Validity of Denture Usage Definitions Based on Claims Data in Japanese Older Adults.

IF 2 Q2 DENTISTRY, ORAL SURGERY & MEDICINE
A Kinugawa, Y Tamada, T Kusama, M Hoshi-Harada, S Ono, F Oda, M Maeda, N Yoda, K Osaka, H Fukuda, K Takeuchi
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引用次数: 0

Abstract

Background: Administrative claims data are increasingly used in oral health research, but their validity for identifying denture use has not been established.

Objective: To evaluate the accuracy of algorithms based on dental claims codes for identifying denture users, dentist-reported oral health screening records were used as the reference standard.

Methods: We analyzed data from 4,053 adults aged ≥65 y in the Longevity Improvement and Fair Evidence (LIFE) Study in Japan. Twelve algorithms incorporating 56 denture-related diagnosis and procedure codes were developed from claims in the 12 mo preceding the screening. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Sensitivity analyses used a 6-mo claims window. A post hoc bias analysis was also performed.

Results: During screening, 59.9% of the participants were classified as denture users. Algorithms based solely on diagnosis codes showed very high specificity (98.3%-100%) but low sensitivity (1.4%-20.8%). Among the procedure-based definitions, oral rehabilitation codes (algorithm f; denture adjustment or instruction) had the highest sensitivity (63.6%). The combined algorithm using both diagnosis and procedure codes (algorithm C) achieved the best balance, with 65.3% sensitivity, 96.6% specificity, 96.6% PPV, and 65.1% NPV. Similar findings were observed using the 6-mo claims data. Bias analysis indicated that the risks for denture use could be underestimated by 26% to 59%, with algorithm C showing the least bias.

Conclusions: Denture use can be identified from dental claims data with moderate accuracy. Algorithms combining denture-related diagnosis and procedure codes or using oral rehabilitation codes provide practical definitions for research on oral and systemic health outcomes.Knowledge Transfer Statement:The result of this validated study can be identified as denture use from dental claims with moderate accuracy. In combination with validated denture use and the number of remaining teeth, it can expand opportunities to assess oral health status and its relationship with systemic health outcomes in large-scale epidemiologic studies using claims data.

基于理赔数据的日本老年人义齿使用定义的有效性。
背景:行政索赔数据越来越多地用于口腔健康研究,但其在识别义齿使用方面的有效性尚未建立。目的:以牙科报告的口腔健康筛查记录为参考标准,评估基于牙科索赔代码的算法识别义齿使用者的准确性。方法:我们分析了日本寿命改善和公平证据(LIFE)研究中4053名年龄≥65岁的成年人的数据。从筛查前12个月的索赔中开发了包含56个假牙相关诊断和程序代码的12种算法。计算敏感性、特异性、阳性预测值(PPV)和阴性预测值(NPV)。敏感性分析采用6个月的索赔窗口。还进行了事后偏倚分析。结果:在筛查过程中,59.9%的参与者被归类为义齿使用者。仅基于诊断代码的算法具有很高的特异性(98.3% ~ 100%),但灵敏度较低(1.4% ~ 20.8%)。在基于程序的定义中,口腔康复代码(算法f;义齿调整或指导)的敏感性最高(63.6%)。同时使用诊断和程序代码的组合算法(算法C)达到最佳平衡,敏感性为65.3%,特异性为96.6%,PPV为96.6%,NPV为65.1%。使用6个月的索赔数据观察到类似的发现。偏倚分析表明,假牙使用风险可能被低估26% ~ 59%,其中算法C的偏倚最小。结论:义齿使用可以从牙科索赔数据中识别,准确度中等。结合假牙相关诊断和程序代码或使用口腔康复代码的算法为口腔和全身健康结果的研究提供了实用的定义。知识转移声明:这项验证研究的结果可以从牙科索赔中确定为假牙使用,准确度中等。结合经过验证的假牙使用和剩余牙齿的数量,它可以在使用索赔数据的大规模流行病学研究中扩大评估口腔健康状况及其与全身健康结果的关系的机会。
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来源期刊
JDR Clinical & Translational Research
JDR Clinical & Translational Research DENTISTRY, ORAL SURGERY & MEDICINE-
CiteScore
6.20
自引率
6.70%
发文量
45
期刊介绍: JDR Clinical & Translational Research seeks to publish the highest quality research articles on clinical and translational research including all of the dental specialties and implantology. Examples include behavioral sciences, cariology, oral & pharyngeal cancer, disease diagnostics, evidence based health care delivery, human genetics, health services research, periodontal diseases, oral medicine, radiology, and pathology. The JDR Clinical & Translational Research expands on its research content by including high-impact health care and global oral health policy statements and systematic reviews of clinical concepts affecting clinical practice. Unique to the JDR Clinical & Translational Research are advances in clinical and translational medicine articles created to focus on research with an immediate potential to affect clinical therapy outcomes.
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