Pine Michael, Fry Donald E, Hannan Edward L, Naessens James M, Whitman Kay, Reband Agnes, Qian Feng, Schindler Joseph, Sonneborn Mark, Roland Jaclyn, Hyde Linda, Dennison Barbara A
1 MPA Healthcare Solutions, Inc., Chicago, IL.
2 University at Albany-State University of New York, Albany, NY.
Am J Med Qual. 2017 Mar/Apr;32(2):163-171. doi: 10.1177/1062860615626279. Epub 2016 Jul 9.
Predictive modeling for postdischarge outcomes of inpatient care has been suboptimal. This study evaluated whether admission numerical laboratory data added to administrative models from New York and Minnesota hospitals would enhance the prediction accuracy for 90-day postdischarge deaths without readmission (PD-90) and 90-day readmissions (RA-90) following inpatient care for cardiac patients. Risk-adjustment models for the prediction of PD-90 and RA-90 were designed for acute myocardial infarction, percutaneous cardiac intervention, coronary artery bypass grafting, and congestive heart failure. Models were derived from hospital claims data and were then enhanced with admission laboratory predictive results. Case-level discrimination, goodness of fit, and calibration were used to compare administrative models (ADM) and laboratory predictive models (LAB). LAB models for the prediction of PD-90 were modestly enhanced over ADM, but negligible benefit was seen for RA-90. A consistent predictor of PD-90 and RA-90 was prolonged length of stay outliers from the index hospitalization.
住院治疗出院后结局的预测模型一直不够理想。本研究评估了添加到纽约和明尼苏达医院管理模型中的入院数字实验室数据,是否会提高心脏病患者住院治疗后90天无再入院出院后死亡(PD - 90)和90天再入院(RA - 90)的预测准确性。针对急性心肌梗死、经皮心脏介入治疗、冠状动脉搭桥术和充血性心力衰竭,设计了预测PD - 90和RA - 90的风险调整模型。模型源自医院理赔数据,随后用入院实验室预测结果进行强化。使用病例水平的区分度、拟合优度和校准来比较管理模型(ADM)和实验室预测模型(LAB)。预测PD - 90的LAB模型比ADM模型略有增强,但对于RA - 90而言,益处可忽略不计。PD - 90和RA - 90的一个一致预测因素是指数住院期间延长的住院时间异常值。