A recent survey conducted by the eHealth Initiative and the College of Healthcare Information Management Executives revealed while 80 percent of CIOs and other healthcare executives believe data analytics are important to their organizations' strategic goals, 84 percent said using big data presents a challenge.
Hospital and health systems' big data challenges often result from the "uniqueness and complexity of healthcare data," says Jonathan Niloff, MD, vice president and executive medical director for population health and health systems performance management at McKesson. "We have a certain set of barriers in the healthcare industry that either don't exist or have been conquered in other industries," he says.
These barriers are often keeping healthcare data siloed, reducing its usefulness. With health IT products that are not interoperable, HIPAA and privacy regulations, a larger amount of unstructured data, and a lack of universal data transmission standards and patient identifiers, it is difficult for healthcare organizations to bring the data together and turn it into actionable information, according to Dr. Niloff.
However, Dr. Niloff is confident McKesson and other vendors will, in the coming years, bring more solutions to the market that will free data from these silos and make it available for use by providers, and the government and industry will make progress on developing transmission and identifier standards. So what should healthcare providers do to ensure they are prepared to take advantage of all this soon-to-be-available data?
"They have to think about analytics differently," says Dr. Niloff. First, healthcare must follow in the footsteps of other industries that have been using data analytics to improve business efficiency and optimize performance.
This means preparing to use analytics to improve the health system of the future. Mergers and acquisitions will create integrated delivery systems that offer services well beyond that of an acute-care hospital, and healthcare reform will increasingly mandate these systems provide the best value and best outcomes for the populations they serve. Analytics, then, will be focused on maximizing efficiency of these new, larger systems in a value-based environment.
"We're going to see analytic tools that bring together population health, financial and operations data to help these systems see how they are operating overall," says Dr. Niloff. "For example, a profit and loss analysis might show you're losing money on a home care unit, but if that unit is decreasing hospital admissions or emergency department visits and thereby generating better returns under your value-based contracts, it might be a good trade-off."
Health systems will also need to bring data analytics into clinical decision-making. Right now, clinicians are facing an "explosion of information," says Dr. Niloff. "It's getting more challenging for them to keep up with all the medical literature or access all the information they might need when they're seeing a patient or remember everything they need to do." An EMR with analytics capabilities will be able to present the most appropriate information at the point of care to help improve outcomes, he says.
This approach will not only be used on the individual level but also on the population health level as well. "You'll have care managers using large sets of data to understand the needs of the population and then analytics to understand how to best intervene to drive better health," says Dr. Niloff.
Some of the country's leading health systems have already begun using analytics to drive these kinds of improvements in their organization. For other systems, now is the time to start. "They have to think about how they will get those analytics into the hands of the team who can use them to implement process changes across the organization," says Dr. Niloff. "They need to think about how they can be empowered by analytics."
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