BMC Medical Informatics and Decision Making (Aug 2021)

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,
  • Richelle J. Koopman

DOI
https://doi.org/10.1186/s12911-021-01598-4
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 14

Abstract

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Abstract Background Home 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. Methods We 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. Results A 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. Conclusions We 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.

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