It’s estimated that by 2020, healthcare will operate in a world of 44 zettabytes of data (a zettabyte is comparable to the number of grains of sand on all the world’s beaches). We’re currently creating that data at a rate of 2.5 quadrillion bytes daily.
Data and medical data analytics can drive ongoing transformation across the industry if they’re used to inform business and clinical decisions and support teams, such as anesthesia. This begins with addressing the “four Vs” in healthcare data analytics: volume, velocity, variety and veracity.
In his talk “Improving Patient Outcomes With Data Analytics,” now available for CME credit through AudioDigest, Dr. Christopher A. Troianos, professor and chair of the Anesthesiology Institute of the Cleveland Clinic and Lerner College of Medicine of Case Western Reserve University, explains how the industry has progressed in its use of big data, offering insight into what this means for healthcare as a whole and for physicianship itself.
Listen to Dr. Troianos’s full lecture on AudioDigest.
Solving complex problems with data
Healthcare challenges are complicated. They include a complex reimbursement environment, multiple intersecting markets, a shifting payer mix, workforce challenges and how to use skill sets to efficiently and effectively deliver care.
Additionally, demographic changes (for instance, baby boomers aging into high-consumption phases of life) continue to drive up the cost of care. For example, between 2014 and 2024, there will be a drop in commercial payers and a shift to government reimbursement, a dynamic that loses Cleveland Clinic 1% of its revenues each year, Dr. Troianos explains.
Arriving at a solution for these challenges starts with reviewing the legislation and efforts currently taking place in healthcare data. This includes an ongoing transformation from a fee-for-service approach that has involved minimal to no data collection or outcome reporting to a point where there is risk involved if positive outcomes aren’t achieved.
Meanwhile, the Institute for Healthcare Improvement is attempting to strengthen healthcare in general through the “triple aim” approach, which involves “improving the health of populations, enhancing the experience of care for individuals, and reducing the per capita cost of health care.”
This timeline of recent developments highlights how the industry has used medical data to help achieve these aims:
- 2009: The Health Information Technology for Economic and Clinical Health Act attempted to increase the use of economic and clinical data. This went a step beyond EHR adoption and was intended to inform doctors and administrators in how they could improve care.
- 2010: 2010 saw the passage of the Affordable Care Act (ACA), which included legislation on collecting and using data. One of the major challenges data is supposed to address is the cost of healthcare. The ACA includes the Meaningful Use program (we are technically still in stage 3), which rewards providers if they produce and use data—and eventually penalizes them if they do not.
- 2015: The Medicare Access and CHIP Reauthorization Act of 2015 made it easier to collect data and support outcome-based reimbursement, starting the industry shift from a focus on volumes to value.
- 2017: While the ACA was designed to reduce cost of care, costs continued to rise, so the American Healthcare Act, or AHCA, was passed.
What data can do
Data gives insight into how a hospital is performing, how much staff is spending and how patients are doing. It’s the key to reducing medical and operating costs and shows how clinical resources are used so that those resources can be deployed more efficiently. Healthcare professionals can use a variety of data when working to improve patient outcomes, including claims data, clinical data, pharma data, patient behavior and patient perception data.
Those working in healthcare still haven’t taken full advantage of what this data can do, but others have. Players like Amazon, JP Morgan, Berkshire Hathaway and CVS have transformed how they deliver products and services in the industry by using this data. Healthcare veterans will need to do the same and rethink how care is delivered.
