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Below is a guest blog by Jon D. Morrow, M.D., Senior Medical Leader, Clinical Business Solutions, at GE Healthcare. Also posted below you will see a video conversation with Eric Dishman, general manager of the Health and Life Sciences Group at Intel, and three experts from GE Healthcare who discuss pending changes in the healthcare landscape when it comes to payment reform and treatment, and trends in healthcare IT that will impact provider's workflows and practices.

 

With enormous changes taking place in the U.S. healthcare system’s clinical and financial models, the coming-of-age of Cloud computing and the advent of Big Data could hardly be better timed.

 

Over the past couple of decades, the practice of medicine has completed an evolution from anecdotal, experience-driven care to evidence-based, experiment-driven care. In the traditional, anecdotal model, physicians made most of their care decisions based on what they had personally observed in their own practices, what treatments they had used successfully before, and what their mentors had taught them. In the evidence-based model that is prevalent today, decisions are made from scientifically proven findings based on rigorous clinical experiments and controlled observations.

 

Medicine is now undergoing another, revolutionary change, in the way care is delivered and the way providers are paid for their services. Modern care is delivered not by physicians driving rigidly hierarchical teams, but by coordinated teams of medical professionals including physicians, nurses, therapists, social workers, physicians’ assistants, and many others, each contributing to a patient’s overall care the unique skills of his or her profession.

 

 

The patient and the patient’s family are also being brought more formally into the care team, with the recognition that good medicine – whether preventative or interventional – is possible only when the patient, supported by his or her family and friends, takes an active role. Moreover, providers, clinics, and hospitals are starting to be rewarded financially not for delivering more services, as was the case in the past, but instead for the quality of the care they deliver, measured by specific clinical outcomes and, increasingly, by the patient’s overall wellness.

 

Integrated care in this new paradigm presents many challenges, and Cloud computing and Big Data are important tools to meet these emerging challenges. Measures of the success of treatment, the quality of a patient’s care, and even the quality of the care that a physician or a nurse or a facility provides are all available from the data in the electronic health record.

 

Cloud-based health records can bring information together from many, disparate sources to provide a big picture of an individual patient beyond the walls of one doctor’s office or one hospital, allowing the integrated care team to draw on findings from many different sources – and many different kinds of sources.

 

Big Data can then leverage these integrated records in a de-identified fashion to learn from the aggregated outcome of various treatments to glean knowledge across many patients and many facilities, much as has been done with GE’s Medical Quality Improvement Consortium, allowing sound, evidence-based medical protocols to be developed. In a sense, the scientific medical knowledge that is already in electronic health records is unleashed when it is delivered in the Cloud and connected through Big Data.

 

Cloud computing also opens opportunities to incorporate the patient and his or her personal support network as full partners in the care team, by securely opening doors for the patient into information, educational resources, and other tools. Concomitant with advances in technology and accessibility, advances in Cloud security and, importantly, increases in the comfort level of patients and physicians in sharing and accessing information will make patients’ direct participation in their care increasingly available and powerful in coming years.

 

The next step is going from observational knowledge to predictive modeling – that is, learning how to predict an outcome before it happens, identifying patients at risk for particular conditions, and enabling the care team to intervene to prevent an illness or a bad outcome before it even happens.

 

While physicians, nurses, and other providers have always been driven by altruism and professionalism to strive for the best possible outcomes for their patients, providers and healthcare organizations are now also being incentivized financially through outcomes-based payment models. With this added incentive, resources can be mobilized to realize the full potential of Cloud-based medical knowledge and Big Data.

 

What do you think?

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