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​Atlas InWay: The digital twin for surgical instruments management

But what is a digital twin?

​How to easily create the digital twin of a Reusable Medical Device (RMD) structure ?

The healthcare facility is already structured in a very specific way and it is enough to recreate this structure with digital data. Adapted to RMDs, the structure is composed of elements such as the user facility, the specialty or the service of use, the composition from 1 to XX RMDs. The RMD itself must be easily identifiable and without possible confusion. A code, a description (correct, precise and complete), one or more images. It is therefore part of a composition, which is itself part of a surgical specialty, located in a healthcare facility. This digitally identified structure often already exists in facilities equipped with an information system dedicated to the traceability of RMDs. However, it most of the time contains defects that prevent the creation of the digital twin. And there the challenge arises, because often, major defects exist in the digital data linked to the RMD.

​Nomenclature and referencing of data related to DMRs :

The objective is to create the data that must be used to trace, count, simulate, to better manage.

However, I would like to insist in this paragraph on a very important notion: When the same DMR is digitally coded in 2 (or more) different ways, this DMR becomes unusable in a digital twin. Why? It's very simple... how to count a number of identical DMRs, if they have different digital identifiers (Codes, descriptions)? And therefore, how to manage stocks, purchases, maintenance of these same DMRs.

Be careful, I am not talking about specific DMRs with serial numbers, such as optics or motors. Nor, individual traceability to the instrument, even if this subject of T2I is related.

Conclusion : While we think that with a lot of data, we could easily obtain calculations and measurements to manage a DMR structure, reality shows that nothing is really possible if the data has not been structured upstream.

Adaptation to Reusable Medical Device management needs

​Once the data is created and structured, many models become accessible.

​Visualizations and sharing : To visualize and share the digital twin

  • Use interfaces such as visual dashboards integrated into SaaS platforms, to allow managers to visualize the status and location of instruments in real time.

  • Implement cloud-based systems to allow access to information by different departments (operating room, sterilization, maintenance, purchasing, external resources), while ensuring data security through access authorizations.

​Situation simulation : The digital twin makes it possible to simulate various situations to anticipate and optimize processes

Availability : Simulate increased demand scenarios (e.g. periods of high surgical activity) to check inventory capacity and anticipate shortages.

Planning: Predict instrument wear and preventative maintenance by simulating usage cycles and risk bills.

Flow: Test reorganizations of the CSSD processes to reduce device turnover time.

Adaptation to specific situations

  • ​Replacement inventory management: By simulating future usage based on past data, the system can suggest the optimal quantities to order to avoid stockouts while limiting overstocking.

  • DMR maintenance management: By integrating predictive analysis algorithms, it is possible to automate the planning of preventive maintenance, thus reducing unplanned breakdowns and extending the life of the instruments.

  • Purchasing management: Anticipating future needs helps to rationalize purchases by prioritizing acquisitions according to actual usage and forecasts based on simulations. This approach optimizes the budget allocated to purchases and reduces unnecessary costs.

​Benefits and Tools for the Future

 

The implementation of a digital twin of the instrumentation structure presents tangible benefits for hospital management.

Thanks to complete digitalization and rigorous structuring of data, establishments can visualize and anticipate in real time the needs and availability of medical devices. This improves planning, reduces operational costs and optimizes stock rotation, while minimizing the risks of shortages or overstocking.

In addition, the ability to simulate specific scenarios strengthens strategic decision-making, whether it concerns purchasing, maintenance or replacement stock management.

These digital innovations also facilitate the well-being of teams by lightening their workload, thus reducing stress and increasing overall productivity.

Conclusion :

​The future of medical device management lies in the integration of digital twins.

Solutions such as Atlas InWay, the only platform with a generic language, are transforming instrument management by making it proactive and predictive, promoting a more efficient and collaborative environment.

Adopting these technologies means investing not only in sustainable savings and better quality of service, but also in a rewarding work environment for healthcare professionals, for the ultimate benefit of patients and the entire healthcare world.

Jean-Paul Averty
Founder and CEO of InWay SAS

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