Ensuring data accurately reflects what it measures is crucial, as assumptions can lead to misleading conclusions. In the context of Australian healthcare, data quality is high due to stringent auditing processes tied to funding. However, challenges arise with de-identified datasets, where probabilistic matching can result in errors, such as patients being recorded as deceased multiple times.
