Melanocytic nevi of right upper eyelid, including canthus
ICD-10 D22.111 is a billable code used to indicate a diagnosis of melanocytic nevi of right upper eyelid, including canthus.
Melanocytic nevi, commonly referred to as moles, are benign tumors of melanocytes, the cells responsible for producing melanin in the skin. When located on the right upper eyelid, including the canthus, these nevi can present as pigmented lesions that may vary in size, shape, and color. While typically asymptomatic, they can occasionally cause cosmetic concerns or irritation, especially if they are located in areas subject to friction or exposure. Diagnosis is primarily clinical, based on visual inspection, although dermatoscopic examination may be utilized for more detailed assessment. Management usually involves monitoring for changes in size, shape, or color, which could indicate malignant transformation. Surgical excision may be considered for symptomatic lesions or for cosmetic reasons. Follow-up care is essential to ensure that any changes in the nevus are promptly evaluated, and patients should be educated about the signs of potential malignancy, such as asymmetry, irregular borders, color variation, and diameter greater than 6 mm.
Detailed description of the nevus, including size, color, and any changes over time.
Routine skin examinations, excision of symptomatic nevi, and monitoring of changes.
Ensure accurate documentation of the nevus characteristics to support coding.
Assessment of visual impact and any associated symptoms.
Evaluation of eyelid lesions, management of cosmetic concerns, and potential surgical intervention.
Document any functional impairment or cosmetic concerns related to the nevus.
Used when excising a symptomatic nevus on the eyelid.
Document the size, location, and reason for excision.
Ensure that the excision is medically necessary and well-documented.
D22.111 refers to melanocytic nevi of the right upper eyelid, while D22.112 refers to those on the left upper eyelid. The distinction is important for accurate coding based on the lesion's location.
