The Centers for Medicare & Medicaid Services in the country state that the national health expenditure in the year 2009 equaled a whopping $2.5 billion! When averaged out, this comes to about $8,086 per person in the country. This amount also answers for 17.6 percent of the GDP (gross domestic product) of the country. When analyzed and compared with global healthcare statistics, the fact is that the United States of America spends the maximum amount of money per person per year as compared to any other country across the globe. However, it is also true that as per the World Health Organization’s 2000 ranking, the US only stands at number 37 when it comes to healthcare system performance. Furthermore, healthcare expenditures are projected to increase by 67.9 percent in comparison to the projected increases of other developed nations in the next decade!
If so much money is being spent on healthcare, why is the result not as stellar as that of other countries? Unfortunately, this question does not have a simple answer. There are a variety of reasons why the healthcare in the US is in desperate need of revamping. Problems like fraud, abuse, inflated administration costs, over-treatment and readmitting of patients, defensive treatments due to the fear of malpractice cases, and lack of coordination are just a few of the issues plaguing the healthcare system and inflating healthcare expenditure.
How Analytics Can Help Healthcare?
IBM defines ‘analytics’ as ‘the systematic use of data and related business insights that are developed through applied analytical disciplines to drive fact-based decision making for planning, management, measurement and learning.’ The inefficiencies in the US healthcare system calls for the increased use of healthcare data analytics to plug the holes that are draining the resources of the country.
The use of data analytics in the healthcare industry will facilitate the move from volume based to value based models of treatment and healthcare. The Accountable Care Act imposes monetary penalties on healthcare service providers who fail to meet the standard of care. With the use of healthcare data analytics, applications can incorporate deep search tools which can then be used to assist healthcare professionals preparing treatments for specific demographics and spotting trends. For example the use of healthcare data analytics can be used to calculate the number of hospital re-admissions. Patients who have been discharged after considered cured of certain illnesses but who come back to the hospital within 30 days after discharge will raise a red flag in the system.
So instead of a volume based treatment model, which would be happy with re-admissions that equal to more profit, the healthcare system is moving toward a value based system, where the patients’ treatment is the primary concern. This is possible through the use of data analytics in healthcare.
How can data analytics improve a hospital’s bottom line?
Every entity in healthcare looks for ways to cut costs. The use of data analytics can help with improving a hospital’s bottom line – for example, data analytics can enhance supply chain management by making it easier to keep watch over hospital materials and inventory since the process can be completely performed electronically.
Another way that data analytics can help with cutting costs is by facilitating patient registration and thereby reducing the amount of man hours needed for the manual process. Tasks like figuring out whether a patient’s insurance is eligible getting demographics and figuring out treatment costs can be all done with software.
Data analytics in the healthcare industry can serve to identify quality incentives and decrease duplication in tests and services, cut costs and drive value in the long run. It will also serve as a means to measure organizational data, expand healthcare access, and curb growth in healthcare expenditure.