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Business Intelligence and Big Data Analytics in Healthcare

August 30, 2017

Business Intelligence and Big Data Analytics in Healthcare

 

Where there is data, there is a need for analytics, and healthcare generates an inordinate amount of data about operations, patient care, prescriptions, work hours, insurance payments and more. Reports show that, in 2011 alone, the U.S. health industry generated about 150 exabytes of data. Kaiser Permanente alone has more than nine million members and 26.5 to 44 petabytes of data from electronic medical records (EMRs).

Healthcare is driven by compliance and regulatory requirements, so the industry generates more records and has a greater need to mine those records for intelligence. Whether it is a hospital, clinic or physician’s office that is seeking to improve operating patient care or efficiency, the data is available to guide clinical decision-making, support disease monitoring and guide population management. And healthcare providers rely on solution providers to show them where the hidden data resides and how to mine that data to provide actionable intelligence using big data techniques.

As the amount of stored healthcare data increases, so does the spending on big data processes. According to MarketsandMarkets, global spending on healthcare analytics is expected to reach $18.7 billion by 2020, up from $5.8 billion in 2015.This is a golden opportunity for solution providers to apply what they know about big data analytics and adapting analytics to the needs of healthcare. Like any other business, healthcare can see real returns from big data insight in all facets of its operations. Here are just a few ways that healthcare can turn big data analytics into applicable business intelligence:

Analytics Promote Better Patient Care

Big data is already proving invaluable in identifying ways to improve patient care, reduce the length of hospital stays and reduce patient readmissions.

For example, research from the Journal of the American Board of Family Medicine shows that personalized patient care (i.e., doctors discussing concerns and strategies with patients informed by their health records) can lower the cost of healthcare by 51.3 percent. At the same time, a study by KPMG shows that only 10 percent of healthcare providers are using data to its fullest extent. By applying analytics to EMRs, caregivers can detect potential health issues and provide proactive treatment measures to decrease the number of hospital visits and improve patients’ lives.

Analytics also can reduce the number of patient readmissions. Ascension Health (the largest Catholic healthcare provider in the U.S., with locations in 23 states) was able to reduce the number of hospital visits by 150,000 in a single year by flagging patients frequently readmitted for preventable chronic conditions, such as acute myocardial infarction, congestive heart failure and pneumonia. Analytics also flag patients who should be scheduled for follow-up appointments before they leave the hospital to reduce readmissions.

Similarly, the University of Pittsburgh Medical Center (UPMC) cut readmission rates from 16.5 percent in 2008 to 13 percent in 2015 using big data analytics. UPMC created a model based on claims data to build a profile for patients likely to be readmitted. It then improved the model with EMRs. As a result, it was able to rank patients and develop the appropriate course of treatment for patients with moderately high risk of readmission.

Big Data Can Improve Operations

Analytics have proven a boon to healthcare business operations as well. For example, analytics can streamline scheduling to see a specialist or for specific diagnostics procedures. Some healthcare providers have been able to improve scheduling by determining the number of patients who miss appointments, which can be as high as 20 percent in some practices.

One healthcare group that has harnessed big data to integrate operations is Mercy, the Catholic health system based in St. Louis, with facilities in Arkansas, Kansas, Missouri and Oklahoma. Mercy was using an enterprise data warehouse EMR system using daily batch updates, so medical information was always a day behind. Mercy wanted to upgrade its system to deliver real-time patient data and improve the efficiency of other operations, such as billing, wellness care and inventory management.

Mercy migrated its data system to a Hortonworks Data Platform 2.2, an open-source data management system with distributed data storage and clusters of commodity hardware. Four clusters of servers host the Hadoop environment, including a 25-server production cluster, a 10-server test cluster, an eight-server R&D cluster and an eight-server engineering cluster. The data feed is about 40 terabytes, with EMRs for up to nine million patients.

With the new system, real-time data is captured as Mercy clinicians enter data on EMRs, and batch SQL data is fed into the system daily with demographics such as medical history, billing and insurance. Batch data is also captured from Mercy’s patient users. The system also is used for enterprise resource planning, and there is a separate database tracking inventory such as medications.

With the big data system in place, Mercy has better documentation, an automated chart-review process and real-time clinical data for better care, and claims are started while the patient is under care so that physicians can document unresolved issues.

Solution-Provider Resources Required

 

When you consider the potential for big data analytics in healthcare, there are any number of use cases that would easily justify a big data project. For example here are some additional products required to support a big data initiative in any care facility—handheld devices for EMR data entry, wireless networks, servers, storage, cloud infrastructure and specialized software and integration.

Healthcare big data initiatives create ongoing demand for new technology. Existing projects need care and feeding, and data can always be refreshed and repurposed for new insights. And once the value of big data has been proven, new projects will present themselves. By providing the right expertise and resources, any solution provider can become an invaluable partner for any healthcare provider.