Casefinding Audits and Process Improvement

Casefinding audits are  randomly selected by the central registry involving independent re-ascertainment of tumor records, usually in a sample of facilities and, within each facility, a sample of time periods. Tumor records identified during the audit are enumerated and matched against the central registry’s files. Unmatched cases are followed back to verify their reportability, and the percent of cases actually missed that should have been reported is calculated [6External Website Policy].

Cancer registry staff should perform quality control at least semi-annually to prevent underreporting their cancer cases and to remain compliant with state reporting. Table 2 shows a sample casefinding completeness log that can be used to ensure complete reporting.

Table 2: Casefinding Completeness Log by Month and Year of Diagnosis
Month Number of cases, 2017 Number of cases, 2018
January 60 85
February 50 60
March 65 72
April 58 50
May 52 61
June 61 64
July 45 57
August 32 62
September 65 72
October 62 78
November 70 80
December 40 62

In Table 2, the decrease in cases in July and August 2017 might correlate with a primary physician taking an extended vacation. The decrease in cases for December 2017 and the increase in January 2018 may be due to a specialty group of physicians leaving the institution in December and the arrival of a new oncology group in January. Fluctuations like those shown in the table should be reviewed and justified when differences are identified to ensure that casefinding is complete. The easiest way to accomplish this task is to request the disease index, a computerize listing of patients discharged from the hospital, organized by disease or diagnosis code. The disease index is usually prepared by the Health Information Management Department.

Process improvement for casefinding audits ensure compliance with new reporting guidelines and reviews sites which may propose a higher risk of casefinding and/or coding errors. Central Cancer Registries has the responsibility of periodically auditing all facilities within their region.

The Future of Casefinding

To improve overall efficiency and quality of data abstraction for cancer registries, technologies such as Natural Language Processing (NLP) can be used to enhance casefinding. NLP is the application of linguistics and computer science to extract and interpret linguistic information from health care documents (e.g., pathology reports, radiology reports, treatment summaries, clinical notes) that are created in electronic medical record systems [7, 8].

SEER*Educate Casefinding Tests

SEER*Educate is a comprehensive training platform tailored specifically for cancer registry professionals to improve technical skills through applied testing on the latest coding guidelines and concepts. It includes hundreds of practice case scenarios provided for coding over 60 data items with detailed rationales.

Refer to https://educate.fredhutch.orgExternal Website Policy.

Updated: December 12, 2023