Know thy eHealth user: Development of biopsychosocial personas from a study of older adults with heart failure

Richard J Holden; Anand Kulanthaivel; Saptarshi Purkayastha; Kathryn M Goggins; Sunil Kripalani

doi:10.1016/j.ijmedinf.2017.10.006

Know thy eHealth user: Development of biopsychosocial personas from a study of older adults with heart failure

Int J Med Inform. 2017 Dec:108:158-167. doi: 10.1016/j.ijmedinf.2017.10.006. Epub 2017 Oct 9.

Authors

Richard J Holden¹, Anand Kulanthaivel², Saptarshi Purkayastha², Kathryn M Goggins³, Sunil Kripalani⁴

Affiliations

¹ Department of BioHealth Informatics, Indiana University School of Informatics and Computing, Indianapolis, IN, USA; Indiana University Center for Aging Research (IUCAR), Regenstrief Institute, Inc., Indianapolis, IN, USA. Electronic address: rjholden@iupui.edu.
² Department of BioHealth Informatics, Indiana University School of Informatics and Computing, Indianapolis, IN, USA.
³ Center for Effective Health Communication, Vanderbilt University Medical Center, Nashville, TN, USA; Center for Clinical Quality and Implementation Research, Vanderbilt University Medical Center, Nashville, TN, USA.
⁴ Center for Effective Health Communication, Vanderbilt University Medical Center, Nashville, TN, USA; Center for Clinical Quality and Implementation Research, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA.

Abstract

Background: Personas are a canonical user-centered design method increasingly used in health informatics research. Personas-empirically-derived user archetypes-can be used by eHealth designers to gain a robust understanding of their target end users such as patients.

Objective: To develop biopsychosocial personas of older patients with heart failure using quantitative analysis of survey data.

Method: Data were collected using standardized surveys and medical record abstraction from 32 older adults with heart failure recently hospitalized for acute heart failure exacerbation. Hierarchical cluster analysis was performed on a final dataset of n=30. Nonparametric analyses were used to identify differences between clusters on 30 clustering variables and seven outcome variables.

Results: Six clusters were produced, ranging in size from two to eight patients per cluster. Clusters differed significantly on these biopsychosocial domains and subdomains: demographics (age, sex); medical status (comorbid diabetes); functional status (exhaustion, household work ability, hygiene care ability, physical ability); psychological status (depression, health literacy, numeracy); technology (Internet availability); healthcare system (visit by home healthcare, trust in providers); social context (informal caregiver support, cohabitation, marital status); and economic context (employment status). Tabular and narrative persona descriptions provide an easy reference guide for informatics designers.

Discussion: Personas development using approaches such as clustering of structured survey data is an important tool for health informatics professionals. We describe insights from our study of patients with heart failure, then recommend a generic ten-step personas development process. Methods strengths and limitations of the study and of personas development generally are discussed.

Keywords: Consumer health information technology; Geriatric heart failure; Human factors; Human-computer interaction; Personas; User-centered design.

MeSH terms

Adult
Aged
Aged, 80 and over
Female
Health Literacy*
Heart Failure*
Humans
Internet / statistics & numerical data*
Male
Medical Informatics / standards*
Middle Aged
Telemedicine / standards*

Abstract

MeSH terms

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