Skip to the content

PLM life is not without risk

This article was first published on www.plm-blog.com/das-plm-leben-ist-nicht-ohne-risiko

After all, we all go through a certain amount of medical training in these times. A few months ago, no one knew what an incidence value was. Today, everyone can calculate it in their head and graphically display the progression over the last week.

In these times, no one can deny that our lives are fraught with risk. In the medical device industry, this risk has always played an important role. The use of medical devices often involves weighing up the benefits against the associated risk of harm.

Here is an illustrative example: a scalpel is used to inflict a wound on a patient during surgery. Without the medical context, this would be an intentional bodily injury. But without accepting this injury, one cannot remove the carcinoma that is spreading in the body. The benefit (removing the carzinoma) outweighs the harm (wound). Of course, everything possible must be done to minimize this injury and to limit the resulting harm.

In the development of medical devices, the analysis and evaluation of risks and the associated harms is an essential part of the product development process. In this process, risk analysis must be performed to ensure the lowest possible risk to patients and medical personnel. This requirement is reflected in relevant norms and standards such as ISO 14971. It requires the performance and documentation of risk analysis, risk assessment, risk control, and information from production and downstream phases.

In this article, however, I do not even want to look at these processes in more depth. There are quality management experts who are really good at this.

I'm more interested in answering the question of how PLM can support risk management to achieve greater effectiveness (doing the right things) and efficiency (doing things right). From my experience, I have been able to identify the following things:

 

Integration of risk management into the digital thread of the medical device

As part of the product development process, risk management requires valid product data as an input variable - after all, the risks of the intended use of the medical device must be analyzed and evaluated. However, this product data is by no means static, but changes. Saving the development status at which a risk assessment was created is essential. In addition, things are done right when the risk analyst does not have to gather his product data from various sources but can rely on validity and data quality.

Breaking down risk assessment within product structures and bills of materials

Medical devices in particular are extremely innovative and contain complex structures - whether from deep BOMs from mechanical design, for example, or, far more often, because the product consists of mechanical, electrical, electronic and software components. More recently, services are also increasingly being added as an integral part of the product, adding another layer of complexity.

This also has an impact on risk assessment. The software risk analysts relates assessments to the software tree of the product structure. The lifecycle of software components is much shorter than that of mechanical ones. Linking the risk assessment into the respective sub-trees helps separating this and thus satisfy the different needs of the software engineers and the mechanical engineers. In other words, doing things right.

Breaking down risk assessment along the product life cycle

Product development in medical technology always starts with the definition of the design input, i.e. the definition of initial intended use and the gathering of the requirements for the medical product. Due to the product complexity already mentioned, the to-be-developed medical device is structured into functional, systemic, or logical components. A Preliminary Hazard Analysis (PHA) can help with providing initial results. This method focuses on identifying vulnerabilities early in a system's life, saving time and money that would be required for a major redesign if the hazards were discovered at a later stage. Therefore, PHAs are related to system design and thus to functional and logical product structure.

 

Holistic change management

Breaking down the risk analysis into components and thus linking the input and output data precisely into the product data model, allows a complete and rapid impact analysis of changes. It will be possible to trace along the digital thread which data is related and how, thus enabling a complete analysis of the affected product data. This saves an immense amount of time and increases quality, especially with regard to risk assessments. If the risk assessments are integrated into the digital thread, necessary changes and adjustments can also be triggered and tracked.

But this significant savings and quality effect stands and falls with the completeness of all individual threads. If some are missing, holes appear in the data model that have to be patched manually at great expense. 

 

Activity tracking

PLM systems already provide features and functions for the creation and tracing of activities. These tasks are sent to the respective persons responsible and their processing is stored in a traceable manner. Reviews and approvals of data and documents are stored in the audit trail.

Tasks also arise in the risk management process, and data and results must be reviewed and approved there as well. This applies in particular to the measures for mitigating risks.

The functions of the PLM system should be used for this purpose. In this way, all users can be provided with a "single source of my tasks" and their processing can be stored in a traceable manner.

 

Support for reporting, data preparation and tracking

In the end, the individual threads of risk assessment must also come together again. At the medical device level, a complete view of all components of the risk assessment is essential. Finally, it must be ensured that all steps of the risk management process have been completed. A Risk Management Report is often used for documentation.

If the Risk Management Reports are comprehensibly linked to the revision statuses of the product data, this has a decisive influence on efficiency and effectiveness: The right things are done, since the development status and maturity level of the medical device is firmly linked to the status of the risk assessment. And things are done right, since work can continue immediately on the development of the medical device and the associated risk assessment, and historical relationships are preserved. Of course, the same applies to the creation of product variants and product families.

 

Reuse Support

A completely new development of a medical product is only done in rare cases. The far more frequent use case is that an existing product is adapted. PLM systems often support these scenarios with functions in the product development module, e.g. by smart copying and adapting parts lists and product structures. If not only parts and assemblies are captured by this intelligence, but also the risk analysis data, then things are done right again. Reuse also saves time and effort here.

All these aspects lead to an often discussed weighing of the pros and cons of a special risk management software versus the use of functions in the PLM system.

The PLM system forms the backbone for all product data and controls the associated value creation processes. This is where the threads come together, which are then joined to a complete digital thread of the medical product.

Whether all the individual threads also have to be generated in the PLM system or some can also be generated by special systems is a company and application case-specific consideration. The only decisive factor is integration; risk management must not continue to exist as an isolated data island.

Doing the right things and doing the right things, both stand and fall with the integration of data. And that is precisely the core of a PLM, the connection of data, processes, systems and the users.

About the author

Christoph Golinski

Christoph has 20 plus years of experience in consulting for PLM solutions in the medical device, aerospace and renewable energy industries. His expertise in project management for PLM implementations with agile methods like Scrum and Kanban, originates from his in-depth knowledge of configuration management, requirements engineering and PLM data quality management.

 

Christoph is a keen PLM blogger, who shares his passion for PLM at his own blog in German for more than 4 years. If you are a German speaker, you should definitely check it out here.

comments powered by Disqus