Added Value from Secondary Use of Person Generated Health Data in Consumer Health Informatics

Abstract

Summary Introduction: Various health-related data, subsequently called Person Generated Health Data (PGHD), is being collected by patients or presumably healthy individuals as well as about them as much as they become available as measurable properties in their work, home, and other environments. Despite that such data was originally just collected and used for dedicated predefined purposes, more recently it is regarded as untapped resources that call for secondary use. Method: Since the secondary use of PGHD is still at its early evolving stage, we have chosen, in this paper, to produce an outline of best practices, as opposed to a systematic review. To this end, we identified key directions of secondary use and invited protagonists of each of these directions to present their takes on the primary and secondary use of PGHD in their sub-fields. We then put secondary use in a wider perspective of overarching themes such as privacy, interpretability, interoperability, utility, and ethics. Results: We present the primary and secondary use of PGHD in four focus areas: (1) making sense of PGHD in augmented Shared Care Plans for care coordination across multiple conditions; (2) making sense of PGHD from patient-held sensors to inform cancer care; (3) fitting situational use of PGHD to evaluate personal informatics tools in adaptive concurrent trials; (4) making sense of environment risk exposure data in an integrated context with clinical and omics-data for biomedical research. Discussion: Fast technological progress in all the four focus areas calls for a societal debate and decision-making process on a multitude of challenges: how emerging or foreseeable results transform privacy; how new data modalities can be interpreted in light of clinical data and vice versa; how the sheer mass and partially abstract mathematical properties of the achieved insights can be interpreted to a broad public and can consequently facilitate the development of patient-centered services; and how the remaining risks and uncertainties can be evaluated against new benefits. This paper is an initial summary of the status quo of the challenges and proposals that address these issues. The opportunities and barriers identified can serve as action items individuals can bring to their organizations when facing challenges to add value from the secondary use of patient-generated health data.

Understanding Women’s Cardiovascular Health Using MyStrengths+MyHealth: A Patient‐Generated Data Visualization Study of Strengths, Challenges, and Needs Differences

“…The PGHD from mHealth apps have the ability to include individuals' perspectives. The use of data visualizations can aid in understanding relationships with multidimensional data; however, this has largely been unexplored with PGHD (Hsueh et al, 2017;Monsen, Kelechi, McRae, Mathiason, & Martin, 2018;O'Connor, Waite, Duce, O'Donnell, & Ronquillo, 2020;Woods et al, 2016;Monsen et al, 2021). This may true be because most PGHD are unstructured, not easily usable, and difficult to analyze (Raghupathi & Raghupathi, 2014).…”

“…Digital technologies such as mobile health applications (mHealth apps) have the potential to influence patient engagement, a person’s willingness and ability to partake in self‐management, by assisting in monitoring their health anywhere and anytime (Chow, Ariyarathna, Islam, Thiagalingam, & Redfern, 2016; Milani, Lavie, Bober, Milani, & Ventura, 2017). The use of mHealth apps generate diverse and complex data streams, also called patient‐generated health data (PGHD; Hsueh et al, 2017; Lai, Hsueh, Choi, & Austin, 2017). PGHD may reveal a whole‐patient perspective by including environmental, psychosocial, physiological, or health‐related behaviors that influence the capability to manage one’s health (Hull, 2015; Rosenbloom, 2016; Woods, Evans, & Frisbee, 2016).…”

Toward Clinical Adoption of Standardized mHealth Solutions

“…[4][5][6][7] These consumer-generated health data have potential to transform individual-and population-level health and enable discovery of new knowledge regarding critical health issues, such as the growing burden of chronic disease. [8][9][10][11][12] However, consumergenerated health data generated by use of mHealth apps may not be standardized, structured, organized, easily stored, recalled, or manipulated. 13 In response to this problem, efforts have been made to standardize and structure consumer-generated health data in mHealth apps.…”

Developing a Dietary Lifestyle Ontology to Improve the Interoperability of Dietary Data: Proof-of-Concept Study

“…Lack of interoperability is one of the main barriers to using PGHD for patient care [12][13][14]. PGHD encompasses various health domains and is generated via multiple channels.…”