Human-Centered Design of Technological Solutions for Supporting Informal Caregivers Engagement in Heart Failure Dyadic Self-care: Developing an Interview Guide
TimeThursday, April 152:21pm - 2:23pm EDT
Heart failure (HF), also known as congestive heart failure, is a complex chronic disease characterized by inadequate blood perfusion to meet the body’s oxygen demands (Yancy et al., 2013). Despite the advancements in medical and surgical treatments in the past two decades (Ponikowski et al., 2016; St. John Sutton et al., 2003), HF remains the most common reason for hospital admissions among the United States older adults (Benjamin et al., 2018). There are currently around 6.5 million HF patients in the United States, with an estimated $60 billion annual healthcare expenditures (Holden et al., 2015). These numbers will noticeably rise with the projected increase of additional 800,000 patients each year (Benjamin et al., 2018; Roger et al., 2012). Considering the significant burden of HF on the health care system, finding novel and scalable solutions that can utilize alternative resources to deliver HF patients’ healthcare services and reduce HF-related hospitalizations is a priority.
Results from prior research studies show HF patients that follow self-care processes will have fewer HF-related hospitalizations (Artinian et al., 2002; Jaarsma et al., 2013; Jovicic et al., 2006; Lee et al., 2011; Sethares et al., 2014). Self-care is defined as the cognitive processes and activities people regularly follow to maintain their health or manage their diseases (Dickson et al., 2008). Examples of HF self-care activities are adhering to treatment plans, monitoring, and managing HF symptoms such as edema or shortness of breath (Riegel et al., 2016). However, evidence shows adhering to self-care is suboptimal in HF patients (Ausili et al., 2016; Karimi & Clark, 2016). More than 80% of HF patients are 65 years of age or older, have other comorbidities, and suffer from the complications caused by HF, such as memory loss, lower cognitive abilities, and fatigue (Holden et al., 2015; Riegel et al., 2016). The comorbidities and complications HF patients face, compounded with the lack of required knowledge for HF self-care among more than 50% of them (Artinian et al., 2002), increase their need for getting daily support from other resources (Dickson et al., 2011, 2013; Holden et al., 2015; Riegel et al., 2016; Riegel et al., 2011).
Informal caregivers, like patients’ spouse, partner, adult children, or friends, are among the most vital care-delivery and support resources for older adults with chronic diseases, including HF (Feinberg et al., 2011; Freedman & Spillman, 2014). They are prominent people who are with the patient throughout their illness (Levine et al., 2010). Prior studies show, patients who receive help from their informal caregivers are motivated to follow HF self-care (Buck et al., 2015) and showed improvements in their physical and mental well-being, quality of life, and health outcomes (Buck et al., 2018; Grant & Graven, 2018). Patients who have an informal caregiver are also shown to have better medication and diet adherence, show up at follow-up visits regularly (Buck et al., 2018; Durante et al., 2019), and have less HF-related hospitalization (Dunbar et al., 2008; Piette et al., 2015).
When informal caregivers engage with helping the patients in routine self-care activities without receiving any financial compensation, a dyad is formed (Buck et al., 2019). More than ever before, informal caregivers are expected to help patients manage increasingly complex diseases in the community (Riegel et al., 2009). However, their needs for effective engagement in the dyad, including their information and training requirements, are unknown (Graham et al., 2009; Levine et al., 2010). Engaging informal caregivers in dyadic HF self-care and supporting them during the care trajectory has been a challenge due to several issues, including lack of interest, skills, or resources among care providers to work with informal caregivers (Bulsara & Fynn, 2006; Greenwood et al., 2010). Lacking a systematic way for engaging and supporting informal caregivers to help patients with HF self-care and failing to provide their needs can lead to a diverse array of negative impacts on both patients’ and informal caregivers’ well-being (Gusdal et al., 2016; Wingham et al., 2015).
During the past two decades, health information technology (HIT) solutions have been widely used in healthcare in the United States (Christopherson et al., 2015; Gagnon et al., 2012; Henry et al., 2016). Several benefits, such as improving communication, quality of care, and access to medical records, have been reported as HIT solutions’ outcomes (Zeng, 2016). These technologies have also been used to build the infrastructure and basis for addressing many educational challenges in health care (Guze, 2015). With the recent advancements and availability of technology, a growing interest among care providers, patients, and their informal caregivers has formed to use the opportunity for fostering self-care (Riegel et al., 2011; Zulman et al., 2013). Examples of these technological advancements are tools like telemedicine, mobile health applications, and patient portals that enable remote patient monitoring, consultation with care providers, and training.
To improve technology solutions’ design and development, the Institute of Medicine (IOM) recommends adopting human factors techniques and user-centered design concepts (Baker, 2001; Donaldson et al., 2000). However, most of these technological solutions are developed with either care providers or patients as their primary users. Prior scholars focused on the psychosocial and physical burden on informal caregivers and their needs and challenges when providing support for their patients (Foust et al., 2012; Pressler et al., 2013; Yuen et al., 2018). A gap remains in knowing informal caregivers’ perception of HF self-care, how different factors influence informal caregivers’ decision-making process, and the cognitive process behind their decisions to differentiate informal caregivers’ decision-making approaches and needs. Our objectives were to identify informal caregivers’ perceptions, attitudes, and needs related to heart failure self-care and characterize factors that influence their decision-making and active engagement in the dyad to inform the design and development of technological solutions that consider informal caregivers as a primary user.
We developed an interview guide to identify the cognition underlying self-care decision-making among HF ’patients’ informal caregivers, factors that influence their effectiveness and active engagement in HF dyadic self-care, and their needs to perform HF self-care tasks. Two theoretical frameworks: 1) the Naturalistic Decision-making – NDM (Klein, 2008), and 2) the Extended Systems Engineering Initiative for Patient Safety – SEIPS 2.0 (Holden et al., 2013) were adopted as the guiding lens for defining the interview questions.
To study cognition underlying informal caregiver decision-making in context and create the personas, we used the cognitive task analysis (CTA) approach to focus on a specific scenario and the roles informal caregivers played in that scenario (Crandall et al., 2006; Holden et al., 2020; Klein, 2008). Helping informal caregivers focus on a relevant and actual incident has shown to be an effective way to elicit the tacit information about concrete experiences they made self-care decisions (Holden et al., 2020).
We piloted the interview guide at the University of Illinois at Chicago (UIC), College of Applied Health Sciences. We conducted the pilot interviews for three weeks with six participants. Our participants included UIC faculty members and graduate students. We also consulted a UIC professor who is an expert in sociolinguistics to revise the questions and apply interview techniques for optimum results. Piloting the guide unfolded the opportunity for iterative refinement of the guide based on the feedback. We revised the questions’ and probes’ wordings and continually improved our interview techniques based on the feedback.