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[Learning from coding data-surgical treatment of benign prostatic syndrome : Big data for BPS]
Nadine Binder1, J Franz2, A Sigle2
1Medizinische Fakultät, Institut für Allgemeinmedizin, Universitätsklinikum Freiburg, Elsässerstr. 2m, 79110, Freiburg, Deutschland. nadine.binder@uniklinik-freiburg.de.
Der Urologe. Ausg. A
|December 24, 2021
Summary
Digital data analysis reveals trends in benign prostatic syndrome (BPS) surgical treatments. This research provides key figures for optimizing BPS care strategies and improving patient outcomes.
Area of Science:
- Urology
- Health Informatics
- Data Science in Healthcare
Background:
- Benign prostatic syndrome (BPS) is a prevalent urological condition requiring diverse surgical interventions.
- The increasing digitalization of healthcare offers novel avenues for analyzing patient treatment pathways.
Purpose of the Study:
- To conduct longitudinal trend analyses specific to benign prostatic syndrome (BPS) surgical treatments.
- To examine treatment-related figures and patient cohorts using validated digital datasets.
Main Methods:
- Performed validated, BPS-specific longitudinal trend analyses on digital healthcare data.
- Analyzed treatment methods and patient cohorts to extract relevant surgical characteristics.
Main Results:
- Quantified treatment-related figures for various surgical BPS therapies.
- Calculated the overall impact of surgical processes for BPS treatment.
Conclusions:
- Digital data analysis provides valuable insights into surgical BPS treatment patterns.
- Findings enable optimization of treatment actions and inform strategic development for medical facilities.
- Further research utilizing comprehensive digital datasets is encouraged.
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