Evaluating Patient-Centered Mobile Health Technologies: Definitions, Methodologies, and Outcomes

Abstract

Several recently published studies and consensus statements have demonstrated that there is only modest (and in many cases, low-quality) evidence that mobile health (mHealth) can improve patient clinical outcomes such as the length of stay or reduction of readmissions. There is also uncertainty as to whether mHealth can improve patient-centered outcomes such as patient engagement or patient satisfaction. One principal challenge behind the “effectiveness” research in this field is a lack of common understanding about what it means to be effective in the digital space (ie, what should constitute a relevant outcome and how best to measure it). In this viewpoint, we call for interdisciplinary, conceptual clarity on the definitions, methodologies, and patient-centered outcomes frequently used in mHealth research. To formulate our recommendations, we used a snowballing approach to identify relevant definitions, outcomes, and methodologies related to mHealth. To begin, we drew heavily upon previously published detailed frameworks that enumerate definitions and measurements of engagement. We built upon these frameworks by extracting other relevant measures of patient-centered care, such as patient satisfaction, patient experience, and patient activation. We describe several definitional inconsistencies for key constructs in the mHealth literature. In an effort to achieve clarity, we tease apart several patient-centered care outcomes, and outline methodologies appropriate to measure each of these patient-care outcomes. By creating a common pathway linking definitions with outcomes and methodologies, we provide a possible interdisciplinary approach to evaluating mHealth technologies. With the broader goal of creating an interdisciplinary approach, we also provide several recommendations that we believe can advance mHealth research and implementation.

The patient as a prosumer of healthcare: insights from a bibliometric-interpretive review

“…Patients are more likely to engage with digital tools when no action is required, but they merely provide information and data about health issues (Bruce et al. , 2020).…”

“…Engaging patients in service co-production (Green cluster). Patients are more likely to engage with digital tools when no action is required, but they merely provide information and data about health issues (Bruce et al, 2020). Such information permits patients to obtain insights about their health condition, nurturing a greater awareness of health determinants, without necessarily implying the adoption of self-care behaviors (Hudson et al, 2020).…”

Effectiveness of Digital Counseling Environments on Anxiety, Depression, and Adherence to Treatment Among Patients Who Are Chronically Ill: Systematic Review

“…Risk of bias; inconsistency; differences in patient populations, settings, and interventions; imprecision; publication bias; and the underreporting of relevant information have been listed as the main reasons why previous reports have only provided low-quality evidence concerning the effectiveness of digital counseling approaches. In addition, the heterogeneity in eHealth definitions also makes between-study comparisons difficult, which are necessary to provide health care professionals with evidence-based recommendations [ 30 , 48 , 86 , 87 ].…”

ProHealth eCoach: User-Centered Design and Development of an eCoach App to Promote Healthy Lifestyle with Personalized Activity Recommendations

“…The study showed promising results on enhancing selfawareness towards a healthy lifestyle and behavioral change, effective engagement, and self-reporting to manage the factors that impact obesity or overweight. McCurdie et al [30] and Bruce et al [31] adopted a UCD evidence-based approach to develop a mHealth consumer app to enhance healthcare delivery and clinical outcomes with remote patient monitoring and early detection of health risks to avoid severe damages. Their research reveals the importance of a user-centered/patient-centered approach in achieving user engagement (or user evaluation) to enhance the effectiveness of behavioral interventions.…”