3 Ways Data Analytics Tools Reduce Health Care Costs and Boost Efficiency

by:
on October 5, 2015

Health care costs are rising—and the desire to pay, among both insurers and government, is diminishing. Reducing costs without sacrificing quality of care is a challenge all providers face. The good news? Hospital workflows produce lots of data, which, when analyzed using business intelligence (BI) and analytics tools, can reveal ways to reduce costs and boost efficiency.

Deciding where to get started is no easy matter, however. Indeed, unlike in an industry such as finance, where advanced data analytics practices are well-established, health care is still in an era of discovery.

Southard Jones, VP of product strategy at cloud BI vendor Birst, describes the sector as extremely “heterogenous—[providers] all seem to have their own way of wanting to handle data.”

With so many possible data-handling practices, it’s all the more important to share information. To learn more, we asked three experts:

What are some practical ways providers can apply health care analytics to the data they collect to help save money and work more efficiently?

1. Optimize Block Scheduling

Using BI tools, health care analytics teams can drill into patterns of room usage and staff availability to identify inefficiencies and avert revenue loss.

Use Case:
Health care providers have so many moving parts that optimizing resources is a challenging task. Isolating and analyzing discrete aspects of the workflow is therefore a key strategy, in order to avoid going down a million analytical rabbit holes.

For instance, operating room scheduling is one area where hospitals suffer inefficiencies. But problems in this area can be remedied through analytics, says Jamie Oswald, associate principal data analyst at Mercy Health in St. Louis.

An empty operating room is a source of waste, says Oswald: “We want [doctors] to be in there and going through as many patients and procedures as they safely and appropriately can.”

Traditionally, a surgeon might request an operating room for a given block of time; for example, between 8 a.m. and 1 p.m. on Tuesday. While this seems simple enough, the room may not actually be in use that entire time—and that translates to lost revenue.

At Mercy, Oswald’s team conducted a detailed analysis of usage patterns. It was not, Oswald stresses, a hugely complex big-data project; rather, it involved the application of BI tools to internal data. In other words: The analysts collected all available data on how the physicians were using their time, and plugged it into their BI system.

“For instance, maybe [the physician has the operating] room from 8 a.m. until 1 p.m., but they’re actually [only] using it from 8 a.m. to 10 a.m., and then 11 a.m. to 12 p.m.,” Oswald explains.

Analytics tools gather and collate this information, which can then be used to make scheduling more efficient. In Oswald’s example, if this information is brought to the physician and their operating room schedule is changed to 8 a.m. to 11 a.m., the extra two hours can now be used by a different surgeon.

The Result:
Consolidating the operating room scheduling information and then providing the hospital with automated access to usage patterns made a “huge difference,” Oswald says. “Those rooms are working 12 percent more than they used to.”

By using BI tools in this way, waste is eliminated and revenue boosted: a win-win.

2: Scrutinize the Supply Chain

Using BI and analytics tools, health care providers can drill into procurement and invoicing billing data to identify off-contract spending and supplier performance, and therefore keep costs as low as possible. This can also help optimize service and patient care and safety, while maximizing patient and employee satisfaction.

Use Case:
With profit margins growing ever tighter, today’s hospitals have to be very lean operationally. With so little room for slack, identifying unnecessary or wasteful spending is more important than ever. Providers can thus analyze the supply chain and evaluate supplier performance based on:

  • Timeliness
  • Quantity
  • Quality
  • Pricing

According to Jon Arck, director of health care industry business solutions for SAP and specialist in clinical supply chain management, one way to improve supplier performance and reduce costs is to evaluate suppliers’ compliance with contract terms—from both performance and cost perspectives.

In health care, unlike in many other industries, price is not necessarily the most important consideration. Obtaining the right supplies, drugs and equipment of the right quality at the right location at the right time—and in the right quantity for the right patient—is critical to optimizing patient care and safety. One way to reduce costs is to consolidate orders and buy necessary supplies in bulk, as well as to rationalize the supplier base to leverage volume and negotiate more favorable contracts.

The alternative, says Dr. David Delaney, chief medical officer of analytics giant SAP, is “all those onesy-twosy orders from different suppliers.” This fragmentation of supply can lead to a much higher spend.

The complexity and size of the health care supply chain, however, makes it extremely difficult to keep an eye on that spending. Staff may not be sticking to the contracts, while vendors may accidentally invoice at the incorrect rate, rather than the one agreed upon.

“Unless you have automation and analysis capabilities, it’s pretty easy for people to fall into something that’s just a little off,” says Delaney.

By using BI and analytics tools, operations staff can monitor all spend and procurement closely, and make informed decisions when sourcing and contracting. These tools enable them to identify and consolidate small orders from multiple, redundant suppliers, and automatically see that both suppliers and buyers are honoring the pricing and terms agreed upon in the contract. To have better suppliers, you also have to be a better customer—compliance works both ways.

The Result:
Patient care and safety are optimized, and wasteful and unnecessary spending is eliminated, thus lowering costs and keeping operations lean and efficient.

3: Maximize the Machines

Using BI and analytics tools, health care analytics teams can monitor essential hardware to predict and prevent breakdowns.

Use Case:
Patient care and safety depend on the availability and accurate performance of medical equipment—and that reliability depends on the proper maintenance of the equipment.

Being able to predict equipment failures in advance, based on maintenance standards as well as past performance and maintenance, ensures that equipment will be available when needed and perform reliably. This can be accomplished by:

  • Remotely sensing operational data from equipment
  • Analyzing and monitoring equipment data
  • Correlating equipment data with business information to predict future malfunctions
  • Optimizing maintenance and service operations by ensuring that work is performed at the right time

BI tools, such as SAP Predictive Maintenance and Service, enable health care organizations to aggregate and analyze this data, and so to monitor the performance of essential devices closely, says Arck.

Meanwhile, Jonathan Kucharski, enterprise sales manager of BI firm iDashboards, points out that BI and analytics dashboards can provide IT teams with insight into essential non-medical hardware—including servers, computers, mobile devices, printers and beyond. The dashboard aggregates the data and consolidates it in a central panel, enabling teams to monitor performance and providing real-time visibility into hardware wear and tear.

For instance, a dashboard can show when a server is reaching capacity: Armed with this information, the health care IT team can carry out an upgrade in advance, rather than waiting for machine failure to alert them of the problem after the fact.

Crucially, the dashboard provides real-time visualizations of performance, enabling IT teams to predict breakdowns and seek solutions, or even to replace technology proactively.

The Result:
Arck cites some illuminating statistics from SAP benchmarking services. These show that, when comparison to organizations that don’t, health care organizations practicing reactive maintenance and service and adopting preventive and predictive maintenance and service achieve:

  • 44 percent lower unplanned downtime
  • 17 percent lower annual service and maintenance costs
  • 28 percent higher return on assets

Meanwhile, patient safety is boosted, repair and maintenance costs are reduced and the likelihood of losing revenue due to downtime or equipment failure is reduced.

What Can You Do Next?

Data analytics represents a brave new world of possibilities for health care providers. If you’ve decided to purchase BI and analytics software, what can you, as a buyer, do next?

Finding a trusted resource for choosing software can help. Our team of Software Advisors has expert knowledge of over 40 BI platforms, and has assisted more than 1,000 buyers in finding solutions that are right for them.

Here are three things you can do right now:

Follow these steps, and you, too can tap into the powerful insights that BI and analytics platforms offer health care organizations.

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