Proposed Statistical Methods for Signal Detection of Adverse Medical Device Events
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PROPOSED STATISTICAL METHODS FOR SIGNAL DETECTION OF ADVERSE MEDICAL DEVICE EVENTS CHANGS. LAO, PHD, LARRYG . KESSLER,ScD, AND THOMAS P.GROSS,MD Office of Surveillance and Biometrics, Center for Devices and Radiological Health, Food and Drug Administration, Rockville, Maryland
This paper proposes several statistical approaches for analyzing spontaneous reports of adverse medical device events. The chi-square statistic is used to detect a sudden increase in reports from pairwise comparison of numbers of reports per month. The Cox-Stuart nonparametric trend test is used to detect a gradual, increasing trend in adverse events reports over time. The negative binomial probability model is also used to assess sudden increases by setting threshold values. In this papel; only numerator data (reports of adverse events), not denominator data (device use), are used. The Box-Jenkins ARIMA time series model failed to fit the observed data successfully due to the extremely irregular distributions, including many zeros, of the observed data. Key Words: Medical device reports; Nonindependence; Overdispersion; Aggregate analysis; Surveillance and monitoring
INTRODUCTION SINCE 1984, THE United States Food and Drug Administration (FDA) has required manufacturers of medical and radiationemitting devices to submit reports of events that reasonably suggest that a medical device has caused or may have caused or contributed to the death, serious injury, or serious illness of a patient, as well as malfunctions whose recurrence would likely result in death, serious injury, or serious illness of a patient. Prior to August 1996, those reports were submitted to the FDA within five (death, serious injury, or serious illness) to 15 days (malfunctions) of the manufacturer’s knowledge of the event. The reports are individually reviewed by clinicians and scientists who as-
sess their clinical and public health significance. Since close to 100,OOO reports were received in 1995, methods needed to be developed to assess those reports in the aggregate. This paper presents three statistical methods which can be used to detect potential signals of adverse events analyzed in the aggregate. In this paper, two medical device products-intravenous (IV)tubes and hip implants-are studied. For the purpose of this exercise, the monthly reported total medical device reports (MDRs), that is, sum of death, injury, or illness, and device malfunction, submitted by manufacturers of these products are analyzed, using the dates received by the FDA.
STATISTICAL ANALYSIS Reprint address: Chang s. Lao, PhD, Office of Surveillance and Biometrics, Center for Devices and Radiological Health, 1350 Piccard Drive, Food and Drug Administration, Rockville, MD 20850.
A Pairwise Monthly Comparison This test is designed to test for any sudden increase in the numbers of adverse events
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