Abstract：
BACKGROUND: Time in healthcare facilities is associated with worse patient quality of life (QoL); however, impact on family caregiver QoL is unknown. We evaluate care recipient days not at home-days in the emergency department (ED), inpatient (IP) care, and post-acute care (PAC)-to understand how care recipient days not at home correspond to family caregiver QoL.
METHODS: Secondary data were linked to care recipient utilization data. Elastic net machine learning models were used to evaluate the impact of a single day of utilization in each setting on binary QoL outcomes. We also compared composite weighted and unweighted \"days not at home\" variables. Two time periods, 6 and 18 months, were used to predict three caregiver QoL measures (self-rated health, depressive symptoms, and subjective burden).
RESULTS: In the 6-month timeframe, a single day of ED utilization was associated with increased likelihood of poor QoL for all three assessed outcomes (range: 1.4%-3.2%). A day of PAC was associated to a modest degree with increased likelihood of caregiver burden (0.2%) and depressive symptoms (0.1%), with a slight protective effect for self-rated health (-0.1%). An IP day had a slight protective effect (-0.2 to -0.1%). At 18 months, ED and IP had similar, albeit more muted, relationships with caregiver burden and depressive symptoms. PAC had a slight protective effect for caregiver burden (-0.1%). Cumulative days in all settings combined generally was not associated with caregiver QoL.
CONCLUSIONS: Whereas total care recipient time away from home had some negative spillovers to family caregivers, the countervailing effects of unique settings on caregiver QoL may mask net QoL effects. This finding limits the utility of a single care recipient home time measure as a valid caregiver-centered measure. Considering cumulative care recipient time in individual settings separately may be needed to reveal the true net effects on caregiver QoL.
METHODS: Secondary data were linked to care recipient utilization data. Elastic net machine learning models were used to evaluate the impact of a single day of utilization in each setting on binary QoL outcomes. We also compared composite weighted and unweighted \"days not at home\" variables. Two time periods, 6 and 18 months, were used to predict three caregiver QoL measures (self-rated health, depressive symptoms, and subjective burden).
RESULTS: In the 6-month timeframe, a single day of ED utilization was associated with increased likelihood of poor QoL for all three assessed outcomes (range: 1.4%-3.2%). A day of PAC was associated to a modest degree with increased likelihood of caregiver burden (0.2%) and depressive symptoms (0.1%), with a slight protective effect for self-rated health (-0.1%). An IP day had a slight protective effect (-0.2 to -0.1%). At 18 months, ED and IP had similar, albeit more muted, relationships with caregiver burden and depressive symptoms. PAC had a slight protective effect for caregiver burden (-0.1%). Cumulative days in all settings combined generally was not associated with caregiver QoL.
CONCLUSIONS: Whereas total care recipient time away from home had some negative spillovers to family caregivers, the countervailing effects of unique settings on caregiver QoL may mask net QoL effects. This finding limits the utility of a single care recipient home time measure as a valid caregiver-centered measure. Considering cumulative care recipient time in individual settings separately may be needed to reveal the true net effects on caregiver QoL.
摘要：
背景：医疗机构中的时间与患者的生活质量（QoL）恶化有关；然而，对家庭照顾者QoL的影响未知。我们评估护理接受者不在家的天数-急诊科(ED)的天数，住院（IP）护理，和急性后护理（PAC）-了解护理接受者不在家的日子如何与家庭护理人员的QoL相对应。
方法：次要数据与护理接受者利用数据相关联。使用弹性网络机器学习模型来评估每种设置中的单日利用率对二元QoL结果的影响。我们还比较了复合加权和未加权的“不在家天数”变量。两个时间段,6个月和18个月，用于预测三种护理人员的QoL测量(自评健康状况，抑郁症状,和主观负担)。
结果：在6个月的时间范围内，在所有3项评估结局中,ED利用单日与QoL差的可能性增加相关(范围:1.4%-3.2%).一天的PAC与照顾者负担（0.2％）和抑郁症状（0.1％）的可能性增加有一定程度的相关性。对自我评估的健康有轻微的保护作用（-0.1％）。IP日具有轻微的保护作用(-0.2至-0.1%)。18个月时,ED和IP相似，尽管更静音，与照顾者负担和抑郁症状的关系。PAC对照顾者负担有轻微的保护作用(-0.1%)。所有情况下的累积天数通常与护理人员QoL无关。
结论：尽管护理接受者离开家的总时间对家庭护理人员有一些负面的溢出效应，独特设置对护理人员QoL的抵消效应可能掩盖净QoL效应。这一发现限制了单一护理接受者家庭时间测量作为有效的以护理人员为中心的测量的效用。可能需要单独考虑个人设置中的累积护理接受者时间，以揭示对护理人员QoL的真实净影响。
方法：次要数据与护理接受者利用数据相关联。使用弹性网络机器学习模型来评估每种设置中的单日利用率对二元QoL结果的影响。我们还比较了复合加权和未加权的“不在家天数”变量。两个时间段,6个月和18个月，用于预测三种护理人员的QoL测量(自评健康状况，抑郁症状,和主观负担)。
结果：在6个月的时间范围内，在所有3项评估结局中,ED利用单日与QoL差的可能性增加相关(范围:1.4%-3.2%).一天的PAC与照顾者负担（0.2％）和抑郁症状（0.1％）的可能性增加有一定程度的相关性。对自我评估的健康有轻微的保护作用（-0.1％）。IP日具有轻微的保护作用(-0.2至-0.1%)。18个月时,ED和IP相似，尽管更静音，与照顾者负担和抑郁症状的关系。PAC对照顾者负担有轻微的保护作用(-0.1%)。所有情况下的累积天数通常与护理人员QoL无关。
结论：尽管护理接受者离开家的总时间对家庭护理人员有一些负面的溢出效应，独特设置对护理人员QoL的抵消效应可能掩盖净QoL效应。这一发现限制了单一护理接受者家庭时间测量作为有效的以护理人员为中心的测量的效用。可能需要单独考虑个人设置中的累积护理接受者时间，以揭示对护理人员QoL的真实净影响。
