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According to a report from the Institute of Medicine, most Americans will encounter at least one diagnostic error in their lifetime. The Kaiser Family Foundation discovered that nearly one in three patients has been affected by a preventable medical error with 21 percent suffering a serious health consequence. Data from a highly-publicized Johns Hopkins study last year found that the number of hospital deaths due to medical errors has escalated to more than 250,000 annually. A 2016 BMJ study found that medical errors were the third leading cause of death in the United States, higher than deaths from diabetes or breast cancer or motor vehicle accidents combined.
Not only does a misguided diagnosis take a toll on a patient’s physical and emotion wellbeing, it also places an unnecessary financial burden on the health care system. Preventable medical errors and subsequent care requirements are estimated to cost the U.S. between $17 and $29 billon each year, according to the Health and Medicine Division of the National Academies. After many years of the lens being fixed on treatment errors, diagnostic inaccuracies are coming into focus.
What if we could use technology to effectively predict which patients are more likely to experience a misdiagnosis and intervene before they become another statistic of the system? Today, many leading employers, health plans, and hospital systems are turning to analytics to help identify populations at risk. Many of the types of cases that are misdiagnosed are those that fall between the cracks in the health care system due to lack of information sharing or lack of a clear designation to build a care plan around. These are the people that are characteristically moving up the medical cost pyramid, driving higher costs across the health care system and creating increased challenges for each individual to identify solutions in a fragmented health environment.
The type of technology we are describing involves identifying individuals who may be at a very high risk of having an error in their diagnosis or having misdirected care. These individuals may include patients struggling with cancer, gastrointestinal disorders, pulmonary issues and heart problems, to name a few. By identifying and helping the right people, misdiagnoses and errors can be dramatically reduced. This reduction spares the physical and emotional toll on the part of the patient related to incorrect treatments, while saving countless dollars in the process.
So how does it work? As the leading global clinical consultation company, Best Doctors has been studying and measuring misdiagnosis for nearly three decades. With a proprietary database of over 100,000 cases, the company set out to design algorithms that could decipher health care data to convert insight into a specific action, that allow us to target the members at the right time and also obtain a second opinion from a world-renowned physician.
“Today, many leading employers, health plans, and hospital systems are turning to analytics to help identify populations at risk”
Second opinions have been validated as a solution for reducing error. In fact, a second look from Best Doctors produced measurable differences including a change in treatment in 78 percent of cases, and an alteration or clarification of a diagnosis in 42 percent of cases. This system now results in the correction of 2 misdiagnoses and 4 treatment plans every hour.
Let’s look at a hypothetical patient named Jane who has been diagnosed with Crohn’s disease and is now using anti-rheumatic agents like Enbrel or Humira. The use of such a high-cost medication might create an alert for some proprietary systems to ensure this medication will be effective for this condition. However, this ignores the fundamental issue of whether the diagnosis was correct in the first place. Using a combination of data, current clinical protocols, and the experience of expert physicians, we now have the ability to build algorithms that identify the potential for a misdiagnosis to occur. Once Jane is identified, we educate her on the value of receiving a second opinion and the potential outcome it could provide. If Jane chooses to initiate a case, a dedicated team works closely with her and her entire clinical team to collect all the clinical source data and information for experts to review. Patients find deep satisfaction and comfort because of the clinical thoroughness and coordination of information between multiple physicians, including the treating physician.
The optimum approach to identifying populations at risk for misdiagnosis is to integrate analytic approaches with clinical resources that are involved in care management to create integrated clinical intelligence. The analysis of health information, including patterns in the claims data and clinical utilization markers, can help recognize a potential issue which can be validated by clinical experts involved in the individual’s care.
In recent months, Best Doctors has made headlines by combining the cognitive computing genius of IBM Watson with the human knowledge of over 53,000 of the world’s leading physicians. It is very difficult for practicing physicians to stay abreast of all the medical changes because of the rapid changes in science and it is recognized that it takes 17 years, on average, for science to be translated into the best clinical practice. IBM Watson can read 200 million documents in three seconds. The aim is to bring the power of cognitive computing and predictive analytics into the support of personalized medical decisions.
Every day, far too many people struggle with medical uncertainty. The most effective weapon against the physical, emotional, and financial tolls of misdiagnosis continues to be a coordinated program of clinical expertise and advanced analytics. Understanding the warning signs and clinical triggers that help identify an individual at risk can be pivotal to improving a person’s quality of life. Although diagnostic errors are an enormous problem in healthcare around the globe, predictive analytics is allowing physicians, employers, and health plans to work in an integrated manner to get ahead of the problem.