Digitalization has emerged as a new area of interest in supply chain for medical device companies. On the one hand, it poses a threat from established technology companies expanding into healthcare. On the other hand, it provides opportunities for medical device companies to provide cutting-edge services to hospitals, improve their partnerships with healthcare providers, and enable the transition towards value-based care.
Why does digitalization matter?
Medical device companies have traditionally relied on the reactive service model for post-sales maintenance and repair. The process begins with an incoming customer call from a hospital department. A vast majority of these calls would be routed to technical experts. About half of these calls would result into onsite support by an engineer. This reactive approach often leads to poor system availability, diminished performance of healthcare assets, and a substandard workflow. The entire process is slow and expensive for both the provider as well as the medical device manufacturer. In addition, it leads to a high down time of ~1%.
How is Philips leading the way?
Connected devices (internet of things), big data, and predictive analytics have provided unforeseen solutions to the problems in maintenance and repair of medical devices. Philips, one of the major players in medical device equipment, has leveraged these trends to offer cutting-edge supply chain solutions – remote upgrade and predictive maintenance. Philips can now remotely identify imaging system errors, diagnose the cause, and finally, troubleshoot and implement repairs. All of this has helped reduce the downtime to 0.1% in several partner hospitals.
Remote upgrade has been a constant feature in smartphones, but was only recently picked up by medical device companies. Philips, in turn, has started upgrading its new diagnostic machines remotely, just as Apple would do for your iPhone. The product team schedules and pushes software updates automatically, and maintains software revision records through ERP system integration. This minimizes system downtime since updates can be performed off hours, maintains latest system software revisions for increased performance, compliance, and security, and reduces travel and workload for internal field engineers.
Predictive maintenance refers to service events being triggered by careful analysis of system data through data analytics algorithms and, therefore, before any major issues arise. These predictive alerts indicate that critical system and/or environmental parameters are out of specification. Philips diagnoses the problem remotely and, if possible, resolves the issue remotely. Otherwise a field service engineer is dispatched with guidance and needed parts for a single visit repair. This helps address system deviations proactively and preempt failures, avoiding system downtime, customer disruption, and associated costs. Further, it improves workforce and spare parts planning, and allows for continuity of care.
In the long term, Philips is looking to re-invent the medical device supply chain by shifting to diagnostics-as-a-service rather than as-a-product. Recently, it launched a portable ultrasound that connects to a tablet, providing incredibly low costs and sharing capabilities. It further began piloting a fee-for-service model for this device based on the number of tests conducted. While it enables the hospital by lowering capital costs, and by increasing accountability for value-based care, it provides opportunities for Philips to continuously engage with the providers, and provide value-added services. However, scaling the new model requires significant upskilling of sales and supply management capabilities. It would also be a challenge to build such products for other bulky diagnostic service machines, such as CT scan, MRI, and X-ray.
What more can Philips do?
Building on their success, Philips can leverage two other opportunities. First, engage in risk-sharing deals with hospitals. Philips can use the data that is now available from its devices, develop a better understanding of the risk of the population, and offer diagnostic services as part of a risk-sharing deal. Second, integrate diagnostics into a broader population health proposition. This could either be a part of bundled payments, or capitation payments model.
However, further progress in use of healthcare data is dependent on Washington D.C.’s ability to shift the patient data ownership to patients from providers. Lack of patient data continuity is a major roadblock for companies, such as Philips, that are looking to broaden the horizons of digital health.
1. What control mechanisms should a medical device company put in place so that a high pace of innovation does not create additional regulatory risks?
2. What are the various business models to offer diagnostics-as-a-service rather than as-a-product? Are there any parallels in another industry where Philips can find inspiration for such a model?
3. How can private enterprises play a stronger role in advocating patient data ownership?
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