Evidence map›Paper›PMID 34353322›Full record

ArticleBMC medical informatics and decision making2021

Home blood pressure data visualization for the management of hypertension: using human factors and design principles.

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

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 12% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

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  8. Patient judgments about hypertension control: the role of patient numeracy and graph literacy.Journal of the American Medical Informatics Association : JAMIA · 2022
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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 at 5 institutions in 2 countries.

Pete Wegier *Humber River Hospital, Toronto, ON, Canada. pete.wegier@utoronto.ca.ORCID 0000-0003-0191-136X
Jeffery L Belden *Department of Family and Community Medicine, University of Missouri-Columbia, Columbia, MO, USA.
Shannon M CanfieldDepartment of Family and Community Medicine, University of Missouri-Columbia, Columbia, MO, USA.
Victoria A ShafferDepartment of Psychological Sciences, University of Missouri-Columbia, Columbia, MO, USA.
Sonal J PatilDepartment of Family and Community Medicine, University of Missouri-Columbia, Columbia, MO, USA.
Michael L LeFevreDepartment of Family and Community Medicine, University of Missouri-Columbia, Columbia, MO, USA.
K D ValentineHealth Decision Sciences Center, Massachusetts General Hospital, Boston, MA, USA.
Mihail PopescuDepartment of Health Management and Informatics, University of Missouri-Columbia, Columbia, MO, USA.
Linsey M SteegeSchool of Nursing, University of Wisconsin-Madison, Madison, WI, USA.
Akshay JainDepartment of Electrical and Computer Engineering, University of Missouri-Columbia, Columbia, MO, USA.
Richelle J KoopmanDepartment of Family and Community Medicine, University of Missouri-Columbia, Columbia, MO, USA.
University of Missouri · USHarvard University · USUniversity of Missouri Health System · USUniversity of Toronto · CAUniversity of Wisconsin–Madison · US

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

backgroundHome blood pressure measurements have equal or even greater predictive value than clinic blood pressure measurements regarding cardiovascular outcomes. With advances in home blood pressure monitors, we face an imminent flood of home measurements, but current electronic health record systems lack the functionality to allow us to use this data to its fullest. We designed a data visualization display for blood pressure measurements to be used for shared decision making around hypertension.

methodsWe used an iterative, rapid-prototyping, user-centred design approach to determine the most appropriate designs for this data display. We relied on visual cognition and human factors principles when designing our display. Feedback was provided by expert members of our multidisciplinary research team and through a series of end-user focus groups, comprised of either hypertensive patients or their healthcare providers required from eight academic, community-based practices in the Midwest of the United States.

resultsA total of 40 participants were recruited to participate in patient (N = 16) and provider (N = 24) focus groups. We describe the conceptualization and development of data display for shared decision making around hypertension. We designed and received feedback from both patients and healthcare providers on a number of design elements that were reported to be helpful in understanding blood pressure measurements.

conclusionsWe developed a data display for substantial amounts of blood pressure measurements that is both simple to understand for patients, but powerful enough to inform clinical decision making. The display used a line graph format for ease of understanding, a LOWESS function for smoothing data to reduce the weight users placed on outlier measurements, colored goal range bands to allow users to quickly determine if measurements were in range, a medication timeline to help link recorded blood pressure measurements with the medications a patient was taking. A data display such as this, specifically designed to encourage shared decision making between hypertensive patients and their healthcare providers, could help us overcome the clinical inertia that often results in a lack of treatment intensification, leading to better care for the 35 million Americans with uncontrolled hypertension.

Indexed as

Data VisualizationHypertensionBlood PressureCommunity Health ServicesHumansUnited StatesBlood pressureData visualizationHypertensionInterface designShared decision making

Identifiers

PMID34353322
PMCPMC8340525
OpenAlexW3191993787

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.