An algorithm for the identification of heparin-induced thrombocytopenia using a medical information database

Abstract

We developed a novel, high-PPV detection algorithm for HIT and identified longer-term treatment with UFH as a risk factor for HIT. Our results support the utility of MIDs for improving pharmacovigilance.

Development of a novel algorithm for detecting glucocorticoid-induced diabetes mellitus using a medical information database

“…On the other hand, in the last 10 years, medical information databases (MIDs) or electronic medical records (EMRs), based on hospital information systems, have been widely used in many countries for PMS studies to identify adverse events. Detection algorithms for adverse reactions using MIDs have been developed by many researchers . Haerian et al .…”

“…developed an automated method to accurately detect two serious adverse events, rhabdomyolysis and agranulocytosis from EMR data. We previously developed a detection algorithm for statin‐induced myopathy, heparin‐induced thrombocytopenia and drug‐induced liver injury . Hence, MIDs are becoming an important tool for pharmacovigilance, and the development of accurate methods for detecting adverse reactions using MIDs is important in PMS, particularly for often overlooked adverse reactions such as GIDM.…”

Validity of diagnostic codes and laboratory measurements to identify patients with idiopathic acute liver injury in a hospital database

“…Search algorithms are more and more used for this purpose and can be highly effective in detecting patients. Such algorithms can be based on diagnostic codes which are generally recorded at hospital discharge using the International Classification of Diseases (ICD). Accuracy and completeness of the diagnostic codes within databases are crucial but depend on multiple factors, such as coding quality and information in the patient records .…”