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Risk Management: An Unlikely Source of Product Innovation?

Risk Management: An Unlikely Source of Product Innovation?
Mining risk management files, postmarket data, and input and output can lead to surprising discoveries that will improve your products.  

Mining risk management files, postmarket data, and input and output can lead to surprising discoveries that will improve your products.   

Editor's note: This is the second installment in David Amor's Med-Dev from Scratch: Compliant Innovation column dedicated to helping entrepreneurs build their medical device companies in a compliant and streamlined way. Read the first installment here.

A former colleague once asked me why companies weren’t using risk management to create more innovative products. A bit confused, I pressed her to continue the thought process that I clearly didn’t understand. Using failure mode and effects analyses (FMEAs) to revolutionize the pacemaker industry? Launching mitigations and risk controls that are awarded multiple patents? As preposterous as these concepts sounded to me at the time, the explanation my old coworker provided me changed my perspective on performing risk management. It initiated my strong belief that—as she later explained—“finding why you fail, fixing the failure, and preventing future failures is true iterative innovation.”

Interested in product development? Don't miss the track on product development for wireless devices at the Wireless Medical Devices West conference December 3–5, 2013, in San Jose, CA.

I now agree. We all know an engineer who believes risk management deliverables are just paperwork exercises. Copy and paste a legacy FMEA, tweak a few things and—voila!—a new FMEA is born. However, the favored approach should always be to examine risk management as a practical approach to problem solving. In a regulatory climate where the burden of demonstrating safe and effective devices has shifted to demonstrating safe, really safe, ultrasafe and—oh yeah—effective medical devices, dedication to true risk management becomes even more important.

Here are a few potential sources of innovation during risk management activities that an engineer should keep in mind:

Review of the Risk Management File. Reviewing the risk management file of a particular product or product family can often result in a treasure hunt with a lucrative payout. Some of the keys I look for during risk management reviews give me important clues as to how effective our risk management process was from the time it was implemented to the present.

For example, during a review of a molded stopcock component’s failure modes at a particular company, we noticed a high scrap rate associated with a sealed valve being punctured. After root cause analysis determined that the silicone oil dispensing needle was puncturing in the wrong position—thus widening the seal slit—we designed a “poka-yoke” fixture designed to center the needle and valve. This was noted in our process FMEA as a risk control/mitigation, bringing the probability of occurrence down from a high probability (based on production scrap data) to a lower, acceptable probability.

During the roll out of this risk mitigation measure, we found additional correlation between the seal issues and failures during design verification testing for leaks in the same spot. After digging a bit further, we found several issues with the design specifications and material composition. We tested a variety of materials and ran technical studies on seal width and came up with a more feasible solution that was incorporated into the new product with great success.

This example illustrates the importance of following up on the risk controls you establish within your process. Trending of production data and deficiencies under QSR Subpart G is not only becoming a big FDA focal point but a practical way of analyzing your process and determining if changes can be made to enhance output.

Postmarket Data on Hazards and Harms. During new product development or even during period analyses of legacy products, one of the first things I take a look at is the performance of similar or predicate products within the portfolio of the company or even within other companies through the appropriate databases.

For example, during a recent catheter development program, we examined the predicate that the new iteration was based on and reviewed complaints data prior to beginning development. The reason was simple: How else will you improve and innovate if you don’t understand the problems of your previous designs? It seems like a logical task but is one that unfortunately gets overlooked due to timelines, eagerness to initiate a program and other factors.

From that initial study, we noticed a trend in reported issues with catheter maneuverability into anatomical landmarks. We took that data, set up a fractional factorial design of experiments (DOE) to examine the main contributing factors (braid construction, braid configurations, and extrusion dimensions) and tested a new design against the same specifications. The results were impressive and allowed us to be confident in a more robust catheter design that would ultimately be more successful than its predecessor with minimal postmarket negatives.

Input and Output Tracing. One of the most important aspects of risk management is verifying the effectiveness of your risk controls. During identification and evaluation of hazards and risks, certain acceptability levels are determined that may or may not require mitigations or other risk controls. When a risk control is place and deemed ineffective, there should be clear linkage from the mitigation to the design input where it stems from.

For example, suppose there are significant field return complaints for a one-way valve that opens prematurely in injection tubing, causing overdosing of a certain drug. You review your historical risk management data, and while poring through a hazard analysis or DFMEA, you note that overdosing (the harm) is caused by a valve opening prematurely (the hazard or failure mode), which leads to an excess volume of drug entering the patient (the hazardous situation or product effect). [Note: Hazard, hazardous situation, harm, and other terminology may be used differently at various companies.] 

As an engineer, you had decided at the time of development that because the outer diameter of the valve was slightly larger than that of the tubing, the interference fit effect would keep the valve closed until significant pressure caused the valve to open. You ascribed this interference fit as a risk control and verified it was effective through subsequent testing. However, you also note through your review that other effects such as environment of use and material degradation were not adequately tested, so through root cause investigation you solve the problem and implement a design fix to the premature opening issue.

The key to this entire exercise was being able to trace the hazard to a hazardous situation, which manifested as harm, and then tracing to the mitigation by design. When this mitigation failed, as noted by the spike in complaints related to the hazard, the engineer was able to use the risk management tool to find exactly the issue that needs to be addressed. This activity in itself led to innovation by creating a safer, more effective product.

All in all, risk management tools exist for a good reason. Understand the failures and hazards with predicate or other similar products, ensure you can follow your activity from input to control, and make sure to routinely monitor your product performance. Altogether, these activities can lead to innovation a la risk management—who would have thought?

Don't miss the conference track on product development for wireless medical devices at Wireless Medical Devices West, December 3–5, 2013, in San Jose, CA.

David Amor is a medical device consultant who has worked with companies such as Boston Scientific, St. Jude Medical, and Hospira to develop quality management systems and product development infrastructures. A graduate of the Senior Innovation Fellows program at the University of Minnesota Medical Device Center, Amor was one of MD+DI's "40 Under 40" medical device innovators in 2012. He founded MEDgineering, a niche quality consulting firm focusing on FDA remediation, quality staffing and consulting, and med-tech investment due diligence. He holds a BS and MS in biomedical engineering from the University of Miami with a focus on innovating around clinical needs. Amor currently serves as chief operating officer of ReMind Technologies, a mobile health start-up dedicated to tackling medication adherence by using smart-device based medication dispensing units and software applications.


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