The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics
Chen Huann-Sheng (),
Zeichner Sarah (),
Anderson Robert N. (),
Espey David K. (),
Kim Hyune-Ju () and
Feuer Eric J. ()
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Chen Huann-Sheng: 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.
Feuer Eric J.: Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, U.S.A.
Journal of Official Statistics, 2020, vol. 36, issue 1, 49-62
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.
Keywords: Joinpoint model; international classification of diseases (ICD); trend analysis; coding change; cancer staging system; comparability ratio (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:36:y:2020:i:1:p:49-62:n:3
DOI: 10.2478/jos-2020-0003
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