MO, USA.
Linsey M SteegeSchool of Nursing, University of Wisconsin-Madison, Madison, WI, USA.
Sonal J PatilDepartment of Family & Community Medicine, University of Missouri-Columbia, Columbia, MO, USA.
Mihail PopescuDepartment of Health Management & Informatics, University of Missouri-Columbia, Columbia, MO, USA.
Michael L LeFevreDepartment of Family & Community Medicine, University of Missouri-Columbia, Columbia, MO, USA.

Funding

Washington University Center for Diabetes Translation Research P30DK092950 · NIDDK · WASHINGTON UNIVERSITY · PI Ross C Brownson, Debra Haire-Joshu · 2011 to 2026
$11.7M
Optimizing Display of Blood Pressure Data to Support Clinical Decision MakingR01HS023328 · AHRQ · UNIVERSITY OF MISSOURI-COLUMBIA · PI KOOPMAN, RICHELLE J · 2015 to 2019
$2.2M
Agency for Healthcare Research and Quality R01HS023328AHRQ HHS R01 HS023328NIDDK NIH HHS P30 DK092950
6 · The paper itself

Abstract

backgroundNearly half of US adults with diagnosed hypertension have uncontrolled blood pressure. Clinical inertia may contribute, including patient-physician uncertainty about how variability in blood pressures impacts overall control. Better information display may support clinician-patient hypertension decision making through reduced cognitive load and improved situational awareness.

methodsA multidisciplinary team employed iterative user-centered design to create a blood pressure visualization EHR prototype that included patient-generated blood pressure data. An attitude and behavior survey and 10 focus groups with patients (N = 16) and physicians (N = 24) guided iterative design and confirmation phases. Thematic analysis of qualitative data yielded insights into patient and physician needs for hypertension management.

resultsMost patients indicated measuring home blood pressure, only half share data with physicians. When receiving home blood pressure data, 88% of physicians indicated entering gestalt averages as text into clinical notes. Qualitative findings suggest that including a data visualization that included home blood pressures brought this valued data into physician workflow and decision-making processes. Data visualization helps both patients and physicians to have a fuller understanding of the blood pressure 'story' and ultimately promotes the activated engaged patient and prepared proactive physician central to the Chronic Care Model. Both patients and physicians expressed concerns about workflow for entering and using home blood pressure data for clinical care.

conclusionsOur user-centered design process with physicians and patients produced a well-received blood pressure visualization prototype that includes home blood pressures and addresses patient-physician information needs. Next steps include evaluating a recent EHR visualization implementation, designing annotation functions aligned with users' needs, and addressing additional stakeholders' needs (nurses, care managers, caregivers). This significant innovation has potential to improve quality of care for hypertension through better patient-physician understanding of control and goals. It also has the potential to enable remote monitoring of patient blood pressure, a newly reimbursed activity, and is a strong addition to telehealth efforts.

Indexed as

Data VisualizationHypertensionPhysiciansAdultBlood PressureFemaleHumansMaleMiddle AgedPhysician-Patient RelationsData visualizationElectronic health recordHome blood pressure monitoringHypertension

Identifiers

PMID32811489
PMCPMC7432548

What OpenQuestion holds

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LicenceCC BY
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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.