Why now?

The rise of software-driven connected technologies has created a fundamental shift in health data and information flows, and thus in the practice of medicine.

Data flows in the digital era of medicine

Historical

Future/Today

“Stock” - A patient receives test result or piece of evidence every couple months or years “Flows” - Data can come in by the minute or millisecond (e.g., heart rate information, continuous glucose monitoring)

 Human Readable: Test results be interpreted by a human (e.g., tissue samples, reactivity of a chemical compound)

Non-Human Readable: Results produced from algorithms run on large samples of data (e.g., genomic sequencing or predictions of abnormal heart conditions). Not feasible for a human to double-check the information.

Human-Shared: Results shared from one human (e.g., a doctor) to another (e.g., a patient), most often in-person, and in an environment with space for context and questions.

Machine-Shared: An algorithm shares a digital result. Limited context exists for a human to correct false positives/negatives in real-time. 

 

digital med 4 In the digital era of medicine, a number of processes, best practices, and ethical norms have started to shift as we learn how to develop trustworthy technologies. Sample paradigm shifts include the need to develop new methods to determine verification and validation, clinical usability and human experience, cybersecurity risks, and data rights and governance from ‘digital specimen’ collection. 

As digital medicine evolves, we must ensure that these technologies are worthy of the trust we place in them. Unlike “digital health” or “digital wellness” products, digital medicine products are characterized by a body of evidence to support their quality and effectiveness.