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Validity of Lichen Planus and Lichen Planopilaris Case Identification Using Diagnostic Codes from a Clinical Database
Natalia Pelet Del Toro1, Andrew Strunk1, Amit Garg1
1Department of Dermatology, Hofstra Northwell School of Medicine, New Hyde Park, New York, USA.
Background:
Case identification strategies to conduct population-based studies have not been developed for lichen planus (LP) or lichen planopilaris (LPP).
Objectives:
The aim of this study was to assess the validity of using diagnostic codes to establish both a cutaneous (non-oral) LP cohort and an LPP cohort from a large clinical database.
Methods:
A retrospective chart review was performed to determine whether patients with ICD-9 or ICD-10 codes for LP and ICD-10 codes for LPP are confirmed cases of LP and LPP. Validation samples were used to estimate the positive predictive value (PPV) of three case definitions any LP, non-oral LP, and LPP defined as: at least one code by any physician, at least two codes by any physician, and at least one code by a dermatologist.
Results:
Among the 199 reviewed LP charts, 166 and 123 were confirmed cases of any LP and non-oral LP, respectively. The PPVs for any LP were: 83.4% (166/199) for one code by any physician, 84.6% (77/91) for two codes by any physician, and 95.1% (97/102) for one code by a dermatologist. The PPVs for non-oral LP were: 61.8% (123/199) for one code by any physician, 70.3% (64/91) for two diagnoses by any physician, and 86.3% (88/102) for one diagnosis by a dermatologist. Of the 139 patients with at least one code for LPP, 122 were confirmed cases of LPP. The case definition for one LPP code applied by any physician had a PPV of 87.8% (122/139) to identify a true case of LPP, whereas two diagnoses by any physician had a PPV of 96.2% (76/79) and a diagnosis by a dermatologist had a PPV of 93% (107/115).
Conclusions:
Diagnosis codes for LP and LPP, restricted by the diagnosing physician's specialty, may be used to accurately identify case cohorts of overall LP, non-oral LP, or LPP in large clinical databases.
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