Background: Mortality prediction models are increasingly being adopted in the clinical setting, both to retrospectively assess quality of care and to prospectively inform clinical practice. An open question is whether a particular hospital should employ a model trained using a diverse nationwide dataset or use a model developed primarily from local data. The Veterans Affairs [...]

Background: Diagnostic errors (DEs) represent ongoing threats to patient safety in the hospital. Little is known about the factors present on admission that can predict DE during the hospital encounter. Such knowledge is essential for prospective identification of hospitalized patients at risk for DE who can be targeted for early intervention. The purpose of this [...]

Background: Mortality prediction models are increasingly being adopted in the clinical setting, both to retrospectively assess quality of care and to prospectively inform clinical practice. An open question is whether a particular hospital should employ a model trained using a diverse nationwide dataset or use a model developed primarily from local data. The Veterans Affairs [...]

Background: Diagnostic errors (DEs) represent ongoing threats to patient safety in the hospital. Little is known about the factors present on admission that can predict DE during the hospital encounter. Such knowledge is essential for prospective identification of hospitalized patients at risk for DE who can be targeted for early intervention. The purpose of this [...]

Background: Discharge to post-acute care settings (PACs), such as skilled nursing facilities (SNFs), requires significant, complex discharge planning which often needs to be started early during hospitalization to be complete by time of discharge. This study sought to identify and model factors which predict a given patient’s likelihood of requiring PAC after discharge, using routinely [...]

Background: Delirium is associated with increased morbidity, mortality and health care costs in the hospital setting secondary to increased length of stay and poor long term outcomes (1,2). A systematic review of different delirium prediction models found limitations with these models including derivation from small patient populations, lack of heterogeneity, accuracy and reliability as noted [...]

Background: Hospitalized COIVD-19 patients are complex and heterogenous with regards to socio-demographics and comorbidities and many patients are at heightened risk for adverse clinical outcome. Early risk stratification enables clinical decision making for appropriateness and timeliness of interventions. Since the pandemic began, more than 100 models to forecast prognosis for hospitalized patients with COVID 19 [...]

Background: Delirium prevention by multicomponent interventions is proven, with strong evidence confirming its effectiveness in both medical and surgical populations. Identifying high risk patients is very important for resource allocation and utilization. Risk factors for delirium are broadly classified into predisposing and precipitating factors. Combinations of these risk factors precipitate delirium and hence a prediction [...]

Background: Complex patients represent a challenge in the health care system, as they are frequently associated with high health care utilization, longer hospital stays, and higher costs. Nonetheless, the characteristics of the complex patients in the hospital setting are not well known, and tools to help hospitals to identify them early in the process of [...]

Background: We conducted a pilot study in an acute care hospital and developed the Saga Fall Risk Model 2 (SFRM2), a fall prediction model comprising eight items: Bedriddenness rank, age, sex, emergency admission, admission to the neurosurgery department, history of falls, independence of eating, and use of hypnotics. Bedriddenness rank is an official scale of [...]