PeraServer and PeraTrend

The PeraServer and PeraTrend System is a software platform that calculates and displays the Rothman Index, a composite score derived from patient EHR data including vital signs, nursing assessments, and lab values. Its purpose is to provide healthcare professionals with a quantitative measure of patient physiological status and statistical mortality risk, thereby serving as an adjunct to clinical decision support across various hospital settings.

The PeraServer and PeraTrend System is a software-based medical device designed to assist healthcare providers in assessing patient condition. PeraServer, the backend component, imports electronic health record (EHR) data, encompassing vital signs, nursing assessments, and laboratory results, to compute the Rothman Index (RI) score. This RI score, along with associated configurable warnings, is stored for analysis. PeraTrend serves as the frontend, web-based user interface, enabling clinicians to view, display, and trend these RI scores and related measures, providing graphical representations over time and comparisons of the RI with its input data. The Rothman Index itself is a single, quantitative measure reflecting a patient's overall physiologic status, derived from the aggregate statistical mortality risk associated with the values of their vital signs, nursing assessments, and selected lab data. The PeraServer/PeraTrend system is intended for use throughout hospital settings, such as emergency departments, general wards, and intensive care units, for neonatal, pediatric, and adult patients, although it is not intended for use in the Neonatal Intensive Care Unit. Retrospective studies have been conducted to validate the mechanics of both adult and pediatric RI scores and to compare the RI with other early warning systems like MEWS, demonstrating its performance in reflecting underlying patient conditions.

AI Regulatory Concerns

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• Q1. How does the Rothman Index's algorithm specifically weigh different input parameters (vital signs, nursing assessments, labs) and how sensitive is it to variations in individual data points?; What are the computational requirements and typical EHR integration challenges encountered when deploying the PeraServer backend in diverse hospital IT environments?; What specific training or protocols are recommended for clinical staff to effectively interpret PeraTrend displays and integrate Rothman Index scores into their decision-making processes without over-reliance?; Beyond general mortality risk, how has the Rothman Index been validated for predicting specific clinical deterioration events or guiding targeted interventions in neonatal, pediatric, and adult populations?; What is the performance of the PeraServer/PeraTrend system when dealing with rapidly changing patient conditions, and how frequently are Rothman Index scores updated from EHR data?