Identical results, hidden data problems: running CMS's digital quality measures on real hospital data
This study demonstrates that while CMS's digital quality measures for severe hypoglycemia and hyperglycemia can be executed efficiently and consistently on real hospital data using FHIR, the resulting metrics are highly sensitive to underlying data quality issues—such as missing units and admission status classifications—rather than execution engine errors, underscoring the critical need for data readiness testing before mandatory FHIR reporting.