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

Chen, Huann-Sheng and Zeichner, Sarah and Anderson, Robert N. and Espey, David K. and Kim, Hyune-Ju and Feuer, Eric J. (2020) The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics. Journal of Official Statistics, 36 (1). pp. 49-62. ISSN 2001-7367. PMCID PMC7380682. https://resolver.caltech.edu/CaltechAUTHORS:20200409-091534034

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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.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.2478/jos-2020-0003DOIArticle
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7380682PubMed CentralArticle
ORCID:
AuthorORCID
Zeichner, Sarah0000-0001-8897-7657
Additional Information:© 2020 Statistics Sweden. Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) Received March 2019; Revised September 2019; Accepted November 2019; Published online: 17 Mar 2020. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention or the National Institutes of Health.
Subject Keywords:Joinpoint model; international classification of diseases (ICD); trend analysis; coding change; cancer staging system; comparability ratio
Issue or Number:1
PubMed Central ID:PMC7380682
Record Number:CaltechAUTHORS:20200409-091534034
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200409-091534034
Official Citation:Chen, H., Zeichner, S., Anderson, R. N., Espey, D. K., Kim, H., & Feuer, E. J. (2020). The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics, Journal of Official Statistics, 36(1), 49-62. doi: https://doi.org/10.2478/jos-2020-0003
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:102426
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:09 Apr 2020 16:39
Last Modified:27 Jul 2020 16:56

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