Coverage and data quality for the Lung Cancer Registry

Degree of coverage and completeness

All patients with tracheal cancer (ICD-10, C33) and lungs and bronchi (ICD-10, C34) in Norway should be included in the registry. Patients with the diagnosis lymphoma, malignant melanoma, sarcoma or mesothelioma in the specified locations are excluded from the registry.

All hospitals that diagnose and/or treat lung cancer are affiliated with the Lung Cancer Registry. All results on tissue samples are reported from the pathology departments of the Cancer Registry. The Cancer Registry's basic registry contains information on 99.2 per cent of all lung cancer patients.

The coverage ratio (for reporting on investigations) for 2021 is 91.3 percent. The national average for surgical report coverage increased from 67.8 percent in 2016 to 100 per cent in 2021, and remains at 100 per cent in 2022.

It is important for the Norwegian Lung Cancer Registry that the positive trend of increased interest in reporting among hospital management and health personnel continues. There are several hospitals that achieve a reporting rate of 100 per cent this year, but not all hospitals still have good enough routines for following up other reporting to the Cancer Registry. In order to follow up reporting further, the Cancer Registry of Norway has established its own team that will work continuously with reporting.

Data quality

Quality assurance of data is done as an integral part of the coding and registration process. In addition, the following examples help to ensure data quality in the Cancer Registry:

• Several independent sources report information
• The information is reported at several points in the course of the disease
• The employees have unique expertise in coding cancer cases according to the Cancer Registry's own code book and international coding systems
• IT systems have rules and barriers for illogical combinations, incorrect information and more
• The Cancer Registry of Norway conducts analyses and control runs that reveal inconsistency in the data
• Data extraction for researchers makes it possible to check a smaller data set of information that can reveal individual errors (e.g. incorrect entry of hospital codes) or systematic differences due to different interpretations of coding systems and rules