Algorithms for ascertaining keratinocyte carcinomas using health insurance claims and prescription records

Zhang, T.; Lee, Tim K.; Lui, Harvey; Kunimoto, Brian; Han, Christina S; Zhou, Youwen; Kalia, Sunil

doi:10.1111/jdv.15490

Cited by 1 publication

(1 citation statement)

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“…This challenge has been appreciated in other areas of dermatology as well. A 2018 systematic review by Dizon et al found that of 59 studies that used routinely collected health data to identify patients with atopic dermatitis, only two described validation of their methods; furthermore, the differences in methodology were associated with up to a threefold variation in prevalence estimates 7 .…”

Section: Introductionmentioning

confidence: 99%

Validation of medical service insurance claims as a surrogate for ascertaining vitiligo cases

et al. 2022

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Background: The epidemiology of vitiligo, especially its disease burden on the healthcare system, can be assessed indirectly by analyzing health insurance claims data. Validating this approach is integral to ensuring accurate case identi cation and cohort characterization.Objectives: The primary aim of this study was to develop and validate an indirect measure of vitiligo ascertainment using health insurance claims data. These data were used secondarily to identify demographic characteristics, body site involvement, vitiligo subtypes, disease associations, and treatments.Methods: This study assessed the validity of identifying vitiligo from billing claims within a Canadian provincial universal health insurance program, versus vitiligo cases accrued from direct medical chart reviews. Claims-based algorithms combining ICD-9-CM diagnostic code 709 with treatment-speci c data were derived and tested to identify vitiligo patients. This was compared against cases arising from the manual review of medical records of 606 patient with a diagnostic code for "dyschromia" (ICD-9-CM diagnostic code 709) from January 1 to December 31, 2016.Results: Based on the chart reviews, 204 (33.7%) patients were con rmed to have vitiligo. 42 separate claims-based algorithms combining ICD-9-CM diagnostic code 709 with treatment data speci c to vitiligo were modelled and individually tested to evaluate their accuracy for vitiligo ascertainment. One algorithm achieved a sensitivity, speci city, PPV and NPV of 86.8% (95% CI 82.1-91.4), 92.5% (95% CI 90.0-95.1), 85.5% (95% CI 80.7-90.3), and 93.2% (95% CI 90.8-95.7), respectively. There was a 2.2 female to male ratio. The most common medical treatments were tacrolimus (74.5%) and topical corticosteroids (54.3%). Hypertension (24.2%) and hypothyroidism (19.6%) were the predominant co-morbidities associated with vitiligo.Conclusions: Health insurance claims data can be used to indirectly ascertain vitiligo for epidemiologic purposes with relatively high diagnostic performance between 85.5-93.2%.

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Section: Introductionmentioning

confidence: 99%