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Analytics Used to Examine Cutting HIT Infrastructure Costs

As healthcare incentive programs grow, organizations are looking to data analytics to cut IT infrastructure costs and improve patient care.

Source: Thinkstock

By Elizabeth O'Dowd

- In recent years, the healthcare industry has seen a series of incentive programs to assist organizations in cutting back on costs while improving patient care. Many organizations are using analytics to examine patient data for better care and to examine the inner workings of HIT infrastructure, ensuring that organizations are not wasting valuable resources.

“As an industry we’ve spent a significant amount of time and money incentivizing healthcare,” Pure Storage Vice President and CTO of Healthcare Vik Nagjee told HITInfrastructure.com. “We’ve spent billions of dollars implementing electronic health records, imaging systems, and putting in mobile access to systems. It’s been a lot of time spent in digitizing everything.”

Nagjee explained that the entire premise for incentivizing healthcare is to reduce patient risk and error, while providing patients with better and faster care. The main challenge with these incentives is that organizations have many disparate health IT infrastructure systems that do not run together in a way that allows IT administrators to get a clear big-picture of the entire infrastructure.

According to Nagjee, organizations are left with large silos of data that are not easy to manage or sort through without a solution powerful enough to handle the data. Organizations need to look at bodies of data across various systems, such as electronic health records (EHRs) and digital systems to see which systems are helping or hindering operations.

“In order to do all of this, you need to unify these systems and bring them together which is hard to do,” Nagjee explained. “People have been trying to do this for quite a while. CTOs and CFOs of all major organizations are faced with a very big challenge at the moment. They’re seeing an increase in the number of patients they actually serve year over year.

READ MORE: Big Data Analytics Solutions Significant to Health IT

“Larger volume would typically indicate better business, however costs for procedures and costs for materials continue to go up while the reimbursements from CMS are going down.”

Many healthcare organizations are actually experiencing very low operating margins with some entities running in the negative, said Nagjee. Healthcare organizations can’t turn patients away, but they cannot continue to operate at low or negative profit margins. This means something has to change in the way things are run beginning with how to improve IT infrastructure to take care of the patient population.

Nagjee used type two diabetes as an example of how healthcare organizations are looking to cut back on casts and improve patient care.

“Type two diabetes is the number one cost for healthcare in the country,” Nagjee noted. “In order for organizations to make steps in curing type two diabetes there has to be patient engagement, population health management, and patient outreach. To implement all of that, you have to start with identifying the right sorts of people, and the right sorts of programs that work.”

“So now we’re talking about healthcare married with analytics and married with things like machine learning and artificial intelligence to help us derive meaning from the data,” Nagjee continued. “These are all data intensive applications. It’s important because proper intervention and treatment will allow these patients to not only get better faster, but save a life.”

READ MORE: Artificial Intelligence Uses EHRs as Smart Analytics Tools

Nagjee explained how Mercy implemented analytics to improve its supply chain, and was able to use the same technology to analyze clinical data related to hip replacement surgery expenses.

“Mercy is a large healthcare organization that deals with many hospital locations. They wanted to figure out how to save money by optimizing their supply chain,” Nagjee explained. “They started to look at the way they were acquiring things like gloves, scissors, and surgical instruments. They’re small things, but they add up.

“They were able to look at their processes and standardize them across the board and figure out where there are variances. They found a group of computer scientists who helped them create and artificial intelligence solution to map this data and helped them optimize their supply chain.”

Mercy was also able to use the same technology to analyze clinical pathways and costs associated with hip replacement surgeries by examining the length of hospital stay in relation to patient readmission.

“You want a short stay after hip replacement and organizations don’t want someone to be readmitted,” said Nagjee. “Mercy’s analytics solution found that the medium cost procedures were the most successful.

READ MORE: How Hadoop Supports Healthcare Data Analytics Infrastructure

“It also found that the length of stay for certain procedures were 50 percent less than the length of stay for other hip replacement procedures due to the way they were administered. They looked further into the data and found that the simple administration of an analgesic as part of the procedure reduced the length of stay by 60 percent. They changed their procedure and saved millions of dollars per year just by changing that one thing.”

Nagjee concluded that organizations need the fundamental foundation to successfully perform data analysis that will save organizations a significant amount of money.

An advanced health IT infrastructure is vital for organizations seeking to lower operating costs while increasing patient care and keeping readmission rates down.


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