EHR model identifies high-risk readmission

EHRs can help predict which inpatients are at high risk for readmission in real time, according to a study published in BMC Medical Informatics and Decision Making.

Researchers analyzed the outcomes of adult patients admitted to internal medical services at seven hospitals owned by three health systems in the Dallas/Fort Worth area, to determine whether EHR-based risk models could identify patients at high risk for readmission within 30 days of discharge. They also sought to compare those models to existing, claims-based models currently used to identify these high-risk patients. The researchers created an EHR model and compared it to two claims-based models.

The model performed better than the claims-based models, and identified high-risk patients in real time shortly after admission, enabling clinicians to take responsive action sooner, according to the findings. The EHR model also doesn't require manual computation by staff because the information can be derived directly from the EHR. The model also can be used for more generalized patient populations.

"Readmission to a hospital within 30 days can be a marker of poor quality of care, but efforts to reduce such events often involve intensive resource management applied to all patients, or interventions that are timed too late in the admission to support effective multi-disciplinary efforts," the authors wrote. "Methods that can identify those at the highest risk of adverse events and allow sufficient time to initiate and coordinate the concentration of scarce resources on those most likely to benefit have great potential for accomplishing the 'triple aim' of higher quality, more cost-conscious care for patients and populations."

Read the study.