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IDENTIFYING MEALS ON WHEELS CLIENTS AT RISK OF HOSPITALIZATION: A STRATEGY FOR ALLOCATING EXTRA HEALTH SERVICES

机译:识别有住院风险的轮船上的用餐者:分配额外健康服务的策略

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摘要

Increasingly, Meals on Wheels (MOW) programs are supplementing home-delivered meals with additional services, like in-home health and safety assessments. Due to limited MOW operating budgets, it is important for special services to be targeted to those who will most benefit. Using MOW administrative data linked to Medicare claims and census data, we performed a retrospective cohort analysis of 8,236 newly enrolled MOW clients from a convenience sample of nine programs across the US to identify characteristics of clients at highest risk for adverse outcomes. The hierarchical outcome variable was derived from clients’ outcomes 30 days after MOW enrollment; 1) 7,487 clients (91%) were alive with no inpatient admission (reference group), 2) 669 clients (8%) had one or more inpatient admission, and 3) 80 clients (1%) had died. We examined clients’ demographic, health, and residential characteristics as predictors of inpatient utilization, adjusting for the competing risk of death in a multinomial logistic regression with program fixed effects. Results suggest 65–74 year-old clients had a higher relative risk of an inpatient admission than older enrollees (RR=1.347, 95% CI [1.063, 1.707]). Presence of a chronic condition diagnosis (e.g. hypertension or depression) prior to enrollment conferred excess risk of inpatient admission, as did an inpatient admission (RR=1.663, 95% CI [1.367, 2.024]) or an emergency department visit (RR=1.661, 95% CI [1.298, 2.126]) in the 30 days prior to enrollment. Our results can help target health services to high-risk clients in MOW programs and further supports the integration of medical and social services.
机译:车轮餐(MOW)计划越来越多地通过家庭健康和安全评估等其他服务来补充家庭提供的餐点。由于MOW的运营预算有限,因此将特殊服务定位于受益最大的人群非常重要。使用链接到Medicare索赔和人口普查数据的MOW行政数据,我们从美国9个项目的便利样本中对8,236名新入职的MOW客户进行了回顾性队列分析,以识别出现不良后果风险最高的客户的特征。分级结果变量是从MOW注册后30天从客户的结果得出的; 1)没有住院的在世患者有7,487名(91%)(参考组),2)有一次或多次住院的有669名患者(8%),以及3)死亡的有80名患者(1%)。我们检查了客户的人口统计学,健康状况和居住特征,将其作为住院使用率的预测指标,并通过具有程序固定效应的多项逻辑回归来调整死亡的竞争风险。结果表明,65-74岁的患者住院患者的相对风险高于老年患者(RR = 1.347,95%CI [1.063,1.707])。入院前存在慢性病诊断(例如高血压或抑郁症)会导致住院的风险过高,住院患者(RR = 1.663,95%CI [1.367,2.024])或急诊就诊(RR = 1.661) ,在注册之前的30天内达到95%CI [1.298,2.126]。我们的结果可以帮助在MOW计划中为高风险客户提供健康服务,并进一步支持医疗和社会服务的整合。

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