Two different and innovative technologies have been recently developed by Israeli start-up ventures as medical decision-support systems that analyze vast amounts of medical data. These systems provide doctors with significant real-time information regarding the patient’s condition, possible risks and complications, and contribute significantly towards making the best possible clinical decisions in time critical situations.
A patient in the intensive care unit is often sedated and on respiratory systems to enable easier care and to stabilize his condition. Occasionally, following several days of treatment, his medical condition may deteriorate, a process which may unfortunately end with his death or with significant long-term damage. The clinicians responsible for his care may not always discern the first signs of deterioration, however, if the patient is connected to a system developed by the Intensix Corporation, it will identify and warn of this risk and immediate care may be rendered, thereby saving his life. Intensix’s system gathers and monitors the clinical information on the patient’s medical condition – blood pressure, pulse, acidity level, oxygen saturation, laboratory data and others – and provides the doctors with real-time alerts about any deterioration in the patient’s condition. The system is designed to present a complete and clear situation report on each patient and to identify the patterns of deterioration internalized by the system using machine learning technologies. The situation report will help doctors provide the patients with the appropriate medical treatment, that in turn, will not only reduce the duration of the patient’s stay in the intensive care unit but will also enable his release in an improved condition.
“The highest rate of patient fatality is in the hospital intensive care units and stands at approximately 30 percent. The reason for this is the critical condition of the patients and their rapid deterioration”, explains Gal Solomon, CEO of the Intensix Corporation that he founded in 2015 together with his partner Avigdor Faians. “The deterioration can stem from different reasons however the majority of deaths result from a multiple organ system failure, cardiological and respiratory problems and infections. The big-data system that we have developed is an analytic system that analyzes the patients’ clinical information and is capable of reducing the number of cases of fatalities caused by these factors. We use analytical mathematic capabilities to identify patterns of deterioration, and our system rapidly analyzes vast amounts of data for each particular situation. Time is critical in the intensive care unit. The earlier the professionals identify the deterioration – the better the chances of saving the patient’s life. Every twenty minutes, the risk of death increases by twenty percent.”
Better Healthcare by means of Data
The Intensix system is connected to a patient hospitalized 24/7, during which time vast amounts of clinical data are gathered regarding his medical condition – a hundred thousand points of information per minute. “There had previously been different attempts to convert the mathematic world of big-data to the world of physiology, but without success,” says Solomon. “Our system is capable of analyzing massive amounts of data in real-time, but we focus not only on the identification of clinical information, but also on the provision of a recommendation for the desired medical treatment. The process identifies a condition and a pattern, the expected complications, the stay duration in intensive care, and the chance of readmission. Our system can thereby significantly enhance the medical decision-making process and reduce medicals costs.”
The development of the system is still in progress. “To date, the company has completed very successful clinical trials,” Solomon points out. “We still have approximately one and a half years of trials to reach the stage at which we will be able to proceed with product sale. As of now, the system has been assembled in one of the world’s best hospitals (Mayo Clinic) in the United States, and also at the Ichilov Medical Center in Tel Aviv. At the same time, we are expanding and also installing the system at the Sheba Medical Center in Tel Hashomer. Our objective is to install the system in some significant and leading hospitals around the world to continue with the trials stage and to enable the medical teams to observe how it works and to learn from their feedback.”
“Fortunately, we began working with the Israel Innovation Authority already at the beginning of the process. I believe that this is an exceptional platform for assisting companies in launching successful ventures. If we hadn’t worked with the Authority, it would have been much harder to take the risk and establish the company. But ultimately, there is no gain without risk, and for that, we owe many thanks to the Innovation Authority.” Solomon summarizes: “Our employees are from a wide range of professions and fields of expertise: doctors, mathematicians, software experts, and it can be said, despite the fear of sounding cliched, that we are all working to save lives and achieve better medicine with the help of data.”
“Initiatives in the field of digital medicine are usually multidisciplinary,” says Zachi Schnarch, Director of the Technology Division at the Israel Innovation Authority, “and each request for support is accordingly processed by the Authority by a team of appraisers, experts in the combined disciplines.”
“With regards to initiatives in the field of machine learning technologies and big-data”, stresses Dr. Talia Ben-Neria, Head of Life Sciences Sector, Israel Innovation Authority, “they are scrutinized and evaluated by a team of expert appraisers in the software field led by Ofer Feldman and Avi Bivas, and from the area of life sciences under my leadership. The integration of medical data from the numerous information sources and the ability to provide precise real-time medical information and insights are critical for guaranteeing the patient’s safety and for providing him with quality medical treatment.”
Understanding the Context in the Clinical Text
Analysis of ‘big-data’ and a patient’s clinical information to improve the quality of his medical treatment also stands at the basis of the software program developed by the OpisoftCare Corporation. The company, that focuses on improving the capability of accurate real-time clinical decision making, was established in 2014 by three entrepreneurs: Gideon Israeli, Erez Peleg, and Amit May-Dan. “OpisoftCare’s development is a system for analyzing all the patient’s clinical data, both structured and unstructured, in real-time and for providing a warning regarding preventable dangerous clinical situations during his hospitalization, such as hospital-acquired infections or readmission and repeat surgery,” explains the CEO, Amit May-Dan. “This development has been made possible by a grant we received from the R&D fund of the Israel Innovation Authority.”
“A fighter pilot needs to process dozens, even hundreds, of pieces of information in real-time to decide his next move,” May-Dan illustrates. “T succeed, he makes use of sophisticated systems that analyze the situation and assist him in making the correct decision. A doctor is in a similar situtaton to a fighter pilot, when in the hospital. Doctors examine thousands of pieces of data and need to make the optimal decision for their patients. The vast scope of data makes it difficult for the medical team to decide correctly in real-time. A comprehensive computerization process began five years ago throughout all hospitals in the United States called ‘Unified Medical Record’ – a single system that gathers information from all systems about all patients but does not assist in decision making. That is where OpisoftCare comes in. Just as the pilot’s systems provide him with recommendations, so too OpisoftCare gathers data from all hospital systems in real-time, thereby enabling the clinician to make an informed decision about a particular patient and to warn of problems long before the medical team is aware of their existence.”
For example, OpisoftCare’s software can ‘read’ the clinical data and provide a warning, by crosschecking the structured and unstructured information in real-time, that one of the hospitalized patients is at risk of a particular infection. This data already exists, but is generally in textual form, because clinicians record visitation summaries and test results in writing. Naturally, this leads to a lack of uniformity – each hospital has a different database system which lacks other data components. Our technology, however, creates uniformity between all the hospitals and supplements the missing information. We are the only technology platform that enables the real-time creation of all necessary data for the different hospitals”, emphasizes May-Dan.
“In practice, one of the innovative components that we have developed, with the assistance of the grant from the Israel Innovation Authority, is an engine that understands the context within a clinical text. For example, when we search for pneumonia, in most cases the medical text does not even mention the word ‘lungs,’ but rather, will provide terms such as ‘Filtrate of the Upper Left Lobe.’ In other cases, the information will be irrelevant, such as evidence of a previous lung infection. It is important to understand that the concept is not only language-biased but also attuned to culture. In South Carolina for example, ‘fainting’ is termed ‘falling.’ Our system understands these nuances and knows to analyze the clinical significance of these medical descriptions in real-time”, he explains.
Analyzing Risks and Complex Situations in Real-Time
“A large number of studies are continually conducted in the medical world, but hospitals’ accessibility to this knowledge is very complicated and not always practical”, mentions May-Dan. “Our technology enables the utilization of this vast knowledge from studies already conducted, in order to solve various medical problems, without the need to go back to the beginning. Our approach is that instead of bringing a research team to the hospital, our innovative technology give them access to all existing knowledge accumulated over time and also provides the knowledge that is lacking so the doctor can treat the patient.”
“The first issue we dealt with was hospital-acquired infections. These infections are a serious and sometimes deadly problem. In the United States alone, approximately one and a half million hospitalized people acquire infections every year, and more than 150 thousand of them die from that same infection. The annual average financial cost to the hospitals in the United States stands at USD 6 million.
Our focus is on the American market, where hospitals there have an immense financial interest in collaborating with us because the average cost of a patient who acquires an infection in hospital can reach tens of thousands of dollars, and on average, that patient will stay ten days longer in the hospital, something for which the hospital receives no refund.
One example of a hospital-acquired infection is pneumonia for patients attached to respiratory machines. In this context, OpisoftCare analyzes the data in the intensive care unit and warns the doctors of patients at high risk to develop that kind of pneumonia, which patients are at low risk and when the risk level changes. The program also continuously informs the doctor which of the patients has already developed pneumonia and how quickly it is possible to wean off the respirator in order to lower the risk”, says May-Dan.
OpisoftCare’s software for reducing infections was first implemented at the Sheba Medical Center in Tel Hashomer and was subsequently installed at University Health Louisiana – a large academic hospital in the United States. At the beginning of the year, the company won a tender for the creation of a national system for the reduction of infections that will include all hospitals nationwide.
“Our plan is to continue development. Every three months we insert an additional content area into our program”, May-Dan says. “We began with hospital-acquired infections and readmissions and today our program also analyzes other medical situations: repeat surgery, resistant bacteria, chronic diseases and other complex situations that require real-time analysis of vast data in order to make clinical decisions.”
“Our business model runs in parallel the concept and the technological model. We have a subsidiary company in the United States that is working with a senior and experienced American team on the business development and sales to the American market. This company is establishing the infrastructure for operations in the American market. Furthermore, we are close to the completion of strategic processes to partner with the largest corporations in the United States, a step that will enable us rapid growth in that market”, summarizes May-Dan.