Finding temporal patterns - A set-based approach

  • Authors:

  • Ted D. Wade;Patricia J. Byrns;John F. Steiner;Jessica Bondy

  • Affiliations:

  • Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver, CO 80262, USA and Center for Health Services Research, University of Colorado Health Scienc ...;Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver, CO 80262, USA and Center for Health Services Research, University of Colorado Health Scienc ...;Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver, CO 80262, USA and Center for Health Services Research, University of Colorado Health Scienc ...;Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver, CO 80262, USA and Center for Health Services Research, University of Colorado Health Scienc ...

  • Venue:
  • Artificial Intelligence in Medicine
  • Year:
  • 1994

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Abstract

We created an inference engine and query language for expressing temporal patterns in data. The patterns are represented by using temporally-ordered sets of data objects. Patterns are elaborated by reference to new objects inferred from original data, and by interlocking temporal and other relationships among sets of these objects. We found the tools well-suited to define scenarios of events that are evidence of inappropriate use of prescription drugs, using Medicaid administrative data that describe medical events. The tools' usefulness in research might be considerably more general.