From Health Data Management
A coming wave of digital health tools has the potential to transform how and where healthcare is provided.
Using information from a patient’s medical record—including lab results, provider notes and images, such as CT scans—along with genomic data, prior insurance claims and environmental information, machine learning algorithms can substantially improve diagnostic testing. They can also support decision-making tools for providers to improve guideline adherence.
The tools’ success is not a given, however. They must first gain the trust of patients, providers and payers. In addition, the tools must not prompt alert fatigue. If providers are flooded with warnings and advice, they may become desensitized and tune out the information.
This coming wave provides a golden opportunity to overcome both hurdles—smart piloting of the new tools. By systematically introducing these digital health tools, we learn what works and what doesn’t. Randomized trials do not need to be limited to pharmaceuticals and medical devices; they can inform healthcare delivery designs as well.