an essential element and includes digital architecture and equipment, information systems, and software where applicable. Analysts should use existing context analysis tools as appropriate to the intervention, such as the Digital Health Investment Review Tool developed under the Maternal and Child Survival Program [28].

The intended decision maker is the organization, body, or group of people who will make use of the information produced in the economic evaluation. It is an important component of the economic evaluation to specify as it informs interpretation and application of all other methodological concepts, including the perspective of the analysis. It is important to note that there is no generalized “correct” intended decision maker for an economic evaluation, but the production of an economic evaluation with an undefined decision maker can potentially lead to inappropriate or incorrect use of the evidence, and sub-optimal decisions. For example, an economic evaluation of a digital health technology intended to inform an investment decision by a secondary care provider (such as a private hospital group) is likely to approach the definition of the comparator, scoping of costs, time horizon and representation of clinical effects and summary impact measures very differently to a country government department of health considering rolling out the same intervention nationally.

Intrinsically linked to the intended decision maker is the context in which the DHI will be implemented. Given the major influence that the context will have on all aspects of a DHI functionality and impact, there is little utility in concepts of efficacy for the economic evaluation of DHIs. The context of the DHI should therefore be established from the outset, with clear explanation of key components of the context, including the country context, health system environment, and digital enabling environment.

Determining the intended decision maker and context does not preclude applicability of the outputs of an economic evaluation to other contexts. In practice, the clear definition of the decision maker, with explanation of how this perspective affects methodological decisions and parameterization will facilitate transferability of economic evaluation to other contexts as users will be able to assess which aspects of an analysis require modification to apply it to another context.

# STEP 2: Determine the intervention type

Specification of the intervention, including its use-case and intended population is an essential element of the evaluation. This framework requires not only a general description of the intervention, but also alignment to established classification systems. In the first instance, the intervention should be assigned to a WHO DHI type, with specification as to whether there is a predictive analytics component. This creates three major categories of DHI, with further granularity for DHIs under the WHO classification system.

1. DHIs defined under the WHO DHI classification system without AI enabling functionality – e.g., simple text message to patients as a reminder for regular followup.

2. DHIs defined under the WHO DHI classification system with AI enabling functionality – e.g., machine learning radiology diagnostics.

3. Non-digital health interventions enabled by the used of AI technology – e.g., use of demographic and clinical information for identification of at-risk patients for health professional consultation.