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  5. Risk Factors For Hospitalization Of Home Hospice Enrollees: Development And Validation Of A Predictive Tool.

Risk Factors For Hospitalization Of Home Hospice Enrollees: Development And Validation Of A Predictive Tool.

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2017-PHONGTANKUEL-RISK_FACTORS_FOR_HOSPITALIZATION_OF_HOME_HOSPICE_ENROLLEES__DEVELOPMENT_AND_VALIDATION_OF_A_PREDICTIVE_TOOL_.pdf (398.59 KB)
Permanent Link(s)
https://hdl.handle.net/1813/64742
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Weill Cornell Theses and Dissertations
Author
Phongtankuel, Veerawat
Abstract

Background: Over 10% of hospice patients experience at least one care transition 6-months prior to death. Transitions at the End-of-Life (EoL), 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. Objectives: To develop and validate a model predictive of hospitalization after enrollment into home hospice using pre-hospice admission risk factors. Design: Retrospective cohort study using Medicare fee-for-service claims. Subjects: Patients enrolled into the Medicare Hospice Benefit >= 18 years old in 2012. Outcome Measured: Hospitalization within 2 days from a hospice discharge. Results: We developed a predictive model using 61,947 hospice enrollments, of which 3,347 (5.4%) underwent a hospitalization. Seven variables were associated with hospitalization: age 18-55 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 non-cancer 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%. Conclusions: 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.

Date Issued
2017
Keywords
disenrollment
•
end of life
•
hospice
•
hospitalization
Degree Discipline
Clinical & Translational Investigation
Degree Level
Master of Science
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights URI
https://creativecommons.org/licenses/by-nc-nd/4.0/
Type
dissertation or thesis

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