Lessons from Surgical Analytics Pioneers
Robert Wood Johnson University Hospital in New Brunswick, N.J. went live with data analytics software in its surgical suite in early 2012. After the second quarter, Amy Smith, vice president of perioperative services, ran her first quarterly report analyzing staffing and operating room use.
Robert Wood Johnson University Hospital in New Brunswick, N.J. went live with data analytics software in its surgical suite in early 2012. After the second quarter, Amy Smith, vice president of perioperative services, ran her first quarterly report analyzing staffing and operating room use.
The report showed that too many staff members were scheduled early each day and not enough in the mid-afternoon. After rearranging schedules the hospital saved $500,000 in overtime during the last three quarters of the year. "It was one of those 'Ah-Ha!' moments," Smith recalls.
With the analytics software from the hospital's core perioperative vendor Surgical Information Systems, Smith is tracking operating room turnaround times, on-time case starts, overtime and OR use. With the information Smith can discover where bottlenecks happen that can shrink operating room use, cutting into the biggest revenue drivers for hospitals.
Data is fed into the analytics dashboard from the SIS perioperative system. For each surgery she knows how long it takes to prep the patient, when the first incision was made, actual time in surgery--from the time when the patient is wheeled in to when he's wheeled out--and how long it takes to clean the room and prep it for the next patient. If cases don't start on time, Smith knows the reason. It could be that the paperwork was incomplete or the surgeon was late, or blood wasn't cross-matched before surgery, housekeeping wasn't available, or the previous surgeon didn't block enough time for the procedure.
She found that the failure to book adequate time was a major cause of scheduling snafus. An analysis of 1,300 procedures found that 500 cases ran over the expected time. Smith also knows who are the chronically late surgeons and is working with them to eliminate that issue.
Understanding and preventing logjams increased case volume in the surgical department and added $3.5 million to the bottom line in 2012, Smith says. "With analytics I realized we had capacity and where it was, and could open block times and increase volume," she says.
Joe Goedert’s feature story in the August issue of Health Data Management looks at the experiences and lessons of early users of surgical data analytics.
The report showed that too many staff members were scheduled early each day and not enough in the mid-afternoon. After rearranging schedules the hospital saved $500,000 in overtime during the last three quarters of the year. "It was one of those 'Ah-Ha!' moments," Smith recalls.
With the analytics software from the hospital's core perioperative vendor Surgical Information Systems, Smith is tracking operating room turnaround times, on-time case starts, overtime and OR use. With the information Smith can discover where bottlenecks happen that can shrink operating room use, cutting into the biggest revenue drivers for hospitals.
Data is fed into the analytics dashboard from the SIS perioperative system. For each surgery she knows how long it takes to prep the patient, when the first incision was made, actual time in surgery--from the time when the patient is wheeled in to when he's wheeled out--and how long it takes to clean the room and prep it for the next patient. If cases don't start on time, Smith knows the reason. It could be that the paperwork was incomplete or the surgeon was late, or blood wasn't cross-matched before surgery, housekeeping wasn't available, or the previous surgeon didn't block enough time for the procedure.
She found that the failure to book adequate time was a major cause of scheduling snafus. An analysis of 1,300 procedures found that 500 cases ran over the expected time. Smith also knows who are the chronically late surgeons and is working with them to eliminate that issue.
Understanding and preventing logjams increased case volume in the surgical department and added $3.5 million to the bottom line in 2012, Smith says. "With analytics I realized we had capacity and where it was, and could open block times and increase volume," she says.
Joe Goedert’s feature story in the August issue of Health Data Management looks at the experiences and lessons of early users of surgical data analytics.
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