CIHI Data... Helps capture the true cost of care

CIHI Data... Helps capture the true cost of care

There’s nothing simple about organ transplants.

Beyond the procedure itself, pre- and post-operative care can involve long waits and weeks, months or years of tests, assessments, diagnostics and lab work.

At the Hospital for Sick Children in Toronto, kids who are in the pre-, peri- and post-transplant phases of care are all active patients in the facility’s transplant database. They move from it only if they die or turn 18 (at which point they transfer into the adult system). In recent years, there’s been steady growth in the number of children waiting for transplants, but it hasn't always been balanced by an equal movement of people off the list. That’s led to a cumulative effect in costs.

“The dilemma is that funding mechanisms typically only fund the episode where the procedure occurs,” says Irene Blais, SickKids’ director of decision support. “But it doesn’t look at the continuum of care and the impact on the organization through that continuum.”

Although some pre- and post-operative costs are funded, what’s covered doesn’t represent the full cost of the transplant program and the funding rates haven’t been revised in years.

To tell the full story, Blais turned to the hospital’s integrated data and costing systems. By illustrating activity beyond the transplant, her team was able to show that the drivers in cost and activity were growing at a faster rate than the ministry was funding them.

So what did they do?

The team started with SickKids’ registration system, as it included all patients on the transplant waiting list, as well as organ recipients and assessed patients. This allowed them to look across the continuum of care to capture the full range of patient activity. After the data had been sorted into organ groupings, Blais worked with clinical teams who provided clinical protocols outlining how many times a patient would be seen and what procedures and tests they’d have done to capture the full scope of activity.

Her team validated this work against the hospital’s comprehensive case-costing system, which has integrated data from 18 sources, including finance, diagnostics, pharmacy, labs and the operating room. So detailed is this system that Blais could determine, to the minute, how much time nurses spent with every patient every day.

Also among the 18 data sources are CIHI’s Discharge Abstract Database (DAD) and National Ambulatory Care Reporting System (NACRS). The DAD captured the reasons why patients were returning to the hospital once they’d left, whether it was rejection-related or something beyond the transplant, given the complex needs of these patients. Among other things, NACRS data told the hospital who was having dialysis or ending up in an emergency room.

“You can’t not have DAD or NACRS in there because it’s the starting point for understanding patient mix and specific patient populations,” Blais says. “Without them, we wouldn’t have known why patients were coming back.”

A Clearer Picture of the Costs

By using the data, Blais and her team were able to illustrate the true costs of transplants.

“While the bulk of the costs (41%) is still inpatient, 33% of care is delivered on an outpatient basis,” she says. “That’s a whole lot that current funding formulas aren’t taking into consideration.”

Everything outside of that 41% must come out of the hospital’s global budget, which was creating a tighter squeeze given the growing number of patients on the transplant list.

SickKids presented this information to the Ministry of Health and Long-Term Care and secured a base funding adjustment for infrastructure.

“We were able to enhance our ability to impact funding and we’re hoping that at some point they’ll review the methodology and the rates at which they fund transplants,” Blais says.

The hospital is now applying this practice to business cases across the continuum.

“For me, the journey of taking data and turning it into information makes for a more insightful organization,” Blais says. “That can be applied to all streams: operational, process improvement, strategy, research and management. When data is integrated and evidence-based, we can improve our decision-making.”