A blog about what is new (and old) in the world of active implantable medical devices 

Facebook Twitter Gplus Flickr LinkedIn YouTube RSS
Home Engineering & OEM Services Reliability Analysis Reliability Analysis of Active Implantable Medical Devices

Reliability Analysis of Active Implantable Medical Devices

Relibility analysis bathtub curveWe conduct reliability analyses for our implantable devices on a continued basis.  I’ve spent the last few days readying the data for this period’s analysis, and thought that  a short primer on how this is actually done would be of interest to fellow engineers who may need it at some point.

You surely have heard of MTBF = Mean Time Between Failures.  This is a key reliability metric.  However, since our implantable devices are single-use, the first failure is the final failure, so MTTF = Mean Time To Failure.  As such, for a device with no possibility of repair (e.g. implantables, satellites), MTBF=MTTF.

From Relex (the makers of some of the reliability software that I use):

“MTBF (mean time between failures) is the expected time between two successive failures of a system. Therefore, MTBF is a key reliability metric for systems that can be repaired or restored. MTTF (mean time to failure) is the expected time to failure of a system. Non-repairable systems can fail only once. Therefore, for a non-repairable system, MTTF is equivalent to the mean of its failure time distribution. Repairable systems can fail several times.”

I predict MTTF using a software tool called “Weibull++ Life Data Analysis” by ReliaSoft.  To do so, the active life of the implanted AIMDs has to be arranged on a spreadsheet such that Weibull++ can know that  some devices have failed, and assume that all others have not failed yet (but will one day fail).  The latter are classified as “suspended.

The way to do it is to first place all the failure lives in one column, and identify the failures and suspensions (state) in the adjacent column to its left.  The data are then sorted according to failure life and fed to  Weibull++’s analysis engine.  The failure rate and MTTF can then be estimated for any given confidence level.

This periodic analysis allows us to demonstrate that our devices are reliable, and makes it possible to detect any changes in specified reliability that could be indicative of changes in the performance of manufacturing processes, as well as make predictions about the performance of our implantables during their useful life and warranty period.

A good reference point for an AIMD manufacturer is to compare these estimated failure rates to the typical failure range seen in the pacemaker/ICD industry (for IPGs with a typical mission life <7 years):

William H. Maisel, MD, MPH; Megan Moynahan, MS; Bram D. Zuckerman, MD; Thomas P. Gross, MD, MPH; Oscar H. Tovar, MD; Donna-Bea Tillman, PhD, MPA; Daniel B. Schultz, MD, Pacemaker and ICD Generator Malfunctions – Analysis of Food and Drug Administration Annual Reports, JAMA. 2006;295:1901-1906.

“Context: Pacemakers and implantable cardioverter-defibrillators (ICDs) are complex medical devices proven to reduce mortality in specific high-risk patient populations. It is not known if increasing device complexity is associated with decreased reliability.

Objectives: To analyze postapproval annual reports submitted to the US Food and Drug Administration (FDA) by manufacturers of pacemakers and ICDs to determine the reported number and rate of pacemaker and ICD malfunctions and to assess trends in device performance.

Design and Setting: Pacemaker and ICD annual reports submitted to the FDA for the years 1990-2002 were reviewed. A pacemaker or ICD generator was defined as having malfunctioned if it was explanted due to an observed malfunction, returned to the manufacturer, and confirmed by the manufacturer to be functioning inappropriately. Leads and biventricular devices were not included in the study. Deaths were attributed to device malfunction only if they were witnessed, the malfunction immediately led to the death, and the malfunction was confirmed by the manufacturer.

Main Outcome Measures: Number of implanted pacemaker and ICD generators; number of reported malfunctions; and annual malfunction replacement rates. Generator malfunction replacement rates were defined as the annual number of replacements due to confirmed malfunction divided by the annual number of implants.

Results: During the study period, 2.25 million pacemakers and 415 780 ICDs were implanted in the United States. Overall, 17 323 devices (8834 pacemakers and 8489 ICDs) were explanted due to confirmed malfunction. Battery/capacitor abnormalities (4085 malfunctions [23.6%]) and electrical issues (4708 malfunctions [27.1%]) accounted for half of the total device failures. The annual pacemaker malfunction replacement rate per 1000 implants decreased significantly during the study, from a peak of 9.0 in 1993 to a low of 1.4 in 2002 (P = .006 for trend). In contrast, the ICD malfunction replacement rate per 1000 implants, after decreasing from 38.6 in 1993 to 7.9 in 1996, increased markedly during the latter half of the study, peaking in 2001 at 36.4 (P = .04 for trend). More than half of the reported ICD malfunctions occurred in the last 3 years of the study. Overall, the annual ICD malfunction replacement rate was significantly higher than the pacemaker malfunction replacement rate (mean [SD], 20.7 [11.6] vs 4.6 [2.2] replacements per 1000 implants; P<.001; rate ratio, 5.9 [95% confidence interval, 2.7-9.1]). Sixty-one deaths (30 pacemaker patients, 31 ICD patients) were attributable to device malfunction.

Conclusions: This study demonstrates that thousands of patients have been affected by pacemaker and ICD malfunctions, the pacemaker malfunction replacement rate has decreased, the ICD malfunction replacement rate increased during the latter half of the study, and the ICD malfunction replacement rate is significantly higher than that for pacemakers. Although pacemakers and ICDs are important life-sustaining devices that have saved many lives, careful monitoring of device performance is still required.”

Reliasoft’s website: weibull.reliasoft.com

 Share on Facebook Share on Twitter Share on Reddit Share on LinkedIn
Comments Off on Reliability Analysis of Active Implantable Medical Devices  comments