Literature DB >> 12954474

Development of a computer algorithm for defining an active drug list using an automated pharmacy database.

Brian C Lund1, Elizabeth A Chrischilles, Barry L Carter, Michael E Ernst, Paul J Perry.   

Abstract

BACKGROUND AND
OBJECTIVE: Increasingly, pharmacy databases are being used to assist in evaluating the appropriateness of drug therapy. Such determinations often require the creation of a drug regimen at a particular point in time. The objective of this study was to develop a computer algorithm for defining a cross-sectional active drug list.
METHODS: Electronic pharmacy data were obtained as part of the Iowa Medicaid Pharmaceutical Case Management Program. The active drug lists generated by the computer algorithm were compared with active drug lists generated by independent pharmacist review of the pharmacy refill data.
RESULTS: In a sample of 25 patients who received 379 potentially active medications, the interrater reliability between pharmacist reviewers was excellent (kappa=0.94). In a second sample of 100 patients who received 1476 potentially active medications, the computer algorithm had a sensitivity of 93.8% and specificity of 91.7%, using pharmacist review as the comparison standard.
CONCLUSION: The computer algorithm was found to be a valid method of processing electronic pharmacy data to yield a characterization of drug exposure at a point in time. The potential benefits and limitations of using this approach are discussed.

Entities:  

Mesh:

Year:  2003        PMID: 12954474     DOI: 10.1016/s0895-4356(03)00140-9

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  8 in total

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Authors:  Michael A Steinman; Marcelo Low; Ran D Balicer; Efrat Shadmi
Journal:  J Gen Intern Med       Date:  2017-05-03       Impact factor: 5.128

2.  Comparison of Pharmacy Database Methods for Determining Prevalent Chronic Medication Use.

Authors:  Timothy S Anderson; Bocheng Jing; Charlie M Wray; Sarah Ngo; Edison Xu; Kathy Fung; Michael A Steinman
Journal:  Med Care       Date:  2019-10       Impact factor: 2.983

3.  A systematic review of methods for determining cross-sectional active medications using pharmacy databases.

Authors:  Timothy S Anderson; Edison Xu; Evans Whitaker; Michael A Steinman
Journal:  Pharmacoepidemiol Drug Saf       Date:  2019-02-13       Impact factor: 2.890

4.  Reliability of medicaid claims versus medical record data: in a cost analysis of palivizumab.

Authors:  Julie Jacobson Vann; John Feaganes; Steven Wegner
Journal:  Pharmacoeconomics       Date:  2007       Impact factor: 4.981

5.  Regional differences in prescribing quality among elder veterans and the impact of rural residence.

Authors:  Brian C Lund; Mary E Charlton; Michael A Steinman; Peter J Kaboli
Journal:  J Rural Health       Date:  2012-08-27       Impact factor: 4.333

6.  Renewed interest in chlorthalidone: evidence from the Veterans Health Administration.

Authors:  Michael E Ernst; Brian C Lund
Journal:  J Clin Hypertens (Greenwich)       Date:  2010-08-30       Impact factor: 3.738

7.  Application of a framework for determining number of drugs.

Authors:  Amber M Goedken; Brian C Lund; Elizabeth A Cook; Mary C Schroeder; John M Brooks
Journal:  BMC Res Notes       Date:  2016-05-13

8.  Impact of a nurse-based intervention on medication outcomes in vulnerable older adults.

Authors:  Michael A Steinman; Marcelo Low; Ran D Balicer; Efrat Shadmi
Journal:  BMC Geriatr       Date:  2018-09-06       Impact factor: 3.921

  8 in total

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