Missing data reporting in clinical pharmacy research.

Purpose This study aimed to document the ways by which missing data were handled in clinical pharmacy research to provide an insight into the amount of attention paid to the importance of missing data in this field of research. Methods Our cross-sectional descriptive report evaluated 10 journals aff...

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Published in:American Journal of Health-System Pharmacy Vol. 76; no. 24; pp. 2048 - 2053
Main Authors: Narayan, Sujita W, Ho, Kar Yu, Penm, Jonathan, Mintzes, Barbara, Mirzaei, Ardalan, Schneider, Carl, Patanwala, Asad E
Format: research tables/charts Journal Article
Published: Oxford University Press / USA 12/15/2019
Online Access:View this record in EBSCOhost
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      dt: 12/15/2019
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      pub: Oxford University Press / USA
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        10.1093/ajhp/zxz245
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        atl: Missing data reporting in clinical pharmacy research.
      aug:
        au:
          Narayan, Sujita W
          Ho, Kar Yu
          Penm, Jonathan
          Mintzes, Barbara
          Mirzaei, Ardalan
          Schneider, Carl
          Patanwala, Asad E
        affil: School of Pharmacy, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
      sug:
        subj:
          Data Management
          Documentation
          Pharmacy Service
          Research, Medical
          Human
          Cross Sectional Studies
          Descriptive Research
          Professional Organizations
          United States
          Canada
          United Kingdom
          Australia
      ab: Purpose This study aimed to document the ways by which missing data were handled in clinical pharmacy research to provide an insight into the amount of attention paid to the importance of missing data in this field of research. Methods Our cross-sectional descriptive report evaluated 10 journals affiliated with pharmacy organizations in the United States, Canada, the United Kingdom, and Australia. Randomized controlled trials, cohort studies, case-control studies, and cross-sectional studies published in 2018 were included. The primary outcome measure was the proportion of studies that reported the handling of missing data in their methods or results. Results A total of 178 studies were included in the analysis. Of these, 19.7% (n = 35) mentioned missing data either in their methods (3.4%, n = 6), results (15.2%, n = 27), or in both sections (1.1%, n = 2). Only 4.5% (n = 8) of the studies mentioned how they handled missing data, the most common method being multiple imputation (n = 3), followed by indicator (n = 2), complete case analysis (n = 2), and simple imputation (n = 1). One study using multiple imputation and both studies using an indicator method also combined other strategies to account for missing data. One study only used complete case analysis for subgroup analysis, and the other study only used this method if a specific baseline variable was missing. Conclusions Very few studies in clinical pharmacy literature report any handling of missing data. This has the potential to lead to biased results. We advocate that researchers should report how missing data were handled to increase the transparency of findings and minimize bias.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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