Department of Neurosciences, Biomedicine, and Movement, University of Verona, Policlinico G.B. Rossi, Verona.
Department of Diagnostic and Public Health, University of Verona, Policlinico G.B. Rossi, Verona, Italy.
J Nerv Ment Dis. 2020 May;208(5):353-361. doi: 10.1097/NMD.0000000000001140.
This study explores whether clinicians or a statistical model can better identify patients at risk of early readmission and investigates variables potentially associated with clinicians' risk judgment. We focus on a total of 142 patients discharged from acute psychiatric wards in the Verona Mental Health Department (Italy). Psychiatrists assessed patients' risk of readmission at 30 and 90 days postdischarge, predicted their postdischarge compliance, and assessed their Global Assessment of Functioning (GAF) score at admission and discharge. Clinicians' judgment outperformed the statistical model, with the difference reaching statistical significance for 30-day readmission. Clinicians' readmission risk judgment, both for 30 and 90 days, was found to be statistically associated with predicted compliance with community treatment and GAF score at discharge. Clinicians' superior performance might be explained by their risk judgment depending on nonmeasurable factors, such as experience and intuition. Patients with a poorer GAF score at discharge and poor assumed compliance were predicted to have a higher risk of readmission.
本研究旨在探讨临床医生或统计模型在识别早期再入院风险方面的表现，并调查与临床医生风险判断相关的潜在变量。我们共关注了来自意大利维罗纳心理健康部门的 142 名急性精神科病房出院患者。精神科医生在出院后 30 天和 90 天评估患者的再入院风险，预测其出院后的依从性，并在入院和出院时评估其总体功能评估 (GAF) 评分。临床医生的判断优于统计模型，30 天再入院的差异具有统计学意义。临床医生的再入院风险判断，无论是 30 天还是 90 天，都与预测的社区治疗依从性和出院时的 GAF 评分存在统计学关联。临床医生表现较好的原因可能是他们的风险判断取决于不可衡量的因素，如经验和直觉。出院时 GAF 评分较低和假定依从性较差的患者被预测有更高的再入院风险。
