Phongtankuel Veerawat, Johnson P, Reid M C, Adelman R D, Grinspan Z, Unruh M A, Abramson E
1 Department of Medicine, Division of Geriatrics and Palliative Medicine, Joan and Sanford I Weill Medical College of Cornell University, New York, NY, USA.
2 Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY, USA.
Am J Hosp Palliat Care. 2017 Nov;34(9):806-813. doi: 10.1177/1049909116659439. Epub 2016 Jul 22.
Over 10% of hospice patients experience at least 1 care transition 6 months prior to death. Transitions at the end of life, particularly from hospice to hospital, result in burdensome and fragmented care for patients and families. Little is known about factors that predict hospitalization in this population.
To develop and validate a model predictive of hospitalization after enrollment into home hospice using prehospice admission risk factors.
Retrospective cohort study using Medicare fee-for-service claims.
Patients enrolled into the Medicare hospice benefit were ≥18 years old in 2012.
Hospitalization within 2 days from a hospice discharge.
We developed a predictive model using 61 947 hospice enrollments, of which 3347 (5.4%) underwent a hospitalization. Seven variables were associated with hospitalization: age 18 to 55 years old (adjusted odds ratio [95% confidence interval]: 2.94 [2.41-3.59]), black race (2.13 [1.93-2.34]), east region (1.97 [1.73-2.24]), a noncancer diagnosis (1.32 [1.21-1.45]), 4 or more chronic conditions (8.11 [7.19-9.14]), 2 or more prior hospice enrollments (1.75 [1.35-2.26]), and enrollment in a not-for-profit hospice (2.01 [1.86-2.18]). A risk scoring tool ranging from 0 to 29 was developed, and a cutoff score of 18 identified hospitalized patients with a positive predictive value of 22%.
Reasons for hospitalization among home hospice patients are complex. Patients who are younger, belong to a minority group, and have a greater number of chronic conditions are at increased odds of hospitalization. Our newly developed predictive tool identifies patients at risk for hospitalization and can serve as a benchmark for future model development.
超过10%的临终关怀患者在死亡前6个月经历过至少1次护理转接。临终时的转接,尤其是从临终关怀机构转至医院,给患者及其家属带来了繁重且碎片化的护理。对于预测该人群住院情况的因素知之甚少。
利用临终关怀入院前的风险因素,开发并验证一个预测居家临终关怀患者入院后住院情况的模型。
使用医疗保险按服务付费理赔数据进行的回顾性队列研究。
2012年参加医疗保险临终关怀福利的患者年龄≥18岁。
临终关怀出院后2天内住院。
我们利用61947例临终关怀患者的登记信息开发了一个预测模型,其中3347例(5.4%)经历了住院治疗。七个变量与住院相关:年龄18至55岁(调整后的比值比[95%置信区间]:2.94[2.41 - 3.59])、黑人种族(2.13[1.93 - 2.34])、东部地区(1.97[1.73 - 2.24])、非癌症诊断(1.32[1.21 - 1.45])、4种或更多慢性病(8.11[7.19 - 9.14])、2次或更多次先前的临终关怀登记(1.75[1.35 - 2.26])以及在非营利性临终关怀机构登记(2.01[1.86 - 2.18])。开发了一个范围从0到29的风险评分工具,临界值为18可识别住院患者,其阳性预测值为22%。
居家临终关怀患者住院的原因很复杂。年龄较小、属于少数群体且患有更多慢性病的患者住院几率增加。我们新开发的预测工具可识别有住院风险的患者,并可作为未来模型开发的基准。