Which type of analysis best helps identify patterns of undercoding and upcoding among physicians?

The correct choice for identifying patterns of undercoding and upcoding among physicians is aggregate analysis. This type of analysis combines data from multiple sources or entities to provide a comprehensive overview of coding practices. By looking at the aggregated data, auditors can effectively identify trends and discrepancies across different practices or providers, which can highlight patterns of undercoding and upcoding that may not be apparent in isolated cases.

Aggregate analysis allows for comparisons between similar types of practices, specialties, or timeframes, making it easier to spot anomalies and deviations from expected coding behaviors. This can be particularly useful when assessing whether physicians are consistently coding at a level that accurately reflects the complexity of the services provided or if there are unusual spikes in coding that could indicate upcoding.

In contrast, comparative analysis focuses more on comparing specific entities against each other without necessarily aggregating data from multiple sources, which may not fully reveal the broader patterns of coding inconsistencies. Trend analysis monitors data over time but may not provide a comprehensive view needed for immediate identification of upcoding or undercoding issues. Lastly, quantitative analysis deals primarily with numerical data but may not contextualize that data into meaningful patterns regarding coding practices.