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Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

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Optimizing Digital Health Informatics Interventions Through Unobtrusive Quantitative Process Evaluations.

Wouter T Gude¹, Sabine N van der Veer², Nicolette F de Keizer¹

¹Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.

Studies in Health Technology and Informatics

|September 1, 2016

Summary

Understanding health informatics interventions like clinical decision support (CDS) requires examining the "information value chain." Measuring this chain quantitatively in digital tools can reveal how interventions improve care and inform better design.

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Area of Science:

Health Informatics
Digital Health Interventions
Healthcare Quality Improvement

Background:

Health informatics interventions, including clinical decision support (CDS) and audit and feedback (A&F), show variable effectiveness due to poorly understood mechanisms of action.
Limited understanding of intervention mechanisms hinders the design of more effective health informatics tools.

Purpose of the Study:

To propose a quantitative, unobtrusive method for measuring the stages of the "information value chain" in digital health interventions.
To enhance the understanding of causal mechanisms underlying health informatics interventions.
To inform the design of more efficacious digital health tools.

Main Methods:

Leveraging electronic data generated as a byproduct of digital intervention use.
Applying quantitative measurement to assess the relationships between stages of the "information value chain" (interactions to outcomes).
Utilizing process evaluation principles to assess fidelity, quality, causal mechanisms, and contextual factors.

Main Results:

Digital interventions generate electronic data suitable for unobtrusive, quantitative measurement of the information value chain.
This approach allows for detailed study of intervention mechanisms, moving beyond traditional process evaluations.
The availability of electronic data provides novel possibilities for understanding how informatics interventions impact care.

Conclusions:

Quantitative measurement of the information value chain in digital interventions offers a powerful new approach to studying their efficacy.
Understanding these mechanisms is crucial for optimizing the design and impact of health informatics tools.
This methodology can significantly advance the field of health informatics by elucidating intervention processes.