The StartBox Patient System generates safety data based on a provider or facility’s behavior. Similar to driving behavior being a predictive factor for auto insurance claims, the StartBox System can inform insurance companies of the individual medical liability risk of a client by creating risk profiles that reflect actual versus perceived risk.
This data increases transparency to actual risks, versus perceived risks based on external rating factors such as geography, number of procedures, surgical specialty, etc. Each individual insured situation can then be assessed based on their unique patient safety performance, and their risk mitigation practices. The near miss data captured through StartBox is predictive and can be used as a leading indicator to assess risk.
A published peer-reviewed study (Gloystein. Front Surg. 2020) has demonstrated success of the StartBox System. In addition to preventing patient harm, the system tracked a number of errors (such as incorrectly scheduled patient, procedure or site/laterality) revealing potential issues prior to bad outcomes occurring. Furthermore, longitudinal use of the system has demonstrated its ability to reduce errors to zero as adoption progressed.
Kim Kramer will lead StartBox in capitalizing on its goals of mitigating risk, reducing medical liability costs and increasing healthcare operational efficiencies.
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