Heart failure (HF) is one of the biggest concerns for health care systems in developed countries. To support the long-term treatment of HF patients, the Austrian Institute of Technology implemented a HF telehealth network called "HerzMobil". While most data within this network are stored in a structured format, health care professionals can also communicate via clinical notes in free text format. These notes are hardly ever analyzed automatically, even though a large number contains valuable information for the patient's treatment process. With currently more than 20,000 notes stored in the system, an automatic approach is beneficial to spare manual screening time. One important step in this process concerns the extraction of time references from the notes. This information could, for example, be used to match the time references with events from the same note. Therefore, two Python scripts were developed to: extract time references from the notes (Script A) and subsequently calculate the corresponding dates (Script B). Script A was compared to an already existing Python library and achieved superior results for all calculated key figures. The time calculation algorithm of Script B achieved an accuracy of 75.34%. These scripts could be implemented in the HerzMobil network to provide additional information for the treatment process and further improve the telehealth system.
|Titel||2020 Computing in Cardiology|
|Publikationsstatus||Veröffentlicht - 2021|
- Exploration of Digital Health