The conceptual model is a high-level overview of the main elements and considerations for digital health evaluation in the context of the Framework. At its centre we identify three distinct phases that serve as key opportunities for evaluating a digital health solution (DHS): Planning, Implementing, and Impact. These phases are embedded within the ongoing cycle of a Learning Health System where the dual processes of Engaging and Reflecting drive the transformation of data to knowledge into practice and policy improvements. Finally, in this conceptual representation, the entire evaluation process is grounded in four foundational concepts that should be considered and represented at all phases and throughout all levels of the DHS evaluation: scalability, sustainability, digital health equity, and digital health governance.

Conceptual Model

Conceptual Model

Click / touch the core phases below to learn more

ENGAGING REFLECTING REFLECTING REFLECTING ENGAGING ENGAGING IMPLEMENTING IMPACT PLANNING Practice/ Policy to Data Data to Knowledge Knowledge to Practice/ Policy DIGITAL HEALTH EQUITY DIGITAL HEALTH GOVERNANCE
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Key Principles

The Framework, as demonstrated with the conceptual model, has been developed with a set of guiding principles in mind. At the core of these principles is the Quintuple Aim for healthcare based on work done at the Institute of Healthcare Improvement as well as the concept of the Learning Health System established by the National Academies of Medicine (formerly the IOM). For further details on these concepts and how they are integrated within the Framework please see below.

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  • Quintuple Aim

    The Quintuple Aim is a model of healthcare quality that considers and measures five aspects of health and healthcare systems:

    • The patient experience
    • The healthcare provider experience
    • The impact on population health
    • Costs to the healthcare system
    • Health equity
  • Digital Health Governance

    Transforming health care to improve quality and efficiency of the health system requires health data and information systems to support effective digital health governance. Considering the types of accountability and decision-making structures that are in place can assist in addressing the risks, rights, and responsibilities in adopting digital innovations in health. It includes policies and legislative acts that govern data sharing, privacy, and confidentiality.

  • Digital Health Equity

    For the framework the term health equity refers to the idea that everyone, regardless of social, economic, geographic, demographic, or racial/ethnic grouping, has a fair chance to live a long and healthy life. Achieving equity should be a guiding principle for digital health implementation and evaluation. Digital Health Equity is realized when all people have equal opportunity to access, use, and benefit from digital health solutions to maintain or improve their health and well-being over the entire course of their lifespan.

  • Sustainability

    The process by which the digital health solution and the practices and policies that support it become institutionalized or integrated within the structures and systems for health care delivery. For example, it can be measured by the number of patients or providers who have used the digital health solution or have recommended it to others during a given time period; frequency of use; or evidence of sustained use following the end of the assessment period. It also considers the long-term environmental impact of the digital health solution including energy use and digital waste where applicable.

  • Scalability

    In the case of evaluating a DHS, scalability refers to any purposeful or deliberate efforts to increase the impact of intervention that have been successfully tested in a pilot or experimental setting with the intention to extend the benefit to more people, as well as to foster policy and program development.

  • Learning Health System

    A Learning Health System aligns science, informatics, incentives and culture for continuous improvement and innovation in evidence-based healthcare delivery. New knowledge is generated from data and applied to facilitate practice and policy improvements. This in turn creates new data, embarking on the learning health system ‘cycle’ again. Fundamental to learning health systems are the processes of Engagement and Reflection.

    Engaging is a process that describes the actions and considerations for engagement with pre-identified community leaders and partners (including policy, clinical, administrative, and regulatory stakeholders), in addition to potential users and beneficiaries of digital health.

    This is important to clarify the value propositions of various partners; facilitate buy in, early adoption and utilization of the technology, and enable refinement of the technology, where needed.

    Equally important is reflecting which describes the ongoing and iterative process of collecting and assessing data (qualitative and quantitative) and other feedback or debriefing methods (co-design, patients, and service users’ input) to appraise progress of evaluation of the DHS, as well as the quality of early findings.