A Framework for Advancing the Identification, Development, and Adoption of Digital Clinical Measures

Within digital health, the existing gold standard of measurement is often inadequate or non-existent and many consortia are convening experts across the industry to identifying new digital benchmarks and measures to verify and validate (yey!). But, how do consortia arrive at these new measures, and how do organizations embed these new standards/endpoint strategies and industry best practices into their internal processes? It requires a systematic approach. Let me break it down:

Identifying New Digital Measures:

1. Identify Meaningful Aspects of Health (MAH): Conduct patient research. Understand how patients experience the condition and how it affects their daily lives. Conduct patient and caregiver interviews.
2. Identify the Concept of Interest (COI): Here you are looking to identify the key idea, theory, or subject matter/theme/topic that you're interested in exploring or understanding more deeply.
3. Develop a Conceptual Model: The model should illustrate the relationships among the various components of the system it represents. The purpose of a conceptual model is to express the underlying principles and structure of the system in a way that's understandable, even to non-experts. Conceptual models often take the form of diagrams, flowcharts, or other visual representations, but they can also be narrative descriptions.
4. Ensure the Conceptual Model Outlines a Shared Terminology and Measurement Ontology: An ontology is a set of measurement concepts showing their properties and relationships which can be demonstrated across devices.?Perform a systemic literature review and converse with regulators.
5. Identify the Outcome to be Measured: If going further to verify and validate the measure and deploy it in clinical trials...Select the outcome to be measured.?Outcomes are the specific measurable characteristics of the disease that evaluate the MAH as defined by the COI. Regardless of whether the outcomes are measured using clinical outcome assessments (COAs) or biomarkers, it is crucial that they reflect the patient-focused COI. Assess the technical specifications of a tool that can measure the outcome in the population of interest.
6. Identify the Endpoint: Define the endpoint. Endpoints are precisely defined variables intended to reflect outcomes of interest that are statistically analyzed to address a research question. As such, “digital endpoints” are?only relevant in research?and are not part of routine care.?In clinical trials, endpoints measure clinical benefit?related to improvement in how patients feel, function, or survive. A key difference between an outcome and an endpoint is that researchers must be able to clearly identify if endpoints were achieved, or not.?

For Implementing These New Measures/Benchmarks:

1. Identification and Acquisition of External Knowledge: Organizations must first identify what external insights, digital measures, and best practices they need to incorporate. This can involve keeping an eye on industry reports, attending conferences and webinars, engaging with thought leaders, reading academic research, and benchmarking against other leading businesses in the industry.
2. Knowledge Management: Once the organization identifies these measures, insights, and best practices, they must manage and store them effectively for easy access and reference. Knowledge management systems are used to store, retrieve, and manage information, ensuring everyone in the organization can easily access and utilize the external insights.
3. Analysis and Customization: Not all external practices will be suitable for every organization. Therefore, the organization needs to analyze and customize these practices to fit its specific context. This may involve reviewing the organization's goals, structures, and culture and then adapting the best practices to align with these factors.
4. Change Management: Introducing new practices often requires changes to existing processes, structures, and behaviors. Change management is thus a critical part of embedding external practices. This might involve communicating the need for change, training staff on new processes, and supporting them through the transition.
5. Implementation: The adapted practices need to be implemented into the organization's processes. This could be through process redesign, technological changes, changes in job roles, or shifts in organizational culture.
6. Monitoring and Evaluation: After implementation, the organization needs to monitor the effectiveness of the new practices and evaluate the results. Feedback mechanisms, KPIs, and other evaluation tools should be used to understand the impact of the new practices and to make any necessary adjustments.
7. Continuous Improvement: The process doesn't end with the implementation of the new practices. There should be a continuous process of learning, adaptation, and improvement. This ensures the organization continues to evolve and adapt in response to changes in industry best practices and external insights.

Without a doubt, digital measures of health require significant resources to develop for use in clinical trials. To ensure these efforts are successful and return value to respective organizations and the patients we all serve, organizations must begin planning for the incorporation of patient input and deployment of digital measures (as exploratory endpoints or otherwise) at the inception of each R&D program and clinical trial.

CREDIT: Heavily paraphrased from the great work that the Digital Medicine Society (DIME) has done in partnership with its corporate sponsors and the FDA and EMA.

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