Unmet Need
Time-series data is essential to understanding patient progress, disease course, and response to treatment. While it is currently possible to store and access time series records, many factors are removed or not recorded, resulting in confounding variables to patient data. Thus, there exists a need for methods to filter time-series data by confounding variables while still maintaining data safety.
Value Proposition:
· Integrates data directly from PhysioCloud to determine patient location
· Allows data-safe storage and association of patient location and time-series data
· Enables high detail subject-data association for retrospective research
Technology Description
Researchers at Johns Hopkins have developed a method to access patient location from the Admit-Discharge-Transfer (ADT) data stream. The method also allows for secure data storage and access. This enables both time-series only research and retrospective, subject-data association research.
Stage of Development
· Proof-of-concept code has been developed. Data transfer methods are currently being improved.
Publication
N/A
