反映生活质量的家庭时间测量:基于数据的医疗利用时间框架和环境的调查。

Informing a home time measure reflective of quality of life: A data driven investigation of time frames and settings of health care utilization.

机构信息

Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Medical Center, Durham, North Carolina, USA.

Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA.

出版信息

Health Serv Res. 2023 Dec;58(6):1233-1244. doi: 10.1111/1475-6773.14196. Epub 2023 Jun 25.

Abstract

OBJECTIVE

To evaluate short- and long-term measures of health care utilization-days in the emergency department (ED), inpatient (IP) care, and rehabilitation in a post-acute care (PAC) facility-to understand how home time (i.e., days alive and not in an acute or PAC setting) corresponds to quality of life (QoL).

DATA SOURCES

Survey data on community-residing veterans combined with multipayer administrative data on health care utilization.

STUDY DESIGN

VA or Medicare health care utilization, quantified as days of care received in the ED, IP, and PAC in the 6 and 18 months preceding survey completion, were used to predict seven QoL-related measures collected during the survey. Elastic net machine learning was used to construct models, with resulting regression coefficients used to develop a weighted utilization variable. This was then compared with an unweighted count of days with any utilization.

PRINCIPAL FINDINGS

In the short term (6 months), PAC utilization emerged as the most salient predictor of decreased QoL, whereas no setting predominated in the long term (18 months). Results varied by outcome and time frame, with some protective effects observed. In the 6-month time frame, each weighted day of utilization was associated with a greater likelihood of activity of daily living deficits (0.5%, 95% CI: 0.1%-0.9%), as was the case with each unweighted day of utilization (0.6%, 95% CI: 0.3%-1.0%). The same was true in the 18-month time frame (for both weighted and unweighted, 0.1%, 95% CI: 0.0%-0.3%). Days of utilization were also significantly associated with greater rates of instrumental ADL deficits and fair/poor health, albeit not consistently across all models. Neither measure outperformed the other in direct comparisons.

CONCLUSIONS

These results can provide guidance on how to measure home time using multipayer administrative data. While no setting predominated in the long term, all settings were significant predictors of QoL measures.

摘要

目的

评估短期和长期医疗保健利用指标-急诊部(ED)、住院部(IP)护理和康复后的急性或康复护理设施(PAC)中的住院天数,以了解居家时间(即活着且不在急性或 PAC 环境中的天数)与生活质量(QoL)的对应关系。

数据来源

社区居住退伍军人的调查数据与医疗保健利用的多付款方行政数据相结合。

研究设计

在调查完成前的 6 和 18 个月内,VA 或 Medicare 医疗保健的利用情况,量化为在 ED、IP 和 PAC 中接受的护理天数,用于预测调查期间收集的七个与 QoL 相关的指标。弹性网络机器学习用于构建模型,使用得到的回归系数开发加权利用变量。然后将其与任何利用天数的未加权计数进行比较。

主要发现

在短期内(6 个月),PAC 利用成为 QoL 下降的最显著预测因素,而在长期(18 个月)内则没有一个环境占据主导地位。结果因结果和时间框架而异,观察到一些保护作用。在 6 个月的时间框架内,每利用一天加权都会增加日常生活活动缺陷的可能性(0.5%,95%CI:0.1%-0.9%),与未加权每天的利用情况相同(0.6%,95%CI:0.3%-1.0%)。在 18 个月的时间框架内也是如此(对于加权和未加权,0.1%,95%CI:0.0%-0.3%)。利用天数也与更大程度的工具性日常生活活动缺陷和较差/较差的健康状况显著相关,尽管并非所有模型都一致。在直接比较中,两种措施都没有表现出优势。

结论

这些结果可以为如何使用多付款方行政数据来衡量居家时间提供指导。虽然在长期内没有一个环境占据主导地位,但所有环境都是 QoL 指标的重要预测因素。

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