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Detecting Secular Trends in Clinical Treatment through Temporal Analysis

  • Systems-Level Quality Improvement
  • Published:
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Abstract

Medical treatments change over time for multiple reasons, including introduction of new treatments, availability of new scientific evidence, change in institutional guidelines, and market efforts by pharmaceutical and medical device companies. Monitoring and analyzing these secular trends will also inform the evaluation of evidence based practice as well as outcome research. Using a large national clinical dataset from the United States Veterans Health Administration (VHA), we measured the change in prevalence of all diseases, medications, and procedures by year from 2001 to 2014. To assess statistical significance, we used a generalized linear model. Among the large number of changes that were observed, multiple significant changes were related to diabetes mellitus type II (DM2). Prevalence of DM2 in the VHA increased after 2001 but plateaued by 2008; blood sugar testing by glycosylated hemoglobin increased consistently while glucose testing decreased; and the trend of insulin and metformin use was consistent with the trend in DM2 prevalence, while glyburide and rosiglitazone use dropped sharply.

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Funding

This study was funded by

• HIR 08–374 VA Health Services Research and Development Consortium for Healthcare Informatics Research (CHIR)

• HIR 08–204 Veterans Affairs Health Services Research & Development, VA Informatics and Computing Infrastructure (VINCI) aka Center for Scientific Computing

• CRE 12–315 Veterans Affairs Health Services Research & Development, CREATE: A VHA NLP Software Ecosystem for Collaborative Development and Integration

• UL1TR001876 and KL2TR001877 NIH National Center for Advancing Translational Sciences, Clinical and Translational Science Institute at Children's National (CTSI-CN), National Institutes of Health (NIH) Clinical and Translational Science Award (CTSA)

Author information

Authors and Affiliations

  1. Washington DC Veterans Affairs Medical Center, 50 Irving St NW, Washington, DC, 20422, USA

    Douglas Redd & Qing Zeng-Treitler

  2. Biomedical Informatics Center, George Washington University School of Medicine and Health Sciences, 800 22nd St NW, Washington, DC, 20052, USA

    Douglas Redd, Yijun Shao, Yan Cheng & Qing Zeng-Treitler

  3. Veterans Affairs Salt Lake City Health Care System, 500 Foothill Dr, Salt Lake City, UT, 84148, USA

    Yijun Shao & Yan Cheng

Authors
  1. Douglas Redd
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  2. Yijun Shao
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  3. Yan Cheng
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  4. Qing Zeng-Treitler
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Corresponding author

Correspondence to Qing Zeng-Treitler.

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The authors declare no conflict of interests.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Redd, D., Shao, Y., Cheng, Y. et al. Detecting Secular Trends in Clinical Treatment through Temporal Analysis. J Med Syst 43, 74 (2019). https://doi.org/10.1007/s10916-019-1173-0

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  • DOI: https://doi.org/10.1007/s10916-019-1173-0

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