PeraHealth, based in Charlotte, North Carolina, recently won FDA clearance for its PeraTrend clinical surveillance offering, which relies on smart algorithms to predict dangerous oncoming health issues, such as cardiac and pulmonary arrest, while the patient is in the hospital.
The algorithms are based on the Rothman Index, a measure of how well a patient is doing, combined with data gathered from the patient’s electronic health record. The two are used to calculate risks, help visualize the relevant parameters in a proper context, and help make quick and proper clinical decisions. The Rothman Index is constantly recalculated as new data comes in, and it has been shown to have a pretty good ability to predict things such as 24-hour mortality, discharge disposition, readmission, and ICU mortality.
Here’s a bit of info on the Rothman Index itself, according to PeraHealth:
The RI is based on a heuristic model that uses a range of physiological measures, including labs, vitals, and most importantly nursing assessments. The model transforms each input into a common representation of univariate risk, allowing heterogeneous data to be summed, solving the data fusion problem. The result is a continuous measure of patient condition, integrated into the EHR, computed on a real-time basis across all conditions, diseases and care settings.
Product info page: PeraTrend…
Via: PeraHealth…