Complex Patients Have More Emergency Visits: Don't Punish the Systems That Serve Them.
Complex Patients Have More Emergency Visits: Don't Punish the Systems That Serve Them.
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DOI：
10.1097/mlr.0000000000001515
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发表时间：
2021-04-01
期刊：
影响因子：
3
通讯作者：
Ash AS
中科院分区：
文献类型：
--
作者：
Mick EO;Alcusky MJ;Li NC;Eanet FE;Allison JJ;Kiefe CI;Ash AS
更好的病人管理可以减少急诊科(ED)的使用。绩效衡量应该奖励通过可预见的高使用率患者来减少使用率的计划，而不是奖励那些回避他们的计划。为诊断患有严重精神疾病(SMI)或物质使用障碍(SUD)的人开发一种ED使用的质量衡量标准，考虑到健康的医学和社会决定因素(SDH)风险。使用基于诊断的模型和SDH增强的模型来预测ED使用率的回归建模，以比较总体和脆弱人群的准确性。马萨诸塞州医疗补助和儿童健康保险计划马萨诸塞州马萨诸塞州医疗补助和儿童健康保险计划马萨诸塞州18-的成员，连续参加2016日历年，诊断为SMI或SUD。基于诊断的模型预测因素是根据医疗接触、年龄和性别进行的诊断。其他SDH预测指标描述了住房问题、行为健康问题、残疾和邻里层面的压力。我们预测了ED的使用率：1)使用年龄/性别，区分单一诊断或双重诊断；2)添加汇总医疗风险(DxCG)；以及3)进一步添加社会风险(SDH)。在144,981名研究对象中，57%是女性，25%被诊断为双重诊断，67%是白人/非西班牙裔，18%是住房不稳定，37%是残疾人。那些被诊断为双重诊断的成员的使用率上升了77%，有住房问题的成员上升了50%，居住在压力最大的社区的成员上升了18%。SDH模型对这些高使用率人群的预测最好，对复杂患者的计划最准确。为了为比较健康计划设定适当的基准，急诊科就诊的质量衡量标准应该根据医疗和社会风险进行调整。
Better patient management can reduce emergency department (ED) use. Performance measures should reward plans for reducing utilization by predictably high-use patients, rather than rewarding plans that shun them. To develop a quality measure for ED use for people diagnosed with serious mental illness (SMI) or substance use disorder (SUD), accounting for both medical and social determinants of health (SDH) risks. Regression modeling to predict ED use rates using diagnosis-based and SDH-augmented models, to compare accuracy overall and for vulnerable populations. MassHealth, Massachusetts’ Medicaid and Children’s Health Insurance Program MassHealth members ages 18–64, continuously enrolled for calendar year 2016, with a diagnosis of SMI or SUD. Diagnosis-based model predictors are diagnoses from medical encounters, age, and sex. Additional SDH predictors describe housing problems, behavioral health issues, disability, and neighborhood-level stress. We predicted ED use rates: 1) using age/sex and distinguishing between single or dual diagnoses; 2) adding summarized medical risk (DxCG); and 3) further adding social risk (SDH). Among 144,981 study subjects, 57% were women, 25% dually diagnosed, 67% White/Non-Hispanic, 18% unstably housed, and 37% disabled. Utilization was higher by 77% for those dually diagnosed, 50% for members with housing problems, and 18% for members living in the highest-stress neighborhoods. SDH modeling predicted best for these high-use populations and was most accurate for plans with complex patients. To set appropriate benchmarks for comparing health plans, quality measures for ED visits should be adjusted for both medical and social risks.