Literature DB >> 32131818

The effect of the look-back period for estimating incidence using administrative data.

Mira Kim1, Kyung-Hee Chae1, Youn-Jee Chung2, HyeJin Hwang2, MinKyung Lee2, Hyun-Kyung Kim2, Hyun-Hee Cho2, Mee-Ran Kim2, Chai-Young Jung3, Sukil Kim4.   

Abstract

BACKGROUND: The look-back period is needed to define baseline population for estimating incidence. However, short look-back period is known to overestimate incidence of diseases misclassifying prevalent cases to incident cases. The purpose of this study is to evaluate the impact of the various length of look-back period on the observed incidences of uterine leiomyoma, endometriosis and adenomyosis, and to estimate true incidences considering the misclassification errors in the longitudinal administrative data in Korea.
METHODS: A total of 319,608 women between 15 to 54 years of age in 2002 were selected from Korea National Health Insurance Services (KNHIS) cohort database. In order to minimize misclassification bias incurred when applying various length of look-back period, we used 11 years of claim data to estimate the incidence by equally setting the look-back period to 11 years for each year using prediction model. The association between the year of diagnosis and the number of prevalent cases with the misclassification rates by each look-back period was investigated. Based on the findings, prediction models on the proportion of misclassified incident cases were developed using multiple linear regression.
RESULTS: The proportion of misclassified incident cases of uterine leiomyoma, endometriosis and adenomyosis were 32.8, 10.4 and 13.6% respectively for the one-year look-back period in 2003. These numbers decreased to 6.3% in uterine leiomyoma and - 0.8% in both endometriosis and adenomyosis using all available look-back periods (11 years) in 2013.
CONCLUSION: This study demonstrates approaches for estimating incidences considering the different proportion of misclassified cases for various length of look-back period. Although the prediction model used for estimation showed strong R-squared values, follow-up studies are required for validation of the study results.

Entities:  

Keywords:  Adenomyosis; Administrative data; Endometriosis; Incidence; Look-back period; Misclassification; Uterine leiomyoma

Year:  2020        PMID: 32131818     DOI: 10.1186/s12913-020-5016-y

Source DB:  PubMed          Journal:  BMC Health Serv Res        ISSN: 1472-6963            Impact factor:   2.655


  4 in total

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