Improve Ovarian Cancer Coding Through Awareness
Understanding this devastating disease is key to accurate ICD-10-CM code selection.
Ovarian cancer ranks fifth in cancer deaths among women in the United States, but is the deadliest of the gynecologic cancers, with a five-year survival rate of 46.5 percent. Because of the location of the ovaries in the body, most ovarian cancers go undiagnosed until the late stages of the disease. When diagnosed in the early stages (stages 1 or 2), the percentage of survival is much higher, at 91.2 percent. The reality is, however, that approximately four out of five ovarian cancer patients are diagnosed with advanced disease that has spread throughout the abdominal cavity. A woman’s lifetime risk for developing ovarian cancer is 1 in 79. Approximately 22,240 new cases will be diagnosed, and 14,070 women will die of ovarian cancer in the United States in 2018.
Ovarian cancer was once believed to be one type of cancer originating in the ovaries. Research has shown there are over 30 different types of ovarian cancer, with some starting in the cells in the far end of the fallopian tubes. Knowing the pathology of a patient’s ovarian cancer is important because it dictates the treatment the patient receives. Understanding the different types of ovarian cancers and what they mean will help you assign ICD-10 diagnosis codes to the patient’s claims.
Types of Ovarian Cancer
The ovaries are made up of different cell types and each can develop into a different type of tumor:
- Epithelial tumors begin in the thin layer of tissue that covers the outside of the ovaries. This is the most common type of tumor.
- Germ cell tumors start in the cells that produce the eggs.
- Stromal tumors originate in ovarian tissue that produces the hormones estrogen and progesterone.
Approximately 85 to 90 percent of malignant ovarian cancers are epithelial tumors. Epithelial tumor cells have unique features when reviewed in the lab that can help classify the cells even further by type:
- Serous carcinomas make up 52 percent of epithelial tumors.
- Clear cell carcinoma make up 6 percent of epithelial tumors.
- Mcinous carcinoma make up 6 percent of epithelial tumors.
- Endometroid carcinoma make up 10 percent of epithelial tumors.
After determining the type of epithelial ovarian carcinomas, pathologists are then able to assign a grade based on how similar the tumor cells look to normal healthy tissue.
- Grade 1 epithelial ovarian carcinomas look more like normal tissue and tend to have a better prognosis.
- Grade 3 epithelial ovarian carcinomas look less like normal tissue and usually have a worse prognosis.
Five percent of ovarian cancers are germ cell carcinoma tumors. These tumors are found mostly in women in their early 20s. There are six kinds of germ cell tumors, but the most common types are teratomas, dysgerminomas, and endodermal sinus tumors. Many germ cell tumors are benign.
An additional 5 percent of ovarian cancers are stromal carcinoma tumors. The two most common types of stromal tumors are granulosa cell tumors and Sertoli Leydig cell tumors. Stromal tumors are often diagnosed in stage 1.
Ovarian Cancer Diagnosis Coding
Per the ICD-10 2018 coding guidelines, “To properly code a neoplasm it is necessary to determine from the record if the neoplasm is benign, in-situ, malignant, or of uncertain histologic behavior.” Although there are many types of ovarian cancer, malignant, in situ, and benign ovarian cancers fall under the following ICD-10 codes.
Malignant ovarian cancer ICD-10 codes, include:
C56 Malignant neoplasm of ovary
C56.1 Malignant neoplasm of right ovary
C56.2 Malignant neoplasm of left ovary
C56.9 Malignant neoplasm of unspecified ovary
The ICD-10 code for ovarian cancer tumors that are in situ, or encapsulated within the organ:
D07.39 Carcinoma in-situ of other female genital organs
Benign ovarian cancer ICD-10 codes, include:
D27 Benign Neoplasm of Ovary
D27.0 Benign neoplasm of right ovary
D27.1 Benign neoplasm of left ovary
D27.9 Benign neoplasm of unspecified ovary
Ovarian Cysts Should Be Monitored
Ovarian cysts, although not cancer, should be monitored closely, particularly on females who are not ovulating. Cysts should cause concern if they do not go away in a few months. Although most cysts are benign, some can become cancerous.
The following ICD-10 codes are used when a patient has an ovarian cyst:
N83.0 Follicular cyst of ovary
N83.00 Follicular cyst of ovary, unspecified side
N83.01 Follicular cyst of right ovary
N83.02 Follicular cyst of left ovary
N83.1 Corpus luteum cyst
N83.10 Corpus luteum cyst of ovary, unspecified side
N83.11 Corpus luteum cyst of right ovary
N83.12 Corpus luteum cyst of left ovary
N83.2 Other and unspecified ovarian cysts
N83.201 Unspecified ovarian cyst, right side
N83.202 Unspecified ovarian cyst, left side
N83.209 Unspecified ovarian cyst, unspecified side
N83.29 Other ovarian cysts
N83.291 Other ovarian cyst, right side
N83.292 Other ovarian cyst, left side
N83.299 Other ovarian cyst, unspecified side
Although ovarian cancer can be hard to detect and is often treated in the later stages, there are signs and symptoms that can be recognized by patients and their families. An easy way to identify and remember the symptoms is with the acronym BEAT:
- Bloating that is persistent
- Eating less, feeling fuller
- Abdominal and/or back pain
- Trouble with your bladder and bowels
If you have these signs and symptoms, make an appointment with your gynecologist. Help spread awareness this month by sharing BEAT!
To learn more about ovarian cancer coding on the AAPC Knowledge Center, read these articles:
American Cancer Society 2018: www.cancer.org/cancer/ovarian-cancer/about/what-is-ovarian-cancer.html
Norma Leah Ovarian Cancer Initiative: http://normaleah.org/
Ovarian Research Fund Alliance (OCRFA): https://ocrfa.org/patients/about-ovarian-cancer/types-ovarian-cancer/
Latest posts by Bridget Toomey (see all)
- Know the Truth About a Technology Takeover in Healthcare - December 1, 2019
- Finding Revenue Cycle Inefficiencies Is a Team Effort - February 5, 2019
- Improve Ovarian Cancer Coding Through Awareness - September 11, 2018