Latent Class Analysis of Specialized Palliative Care Needs in Adult Intensive Care Units From a Single Academic Medical Center

单一学术医疗中心成人重症监护病房专业姑息治疗需求的潜在类别分析

阅读:2

Abstract

CONTEXT: In the intensive care unit (ICU), 14% of patients meet criteria for specialized palliative care, but whether subgroups of patients differ in their palliative care needs is unknown. OBJECTIVES: The objective of this study was to use latent class analysis to separate ICU patients into different classes of palliative care needs and determine if such classes differ in their palliative care resource requirements. METHODS: We conducted a retrospective cohort study of ICU patients who received specialized palliative care, August 2013 to August 2015. Reason(s) for consultation were extracted from the initial note and entered into a latent class analysis model to generate mutually exclusive patient classes. Differences in "high use" of palliative care (defined as having five or more palliative care visits) between classes were assessed using logistic regression, adjusting for age, race, Charlson Comorbidity Index, and length of stay. RESULTS: In a sample of 689 patients, a four-class model provided the most meaningful groupings: 1) Pain and Symptom Management (n = 218, 31.6%), 2) Goals of Care and Advance Directives (GCAD) (n = 131, 19.0%), 3) All Needs (n = 112, 16.3%), and 4) Supportive Care (n = 228, 33.1%). In comparison to GCAD patients, all other classes were more likely to require "high use" of palliative care (adjusted odds ratio [aOR] 2.61 [1.41-4.83] for "All Needs," aOR 2.01 [1.16-3.50] for "Pain and Symptom Management," aOR 1.94 [1.12-3.34] for "Supportive Care"). CONCLUSION: Based on the initial reason for consultation, we identified four classes of palliative care needs among critically ill patients, and GCAD patients were least likely to be high utilizers. These findings may help inform allocation of palliative care resources for this population.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。