The Impact of Frontline Service Technology in Healthcare on Patient Well-Being

Abstract

The rise of frontline service technologies (FSTs) in healthcare is fueled by the ‘Quintuple Aim,’ which is based on five interrelated aims: (1) improved population health, (2) reduced costs, (3) improved patient well-being, (4) improved provider well-being, and (5) health equity. While researchers and practitioners frequently highlight the benefits of FSTs in terms of reduced costs and improved health, they often overlook their impact on patients’ roles and, consequently, their well-being. The significance of well-being lies in its association with decreased illness, improved quality of life, and improved provider performance. Moreover, well-being is manageable and serves as a universally applicable outcome measure across diverse groups and time periods. Therefore, and consistent with recent calls, this research aims to understand the influence of healthcare FSTs on patients’ well-being, addressing two research questions: (1) What elements do patients perceive as demands and resources when using healthcare FST? and (2) What is the impact of these elements on patients’ well-being? To answer these questions, this research builds on the Job Demands-Resources (JD-R) model, which hypothesizes that task characteristics (i.e., demands and resources) influence well-being via a negative (i.e., strain) and positive pathway (i.e., motivation). On the one hand, demands are physical, social, and organizational characteristics of FST usage that require sustained physical and/or mental effort and can thus be seen as a cost or sacrifice. Qualitative workload is an example of a demand, which refers to the mental effort associated with FST usage. On the other hand, resources include physical, social, and organizational characteristics of FST usage that (a) are functional in achieving goals, (b) help deal with demands and the associated costs, and (c) stimulate personal growth, learning, and development. An example of a resource includes role clarity, which reflects the extent to which patients believe that they receive clear and precise information about their roles and behaviors in the FST-enabled healthcare service. The JD-R model allows us to have a balanced perspective by capturing the negative as well as positive aspects of using healthcare FST. Such a balanced perspective is crucial to avoid a one-sided view, which may over- or underestimate FSTs’ impact on patients’ well-being.

To collect data, we work with two organizations interested in using FST for their patients. A mixed- method multi-sample approach is employed, utilizing both qualitative (i.e., interviews, focus groups)

and quantitative (i.e., questionnaire) methods across multiple samples, including patients and caregivers. Data collection is currently being executed, with preliminary results expected in June 2024. This research provides at least four contributions. First, this research offers a rigorous empirical assessment of how FSTs impact patient well-being. Second, its balanced perspective on well-being yields novel insights into crucial Transformative Service Research questions. Third, by examining technology usage through the lens of individual-level psychological processes, it extends existing

theoretical models from the technology usage literature. Fourth, the results provide a foundation for evidence-based, user-centric decision-making regarding FST implementation.