Our colleague Lucian Nita, head of Research and Development at RomSoft, presented the EMIM solution in the New Solution for Digital Health webinar, on May 14th 2020.
Our R&D department at RomSoft was established back in 2008, when we were granted the Certification for Scientific Development and Research by ANCS. Since then, we gained solid know how in national and EU funded research projects, especially in developing e-health and mobile health services, such as EMIM.
Recently, the EMIM team had the chance to pitch their idea in a European-wide webinar to look for partners and apply for EU funding. I caught up with Lucian Nita, head of R&D, to find out more about this event and what comes next for EMIM.
About the New Solution for Digital Health webinar
Please tell us more about the circumstances of your participation. Who organized it? What was the purpose?
The webinar was organized within an already approved EU funded project – Digi-B-Cube. The purpose was to offer SMEs the opportunity to present their pitches on new e-health and mobile health solutions; to help them know each other, exchange ideas, and further help them form some associations – the so called research consortia. After forming the consortia, the partners would share the responsibility to write and submit their project propositions to Digi-B-Cube, in order to get funding.
In the next phase, the Digi-B-Cube commission of specialists would analyze the proposals submitted by each consortium and fund the ones meeting the highest scores.
There are three sub-calls within Digi-B-Cube, one for travelling vouchers to facilitate scientific exchange between partners, one for prototyping new ideas and the most important one, for those SMEs that already have a prototype and want to switch to real-life implementation phase. We are in the third category. So, we have the EMIM medical platform that is truly integrative for any medical service and also very offering in terms of specialized medical services. And we want to take the next step, towards managing medical imaging data and telemedicine services.
How did you get the idea for your pitch?
Some time ago, at RomSoft, we worked on a prototype – USMED, in collaboration with other iMAGO-MOL cluster members. The project was meant to integrate medical imaging data of the same patient from various sources (clinics, hospitals, laboratories) and make it available for any physician, at any time.
In the meantime, EMIM took off. And we saw an opportunity to integrate the USMED agent with EMIM, in order to develop a fully web-based medical imaging solution for telemedicine.
USMED is at this stage what we call a functional prototype. Its purpose is to inter-connect hospitals with medical imaging laboratories. Now we would need to implement it in real life, and make it available from EMIM, so that doctors can use it in a telemedicine regime whenever needed. For this we needed to find a medical partner, a medical imaging laboratory, and therefore our participation in the Digi-B-Cube webinar.
The EMIM Data Access Workflow
How does the solution work?
Although we already integrated it in EMIM, the medical imaging module is not currently visible because we are bound by data privacy law. In EMIM, the flow is like this:
- If a doctor is looking for a medical image of a specific patient, based on the CNP (national identification number), then our application, that is installed at different hospitals, will look-up all existing medical imaging data of that patient, and will download it on the local hospital server. The data could be spread throughout various hospitals and ambulatory medical units, where the patient has made investigations in the past.
- For example, if a patient is brought from a small town hospital to a regional hospital in an ambulance, within an emergency situation, at his/her arrival, the doctors would already have available the patient medical history through EMIM, including eventual x-ray already performed at the local hospital.
Is there another similar system out there?
There are protocols between hospitals or clinics in the same network, but at national level there is not such a system. The main problem is that the law regarding personal data exchange between different medical units is very strictly regulated. Basically, you are not allowed to give the data to any third party without consent from data owner.
In EMIM we solve this issue through a new method. We start from the premise that the patient is the sole owner of his/her medical data, and, in any situation, he or she is the only one who can take the decision to give access to it, whether it is to a doctor or other healthcare worker.
To continue with our example, the doctor from the regional hospital, who was already informed that a patient is soon being transferred to his ward, can already enter the system, look-up the patient and request access to the patient data. The patient receives a code through an SMS. As soon as the patient communicates the code to the doctor, the doctor can access the patient’s medical data.
If the patient is unconscious or otherwise unable to give his consent, the data cannot be accessed. But still, the patient would benefit from EMIM if he/she had previously set a number of public values to only be accessed in emergency cases, such as having a cardiac condition, or known drug allergies.
From the data safety perspective, this system is similar to the one used in online payments. And this workflow can ease the process to consult patients in telemedicine regime, especially in situations like this new coronavirus crisis, when the authorities institute circulation restrictions.
This saves the patient from having to make a pointless trip to the doctor’s office just for a x-ray interpretation for example. And at the same time the patient data is transferred to the physician in a secure way.
Objectives and challenges
What were the objectives of your webinar participation?
For this first phase, we set the objective to find a medical imaging partner. And we did. It’s a partner with multiple medical imaging clinics in our area (the bigger the case base, the better perspectives for our project). In the next phase, together, we must write the project proposal and submit it for funding within the Digi-B-Cube initiative.
The financing is of maximum 50 000 EUR per SME and maximum 150 000 EUR per project. This means we still have room for a third partner in our consortium. And we were thinking that the highest added value at this stage would come from an artificial intelligence specialist. With a database at the scale of our current partner, it is feasible for somebody with AI expertise to build some tools to help guide the physician in the diagnosis process. The larger the database, the more chances to identify imaging patterns for various diseases, and the more precise the machine learning algorithms will get.
„We still have room for a third partner in our consortium. And the highest added value at this stage would come from an artificial intelligence specialist.“
Lucian Nita, Head of RomSoft Research & Development Department
If the project is approved, the implementation phase will be very short (6 months) but even so, it’s a good opportunity to make strategic advancements for a complex project like EMIM.
Who are the beneficiaries of this project, if it were to be approved?
For sure, all involved parties will benefit from using the platform.
- The doctors will have access to the entire patient medical history in an easy accessible format, anytime, anywhere. This allows more timely interventions and in some cases it could be life-saving. And this benefits the patient, too.
- Also, more than often, people lose their medical documents. After a while they throw them away just for lack of storage space. Or store them in inappropriate conditions and they get deteriorated. It happened to me lots of times. With EMIM no data is lost.
- Sometimes, redundant investigations will be eliminated. Other times the doctor will reach a diagnostic faster, or with more accuracy.
- The medical imaging clinics will save time and money by storing x-ray or MRI data exclusively in digital format. No more prints and CDs needed. At the same time they will benefit from the inter-connectivity with the hospitals.
What is the biggest challenge to this project?
Of course, when entering the research field you should expect challenges of all kinds. Some of them are impossible to predict. At this moment I can think of three main directions:
The first one is to interconnect the medical imaging databases from hospitals and clinics and offer physicians access to all medical imaging history of the patient.
The second one is to implement to the EMIM web application a DICOM viewer. In order to correctly view and interpret medical imaging data they must be opened in a specialized application. Besides the system requirements, the licenses for these applications are costly and doctors can’t always have them installed in a home office. That’s why we want to integrate a DICOM viewer with EMIM so that we can truly head towards a telemedicine application in terms of medical imaging.
The third challenge is finding a partner with solid expertise in AI/machine learning to help us with the diagnostic-assisting feature.
These are very complex issues to such a small project, but it can be step forward for example in setting some standards and making some effective steps, with the possibility to develop them in further research.
What was the overall impression after this first pitch?
I think we have chances. We fulfilled our main objective, that in this phase was to find a medical partner, and we are now able to form our research consortium.
As for the webinar, it was a new experience for us having this kind of event organized online, but to everybody’s surprise, it went very well, it was more effective cost-wise, and less time consuming.
As said before, together with our partner, we have to write our project proposal and submit it to Digi-B-Cube for evaluation.
Also, we are still hung up on the idea to find a third partner. So, I’d like to end this by letting our readers know that we are looking for an entity with a fair amount of expertise in AI/machine learning to join the project. If you know somebody in the business, let us know. 🙂