Literature DB >> 30761662

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

Timothy S Anderson1,2, Edison Xu2,3, Evans Whitaker4, Michael A Steinman2,3.   

Abstract

PURPOSE: Pharmacy dispensing databases are often used to identify patients' medications at a particular time point, for example to measure prescribing quality or the impact of medication use on clinical outcomes. We performed a systematic review of studies that examined methods to assess medications in use at a specific point in time.
METHODS: Comprehensive literature search to identify studies that compared active medications identified using pharmacy databases to medications identified using nonautomated data sources. Two investigators independently reviewed abstracts and full-text material.
RESULTS: Of 496 studies screened, 29 studies evaluating 50 comparisons met inclusion criteria. Twenty-nine comparisons evaluated fixed look-back period approaches, defining active medications as those filled in a specified period prior to the index date (range 84-730 days). Fourteen comparisons evaluated medication-on-hand approaches, defining active medications as those for which the most recent fill provided sufficient supply to last through the study index date. Sensitivity ranged from 48% to 93% for fixed look-back period approaches and 35% to 97% for medication-on-hand approaches. Interpretation of comparative performance of methods was limited by use of different reference sources, target medication classes, and databases across studies. In four studies with head-to-head comparisons of these methods, sensitivity of the medication-on-hand approach was a median of 7% lower than the corresponding fixed look-back approach.
CONCLUSIONS: The reported accuracy of methods for identifying active medications using pharmacy databases differs greatly across studies. More direct comparisons of common approaches are needed to establish the accuracy of methods within and across populations, medication classes, and databases.
© 2019 John Wiley & Sons, Ltd.

Entities:  

Keywords:  Pharmacoepidemiology; databases; drug prescribing; pharmaceutic; quality of care; research methodology; systematic review

Mesh:

Year:  2019        PMID: 30761662      PMCID: PMC7050409          DOI: 10.1002/pds.4706

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  48 in total

1.  Pharmacy data in epidemiological studies: an easy to obtain and reliable tool.

Authors:  Taco B M Monster; Wilbert M T Janssen; Paul E de Jong; Lolkje T W de Jong-van den Berg
Journal:  Pharmacoepidemiol Drug Saf       Date:  2002 Jul-Aug       Impact factor: 2.890

Review 2.  Methods for evaluation of medication adherence and persistence using automated databases.

Authors:  Susan E Andrade; Kristijan H Kahler; Feride Frech; K Arnold Chan
Journal:  Pharmacoepidemiol Drug Saf       Date:  2006-08       Impact factor: 2.890

3.  Agreement and validity of pharmacy data versus self-report for use of osteoporosis medications among chronic glucocorticoid users.

Authors:  Jeffrey R Curtis; Andrew O Westfall; Jeroan Allison; Allison Freeman; Stacey H Kovac; Kenneth G Saag
Journal:  Pharmacoepidemiol Drug Saf       Date:  2006-10       Impact factor: 2.890

4.  Comparison of health insurance claims and patient interviews in assessing drug use: data from the Three-City (3C) Study.

Authors:  Pernelle Noize; Fabienne Bazin; Carole Dufouil; Nathalie Lechevallier-Michel; Marie-Laure Ancelin; Jean-François Dartigues; Christophe Tzourio; Nicholas Moore; Annie Fourrier-Réglat
Journal:  Pharmacoepidemiol Drug Saf       Date:  2009-04       Impact factor: 2.890

5.  Validity of Self-Reported Medication Use Compared With Pharmacy Records in a Cohort of Older Women: Findings From the Women's Health Initiative.

Authors:  Rebecca L Drieling; Andrea Z LaCroix; Shirley A A Beresford; Denise M Boudreau; Charles Kooperberg; Susan R Heckbert
Journal:  Am J Epidemiol       Date:  2016-07-07       Impact factor: 4.897

6.  An exploratory comparison of medication lists at hospital admission with administrative database records.

Authors:  Terri L Warholak; Matthew McCulloch; Alysson Baumgart; Mindy Smith; William Fink; William Fritz
Journal:  J Manag Care Pharm       Date:  2009 Nov-Dec

7.  Information on drug use in the elderly: a comparison of pharmacy, general-practitioner and patient data.

Authors:  E R Heerdink; H G Leufkens; C Koppedraaijer; A Bakker
Journal:  Pharm World Sci       Date:  1995-01-27

8.  Fracture risk from psychotropic medications: a population-based analysis.

Authors:  James M Bolton; Colleen Metge; Lisa Lix; Heather Prior; Jitender Sareen; William D Leslie
Journal:  J Clin Psychopharmacol       Date:  2008-08       Impact factor: 3.153

9.  Completeness of prescription information in US commercial claims databases.

Authors:  Julie C Lauffenburger; Akhila Balasubramanian; Joel F Farley; Cathy W Critchlow; Cynthia D O'Malley; Mary T Roth; Virginia Pate; M Alan Brookhart
Journal:  Pharmacoepidemiol Drug Saf       Date:  2013-05-21       Impact factor: 2.890

10.  Agreement between the pharmacy medication history and patient interview for cardiovascular drugs: the Rotterdam elderly study.

Authors:  S I Sjahid; P D van der Linden; B H Stricker
Journal:  Br J Clin Pharmacol       Date:  1998-06       Impact factor: 4.335

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  5 in total

1.  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

2.  Comparison of measures of medication adherence from pharmacy dispensing and insurer claims data.

Authors:  Constance P Fontanet; Niteesh K Choudhry; Thomas Isaac; Thomas D Sequist; Chandrasekar Gopalakrishnan; Joshua J Gagne; Cynthia A Jackevicius; Michael A Fischer; Daniel H Solomon; Julie C Lauffenburger
Journal:  Health Serv Res       Date:  2021-08-13       Impact factor: 3.734

3.  Validation of self-reported medication use for hypertension, diabetes, and dyslipidemia among employees of large-sized companies in Japan.

Authors:  Kota Fukai; Tomohisa Nagata; Koji Mori; Makoto Ohtani; Kenji Fujimoto; Masako Nagata; Yoshihisa Fujino
Journal:  J Occup Health       Date:  2020-01       Impact factor: 2.708

4.  Intensification of Diabetes Medications at Hospital Discharge and Clinical Outcomes in Older Adults in the Veterans Administration Health System.

Authors:  Timothy S Anderson; Alexandra K Lee; Bocheng Jing; Sei Lee; Shoshana J Herzig; W John Boscardin; Kathy Fung; Anael Rizzo; Michael A Steinman
Journal:  JAMA Netw Open       Date:  2021-10-01

5.  Prevalence of Diabetes Medication Intensifications in Older Adults Discharged From US Veterans Health Administration Hospitals.

Authors:  Timothy S Anderson; Sei Lee; Bocheng Jing; Kathy Fung; Sarah Ngo; Molly Silvestrini; Michael A Steinman
Journal:  JAMA Netw Open       Date:  2020-03-02
  5 in total

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