Andrew S. Hackbarth
Papers
1
Total Citations
11
H-Index
1
About
Andrew S. Hackbarth is a health services researcher whose work sits at the intersection of clinical informatics, quality measurement, and urologic oncology. His primary contributions involve the development and validation of novel methods to leverage electronic health record data for surgical quality improvement. In his most cited work, Hackbarth and colleagues pioneered the use of natural language processing (NLP) to automatically identify patients undergoing radical cystectomy for bladder cancer, demonstrating that automated text analysis can reliably replace manual chart review for case identification. This foundational study, with 11 citations, established a scalable approach to enrich quality measurement in complex surgical populations. Hackbarth’s research addresses a critical bottleneck in health services research: the accurate, efficient extraction of clinical data from unstructured text. By advancing NLP-based phenotyping, his work has implications for comparative effectiveness research, surgical outcomes surveillance, and the development of real-time quality dashboards. Hackbarth’s contributions sit at the forefront of efforts to transform electronic health records from passive documentation tools into active instruments for measurement and improvement.
Research Focus
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Top Papers
- 1