Patient Portal Acceptance by the Elderly: Explained by the Elaboration Likelihood Model and Social Heuristics

Patient Portal Acceptance by the Elderly: Explained by the Elaboration Likelihood Model and Social Heuristics

Karoly Bozan (Duquesne University, USA), Kevin R. Parker (Idaho State University, USA) and Bill Davey (RMIT University, Melbourne, Australia)
DOI: 10.4018/978-1-7998-1371-2.ch005

Abstract

The motivating factors that influence patient portal acceptance among the elderly are not well understood. Using the social heuristic theory, the elaboration likelihood model, and the unified theory of acceptance and use of technology, this study proposes a model that examines the persuasive mechanisms for the elderly to use patient portals. An empirical study involving 117 subjects in the United States was used to test the proposed model. Using the partial least squares method, social power, and imitate-the-successful social heuristics were found to significantly influence patient portal acceptance among the elderly. These findings indicate that older people invest less effort cognitively elaborating when presented with technology acceptance decisions and accept influence from their higher status peers from their network. Imitate-the-majority heuristics and central route processing were not found to be significant, implying that older people are more inclined to take advice from sources, which they find credible and invest less cognitive effort in evaluating the complex phenomena.
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Introduction

The healthcare industry is paying greater attention to improving patient outcomes through better provider-patient communication (Tang et al., 2013; Chrischilles et al., 2014). One such tool that is seeing greater utilization by healthcare providers is the patient portal. Patient portals are secure online websites that allow patients to access their personal health information, such as communicate summaries of recent visits, medications, immunizations, allergies, and lab results, from any location with an Internet connection (Krist et al., 2012; HealthIT.gov at https://www.healthit.gov/). More sophisticated patient portals are also capable of scheduling non-urgent appointments, downloading and submitting forms, processing prescription refills, accepting payments, and providing viewable educational material (Goldzweig et al., 2013). Patient portals have become a valuable tool for addressing the problem of rapidly aging populations in most countries (Bierman, 2012).

The use of electronic health records (EHR) is also on the rise. A 2014 study (Hsiao & Hing, 2014) shows that about 80% of office-based physicians in the US use EHRs, and a majority of them (69%) are committed to participate in the meaningful use incentive payment program available in the United States (Blumenthal & Tavenner, 2010). One of the Stage 2 Core Set objectives to achieve meaningful use is “provide patients the ability to view online, download, and transmit their health information” (HealthIT.gov). This means that healthcare providers with EHR systems are mandated to provide patients with access to personal health information over the Internet using a secure online portal. Several other countries are introducing similar initiatives as they try to both improve health outcomes and strive for efficiencies in their health systems (Wickramasinghe, Davey, & Tatnall, 2013).

Numerous studies examine patient portal acceptance and use (Goldzweig et al., 2013; Ancker et al., 2011; Smith et al., 2015; Sarkar et al., 2011; Goel et al., 2011; Jung et al., 2011; Weppner et al., 2010). Patients with chronic conditions are more likely to accept and use patient portals (Goldzweig et al., 2013; Ancker et al., 2011; Millard & Fintak, 2002). Patient age is negatively correlated with portal adoption and use, especially among older patients (Goel et al., 2011; Jung, Padman, Shevchik, et al., 2011; Weppner et al., 2010). Roughly 20% of the US population will be over the age of 65 by 2030 due to longer life spans and aging baby boomers (CDC, 2013), and it has been established that doctor visits and medical spending increase during the final years of life (Hogan, Lunney, Gabel, & Lynn, 2001). In fact, some studies indicate a quarter of an individual’s medical spending occurs in their final year (Lubitz & Riley, 1993). Hence, one can conclude that while older patients could benefit most from patient portals, they are the least likely group to use them.

Key Terms in this Chapter

Elderly Citizens: People over the age of 65 years.

Social Heuristics: In the context of this study, we define social heuristics as the decision making and behavioral guiding principles followed by the elderly. For example, ignoring certain complex aspects of technology or relying on more knowledgeable peers is an example of social heuristics as a tool of bounded rationality among the elderly.

Institutional Theory: In this paper, Institutional Theory is defined as the guidelines for social behavior in the form of accepted structures, schemas, rules, norms, and routines influenced by other members of the collective network of actors.

Health IT Adoption: Healthcare information technology (Health IT) is the use of computer applications to record, store, protect, retrieve, and transfer clinical, administrative, and financial information electronically within and among various health care settings. Adoption of Health IT for the purposes of this research is defined as the process from being aware of the technology to the effective and efficient usage for the intended purpose.

Health IT Usage: Accessing personal health information by the intended recipient through electronic medium and application designed for informational or decision-making reason purpose.

Unified Theory of Acceptance and Use of Technology (UTAUT): The UTAUT model explains technology use intention and behavior with numerous constructs, including social influence.

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