Patrick Ryan, PhD
Vice President, Observational Health Data Analytics
Janssen Research and Development
Assistant Professor, Adjunct; Department of Biomedical Informatics
Columbia University Medical Center
Patrick Ryan, PhD is Vice President, Observational Health Data Analytics at Janssen Research and Development, where he is leading efforts to develop and apply analysis methods to better understand the real-world effects of medical products. He is an original collaborator in Observational Health Data Sciences and Informatics (OHDSI), a multi-stakeholder, interdisciplinary collaborative to create open-source solutions that bring out the value of observational health data through large-scale analytics. He served as a principal investigator of the Observational Medical Outcomes Partnership (OMOP), a public-private partnership chaired by the Food and Drug Administration, where he led methodological research to assess the appropriate use of observational health care data to identify and evaluate drug safety issues.
Patrick received his undergraduate degrees in Computer Science and Operations Research at Cornell University, his Master of Engineering in Operations Research and Industrial Engineering at Cornell, and his PhD in Pharmaceutical Outcomes and Policy from University of North Carolina at Chapel Hill. Patrick has worked in various positions within the pharmaceutical industry at Pfizer and GlaxoSmithKline, and also in academia at the University of Arizona Arthritis Center.
Schuemie MJ, Trifiro G, Coloma PM, Ryan PB, Madigan D. Detecting adverse drug reactions following long-term exposure in longitudinal observational data: The exposure-adjusted self-controlled case series. Stat Methods Med Res. 2014 Mar 31;31:31.
Schuemie MJ, Ryan PB, Suchard MA, Shahn Z, Madigan D. Discussion: An estimate of the science-wise false discovery rate and application to the top medical literature. Biostatistics. 2014 Jan;15(1):36-9; discussion 9-45. doi: 10.1093/biostatistics/kxt037. Epub 2013 Sep 25.
Boyce RD, Ryan PB, Noren GN, et al. Bridging Islands of Information to Establish an Integrated Knowledge Base of Drugs and Health Outcomes of Interest. Drug Saf. 2014 Jul 2;2:2.
Schuemie MJ, Ryan PB, DuMouchel W, Suchard MA, Madigan D. Interpreting observational studies: why empirical calibration is needed to correct p-values. Stat Med. 2014 Jan 30;33(2):209-18. doi: 10.1002/sim.5925. Epub 2013 Jul 30.
Weng C, Li Y, Ryan P, et al. A Distribution-based Method for Assessing The Differences between Clinical Trial Target Populations and Patient Populations in Electronic Health Records. Appl Clin Inform. 2014 May 7;5(2):463-79. doi: 10.4338/ACI-2013-12-RA-0105. eCollection 2014.
Madigan D, Stang PE, Berlin JA, et al. A Systematic Statistical Approach to Evaluating Evidence from Observational Studies. Annual Review of Statistics and Its Application. 2014;1(1):11-39.
Stang P, Ryan P, Hartzema AG, et al. Development and Evaluation of Infrastructure and Analytic Methods for Systematic Drug Safety Surveillance: Lessons and Resources from the Observational Medical Outcomes Partnership. In: Elizabeth B. Andrews NM, editor. Mann’s Pharmacovigilance. Third ed: Wiley-Blackwell; 2014. p. 866.
Schuemie MJ, Madigan D, Ryan PB. Empirical performance of LGPS and LEOPARD: lessons for developing a risk identification and analysis system. Drug Saf. 2013 Oct;36(Suppl 1):S133-42. doi: 10.1007/s40264-013-0107-x.
Madigan D, Schuemie MJ, Ryan PB. Empirical performance of the case-control method: lessons for developing a risk identification and analysis system. Drug Saf. 2013 Oct;36(Suppl 1):S73-82. doi: 10.1007/s40264-013-0105-z.
Cepeda MS, Fife D, Ma Q, Ryan PB. Comparison of the risks of opioid abuse or dependence between tapentadol and oxycodone: results from a cohort study. J Pain. 2013 Oct;14(10):1227-41. doi: 10.016/j.jpain.2013.05.010. Epub Jul 10.
Ryan PB, Madigan D, Stang PE, Schuemie MJ, Hripcsak G. Medication-wide association studies. CPT Pharmacometrics Syst Pharmacol. 2013 Sep 18;2:e76.(doi):10.1038/psp.2013.52.
Reich CG, Ryan PB, Suchard MA. The impact of drug and outcome prevalence on the feasibility and performance of analytical methods for a risk identification and analysis system. Drug Saf. 2013 Oct;36(Suppl 1):S195-204. doi: 10.1007/s40264-013-0112-0.
Reich CG, Ryan PB, Schuemie MJ. Alternative outcome definitions and their effect on the performance of methods for observational outcome studies. Drug Saf. 2013 Oct;36(Suppl 1):S181-93. doi: 10.1007/s40264-013-0111-1.
Ryan PB, Schuemie MJ. Evaluating performance of risk identification methods through a large-scale simulation of observational data. Drug Saf. 2013 Oct;36(Suppl 1):S171-80. doi: 10.1007/s40264-013-0110-2.
Ryan PB, Stang PE, Overhage JM, et al. A comparison of the empirical performance of methods for a risk identification system. Drug Saf. 2013 Oct;36(Suppl 1):S143-58. doi: 10.1007/s40264-013-0108-9.
DuMouchel W, Ryan PB, Schuemie MJ, Madigan D. Evaluation of disproportionality safety signaling applied to healthcare databases. Drug Saf. 2013 Oct;36(Suppl 1):S123-32. doi: 10.1007/s40264-013-0106-y.
Noren GN, Bergvall T, Ryan PB, Juhlin K, Schuemie MJ, Madigan D. Empirical performance of the calibrated self-controlled cohort analysis within temporal pattern discovery: lessons for developing a risk identification and analysis system. Drug Saf. 2013 Oct;36(Suppl 1):S107-21. doi: 10.1007/s40264-013-0095-x.
Ryan PB, Schuemie MJ, Madigan D. Empirical performance of a self-controlled cohort method: lessons for developing a risk identification and analysis system. Drug Saf. 2013 Oct;36(Suppl 1):S95-106. doi: 10.1007/s40264-013-0101-3.
Suchard MA, Zorych I, Simpson SE, Schuemie MJ, Ryan PB, Madigan D. Empirical performance of the self-controlled case series design: lessons for developing a risk identification and analysis system. Drug Saf. 2013 Oct;36(Suppl 1):S83-93. doi: 10.1007/s40264-013-0100-4.
Ryan PB, Schuemie MJ, Gruber S, Zorych I, Madigan D. Empirical performance of a new user cohort method: lessons for developing a risk identification and analysis system. Drug Saf. 2013 Oct;36(Suppl 1):S59-72. doi: 10.1007/s40264-013-0099-6.
Hartzema AG, Reich CG, Ryan PB, et al. Managing data quality for a drug safety surveillance system. Drug Saf. 2013 Oct;36(Suppl 1):S49-58. doi: 10.1007/s40264-013-0098-7.
Ryan PB, Schuemie MJ, Welebob E, Duke J, Valentine S, Hartzema AG. Defining a reference set to support methodological research in drug safety. Drug Saf. 2013 Oct;36(Suppl 1):S33-47. doi: 10.1007/s40264-013-0097-8.
Stang PE, Ryan PB, Overhage JM, Schuemie MJ, Hartzema AG, Welebob E. Variation in choice of study design: findings from the Epidemiology Design Decision Inventory and Evaluation (EDDIE) survey. Drug Saf. 2013 Oct;36(Suppl 1):S15-25. doi: 10.1007/s40264-013-0103-1.
Overhage JM, Ryan PB, Schuemie MJ, Stang PE. Desideratum for evidence based epidemiology. Drug Saf. 2013 Oct;36(Suppl 1):S5-14. doi: 0.1007/s40264-013-0102-2.
Simpson SE, Madigan D, Zorych I, Schuemie MJ, Ryan PB, Suchard MA. Multiple self-controlled case series for large-scale longitudinal observational databases. Biometrics. 2013 Dec;69(4):893-902. doi: 10.1111/biom.12078. Epub 2013 Oct 11.
Katz AJ, Ryan PB, Racoosin JA, Stang PE. Assessment of case definitions for identifying acute liver injury in large observational databases. Drug Saf. 2013 Aug;36(8):651-61. doi: 10.1007/s40264-013-0060-8.
Madigan D, Ryan PB, Schuemie M, et al. Evaluating the impact of database heterogeneity on observational study results. Am J Epidemiol. 2013 Aug 15;178(4):645-51. doi: 10.1093/aje/kwt010. Epub 2013 May 5.
Ryan PB, Madigan D, Stang PE, Marc Overhage J, Racoosin JA, Hartzema AG. Response to comment on ’empirical assessment of methods for risk identification in healthcare data’. Stat Med. 2013 Mar 15;32(6):1075-7. doi: 10.02/sim.5725.
Defalco FJ, Ryan PB, Soledad Cepeda M. Applying standardized drug terminologies to observational healthcare databases: a case study on opioid exposure. Health Serv Outcomes Res Methodol. 2013 Mar;13(1):58-67. Epub 2012 Oct 27.
Zorych I, Madigan D, Ryan P, Bate A. Disproportionality methods for pharmacovigilance in longitudinal observational databases. Stat Methods Med Res. 2013 Feb;22(1):39-56. doi: 10.1177/0962280211403602. Epub 2011 Aug 30.
Ryan P, Suchard MA, Schuemie M, Madigan D. Learning From Epidemiology: Interpreting Observational Database Studies for the Effects of Medical Products. Statistics in Biopharmaceutical Research. 2013;5(3).
Madigan D, Ryan PB, Schuemie M. Does design matter? Systematic evaluation of the impact of analytical choices on effect estimates in observational studies. Therapeutic Advances in Drug Safety. 2013 April 1, 2013;4(2):53-62.
Suchard MA, Simpson SE, Zorych I, Ryan P, Madigan D. Massive Parallelization of Serial Inference Algorithms for a Complex Generalized Linear Model. ACM Trans Model Comput Simul. 2013;23(1):1-17.
Ryan P. Statistical challenges in systematic evidence generation through analysis of observational healthcare data networks. Statistical Methods in Medical Research. 2013;22(1):3-6.
Li X, Hui S, Ryan P, Rosenman M, Overhage M. Statistical visualization for assessing performance of methods for safety surveillance using electronic databases. Pharmacoepidemiol Drug Saf. 2013 May;22(5):503-9. doi: 10.1002/pds.3419. Epub 2013 Feb 14.
Ryan PB, Madigan D, Stang PE, Overhage JM, Racoosin JA, Hartzema AG. Empirical assessment of methods for risk identification in healthcare data: results from the experiments of the Observational Medical Outcomes Partnership. Stat Med. 2012 Dec 30;31(30):4401-15. doi: 10.1002/sim.5620. Epub 2012 Sep 27.
Reich C, Ryan PB, Stang PE, Rocca M. Evaluation of alternative standardized terminologies for medical conditions within a network of observational healthcare databases. J Biomed Inform. 2012 Aug;45(4):689-96. doi: 10.1016/j.jbi.2012.05.002. Epub Jun 7.
Gagne JJ, Fireman B, Ryan PB, et al. Design considerations in an active medical product safety monitoring system. Pharmacoepidemiol Drug Saf. 2012 Jan;21(Suppl 1):32-40. doi: 10.1002/pds.2316.
Overhage JM, Ryan PB, Reich CG, Hartzema AG, Stang PE. Validation of a common data model for active safety surveillance research. J Am Med Inform Assoc. 2012 Jan-Feb;19(1):54-60. doi: 10.1136/amiajnl-2011-000376. Epub 2011 Oct 28.
Harpaz R, DuMouchel W, Shah NH, Madigan D, Ryan P, Friedman C. Novel data-mining methodologies for adverse drug event discovery and analysis. Clin Pharmacol Ther. 2012 Jun;91(6):1010-21. doi: 10.38/clpt.2012.50.
Ryan P. Using Exploratory Visualization in the Analysis of Medical Product Safety in Observational Healthcare Data. In: Krause A, OConnell, Michael editor. A Picture is Worth a Thousand Tables: Springer; 2012. p. 429.
Stang PE, Ryan PB, Dusetzina SB, et al. Health Outcomes of Interest in Observational Data: Issues in Identifying Definitions in the Literature. Health Outcomes Research in Medicine. 2012 2//;3(1):e37-e44.
Murray RE, Ryan PB, Reisinger SJ. Design and validation of a data simulation model for longitudinal healthcare data. AMIA Annu Symp Proc. 2011;2011:1176-85. Epub 2011 Oct 22.
Madigan D, Ryan P. What can we really learn from observational studies?: the need for empirical assessment of methodology for active drug safety surveillance and comparative effectiveness research. Epidemiology. 2011 Sep;22(5):629-31. doi: 10.1097/EDE.0b013e318228ca1d.
Stang PE, Ryan PB, Racoosin JA, et al. Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership. Ann Intern Med. 2010 Nov 2;153(9):600-6. doi: 10.7326/0003-4819-153-9-201011020-00010.
Reisinger SJ, Ryan PB, O’Hara DJ, et al. Development and evaluation of a common data model enabling active drug safety surveillance using disparate healthcare databases. J Am Med Inform Assoc. 2010 Nov-Dec;17(6):652-62. doi: 10.1136/jamia.2009.002477.
Ryan P, Welebob E, Hartzema A, Stang P, Overhage JM. Surveying US Observational Data Sources and Characteristics for Drug Safety Needs. Pharm Med. 2010 2010/08/01;24(4):231-8.
