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A population‐based study to develop juvenile arthritis case definitions for administrative health data using model‐based dynamic classification
- Source :
- BMC Medical Research Methodology, BMC Medical Research Methodology, Vol 21, Iss 1, Pp 1-13 (2021)
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- Background Previous research has shown that chronic disease case definitions constructed using population-based administrative health data may have low accuracy for ascertaining cases of episodic diseases such as rheumatoid arthritis, which are characterized by periods of good health followed by periods of illness. No studies have considered a dynamic approach that uses statistical (i.e., probability) models for repeated measures data to classify individuals into disease, non-disease, and indeterminate categories as an alternative to deterministic (i.e., non-probability) methods that use summary data for case ascertainment. The research objectives were to validate a model-based dynamic classification approach for ascertaining cases of juvenile arthritis (JA) from administrative data, and compare its performance with a deterministic approach for case ascertainment. Methods The study cohort was comprised of JA cases and non-JA controls 16 years or younger identified from a pediatric clinical registry in the Canadian province of Manitoba and born between 1980 and 2002. Registry data were linked to hospital records and physician billing claims up to 2018. Longitudinal discriminant analysis (LoDA) models and dynamic classification were applied to annual healthcare utilization measures. The deterministic case definition was based on JA diagnoses in healthcare use data anytime between birth and age 16 years; it required one hospitalization ever or two physician visits. Case definitions based on model-based dynamic classification and deterministic approaches were assessed on sensitivity, specificity, and positive and negative predictive values (PPV, NPV). Mean time to classification was also measured for the former. Results The cohort included 797 individuals; 386 (48.4 %) were JA cases. A model-based dynamic classification approach using an annual measure of any JA-related healthcare contact had sensitivity = 0.70 and PPV = 0.82. Mean classification time was 9.21 years. The deterministic case definition had sensitivity = 0.91 and PPV = 0.92. Conclusions A model-based dynamic classification approach had lower accuracy for ascertaining JA cases than a deterministic approach. However, the dynamic approach required a shorter duration of time to produce a case definition with acceptable PPV. The choice of methods to construct case definitions and their performance may depend on the characteristics of the chronic disease under investigation.
- Subjects :
- Medicine (General)
Canada
Adolescent
Databases, Factual
Epidemiology
Population
Administrative data
Juvenile arthritis
Health Informatics
Cohort Studies
03 medical and health sciences
R5-920
0302 clinical medicine
International Classification of Diseases
Positive predicative value
Statistics
Health care
Humans
Medicine
030212 general & internal medicine
Medical diagnosis
Child
education
030203 arthritis & rheumatology
education.field_of_study
business.industry
Repeated measures design
Classification
Linear discriminant analysis
Discriminant analysis
Arthritis, Juvenile
3. Good health
Hospitalization
Longitudinal analyses
Cohort
Construct (philosophy)
business
Research Article
Subjects
Details
- ISSN :
- 14712288
- Volume :
- 21
- Database :
- OpenAIRE
- Journal :
- BMC Medical Research Methodology
- Accession number :
- edsair.doi.dedup.....2308604c9a152cbdcd0da4356701ea1d