Journal of the American Medical Informatics Association · 2010 · 31 citations · 24 references
ComputingBiomedical InformaticsHealth InformaticsElectronic Health RecordsHealth Information SystemsPatient SafetyAdverse Drug Event DetectionAdverse Drug Event ReportingAdverse Event Data ManagementAdverse Event ReportingMedication Error Reporting SystemsAdministrative Data SourcesClinical Quality MeasuresElectronic Health Record DataElectronic Health Record Data AnalysisElectronic Medical RecordsElectronic Medication Reporting SystemsElectronic Record SystemsPediatric Electronic Health Records
OBJECTIVE: To examine the impact of billing and clinical data extracted from an electronic medical record system on the calculation of an adverse drug event (ADE) quality measure approved for use in The Joint Commission's ORYX program, a mandatory national hospital quality reporting system. DESIGN: The Child Health Corporation of America's "Use of Rescue Agents-ADE Trigger" quality measure uses medication billing data contained in the Pediatric Health Information Systems (PHIS) data warehouse to create The Joint Commission-approved quality measure. Using a similar query, we calculated the quality measure using PHIS plus four data sources extracted from our electronic medical record (EMR) system: medications charged, medication orders placed, medication orders with associated charges (orders charged), and medications administered. MEASUREMENTS: Inclusion and exclusion criteria were identical for all queries. Denominators and numerators were calculated using the five data sets. The reported quality measure is the ADE rate (numerator/denominator). RESULTS: Significant differences in denominators, numerators, and rates were calculated from different data sources within a single institution's EMR. Differences were due to both common clinical practices that may be similar across institutions and unique workflow practices not likely to be present at any other institution. The magnitude of the differences would significantly alter the national comparative ranking of our institution compared to other PHIS institutions. CONCLUSIONS: More detailed clinical information may result in quality measures that are not comparable across institutions due institution-specific workflow, differences that are exposed using EMR-derived data.
24
Measuring Diagnoses: ICD Code Accuracy
Kimberly J. O’Malley, Karon F. Cook, Matt D. Price et al. · Health Services Research · 2005 · 1.1K citations · Full text
Health Professions, Biomedical Informatics, Clinical Classification Systems +16
Computerized Surveillance of Adverse Drug Events in Hospital Patients
David C. Classen · JAMA · 1991 · 644 citations · Full text