How Predictive Modeling Cuts Hospital Readmissions
Mount Sinai hopes to integrate the risk score into the EMR and use it in conjunction with the transitional social worker's assessment to develop a tiered approach to intervention. "Patients at low risk for readmission may do best with a single follow-up call postdischarge, while a moderate-risk patient may need several calls. This is one way in which the predictive model could have a direct impact on the allocation of resources," Basso Lipani says.
"We wondered if modeling readmissions was going to require us to use more data and create a complex score, but we're validating that a simple [admission history] approach works, and we believe it can be set up easily, regardless of where [an organization] is located, its size, or the level of IT support," says Kalman.
The predictive model and transitional care program is showing promise, so much so that Mount Sinai has four federal proposals and PACT is a part of each of them. "The institution really sees this [approach] as a positive, and it has a desire to see it incorporated into future designs, be it ACO or a medical home," she adds.
Cincinnati Children's Hospital Medical Center: Proactive care and readmission rates
Given the young, average age of the patients at Cincinnati Children's Hospital Medical Center, the decision to create a predictive model program wasn't primarily directed at reducing readmissions, explains Frederick C. Ryckman, MD, senior vice president for medical operations and professor of surgery at CCHMC. Rather it was directed at changing the hospital's approach to care from reactive to proactive. However, the preventable admission rates were positively influenced, he says.
"[Predictive modeling] leads to better communication, better coordination of care, and better outcomes—it's the key to preventable admissions," he says. "Our hypothesis is that a lot of healthcare is very predictable, and if you're able to predict at-risk situations, you can preempt them by building robust mitigation strategies. You can deliver better care, improve [patient] safety, use your capacity and space more efficiently, and create a better patient experience overall by preventing problems."
Several years ago, the organization decided to make the shift from reactive care to proactive care, and Ryckman explains that data was essential. His colleague, Stephen Muething, MD, the organization's vice president of safety, started analyzing and modeling data in specific areas of the hospitals to see patterns that would identify patients at risk for complications.
"We wanted to understand when an event might occur, so we could plan for how to react when an adverse event actually happened. We could come up with a solution to prevent the situation or be better prepared to handle it," Ryckman says.
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