Optimizing Digital Health Informatics Interventions Through Unobtrusive Quantitative Process Evaluations

Health informatics interventions such as clinical decision support (CDS) and audit and feedback (A&F) are variably effective at improving care because the underlying mechanisms through which these interventions bring about change are poorly understood. This limits our possibilities to design better interventions. Process evaluations can be used to improve this understanding by assessing fidelity and quality of implementation, clarifying causal mechanisms, and identifying contextual factors associated with variation in outcomes. Coiera describes the intervention process as a series of stages extending from interactions to outcomes: the "information value chain". However, past process evaluations often did not assess the relationships between those stages. In this paper we argue that the chain can be measured quantitatively and unobtrusively in digital interventions thanks to the availability of electronic data that are a by-product of their use. This provides novel possibilities to study the mechanisms of informatics interventions in detail and inform essential design choices to optimize their efficacy