Quality performance measures based on data in electronic health records are still in their infancy and have yet to tap many of the unique features of EHRs, according to a new study in the International Journal for Quality in Health Care. The study, which was re-published in Medscape, provides a conceptual framework for defining levels of electronic quality measures, or e-QMs.
The study proposes the following five-level typology for defining e-QMs:
–Translated e-QMs. Measures designed for use with paper records, such as whether patients with diabetes have received HbA1c tests. These measures can use claims data or information from chart abstraction, as well as EHRs.
–Health IT-assisted. Measures that could be derived from non-EHR data sources, such as blood pressure or body mass index information, but that require EHRs for reporting on 100% of a patient population.
–Health IT-enabled. Metrics that take advantage of an EHR’s features, such as the percentage of abnormal test results read and acted upon by a clinician within 24 hours of receipt, or the percentage of relevant clinical alerts that are acted upon.
–Health IT system management. Measures of how providers use health IT systems, such as the percentage of all prescriptions ordered via electronic prescribing.
–E-iatrogenesis. Measures of patient harm caused at least in part by the health IT system, such as the percentage of patients for whom the wrong drug was ordered because of an error in an e-prescribing system, or the percentage of critical lab findings that did not lead to patient notification.
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