Rewiring Medtech in the digital era - Moving from proof of concepts to enterprise-wide scale

The last few years have seen an influx of challenges for the medical devices industry - stringent and dynamic regulations, increasing demand for measurable healthcare value, and supply chain pressures to name a few. Consequently, this has resulted in a slacking pace of product development, product recalls, overwhelming operational inefficiencies, and dissatisfied customers.

At the Indegene Digital Summit 2022, industry leaders from GE Healthcare, Philips, and Exo shared their thoughts on the current state of digitization in the industry and the essential factors that impact the success of digital initiatives for medical device organizations. The key highlights of their session are summarized below.

The emergence of hybrid engagement models

New business models that are more patient-centric and value-based have emerged. Hybrid or virtual customer engagement models are bringing in not only substantial cost savings but also generating a wealth of data that can be used for enhancing interactions and assessing the performance of various sales and marketing initiatives and tactics. This intelligence has also improved clinical decision-making and the development of new products and therapies.

Digital has also made it easier for customers to connect, and share information and experiences. This has led to the rise of social media, and the need for MedTech organizations to be active on platforms such as Twitter, Facebook, TikTok, and Instagram.

AI in healthcare is still in its infancy. However, it holds a lot of promise.

The Healthcare industry is beginning to recognize the value of data-driven AI applications. AI has the potential to transform healthcare by improving patient outcomes, reducing costs, and increasing access to care. From diagnosing diseases and providing personalized treatments, to improving patient safety and reducing administrative burden, AI is playing an increasingly important role in improving the quality and efficiency of healthcare. However, data is integral to the success of AI in healthcare. Without access to large and high-quality datasets, AI applications will not be able to reach their full potential. These datasets are necessary to train and validate AI models.

Currently, in the MedTech industry, data is difficult to obtain and often exists in silos. However, recent advances in data collection and sharing technologies have made it possible to collect and share healthcare data more effectively. AI-powered medical devices have the potential to transform patient care. One example is the development of AI-powered prosthetic devices. These devices can provide a level of functionality and dexterity that was not possible with previous generations of prosthetics. This is thanks to the use of data that is collected from sensors embedded in the devices as well as from the patients themselves which are helping in building a greater understanding of how the device is being used and how it can be further improved.

Another example where AI can bring tremendous value is in medical imaging. AI allows lesser trained individuals to capture images and interpret them and then be able to triage the patient population appropriately at much lower costs thereby bringing in both time and cost efficiencies. This also helps doctors practice a complete care continuum as they can use technology to create systems that can monitor cohorts of people based on health risk levels and tie that data to hospital records.

Digital tools enable continuous and personalized communication between physicians and patients

Digitization is helping doctors and patients communicate more effectively than ever. In the past, patients would have to wait for their doctor's appointment to ask questions or get clarification on their treatment plan. Now, thanks to digital communication tools like email, text messaging, and online patient portals, patients can get the answers they need more quickly and easily. Digital technology is also making it possible for doctors to provide more personalized and targeted care. Thanks to data gathered from wearable devices and other digital tools, doctors can now get a more complete picture of their patient’s health and activity levels. This information can be used to tailor treatment plans to each patient, resulting in better outcomes.

Concluding thoughts

The value of digitization for the medical devices industry is profound. However, there are certain macro changes required for companies to truly reap the benefits and reach their goals of helping physicians deliver the best health outcomes. Companies need to adopt a change mindset to ensure sustainable enterprise-wide adoption of the digital-first model. It is equally critical to invest resources in effective data management strategies. Lastly, if companies want to use digitization to provide patient care and treatment for all segments of the population, especially in countries where healthcare is very limited, they need to work with regulators to create policies that monitor the application of AI. With this, they can bring the right innovation to market while adhering to data privacy laws.