Call for Papers, Issue 3/2024

While digital health applications and telemedicine have become the norm in many settings, there are still large uncertainties for organizations introducing innovative technologies into healthcare settings. These concerns include, among others, regulatory and technological complexities related to medical device and digital therapeutics (DTx) regulation, data security and privacy, and healthcare standards and interoperability. On the other hand, traditional healthcare IT implementations have been characterized by low levels of usability and user-friendliness, leading to low acceptance rates and dissatisfaction among patients and healthcare professionals. Extant implementations have also often focused on the provider perspective, leaving the creation of value for patients largely aside (Teisberg et al. 2020). Against this backdrop, we call for studies that aim to better understand how emerging health technologies are to be embedded into user-friendly and future-oriented patient care journeys. Studies may use existing or new theoretical perspectives and should go beyond simplified characterizations of technology acceptance. We see room for studies to be located on different levels of investigation such as the individual, the community, or the societal level, and may even consider multiple of those levels simultaneously. Studies may shift the focus away from only considering healthcare organizations and enterprise IT (e.g., Baird et al. 2018), to an emphasis of patient- and value-based perspectives. Arriving at such analysis may require new approaches to engage with user needs such as via behavioral nudging (Lehrer et al. 2021), gamification (Schmidt-Kraepelin et al. 2020), or virtual coaches (Tropea et al. 2021; Makin 2019), while ensuring the privacy of the emerging digital health solutions (Sunyaev et al. 2014). It may also require socio-technical processual analyses of the digital transformation of healthcare workflows and practices, for example, considering institutional (Burton-Jones et al. 2020; Faik et al. 2020), path-constitutional (Singh et al. 2015; Agarwal et al. 2022), or practice-based (Reckwitz 2020; Orlikowski and Scott 2015) perspectives.

Recent advances in wearables, devices, apps, and other digital health technologies produce increasingly large amounts of data. This data enables new possibilities for capturing, monitoring, and steering the efficiency and quality of care processes and informing research. Digital health platforms such as Ping-an-doctor (Jiang et al. 2021) and Amazon / Pillpack (Gleiss et al. 2021), on the private end of the spectrum, and community-/socially-driven approaches like PatientsLikeMe (Tempini 2015), the German Healthy Kinzigtal (Schubert et al. 2021), and APST (Fürstenau et al. 2021) are becoming increasingly widespread and store increasingly large treasures of valuable behavioral and health data, while using rating systems to give all-around feedback on the quality of healthcare processes. Beyond unlocking genuine business opportunities for the involved firms, data generated within these platforms and in the context of the arising data ecosystems need to be considered in terms of maximizing patient value. One promising way forward is to consider value in healthcare in a multi-facetted way (Barrett et al. 2016), e.g., for patients via patient-centered outcomes and procedural and structural effects on them, especially using novel real-world evidence and digital trace data. In these settings, we also need to rethink the role of data privacy with patient-generated health data (Kaplan et al. 2019). Against the background of the increasing amounts of data on many patient histories over long periods of time, and the incentive differences between stakeholders that arise, we also need to better understand health data governance in such emerging health data ecosystems (Witte et al. 2020; Winter and Davison 2019). This needs to consider new technical, organizational, and regulatory challenges (Winter and Davison in press) and emerging (infra-) structures such as health data spaces, data repositories, data commons, data natives, data trustees, and data collectives.

Some topics of interest include: