Is Digital Health Revolutionizing Cardiac Care
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Revolutionizing cardiac care, Digital Health has grown leaps and bounds, especially in IoT, MIoT, and AI algorithms but some questions still remain.
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Is Digital Health Revolutionizing Cardiac Care
- 1. Is Digital Health Revolutionizing Cardiac Care? Dina Sifri Founder & CEO of MedDev Soft Israel
- 2. Agenda
- 3. What is Digital Health? IoT AI Big Data Tele- Medicine
- 4. Stakeholders – 4 Ps Patient Physician Programmers Payers
- 5. Stakeholders – 4 Ps Patient Physician Patients- Are they interested that their data is transferred to the cloud? What about their privacy? Will they wear these wearables continuously? Is there a single dominant player in the market? Physician- Do they have time and are they trained to use these devices and data? Do they have time for interruptions like these? Are they interested in all information that these devices provide?
- 6. Stakeholders – 4 Ps Programmers- The see only the technology side without fully understanding the hospital/home environment, possibly without understanding the real needs of the device. So they develop the most up to date technological device, which cannot be used in daily practice. Payers- Who is paying for the digital healthcare? If the hospital buys an MRI scanner, the hospital pays for it. If the patient buys a drug, the patient pays for it. Who is going to pay for the algorithm? How can we measure the cost of the algorithm?
- 8. SWOT Strength Weakness Opportunity Threats Pros: Machines are • More precise • Don’t get tired • Are powerful • Decisions based on a collective of information • Save hospitalization time Cons: • Irrelevant data collection • Long AI training times • How is new data integrated? • Under developed Regulation • Unclear Validation
- 9. AI Revolution in Cardiac Care Continuous Monitoring Diagnostics Imaging Therapy Selection
- 10. AI Revolution in Cardiac Care Continuous Monitoring Continuous monitoring: Consumer grade wearable devices can continuously monitor a consumer’s heart rate, activity and location, serve as a good platform for building AI tools that can predict early warning signs of lifestyle diseases including cardiovascular anomalies.
- 11. AI Revolution in Cardiac Care Diagnostics: Typical diagnostic pathways involve three stages. The first stage is measuring an electrocardiogram (ECG) at rest. Anomalies in this stage results in a combination of semi-invasive tests such as ECG stress test, stress echocardiography, and chest CT scan. Anomalies in this tests lead to an invasive angiography. Researchers and companies are already using AI to predict the anomalies quickly, cheaply, and accurately without using the third invasive step. Diagnostics
- 12. AI Revolution in Cardiac Care Therapy selection: One of the biggest challenges for cardiologists, hospital systems, patients, and their families is to determine the risk and cost of care pathways recommended by the cardiologists. AI can simplify this decision. Therapy Selection
- 13. AI Revolution in Cardiac Care Cardiac imaging: AI is enhancing live visualization of the heart, by color coding the different heart chambers in real time from low-resolution grayscale echocardiography images. This technology was not available a couple of years ago and is now vastly improving the efficiency of clinical workflow for both cardiologists and radiologists. Imaging
- 14. 5G Transforming Digital Healthcare The future is still not fully here but we are making huge strides towards it. • Assisted medical services that enable specialists to help with delicate operations remotely. • Telemedicine via superfast wireless technology to tackle the problem of rural patients. • Health and medical care are considered as one of the most fascinating applications that can fully benefit from the IoT. Internet of Medical Things (IMedT) for monitoring cardiac activity. • Remote monitoring of patients • Medical image transmitting • AI/Big data • Mobile robotic surgery • Patients are the point of care • Patients getting more involved in their own care • Personalized Health Care
- 15. Thank You Dina Sifri Founder & CEO MedDev Soft , dina@meddevsoft.com +972-52-8656864
Notes de l'éditeur
- Good afternoon, I’m very glad to be here and to give you a short talk regarding the digital revolution in medicine and, especially in the field of cardiac health. I have only 5 minutes so I will only be touching upon high level topics, if you would like more information, I’m available by email and phone. Two words about myself. My name is Dina Sifri and I’m the founder and CEO of MedDev Soft, which develops software and prepares software regulation for medical devices, pharma, and of course any digital health applications.
- Today’s presentation will be divided by 4, the same as the chambers of our heart. I’ll touch upon the following topics: What is digital health and why it is called digital health? Who are the players in the digital health? Strengths, weaknesses, opportunities, and threats of this technology How AI will revolution cardiac care And I’ll round out the presentation with the future, where things are going…
- So let’s start, What is digital health? Is it a popular Buzz-word, or is it really revolutionizing today’s medicine? Digital health is a technological intervention in medical care (disease prevention, management, monitoring or even treatment) by either hardware and software solutions, which may include but are not limited to AI, Machine learning, mobile phones and applications, wearable devices, telemedicine, sensors for clinic or home monitoring and so on, so on. What is IoT? These are small wearable or implanted devices, which are connected to any mobile device, that collect data from sensors, and transfers it to the cloud. In the cloud the data is collected from many devices from many patients and organized into “Big Data”. This contains huge collections of data which the diagnosis can be based on for increased accuracy. But how is this done? The data is analyzed using Artificial Intelligence (machine learning) algorithms. The algorithms should be trained on known data sets, and than run on unknown data and suggest analysis. This is the whole Torah on one leg, the problem is that it is not so simple, and I’ll explain a little bit more in the following slides.
- But before we continue to the Big data and AI challenges, I would like to think together about who are the players in the digital health? First of all, these are the patients, who are diagnosed, treated, monitored; the patients’ family, who can access the patient’s condition online. But are all patients interested in such devices? Are they interested that their data is transferred to the cloud? What about their privacy? Will they wear these wearables continuously? Is there a single dominant player in the market? The second stakeholder is the physician, which gets the information from these devices in order to get better diagnosis, the monitored data is flowing to him online and there are notifications from the algorithms, such as if the patient condition worsens. And I have another question, do physicians today have time, and are they trained to use these devices and data? Do they have time for interruptions like these? Are they interested in all information that these devices provide??? The next player is the technology, which are represented by companies that develop these devices. The company has an idea, finds the pain, and runs to develop the device by software programmers and other engineers. The engineers see only the technology side without fully understanding of the real hospital/home environment, without knowing the previous 2 stakeholders (patients and physicians), without understanding the real needs of the device, so they develop the most up to date technological device, which cannot be used in daily practice. And the last but for sure not least, who is paying for the digital healthcare? If the hospital buys an MRI scanner, the hospital pays for it. If the patient buy a drug, a patient pays for it. Who is going to pay for the algorithm? How can we measure the cost of the algorithm? So after briefly reviewing the stakeholders, let continue to the SWOT of the digital health
- But before we continue to the Big data and AI challenges, I would like to think together about who are the players in the digital health? First of all, these are the patients, who are diagnosed, treated, monitored; the patients’ family, who can access the patient’s condition online. But are all patients interested in such devices? Are they interested that their data is transferred to the cloud? What about their privacy? Will they wear these wearables continuously? Is there a single dominant player in the market? The second stakeholder is the physician, which gets the information from these devices in order to get better diagnosis, the monitored data is flowing to him online and there are notifications from the algorithms, such as if the patient condition worsens. And I have another question, do physicians today have time, and are they trained to use these devices and data? Do they have time for interruptions like these? Are they interested in all information that these devices provide??? The next player is the technology, which are represented by companies that develop these devices. The company has an idea, finds the pain, and runs to develop the device by software programmers and other engineers. The engineers see only the technology side without fully understanding of the real hospital/home environment, without knowing the previous 2 stakeholders (patients and physicians), without understanding the real needs of the device, so they develop the most up to date technological device, which cannot be used in daily practice. And the last but for sure not least, who is paying for the digital healthcare? If the hospital buys an MRI scanner, the hospital pays for it. If the patient buy a drug, a patient pays for it. Who is going to pay for the algorithm? How can we measure the cost of the algorithm? So after briefly reviewing the stakeholders, let continue to the SWOT of the digital health
- But before we continue to the Big data and AI challenges, I would like to think together about who are the players in the digital health? First of all, these are the patients, who are diagnosed, treated, monitored; the patients’ family, who can access the patient’s condition online. But are all patients interested in such devices? Are they interested that their data is transferred to the cloud? What about their privacy? Will they wear these wearables continuously? Is there a single dominant player in the market? The second stakeholder is the physician, which gets the information from these devices in order to get better diagnosis, the monitored data is flowing to him online and there are notifications from the algorithms, such as if the patient condition worsens. And I have another question, do physicians today have time, and are they trained to use these devices and data? Do they have time for interruptions like these? Are they interested in all information that these devices provide??? The next player is the technology, which are represented by companies that develop these devices. The company has an idea, finds the pain, and runs to develop the device by software programmers and other engineers. The engineers see only the technology side without fully understanding of the real hospital/home environment, without knowing the previous 2 stakeholders (patients and physicians), without understanding the real needs of the device, so they develop the most up to date technological device, which cannot be used in daily practice. And the last but for sure not least, who is paying for the digital healthcare? If the hospital buys an MRI scanner, the hospital pays for it. If the patient buy a drug, a patient pays for it. Who is going to pay for the algorithm? How can we measure the cost of the algorithm? So after briefly reviewing the stakeholders, let continue to the SWOT of the digital health
- So let start from Strengths of the digital health: No one argues, that the technology (computers) are: more precise, don’t get tired, are powerful get decisions based on a collective of information Save hospitalization time Get decision based on many specialists and so on and so on But there are also dangers in the digital health, especially in AI and big data. I’ll mention some of them: There is a lot of data being collected, especially in Israel, but the problem is that the data is not always relevant, there is a lot of noise and not enough accurate data, the data should be cleaned and separated to the relevant topics. There is a lot of work for training the algorithms, defining what is the ground truth and which decision should be done based on which data. What happens if new data arrives? Again there should be room ongoing changes in the algorithm And all this is before I mentioned the REGULATION. How do we test the correctness of the algorithm? It is the same for how do we test that the physician gave a correct diagnosis, we cannot, but when the software is involved the regulator asks us for the validation! Of course there are a lot of opportunities in digital health for all players in the field (patients, physicians, developers and even payers, for reducing the medicine prices), but there are also a lot of threats like patient privacy, cyber security, technological complications, and so on…
- So let start from Strengths of the digital health: No one argues, that the technology (computers) are: more precise, don’t get tired, are powerful get decisions based on a collective of information Save hospitalization time Get decision based on many specialists and so on and so on But there are also dangers in the digital health, especially in AI and big data. I’ll mention some of them: There is a lot of data being collected, especially in Israel, but the problem is that the data is not always relevant, there is a lot of noise and not enough accurate data, the data should be cleaned and separated to the relevant topics. There is a lot of work for training the algorithms, defining what is the ground truth and which decision should be done based on which data. What happens if new data arrives? Again there should be room ongoing changes in the algorithm And all this is before I mentioned the REGULATION. How do we test the correctness of the algorithm? It is the same for how do we test that the physician gave a correct diagnosis, we cannot, but when the software is involved the regulator asks us for the validation! Of course there are a lot of opportunities in digital health for all players in the field (patients, physicians, developers and even payers, for reducing the medicine prices), but there are also a lot of threats like patient privacy, cyber security, technological complications, and so on…
- It is clear that AI will revolution medicine and specially Cardiac care. I mentioned here 4 main fields where AI is already involved and will take an increased role in the coming years. Diagnostics: Typical diagnostic pathways involve three stages. The first stage is measuring an electrocardiogram (ECG) at rest. Anomalies in this stage results in a combination of semi-invasive tests such as ECG stress test, stress echocardiography, and chest CT scan. Anomalies in this tests lead to an invasive angiography. Researchers and companies are already using AI to predict the anomalies quickly, cheaply and accurately without using the third invasive step. Cardiac imaging: AI is enhancing live visualization of the heart, by color coding the different heart chambers in real time from low-resolution grayscale echocardiography images. This technology was not available a couple of years ago and is now vastly improving the efficiency of clinical workflow for both cardiologists and radiologists. Therapy selection: One of the biggest challenges for cardiologists, hospital systems, patients and their families is to determine the risk and cost of care pathways recommended by the cardiologists. The AI can simplify this decision Continuous monitoring: Consumer grade wearable devices that continuously monitor a consumer’s heart rate, activity and location, serve as a good platform for building AI tools that can predict early warning signs of lifestyle diseases including cardiovascular anomalies. AI is truly at the verge of redefining how cardiovascular care is delivered to patients. Companies and researchers have implemented AI in every step of the process, from continuous monitoring of basal heart rate for early warning signs to quick and efficient noninvasive diagnosis of cardiac conditions. AI is also making later stages of the care pathway more efficient, such as real-time visualization of the cardiac anomaly and subsequent therapy selection. However, the question that remains to be answered is will this advanced technology, in the long run, be able to bring down cost and time of cardiovascular care for patients.
- It is clear that AI will revolution medicine and specially Cardiac care. I mentioned here 4 main fields where AI is already involved and will take an increased role in the coming years. Diagnostics: Typical diagnostic pathways involve three stages. The first stage is measuring an electrocardiogram (ECG) at rest. Anomalies in this stage results in a combination of semi-invasive tests such as ECG stress test, stress echocardiography, and chest CT scan. Anomalies in this tests lead to an invasive angiography. Researchers and companies are already using AI to predict the anomalies quickly, cheaply and accurately without using the third invasive step. Cardiac imaging: AI is enhancing live visualization of the heart, by color coding the different heart chambers in real time from low-resolution grayscale echocardiography images. This technology was not available a couple of years ago and is now vastly improving the efficiency of clinical workflow for both cardiologists and radiologists. Therapy selection: One of the biggest challenges for cardiologists, hospital systems, patients and their families is to determine the risk and cost of care pathways recommended by the cardiologists. The AI can simplify this decision Continuous monitoring: Consumer grade wearable devices that continuously monitor a consumer’s heart rate, activity and location, serve as a good platform for building AI tools that can predict early warning signs of lifestyle diseases including cardiovascular anomalies. AI is truly at the verge of redefining how cardiovascular care is delivered to patients. Companies and researchers have implemented AI in every step of the process, from continuous monitoring of basal heart rate for early warning signs to quick and efficient noninvasive diagnosis of cardiac conditions. AI is also making later stages of the care pathway more efficient, such as real-time visualization of the cardiac anomaly and subsequent therapy selection. However, the question that remains to be answered is will this advanced technology, in the long run, be able to bring down cost and time of cardiovascular care for patients.
- It is clear that AI will revolution medicine and specially Cardiac care. I mentioned here 4 main fields where AI is already involved and will take an increased role in the coming years. Diagnostics: Typical diagnostic pathways involve three stages. The first stage is measuring an electrocardiogram (ECG) at rest. Anomalies in this stage results in a combination of semi-invasive tests such as ECG stress test, stress echocardiography, and chest CT scan. Anomalies in this tests lead to an invasive angiography. Researchers and companies are already using AI to predict the anomalies quickly, cheaply and accurately without using the third invasive step. Cardiac imaging: AI is enhancing live visualization of the heart, by color coding the different heart chambers in real time from low-resolution grayscale echocardiography images. This technology was not available a couple of years ago and is now vastly improving the efficiency of clinical workflow for both cardiologists and radiologists. Therapy selection: One of the biggest challenges for cardiologists, hospital systems, patients and their families is to determine the risk and cost of care pathways recommended by the cardiologists. The AI can simplify this decision Continuous monitoring: Consumer grade wearable devices that continuously monitor a consumer’s heart rate, activity and location, serve as a good platform for building AI tools that can predict early warning signs of lifestyle diseases including cardiovascular anomalies. AI is truly at the verge of redefining how cardiovascular care is delivered to patients. Companies and researchers have implemented AI in every step of the process, from continuous monitoring of basal heart rate for early warning signs to quick and efficient noninvasive diagnosis of cardiac conditions. AI is also making later stages of the care pathway more efficient, such as real-time visualization of the cardiac anomaly and subsequent therapy selection. However, the question that remains to be answered is will this advanced technology, in the long run, be able to bring down cost and time of cardiovascular care for patients.
- It is clear that AI will revolution medicine and specially Cardiac care. I mentioned here 4 main fields where AI is already involved and will take an increased role in the coming years. Diagnostics: Typical diagnostic pathways involve three stages. The first stage is measuring an electrocardiogram (ECG) at rest. Anomalies in this stage results in a combination of semi-invasive tests such as ECG stress test, stress echocardiography, and chest CT scan. Anomalies in this tests lead to an invasive angiography. Researchers and companies are already using AI to predict the anomalies quickly, cheaply and accurately without using the third invasive step. Cardiac imaging: AI is enhancing live visualization of the heart, by color coding the different heart chambers in real time from low-resolution grayscale echocardiography images. This technology was not available a couple of years ago and is now vastly improving the efficiency of clinical workflow for both cardiologists and radiologists. Therapy selection: One of the biggest challenges for cardiologists, hospital systems, patients and their families is to determine the risk and cost of care pathways recommended by the cardiologists. The AI can simplify this decision Continuous monitoring: Consumer grade wearable devices that continuously monitor a consumer’s heart rate, activity and location, serve as a good platform for building AI tools that can predict early warning signs of lifestyle diseases including cardiovascular anomalies. AI is truly at the verge of redefining how cardiovascular care is delivered to patients. Companies and researchers have implemented AI in every step of the process, from continuous monitoring of basal heart rate for early warning signs to quick and efficient noninvasive diagnosis of cardiac conditions. AI is also making later stages of the care pathway more efficient, such as real-time visualization of the cardiac anomaly and subsequent therapy selection. However, the question that remains to be answered is will this advanced technology, in the long run, be able to bring down cost and time of cardiovascular care for patients.
- It is clear that AI will revolution medicine and specially Cardiac care. I mentioned here 4 main fields where AI is already involved and will take an increased role in the coming years. Diagnostics: Typical diagnostic pathways involve three stages. The first stage is measuring an electrocardiogram (ECG) at rest. Anomalies in this stage results in a combination of semi-invasive tests such as ECG stress test, stress echocardiography, and chest CT scan. Anomalies in this tests lead to an invasive angiography. Researchers and companies are already using AI to predict the anomalies quickly, cheaply and accurately without using the third invasive step. Cardiac imaging: AI is enhancing live visualization of the heart, by color coding the different heart chambers in real time from low-resolution grayscale echocardiography images. This technology was not available a couple of years ago and is now vastly improving the efficiency of clinical workflow for both cardiologists and radiologists. Therapy selection: One of the biggest challenges for cardiologists, hospital systems, patients and their families is to determine the risk and cost of care pathways recommended by the cardiologists. The AI can simplify this decision Continuous monitoring: Consumer grade wearable devices that continuously monitor a consumer’s heart rate, activity and location, serve as a good platform for building AI tools that can predict early warning signs of lifestyle diseases including cardiovascular anomalies. AI is truly at the verge of redefining how cardiovascular care is delivered to patients. Companies and researchers have implemented AI in every step of the process, from continuous monitoring of basal heart rate for early warning signs to quick and efficient noninvasive diagnosis of cardiac conditions. AI is also making later stages of the care pathway more efficient, such as real-time visualization of the cardiac anomaly and subsequent therapy selection. However, the question that remains to be answered is will this advanced technology, in the long run, be able to bring down cost and time of cardiovascular care for patients.
- So the future is here, no it is still not fully here but we are making huge strides towards it. Assisted medical services that enable specialists to help with delicate operations being performed hundreds of kilometers away. Telemedicine via superfast wireless technology will help tackle the problem by allowing more patients to receive high-quality treatment at clinics near their homes Health and medical care are considered as one of the most fascinating applications that can fully benefit from the IoT. Internet of Medical Things (IMedT) for monitoring cardiac activity remote monitoring of patients, as it could potentially speed up transmission of vitals and other health data regarding patients. Medical image transmitting AI/Big data Mobile robotic surgery patients the point of care patient more involved in care Personalized Health Care And so on..
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