Which process is used to improve data accuracy in health records?

Data cleansing is the process specifically aimed at improving data accuracy in health records. It involves identifying and correcting errors or inconsistencies in the data. This can include correcting typos, standardizing formats, and removing duplicate records. The main goal of data cleansing is to ensure that the information collected is accurate, complete, and reliable, which is essential for effective patient care and decision-making in healthcare settings.

By focusing on data cleansing, organizations can enhance the overall quality of their health data, which in turn supports better clinical outcomes, effective reporting, and compliance with regulations. Data cleansing plays a crucial role in maintaining the integrity of health records and ensuring that professionals have access to the most accurate and up-to-date information for patient management and treatment decisions.