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Academic Psychiatry

, Volume 33, Issue 1, pp 27–30 | Cite as

Utilizing VA Information Technology to Develop Psychiatric Resident Prescription Profiles

  • Robert Rohrbaugh
  • Daniel G. Federman
  • Lydia Borysiuk
  • Michael Sernyak
Brief Report

Abstract

Objectives

Feedback about resident prescription practices allows psychiatry educators to ensure that residents have broad prescribing experience and can facilitate practice-based learning initiatives. The authors report on a procedure utilizing U.S. Department of Veterans Affairs’ computerized pharmacy records to efficiently construct comprehensive individual psychiatric resident prescription practice profiles.

Methods

Veterans Affairs information technology provided a methodology to efficiently construct individual and aggregate resident prescription profiles, including cost data. To demonstrate the utility of prescription profiles, individual and aggregate antipsychotic medication prescription profiles were constructed of nine residents working in a Veterans Affairs psychotic disorders clinic.

Results

Developing the individual and aggregate prescription profiles required only 5 hours. The profiles revealed that residents had a restricted range of experience prescribing antipsychotic medications, with some residents not having prescribed all five major atypical agents and the majority having prescribed a limited number of typical agents. The profiles highlighted cost differences among the atypical antipsychotic medications and between the typical and atypical antipsychotic medications.

Conclusion

Prescription profiles facilitate resident education by enabling educators to determine the range of antipsychotic medications residents prescribe. A psychiatric residency program could utilize these prescription profiles to improve resident competency in practice based learning.

Keywords

Veteran Affair Aripiprazole Academic Psychiatry Ziprasidone Typical Agent 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Academic Psychiatry 2009

Authors and Affiliations

  • Robert Rohrbaugh
    • 1
    • 3
  • Daniel G. Federman
    • 2
    • 3
  • Lydia Borysiuk
    • 3
  • Michael Sernyak
    • 1
    • 3
  1. 1.Department of PsychiatryYale School of MedicineNew HavenUSA
  2. 2.Department of Internal Medicine at YaleNew HavenUSA
  3. 3.VA-Connecticut Healthcare SystemWest HavenUSA

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