Applying business analytics to the healthcare market
Medical treatment costs have been under a great deal of scrutiny in recent years. Despite efforts by the federal government to expand the reach of health insurance in the United States, 48.6 million Americans currently lack any coverage, according to the most recent census information. To stem the tide of rising medical costs, many members of the healthcare community have pushed to transition from the current "fee-for-service" model to a "pay-for-performance" paradigm. Under the traditional healthcare system, physicians and medical facilities have been paid largely by the number of patients treated and the amount of procedures they conduct. This approach to administering healthcare has resulted in two enormously pernicious consequences: Patients have, by and large, received more impersonal treatment and medical costs have risen as more physicians haphazardly order a litany of unnecessary tests and procedures in order to drive hospital revenue.
The counter-balance to this model, pay for performance, stresses the value of prevention and reducing readmission rates. This approach is expected by numerous healthcare experts to not only improve the overall well being of the American population, but reduce healthcare expenses as well, as many costly illnesses and ailments could be avoided altogether.
The need for business analytics
Effectively providing patients with a high level of preventive care will require physicians and other medical personnel to engage with them on a deeper level, however. Doctors will need access to a variety of information about a patient's risk factors and lifestyle in order to come to an accurate conclusion regarding the potential for developing a particular disease and offering suitable solutions. According to EHR Intelligence, this need for greater insight into patients' behavior and history has driven the demand for business analytics tools. With the advent of electronic healthcare records, physicians now have a steady resource of patient history and medical information to draw from when creating risk models. Sophisticated Hadoop-based analytics programs can facilitate this process by digging deep into available data streams and extracting connections and insights that may have eluded medical personnel.
A recent survey of more than 100 C-suite healthcare executives jointly conducted by the eHealth Initiative and the College of Health Information Management Executives found that nearly 80 percent stated advanced analytics resources such as big data and predictive modeling were becoming integral components to their organizations' future plans. According to Information Management, 90 percent of participants reported leveraging analytics tools for the sake of quality improvement. As more healthcare facilities deploy business analytics and personnel become better acquainted with the software available to them, these resources can help physicians provide more personalized and effective treatment.
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