The Data Extraction and Longitudinal Trend Analysis Network Study of Distributed Automated Postmarket Cardiovascular Device Safety Surveillance | Journal Scan
Can postmarket surveillance of medical device safety be enhanced by a prospective automated device safety surveillance tool?
The Data Extraction and Longitudinal Trend Analysis (DELTA) network study was a multicenter, prospective, observational study designed to evaluate the safety of devices used during percutaneous coronary interventions (PCIs). All adult patients undergoing PCI from January 2008 to December 2012 at five participating Massachusetts sites were included. A safety alert was triggered if the cumulative observed adverse event rates for the study device exceeded the upper 95% confidence interval of the event rates of the propensity-matched control cohort. Prespecified sensitivity analyses were developed to validate any identified safety signal.
A total of 23,805 consecutive PCI procedures were evaluated. Two of 24 safety analyses triggered safety alerts. Patients receiving the Perclose vascular closure device experienced an increased risk of minor vascular complications (relative risk, 4.14; p < 0.01) and any vascular complication (relative risk, 2.06; p = 0.01) when compared with propensity-matched patients receiving alternative vascular closure device, a result primarily driven by relatively high event rates at one participating center. Sensitivity analyses based on alternative risk adjustment methods confirmed a pattern of increased rate of complications at one of the five participating sites in their use of the Perclose vascular closure device.
Distributed automated prospective safety surveillance has the potential of providing near real-time assessment of safety risks of newly approved medical devices.
Postmarket medical device safety surveillance is essential for patient safety, yet it is carried out with an inconsistent mix of mandatory and voluntary adverse event reporting systems. The existing systems are compromised by under-reporting and a lack of information on the total number of devices implanted. The current study offers an example of a ‘prospective’ automated surveillance tool allowing for near ‘real-time’ postmarket surveillance with the use of a clinical database. The advantage of this approach is its ability to identify low-frequency safety signals early; however, its robustness depends on an a priori prespecification of sensitivity, subgroup, and secondary endpoint analysis. In addition to potentially revealing safety issues intrinsic to the device in question, this approach may allow monitoring of operator-dependent complications. In a nutshell, the authors present a model for merging post-market safety surveillance with quality improvement initiatives in a single platform, something very desirable in value-based provision of care. A similar surveillance system might have alerted us to the excessive rates of Sprint Fidelis and Riata implantable cardioverter-defibrillator lead failures, before they were implanted in hundreds of thousands of patients.
Keywords: Defibrillators, Implantable, Equipment Safety, Massachusetts, Patient Safety, Percutaneous Coronary Intervention, Risk Adjustment
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