Healthcare Organizations Face Daunting Data Challenges
The healthcare industry is not only awash in data–it’s also inundated with mandates to make better use of that data. And yet, despite the incentives and the opportunity, the healthcare industry is struggling to turn that data into better, more efficient care. In a new report, the Institute for Health Technology Transformation (iHT2) looked into the causes and pointed to possible solutions.
In the healthcare field, data analysis is boiled down to two forms: business intelligence, which is focused on making the organization run more efficiently, and clinical intelligence, which is focused on improving care and saving lives. Hospitals and other healthcare organizations should do better to improve the use of analytics in both of these areas, according to the iHT2’s latest report, “Analytics: The Nervous System of IT-Enabled Healthcare.”
The healthcare industry has lagged other industries in exploiting data. There are some good reasons for that, including the fact that 80 percent of data in healthcare is unstructured, according to the iHT2. The unstructured data problem even afflicts organizations that have implemented electronic health record (EHR) platforms, since much of this information is captured by dictation, even though it is stored digitally. And with more than 1,000 reports required to be filed with regulators every year, just keeping up with the current reporting demands is a considerable job for the average hospital.
Attempts to extract meaningful information from unstructured data are notoriously difficult, especially when traditional tools, such as relational data stores, form the basis of the analytics platform. And few hospitals have even started investing in the types of platforms that will help with the data integration and analysis problem. According to HIMSS Analytics, only about 30 percent of hospitals had a clinical data warehouse or data mining solution in place in 2011. The capability to leverage these advanced analytical tools is decidedly skewed toward the larger hospitals, which tend to have more sophisticated IT systems.
The good news is that there’s a lot of low-hanging fruit that healthcare organizations can grab, given the right data tools. According to 2011 McKinsey report, the healthcare industry could realize $300 billion in annual value by making better use of patient and clinical data. That savings would be a boon to taxpayers and patients alike.
The numbers are a little starker when analyzing improvements in patient outcome. The 2013 Healthgrades Hospital Clinical Excellence report found that, from 2009 through 2011, more than 164,000 lives could have been saved if all other hospitals performed at the level of Distinguished Hospitals for Clinical Excellence.
That may be asking a lot out of hospitals, but it shows how much potential room there is for improvement. One possible ways that data could be applied to get this result is by creating a data warehouse that gets all relevant clinical data on patients within 24 hours and then pushes that data out to doctors and nurses via alerts, a suggestion that was made in the iHT2 report by Charles DeShazer, MD, the chief quality officer of Baycare Health System in Clearwater, Florida.
Others, such as Chad Brisendine, vice president and CIO of St. Luke’s University Health Network in Bethlehem, Pennsylvania, advocate bolstering the existing Healthcare Information Exchange (HIEs) with the capability to send alerts to all doctors within a given system.
While the data in the healthcare industry is of a different type, the participants face some of the same problems dealing with it that organizations in other industries do. “The healthcare industry must identify and establish proven strategies and best practices to manage data and to conduct the advanced analysis necessary to generate real insights that can benefit the health system,” the iHT2 report authors writes. “Those healthcare organizations focused today on gathering patient and clinical data, decoupling the data from siloed applications and solutions, and determining which data points to measure will be well positioned for the evolving future state of the healthcare landscape.