查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating in Mississauga, C anada, by NewsRx journalists, research stated, “Identifying skilled nursing faci lity (SNF) patients at risk for hospitalization or death is of interest to SNFs, patients, and patients’ families because of quality measures, financial penalti es, and limited clinical staffing. We aimed to develop a predictive model that i dentifies SNF patients likely to be hospitalized or die within the next 7 days a nd validate the model’s performance against clinician judgment.” The news reporters obtained a quote from the research, “Retrospective multivaria te prognostic model development study. Patients in US SNFs that use the PointCli ckCare electronic health record (EHR) system. We used data from the first 100 da ys of skilled stays for 5,642,474 patients in 8440 SNFs, from January 1, 2019, t hrough March 31, 2023. We used data collected in the course of clinical care to develop a machine learning model to predict the likelihood of patient hospitaliz ation or death within the next 7 days. The data included vital signs, diagnoses, laboratory results, food intake, and clinical notes. We also asked SNF nurses a nd hospital case managers to make their own predictions as a comparison. The EHR was used as the source of information on whether the patient died or was hospit alized. The model had sensitivity of 35%, specificity of 92% , positive predictive value (PPV) of 18%, and area under the receiv er operator curve (AUC) of 0.75. A variation of the model in which we did not in clude progress notes and food intake achieved an AUC of 0.70. Nurse raters achie ved a sensitivity of 61%, specificity of 73%, and PPV of 10%. Machine learning models can accurately predict the likeliho od of hospitalization or death within the next 7 days among SNF patients.”
NETL
NSTL