The Path Forward for Digital Measures: Suppressing the Desire to Compare Apples and Pineapples

Abstract

Digital measures are becoming more prevalent in clinical development. Methods for robust evaluation are increasingly well defined, yet the primary barrier for digital measures to transition beyond exploratory usage often relies on a comparison to the existing standards. This article focuses on how researchers should approach the complex issue of comparing across assessment modalities. We discuss comparisons of subjective versus objective assessments, or performance-based versus behavioral measures, and we pay particular attention to the situation where the expected association may be poor or nonlinear. We propose that, rather than seeking to replace the standard, research should focus on a structured understanding of how the new measure augments established assessments, with the ultimate goal of developing a more complete understanding of what is meaningful to patients.

Evaluation, Acceptance, and Qualification of Digital Measures: From Proof of Concept to Endpoint

“…One option for developing digital measures to address the MAH of these patients may require a ground-up approach utilizing psychometric methods to establish utility and clinical validity [45, 66, 67].…”

“…Working in partnership with patients and their caregivers is critical to defining a COI that will remain relevant throughout the long journey ahead [45].…”

Beyond the Therapist’s Office: Merging Measurement-Based Care and Digital Medicine in the Real World

“…This should not be viewed as a disadvantage but as a strength. The goal should not be to replace current measurement standards, but to comprehend ways in which new digital measures can augment traditional (self-report) measures to form a more wholistic, patient-centered clinical picture [ 33 ]. It is possible that combining data types may capture different elements of the disease experience and progression [ 2 ] and may point the way to more precise intervention targets [ 2 ].…”

The Future of Digital Health: Meeting Report

“…Best practice, from the field of psychometrics, towards engaging patients directly in helping to develop “measures that matter” was also discussed [6]. Research on advancements in making real-world step detection more flexible showed how algorithmic improvements can give patients more flexibility in terms of how they wear a device without compromising accuracy [7].…”