Stephanie J Reisinger

Summary

Publications

  1. ncbi Development and evaluation of a common data model enabling active drug safety surveillance using disparate healthcare databases
    Stephanie J Reisinger
    ProSanos Corporation, Harrisburg, Pennsylvania 17101, USA
    J Am Med Inform Assoc 17:652-62. 2010
  2. ncbi Drug-versus-drug adverse event rate comparisons: a pilot study based on data from the US FDA Adverse Event Reporting System
    Alan M Hochberg
    ProSanos Corporation, Harrisburg, Pennsylvania 17101, USA
    Drug Saf 32:137-46. 2009
  3. ncbi Systematic investigation of time windows for adverse event data mining for recently approved drugs
    Alan M Hochberg
    ProSanos Corporation, 225 Market St, Suite 502, Harrisburg, PA 17102, USA
    J Clin Pharmacol 49:626-33. 2009
  4. ncbi An evaluation of three signal-detection algorithms using a highly inclusive reference event database
    Alan M Hochberg
    ProSanos Corporation, Harrisburg, Pennsylvania 17102, USA
    Drug Saf 32:509-25. 2009
  5. ncbi Influence of the MedDRA hierarchy on pharmacovigilance data mining results
    Ronald K Pearson
    ProSanos Corporation, Harrisburg, PA 17102, USA
    Int J Med Inform 78:e97-e103. 2009

Collaborators

Detail Information

Publications5

  1. ncbi Development and evaluation of a common data model enabling active drug safety surveillance using disparate healthcare databases
    Stephanie J Reisinger
    ProSanos Corporation, Harrisburg, Pennsylvania 17101, USA
    J Am Med Inform Assoc 17:652-62. 2010
    ..The objective of this study was to develop and evaluate a common data model (CDM) enabling rapid, comparable, systematic analyses across disparate observational data sources to identify and evaluate the effects of medicines...
  2. ncbi Drug-versus-drug adverse event rate comparisons: a pilot study based on data from the US FDA Adverse Event Reporting System
    Alan M Hochberg
    ProSanos Corporation, Harrisburg, Pennsylvania 17101, USA
    Drug Saf 32:137-46. 2009
    ..The accuracy of comparative AERS-based data mining has been questioned, but has not been systematically studied...
  3. ncbi Systematic investigation of time windows for adverse event data mining for recently approved drugs
    Alan M Hochberg
    ProSanos Corporation, 225 Market St, Suite 502, Harrisburg, PA 17102, USA
    J Clin Pharmacol 49:626-33. 2009
    ..Data mining may be most useful for early signal detection during the first 3 years of a drug's postmarketing life. Beyond that, it may be most useful for supporting or weakening hypotheses...
  4. ncbi An evaluation of three signal-detection algorithms using a highly inclusive reference event database
    Alan M Hochberg
    ProSanos Corporation, Harrisburg, Pennsylvania 17102, USA
    Drug Saf 32:509-25. 2009
    ..Pharmacovigilance data-mining algorithms (DMAs) are known to generate significant numbers of false-positive signals of disproportionate reporting (SDRs), using various standards to define the terms 'true positive' and 'false positive'...
  5. ncbi Influence of the MedDRA hierarchy on pharmacovigilance data mining results
    Ronald K Pearson
    ProSanos Corporation, Harrisburg, PA 17102, USA
    Int J Med Inform 78:e97-e103. 2009
    ..To compare the results of drug safety data mining with three different algorithms, when adverse events are identified using MedDRA Preferred Terms (PT) vs. High Level Terms (HLT) vs. Standardised MedDRA Queries (SMQ)...