A patient twin to protect John’s heart

Developers from Siemens Healthineers addressed these complex questions in collaboration with clinical partners. Within the framework of interdisciplinary workshops, approx. 40 team members came up with John’s story as a realistic future scenario for the early detection of cardiovascular diseases such as progressive coronary artery disease (CAD) or arrhythmia. They based their considerations on the results of the latest research studies and technical developments. In around 10 years, a patient story like John’s could become a reality.

Allow us to introduce our future patient. This is John. He’s 62 and feels on top form. His heart has never given him problems before, although there is a history of cardiovascular disease in his family. And the last time John visited his physician, he was diagnosed with high blood pressure and high cholesterol, both of which are risk factors for developing coronary artery disease. John’s love of getting together with friends for barbecued steaks and a few beers is probably not helping the situation either.
In view of his medical history, John's physician advises him to keep a constant eye on his health parameters. Taking this advice, John decides to register for a special health app featuring his very own patient twin.

From now on, the patient twin, which brings together all of John’s relevant digital health data, will interact with learning software or artificial intelligence (AI) to take care of John and his heart. The patient twin measures and collects important cardiovascular data, like blood pressure, in real time and combines it with other relevant data such as laboratory data or data from medical imaging. The artificial intelligence compares John’s data continuously with the health data of a suitable comparison group of other people.

In this way, the digital patient model can create, visualize and test simulations of John's future state of health and possible next diagnostic steps and therapies. The patient twin gives recommendations to John and the team of medical practitioners looking after him: How can John keep himself healthy? What next medical steps could or should be initiated? The patient twin simulates future scenarios to enable preventive measures are taken before John’s condition takes a turn for the worse. The AI gives John and his physicians recommendations for targeted diagnostic prevention or follow-up examinations such as laboratory tests or ultrasound. The medical practitioners approve the appropriate proposals either in a face-to-face meeting or digitally. However, John always has the final say on whether the examination will go ahead.

The RHÖN-KLINIKUM Campus in Bad Neustadt (Germany) relies strongly on future technologies and digital networking. Professor Dr. Sebastian Kerber is medical director and chief physician at Clinic for Cardiology I, and Professor Dr. Thomas Deneke is chief physician at Clinic for Cardiology II. We questioned the medical practitioners on key aspects of our vision.

John is perfectly networked in the digital space, and not just via his patient twin. After talking with his physician, he understands the value of collecting data using mobile devices and merging it with his own health data. 

John's smartphone and his wearables – his smartwatch and his intelligent T-shirt with integrated sensors – continuously provide his patient twin with medical and lifestyle data to monitor John's condition, including blood pressure, oxygen saturation, heart rate, ECG, and data regarding John's current physical strain. 

Even John’s smart coffee machine is hooked up to the network and collects data on his coffee consumption. Just now, John’s heart rate rose briefly. But through the combined evaluation of the data from his coffee machine and smartwatch, the artificial intelligence can attribute this to the cup of very strong espresso John drank a few minutes ago. Nothing to worry about, John.

Some friends are coming over for a barbecue this evening. John still has to visit the shopping mall to pick up some meat. A message pops up on his smartphone: “You could combine that with a cardiac ultrasound,” suggests his patient twin. “You're due this preventive examination and your cardiologist has already authorized it.” John thinks that’s a great idea. He won't even have to go out of his way, as the diagnostic center is also located right in the shopping mall. On evaluating the ultrasound, John's patient twin fortunately identifies no abnormalities.

John is working in the garden. It’s a hot summer's day, and he’s already starting to perspire in the glaring sunshine. His patient twin notices this, and warns John via his smartphone of an impending electrolyte imbalance: “Please drink some water immediately.” However, John is so engrossed in his weeding that he misses the message. 

Suddenly John becomes dizzy and breaks out into a sweat. And gets a strange feeling in his chest. “You have an irregular heartbeat, and this time the espresso is not to blame,” announces his patient twin. The artificial intelligence compares John’s current condition immediately with the available data from the continuous health monitoring and concludes that it is abnormal.

John starts to get worried. What’s the matter with him? John’s patient twin contacts him immediately via his smartphone, without waiting for his cardiologist to do so first. John had consented to this in advance. Together with John, the patient twin goes through further possible causes of his cardiac arrhythmia.

What about John’s blood pressure? Has his ECG changed in any way? Are the abnormal rhythms extrasystoles, in other words generally harmless “extra beats” outside of the regular basic rhythm of the heart? Or are they atrial fibrillations? The artificial intelligence gives John recommendations as to what he can do next, and he can ask questions. In this way, the AI obtains a more detailed picture and can put John’s mind somewhat at ease.

John’s patient twin asks him to carry out various tests at home, which he has on hand as agreed to with his cardiologist. Via a sensor directly in his arm, John takes a number of home tests, including a highly sensitive troponin blood test. The patient twin also records John’s resting ECG via his smart T-shirt and measures the oxygen saturation of John’s blood.

The medical specialists in the team looking after John also have digital counterparts. These digital twins of the physicians are now informed by John's patient twin about John's current condition. The physicians have made the settings in advance for the notifications about John. In this way, the medical practitioners looking after John are kept informed at all times and are warned at an early stage of any relevant change or deterioration. The digital twin of the cardiological imaging specialist provides the digital twin of John's cardiologist with suggestions for examinations and necessary next steps.

At the same time, John’s digital twin sends an alert and current data to John’s “real” cardiologist, with data-based probabilities for possible diagnoses and action recommendations. The cardiologist reviews the information and concludes that John's situation is highly unlikely to be life-threatening. She calls John personally to discuss the next steps with him. She agrees with John that a computed tomography (CT) scan of the heart would be in order.

In our future scenario, the CT systems are located in places like shopping malls, radiological practices and micro-hospitals or are deployed as mobile units. When John arrives at the micro-hospital – a local cardiological care center – the CT system has already been personalized for his examination. From the information provided by John’s patient twin, it knows what settings it needs to make to achieve an optimum result. There’s good news following the examination. The AI on the CT twin reports that the examination has been performed without any complications or measurement errors, and serious, acute heart disease can be excluded. The AI then instructs John to consult his cardiologist to plan further clarification steps. John is relieved. And John's patient twin will use its current data to help John’s cardiologist identify the cause of this episode.

Several years have passed without incident for John in “matters of the heart”. He’s now celebrated his 75th birthday – with a big barbecue party, of course. But a few days later, as John is digging the garden again, it happens. The artificial intelligence registers the first early signs of an impending heart attack. John himself has noticed nothing until this point, and has had no symptoms. 

But this time the situation could get really serious, as the AI has realized immediately by referring to all John's available profile data. It all happens very quickly from here. The AI sends a warning to John, who is still showing no symptoms, and simultaneously calls an ambulance. John and his physician had jointly agreed and set up this scenario in advance. 

The AI identifies the nearest micro-hospital with suitable automated diagnostic equipment and an interventional vascular robot. It notifies the micro-hospital of John's arrival and supplies it with all relevant data so that it can prepare preventive measures tailored individually to John. At the same time, it sends messages to John's family to inform them about his condition and the next steps.

Minutes later the ambulance arrives. The emergency physician and the paramedics initiate immediate preventive measures. At the same time, they collect and analyze more of John’s data, which is added in real time to his digital health record and forwarded by his patient twin. Even before John arrives at the micro-hospital, the cardiologist in charge can view the latest data via John’s patient twin in real time.

When John reaches the micro-hospital several minutes later in the ambulance, everything is already prepared for his individual needs. The team of medical practitioners on site waste no time in providing him with targeted treatment. Based on an automated CT scan and a remote-controlled, robot-assisted coronary angiography, they identify a worrying congestion in a coronary blood vessel. 

Controlling the robot remotely, the medical practitioners widen the congested vessel with the help of a balloon catheter, which is introduced into the coronary blood vessel. They support the vascular wall with a stent, a medical implant designed to keep vessels open. Fortunately, John's heart muscle is not yet irreparably damaged. 

The integrated early warning systems and the rapid medical care tailored individually to John and provided close to where he lives have ultimately prevented heart failure. Our future patient is soon on the road to recovery. This sprightly pensioner will hopefully live to throw many more barbecue parties for his friends. Smart digital recommendations aside, it would after all be a bit boring to live a healthy life all the time.

Patient twins are still a future vision, but progress is being made all the time, for example in research aimed at developing a digital twin of the heart, the first realistic model of a human organ. 

And with cutting-edge imaging devices that automatically identify patients and their individual needs and adapt themselves accordingly, we’re ultimately paving the way for the digital twin technology. The future has already begun.