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3 ways data analytics can reduce total healthcare costs

3 ways data analytics can reduce total healthcare costs

You want to provide the best care possible to each patient who walks through your hospital's doors, but you also need to keep cost of care low in order to keep those doors open and help patients for years to come. This can often be a tough balancing act for healthcare leaders. However, with the help of data analytics, your organization may be able to provide more personalized services to patients while reducing the total costs of care.

To date, these capabilities are largely underutilized: A KPMG survey of healthcare facilities found that only 10 percent of healthcare professionals use advanced data analytics tools with both analytic and predictive capabilities. By using analytics to reduce costs in ways that do not impact quality of care, you can use the savings to improve the service provided to each patient. Hospitals that do not use data analytics to reduce cost of care are effectively leaving money on the table.

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The following are three ways that healthcare analysis and data analytics are currently helping medical providers find cost-saving opportunities.

By using analytics, Beaufort Memorial Hospital in South Carolina determined that it could save an estimated $435,000 each year by discharging patients half a day early, according to U.S. News & World Report. The facility's IT department now analyzes 180 parameters and reports on key data points to plan prescriptions, follow-up visits, wheelchair transportation and room cleaning to reduce lag time between patient treatment steps. This has helped improve patient satisfaction and hospital costs.

Because Beaufort is typically at capacity, reducing the length of hospital stays by even just a few hours allows the hospital to better serve patients who are waiting for care. By setting small goals for the staff, such as assigning patients to beds in under 10 minutes, the hospital has seen an overall reduction in average stay length. Most importantly, staff support the process because the objectives are feasible.;

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