Journal of Medical Internet Research

Digital health interventions (DHIs) have the potential to improve health care and health promotion. However, there is a lack of guidance in the literature for the development, refinement, and prioritization of key performance indicators (KPIs) for the evaluation of DHIs. This paper presents a 4-stage process used in the Gravitate Health project based on stakeholder consultation and consensus for this purpose. The Gravitate Health consortium, which comprises private and public partners from across Europe and the United States, is developing innovative digital health solutions in the form of Federated Open-Source Platform and G-lens to present users with individualized digital information about their medicines. The first stage of this was the consultative process for the development of KPIs involving stakeholder (Gravitate Health project leads) consultations at the planning stages of the project. This resulted in the formation of an extensive list of KPIs organized into 7 categories. The second stage was conducting a scoping review, which confirmed the need for extensive stakeholder consultation in all stages of the KPI development, refinement, and prioritization process. The third stage was a period of further consultation with all consortium members, which resulted in the elimination of 1 category of KPIs. The fourth stage involved using the Delphi technique for refining and prioritizing the remaining 6 categories of KPIs. It is unusual to use this methodology in a nonresearch exercise, but it provided a clear consultative framework and structure that facilitated the achievement of consensus within a large consortium of 250 members on a substantial list of KPIs for the project. Consortium members ranked the relevance and importance of each KPI. The final list of KPIs provides substantial indicators sensitive to the needs of a broad group of stakeholders that are being used to capture real-world data in developing and evaluating DHIs.

Sleep disorders are common among older adults and have a bidirectional impact on their emotional well-being. While some studies suggest that internet use may offer mental health benefits to this population, the relationship between internet use and sleep outcomes remains underexplored.

Chronic diseases are a major global health burden, accounting for nearly three-quarters of the deaths worldwide. Large language models (LLMs) are advanced artificial intelligence systems with transformative potential to optimize chronic disease management; however, robust evidence is lacking.

Chronic kidney disease (CKD) is a serious condition affecting millions of individuals worldwide. Adherence to medication regimens among patients with CKD is often suboptimal, leading to poor health outcomes. In recent years, mobile apps have gained popularity as a promising tool to improve medication adherence and self-management in various chronic diseases.

Vaping rates in Canada are continuing to increase. In 2019, 4.7% of Canadians used an electronic cigarette (e-cigarette) in the past 30 days, which rose to 5.8% in 2022. In the same year, young adults aged 20-24 years demonstrated the highest use among Canadians, at 19.7%. Given this, existing interventions are not resulting in the desired outcomes, and smartphone apps have the potential to address this gap. Although limited, current evidence highlights that apps can be an effective cessation support; however, a gap persists in understanding the user experience of vaping cessation apps.

Real-world data (RWD) from sources like administrative claims, electronic health records, and cancer registries offer insights into patient populations beyond the tightly regulated environment of randomized controlled trials. To leverage this and to advance cancer research, 6 university hospitals in Bavaria have established a joint research IT infrastructure.

Telehealth interventions are effective in hypertension management. However, the cost-effectiveness of using them for managing patients with hypertension remains inconclusive. Further research is required to understand the effectiveness and cost-effectiveness in the real-world setting.

Sub-Saharan Africa (SSA) accounts for up to 67% of the global HIV burden yet grapples with health system challenges like distant health facilities, low doctor-to-patient ratio, and poor or non-functioning post-hospital follow-up mechanisms. The rising phone ownership and internet penetration in SSA (46% and 67%, respectively) offer an opportunity to leverage technology to address these gaps and drive toward achieving the UNAIDS (Joint United Nations Programme on HIV and AIDS) 95-95-95 targets.

Following the proposal by Tsafnat et al (2024) to converge on three open health data standards, this viewpoint offers a critical reflection on their proposed alignment of openEHR, Fast Health Interoperability Resources (FHIR), and Observational Medical Outcomes Partnership (OMOP) as default data standards for clinical care and administration, data exchange, and longitudinal analysis, respectively. We argue that open standards are a necessary but not sufficient condition to achieve health data interoperability. The ecosystem of open-source software needs to be considered when choosing an appropriate standard for a given context. We discuss two specific contexts, namely standardization of (1) health data for federated learning, and (2) health data sharing in low- and middle-income countries. Specific design principles, practical considerations, and implementation choices for these two contexts are described, based on ongoing work in both areas. In the case of federated learning, we observe convergence toward OMOP and FHIR, where the two standards can effectively be used side-by-side given the availability of mediators between the two. In the case of health information exchanges in low and middle-income countries, we see a strong convergence toward FHIR as the primary standard. We propose practical guidelines for context-specific adaptation of open health data standards.

Concerned significant others (CSOs) play a significant role in supporting individuals with substance use disorders. There is a lack of tailored support services for these CSOs, despite their substantial contributions to the well-being of their loved ones (LOs). The emergence of helplines as a potential avenue for CSO support is outlined, culminating in the focus on the Partnership to End Addiction’s helpline service, an innovative public health intervention aimed at aiding CSOs concerned about an LO’s substance use.

Prevention of drug-induced QT prolongation (diLQTS) has been the focus of many system-wide clinical decision support (CDS) tools, which can be directly embedded within the framework of the electronic health record system and triggered to alert in high-risk patients when a known QT-prolonging medication is ordered. Justification for these CDS systems typically lies in the ability to accurately predict which patients are at high risk; however, it is not always evident that identification of risk alone is sufficient for appropriate CDS implementation.

Digital health has become integral to public health care, advancing how services are accessed, delivered, and managed. Health organizations increasingly assess their digital health maturity to leverage these innovations fully. However, existing digital health maturity models (DHMMs) primarily focus on technology and infrastructure, often neglecting critical communication components.