Regenstrief Institute
Indiana University School of Medicine
410 West 10th St
Suite 2000
Indianapolis,
IN
USA
46202
jfriedlin@regenstrief.org
Biographical Sketch:
I am a family physician who completed a medical informatics fellowship in 2008 and then became an Assistant Professor of Family Medicine for Indiana University School of Medicine, and a Research Scientist with Regenstrief Institute, Inc. My research interests include improving population health, data mining population health data, data analysis, and developing natural language processing (NLP) software to automatically identify, extract and encode concepts found in medical documents. My research focus includes using data mining and NLP technology to identify novel patterns, relationships and correlations that exist in public health as well as clinical data. I have recently worked on helping to improve an automated notifiable condition detector (NCD) that analyzes clinical data created in a large health information exchange and identifies diseases that may have detrimental effects on the health of the population as a whole. This system is part of an overall public health monitoring system currently in place at the Regenstrief institute and that was developed in collaboration with the Indiana State Department of Public Health. I have published numerous peer-reviewed abstracts and manuscripts in the field of NLP and de-identification, and several of these pertain to public health informatics and research on advanced concepts in public health surveillance. I was a finalist in the Student Paper Competition at the American Medical Informatics Association (AMIA) Symposium for the years 2006, 2007, 2008. In the past 3 years as a Regenstrief investigator, I have developed NLP technology that processed microbiology culture reports in order to detect patients that were positive for methicillin-resistant Staphylococcus aureus. I also was the Principal Investigator in a study to evaluate its effectiveness. I have also assisted in the development, design, and implementation of the NCD.
Friedlin FJ, Grannis SJ, Overhage, M. Using Natural Language Processing to Improve Accuracy of Automated Notifiable Disease Reporting. AMIA Annu Symp Proc. 2008 Nov 6:207-11. PMID: 18999177
Shepherd D, Friedlin FJ, Grannis S, Hui S, Kho A. A comparison of automated methicillin-resistant Staphylococcus aureus identification with current infection control practice. AMIA Annu Symp Proc. 2009;2009:594-8. PMID: 20351924.
Friedlin FJ, Overhage M. Comparing methods for identifying pancreatic cancer patients using electronic data sources. AMIA Annu Symp Proc. 2010;2010:In press.
Al-Haddad MA, Friedlin FJ, Kesterson J, Waters JA, Agulair-Saavedra JR, Schmidt CM. Natural language processing for the development of a clinical registry: a validation study in intraductal papillary mucinous neoplasms. HPB (Oxford). 2010 Dec;12(10):688-95. PMID: 21083794