Readmission Prediction Score Validated in Multi-country Study

A score derived from seven clinical variables "has the potential to easily identify patients in need of more intensive transitional care interventions to prevent avoidable hospital readmissions," researchers conclude.

Until now it has been known that certain interventions are effective in reducing 30-day readmissions, such as coordinating nurse visits at home. But it has also been known that a blanket application of these interventions to everyone who's discharged is not cost effective.

That's why the so-called HOSPITAL score, which an international, multicenter study has shown to successfully predict patients at high risk of a 30-day potentially avoidable readmission, has the potential to benefit hospitals and health systems. The study was published in JAMA Internal Medicine.

The HOSPITAL score is an acronym created to identify the variables associated with 30-day hospital readmissions:

• Hemoglobin level
• Discharge from an Oncology service
• Sodium level
• Procedure during the index admission;
• Index Type of admission (urgent)
• Number of Admissions during the last 12 months
• Length of stay 

Ideally, the score would be automatically calculated using an organization's e-health resources.

"Studies show that some interventions can reduce the risk of readmissions," says Jacques Donzé, MD, MSc, lead author of the study and research associate at Brigham and Women's Hospital, and associate physician at the Bern University Hospital (Switzerland). But they are often complex and very demanding.

"We need to target the patients who are most likely to benefit from these interventions," he says.

"This tool is actually pretty easy to use, with only seven variables," Donzé points out, and the information is readily available at discharge.

The researchers used data from 117,065 adult patients who were discharged from nine different hospitals across four countries, and gave each patient a score between 0 and 13, which reflects the risk of readmission.

Within 30 days of discharge, 15% of the medical patients had a readmission, and 9.7% had a potentially avoidable readmission. Using the HOSPITAL score, 62% of the patients were categorized as low risk (with a score of four points or less), 24% as intermediate risk, and 14% as high risk (with a score of seven points or more) for a potentially avoidable readmission.

The high-risk patients had four times the risk of being readmitted within 30-days as compared to patients at low risk.

"We can say now the score works," Donzé says.  In addition, a 30-day potentially avoidable readmission was predicted with a 72% probability using the HOSPITAL score, and the predicted probabilities of readmission in each risk category matched exactly the real observed proportion of readmission.

Donzé says he and his team were pleasantly surprised that the score performed as well in the validation study as it did when they first derived the score.

"It has a good generalizability," he says.

Now, the researchers have to prove that using the score to target interventions will reduce 30-day readmissions among this high-risk group.

"The aim, really, now is to say, we can better notify the patients who are at high risk for readmission," he says, and then target interventions to only those patients. "We still need to show that the interventions will reduce readmission by these patients."

That means the next research step, Donzé says, is a randomized controlled study in which the researchers provide interventions to some high-risk patients and not to other high-risk patients. They hope to begin that research early next year.

"We expect the interventions to be even more efficient than when they are simply given to all the patients," he says.