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The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics

Author

Listed:
  • Chen Huann-Sheng
  • Feuer Eric J.

    (Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, U.S.A.)

  • Zeichner Sarah

    (Division of Geological and Planetary Sciences, California Institute of Technology, 1200 E California Blvd, Pasadena, CA 91125, U.S.A.)

  • Anderson Robert N.

    (Division of Vital Statistics, National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD, U.S.A.)

  • Espey David K.

    (Division of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Albuquerque, NM, U.S.A.)

  • Kim Hyune-Ju

    (Department of Mathematics, Syracuse University, Syracuse, NY, U.S.A.)

Abstract

Analysis of trends in health data collected over time can be affected by instantaneous changes in coding that cause sudden increases/decreases, or “jumps,” in data. Despite these sudden changes, the underlying continuous trends can present valuable information related to the changing risk profile of the population, the introduction of screening, new diagnostic technologies, or other causes. The joinpoint model is a well-established methodology for modeling trends over time using connected linear segments, usually on a logarithmic scale. Joinpoint models that ignore data jumps due to coding changes may produce biased estimates of trends. In this article, we introduce methods to incorporate a sudden discontinuous jump in an otherwise continuous joinpoint model. The size of the jump is either estimated directly (the Joinpoint-Jump model) or estimated using supplementary data (the Joinpoint-Comparability Ratio model). Examples using ICD-9/ICD-10 cause of death coding changes, and coding changes in the staging of cancer illustrate the use of these models.

Suggested Citation

  • Chen Huann-Sheng & Feuer Eric J. & Zeichner Sarah & Anderson Robert N. & Espey David K. & Kim Hyune-Ju, 2020. "The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics," Journal of Official Statistics, Sciendo, vol. 36(1), pages 49-62, March.
    • Handle: RePEc:vrs:offsta:v:36:y:2020:i:1:p:49-62:n:3
    DOI: 10.2478/jos-2020-0003
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    References listed on IDEAS

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    1. P. M. Lerman, 1980. "Fitting Segmented Regression Models by Grid Search," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(1), pages 77-84, March.
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