Article
MedTech Quality Costs: More than 'license to operate'
How quality and regulatory compliance in MedTech became a driver of financial performance
MedTech companies reporting quality and regulatory deficiencies are not only struggling to ensure patient safety. Such deficiencies and product recalls also have a long-term impact on a company's competitive financial performance. While stock markets did not seem to systematically penalize poor quality and regulatory compliance in the MedTech sector over the past decades, this has completely changed in recent years. In our Deloitte-paper, we see a dramatically widening gap in stock market performance that can be associated with good and poor quality and regulatory compliance. The data indicates that the ability to consistently meet quality and regulatory requirements without compromising a company's agility and speed has become a strategic differentiator. In this paper, we discuss the reasons for this shift and illustrate how MedTech companies are responding with targeted investments.
Measuring the capital markets' price tag on product recalls
The results show that the quantile of 30% of companies with the lowest 'recalls per 1 million USD revenue' ratio outperformed their peers in the quantile of 30% of companies with the highest ratio by 256 percentage points (Fig. 1). Interestingly, this effect has only become (increasingly) significant in the last five years (since 2018). This observation is fully consistent with previous research1 that found no evidence of market penalties for medical device recalls at the aggregate level at that time.
What are the early warning signs?
We analyzed the most frequently raised recall reasons using the FDA Medical Device Recalls Data-base to better understand root causes and early warning signs of emerging non-compliance issues2 . Unsurprisingly, poor design controls topped the list by a large margin, accounting for 34.8% of recall reasons. This is followed by poor labelling and packaging controls (23.0%), non-conforming product (17.9%) and poor production and process controls (15.2%). Deficiencies in any of these categories are highly likely to put patients at risk and are often the reason for recall decisions.
Unfortunately, the role of quality and regulatory compliance as a factor seems to be obscured by the primary recall reasons. Although quality system deficiencies do not appear in the top recall reasons, they are often a key underlying factor leading to design deficiencies, product nonconformance or poor execution of production processes. Quality system deficiencies cause more indirect harm to patients than direct harm. Therefore, products are not recalled because of poor quality and regulatory compliance, but because of the indirect consequences.
Rethinking quality assurance and regulatory affairs to gain real competitive advantage
MedTech executives have increased their efforts in recent years to innovate, automate, harmonize and simplify their quality management systems and regulatory affairs functions and to increase digitalization. Below we present selected areas of innovation in the quality and regulatory space:
'From documents to data' and automated workflows
A key investment area is technologies for workflow automation (e.g., PLM, RIMS, eQMS or eDMS). If not managed well, however, these investments tend to simply make electronic versions of familiar manual, paper-based processes (digitization), rather than digitally transforming the business by establishing new ways of working (digitalization).
Moving from reactive to preventive quality
In contrast to audits as a retrospective means of assurance, predicting and preventing quality events before they occur, requires a change in mindset, new ways of working, and a whole new set of capabilities. Data from various sources need to be managed centrally on a unified data platform. Artificial intelligence (AI) and machine learning (ML) in regulated processes is used to make accurate predictions based on historical and real-time data.
Validate AI for use in GxP regulated processes
Deploying AI in highly regulated process areas require a more sophisticated approach to computer system validation (CSV) since machine learning functionalities are leveraged and the data used to train the algorithm needs to be in the scope of validation as well. This and other factors limit the scalability of AI minimum viable products (MVPs) in practice, so that they likely get stuck in the pilot phase before moving on to operations³.
Ensuring efficiency and compliance in modern agile engineering
While medical devices, in vitro diagnostics and healthcare software are becoming increasingly complex, so are the requirements and procedures for developing them. Improving and accelerating the product engineering process while implementing new regulations has become another key capability.
Risk-based approach and quality by Design
The move from compliance-based thinking to risk-based thinking can allow effective risk prevention but requires advanced risk management capabilities. Systematic consideration of risk in the design of quality management systems and in product design processes (‘Quality by Design’) requires a risk-oriented mindset.
Balancing local and global governance
QA and RA are no longer local endeavors. Regulators increasingly demand evidence of oversight across sites and along the entire global supply chain. Investing in the optimal balance between local empowerment and global oversight can significantly reduce the workload and create a culture of end-to-end thinking, ownership, and cooperation in the organization.
Increasing the agility and speed of controlled changes
Managing day-to-day regulatory activities while keeping a finger on the pulse of regulatory change can be made more efficient by partly automating the monitoring of regulatory trends. Re-using modular text fragments in large dossiers or in QMS content or using automated linkages between regulatory requirements and product submissions foster acceleration and probability of success.
Providing on-demand guidance for employees
Tools like chatbots, smart watches and augmented reality can provide guidance on-demand to employees. From a QMS standpoint this causes an evolving content management challenge as block text SOPs have to be transformed to provide step-by-step guidance.
Role-specific, on-demand training instead of 'read and understand'
‘Read and understand’ training is a painful and bureaucratic experience for many employees in MedTech companies. Innovative approaches are emphasizing employee training in a holistic way and aim to deliver specific guidance on demand – when it is actually needed to complete a task. This increased flexibility requires out-of-the-box thinking, advanced capabilities of the learning management system (LMS), and the willingness to actively approach regulators and explain and defend the approach.
Summary, outlook, and invitation
The regulatory and business environment for the MedTech industry has changed significantly in recent years. This has accelerated the increase in the cost of regulatory non-compliance. The ability to consistently meet quality and regulatory requirements without compromising a company's agility and speed has become a strategic differentiator and driver of financial performance.
In future research, we aim to extend our investigations further into individual firm-level factors. At present, we find that there is a lack of factual evidence as to how exactly the (business) case for quality and regulatory compliance is supported by the aforementioned and other investments, including compliance culture, QA/RA headcount, QA/RA organizational structures, digital maturity, production strategies4 , etc.
Therefore, we invite our readers to support our future research efforts by participating in more detailed firm-level analysis and benchmarking activities. For more information, download our paper on MedTech Quality Costs here.
- 1 Thirumalai, Sriram/ Sinha, Kingshuk K. (2011): Product recalls in the medical device industry: An empirical exploration of the sources and financial consequences, Management Science 57, no.2, pp. 376-392.
- 2 All FDA medical device recalls listed in the FDA Medical Device Recalls Database in the period 2012 -2022 were filtered for ‘root cause’ and mapped to the respective 21 CFR 820 subpart. We excluded recalls labelled as ‘under investigation by firm’, last access on August 7, 2023.
- 3 Erdmann, Nico et al. (2022): "AI Maturity Model for GxP-Application: A Foundation for AI Validation”, ISPE, last access on August 23, 2023.
- 4 Similar research in the automotive industry has identified product variety and production plant capacity (over-) utilization as drivers of subsequent recalls. See Shah, Rachna/Ball, George/Netessine, Serguei (2016): Plant Operations and Product Recalls in the Automotive Industry: An Empirical Investigation, Management Science 63, no. 8, pp. 2439-2459.
Further Reads
- Developing Medical Devices using Artificial Intelligence
- 2023 Global Life Sciences Outlook
- Never the same again: How COVID-19 created seismic change in global life sciences regulations
- MedTech commercial transformation: Moving from “doing digital” to “being digital”
- Disruption and innovation, two sides of the coin: 2022 Medtech industry trends
- Exponential innovation in MedTech: Unleashing the full potential of digital technologies
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