Building Personas for Care-Seeking Older Adults with Acute Illness
Event Type
Poster Presentation
TimeThursday, April 152:00pm - 3:00pm EDT
LocationHospital Environments

The Emergency Department (ED) represents a high-risk healthcare environment for the one in five older adults in the United States who are treated in the ED annually (1). Following an ED visit, older adults have a higher risk of suboptimal outcomes such as increased risk of readmission to the ED, increased risk of admission to a hospital or nursing home, and a decrease in quality of life (2,3). Research indicates that many of older adults’ ED visits are potentially avoidable. However, efforts to encourage older adults to seek acute illness care outside of the ED (e.g., primary care) have had limited success.

Recent research has identified multiple system factors contributing to older adults’ accessing acute illness care in the ED (4). Further, system factors influencing acute illness care-seeking are often unique to individuals, which poses challenges for adequately addressing older adults’ needs. To design interventions and models of care that fully account for older adults’ individual differences, future work must balance designing for a single individual and designing for a non-specific aggregate of older adults.

The persona method has the potential to address this challenge by providing a deep yet actionable understanding of a patient population to inform design and development of patient-informed interventions. Personas are user-inspired, fabricated yet realistic representations of targeted users of a system or product. Personas do not encompass the average user. Rather, they encompass a representative user, making them invaluable during intervention design and development as a means to facilitate decision-making, engage the design team and develop tailored interventions that adequately support users. Given the disintegrated information related to older adults’ ED experiences that is currently available, personas provide a mechanism to synthesize this information into a holistic “person” who is readily accessible to clinicians, designers and researchers.

Thus, the objective of the study was to create dimensions related to older adults seeking care in the ED and observe the interactions between them for each study participant. This will facilitate development of personas that characterize older adults’ decision-making process in the context of personal and situational factors.


We conducted a secondary analysis of interview data from fifteen community-dwelling older adults (≥ 65 years) and caregivers. The average age was 74 years with a range of 65-94 years; 53% were female and 47% were male. The participants had visited a level 1 trauma center ED in upstate New York to address a healthcare need, had either been treated and released or observed in the ED for 5-48 hours and ultimately discharged. A convenience sample of older adults was recruited between 9:00 a.m. and 9:00 p.m. Data collection occurred over a one-year period from 2013-2014.

In this secondary analysis, we performed an inductive content analysis of interviews conducted in the ED. To develop the codebook, four coders independently coded a subset of two transcripts to identify dimensions related to older adults’ decision to present to the ED. The research team met to discuss and identify codes. Once a codebook was established, four coders dual-coded all transcripts using NVivo 12.4.0. Coding reliability and consistency were managed through regular meetings to compare coding and resolve discrepancies by consensus.


We identified four key dimensions relevant to older adults’ decision to seek care in the emergency department: symptom evaluation; access to alternatives; personal factors; and care network. Symptom evaluation included underlying conditions, patient and caregiver perceptions of symptom severity, and associated emotional aspects such as fear and anxiety. Access to alternatives incorporated the patient’s attempts to avoid an emergency department visit and the ability to access primary and specialty care services. Personal factors encompassed the patient’s self-care capacity, perspectives on health and safety, risk tolerance, self-efficacy, and expectations specific to provision of health care. Care network consisted of support persons and the type of support they provided, supplementary healthcare services, and care coordination, as well as the decisions and expectations of formal and informal caregivers within the older adult’s care network.


Our results provide the key dimensions that form the foundation for older adult acute illness care seeking personas. The next step in the process is to create meaningful clusters (5) to transform findings from the inductive content analysis into personas. Development of personas will capture a broad range of perceptions and experiences while avoiding the limitations of attempting to design for a unique individual or the opposite extreme of generalizing to all older adults.


1. National Center for Health Statistics (US) (2017). Health, United States, 2016: With Chartbook on Long-term Trends in Health. Hyattsville, MD.: National Center for Health Statistics (US).
2. McCusker, J., D. Roberge, A. Vadeboncoeur & J. Verdon (2009). Safety of discharge of seniors from the emergency department to the community. Healthc Q., 24-32.
3. Suffoletto, B., T. Miller, R. Shah, C. Callaway & D. M. Yealy (2016). Predicting older adults who return to the hospital or die within 30 days of emergency department care using the ISAR tool: subjective versus objective risk factors. Emergency Medicine Journal., 33, 4-9.
4. Lutz, B. J., A. G. Hall, S. B. Vanhille, A. L. Jones, J. R. Schumacher, P. Hendry, J. S. Harman & D. L. Carden (2018). A framework illustrating care-seeking among older adults in a hospital emergency department. The Gerontologist, 58, 942-952.
5. Holden, R. J., C. N. Daley, R. S. Mickelson, D. Bolchini, T. Toscos, V. P. Cornet, A. Miller & M. J. Mirro (2020). Patient decision-making personas: An application of a patient-centered cognitive task analysis (P-CTA). Applied Ergonomics., 87, 1-11.