ScanHealth

ScanHealth is a digital health analytics platform that scans and interprets medical data to support clinical decision making. It aggregates structured data from electronic health records, imaging studies, laboratory results, genomics, and wearable devices, and uses a combination of machine learning and rule-based reasoning to identify risks, track disease progression, and flag adverse events.

Designed for interoperability and privacy, ScanHealth supports standard formats such as HL7 FHIR for data exchange and DICOM for imaging. It generates clinician-facing dashboards, patient summaries, and automated alerts, while maintaining detailed audit trails and access controls.

Technology and methods include natural language processing to extract information from clinical notes, computer vision for radiology images, time-series analysis for vital signs, de-identification processes, and explainable AI techniques to justify risk scores and recommendations.

Applications include population health management, early detection and triage, support for clinical trials and pharmacovigilance, and post-market safety monitoring. The system is intended to augment, not replace, clinician judgment.

History and development: a consortium of hospitals and research institutions began development in the early 2020s, with pilots across multiple care settings and subsequent commercial deployment. Ongoing updates expand coverage to additional imaging modalities, genomic data, and consumer health devices.

Reception and regulation: proponents cite improvements in detection rates and efficiency, while critics emphasize data privacy risks, potential bias in training data, and the need for transparency. Compliance with privacy and medical device regulations varies by jurisdiction and use case.