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Driven by need, shaped by access: Heterogeneity in patient profiles and patterns of service utilization in patients with alcohol use disorders
被引:0
|作者:
Miele, Andrew S.
[1
,2
,5
]
Fleury, Marie-Josee
[3
]
Zeluff, Heather
[1
]
Mendieta, Ashley
[1
]
Phillips, Christine
[2
]
Roth, Alan
[2
]
Basello, Gina
[2
]
Nienaber, Cameron
[2
]
Crupi, Robert
[4
]
Brondolo, Elizabeth
[1
,2
]
机构:
[1] St Johns Univ, Dept Psychol, Queens, NY USA
[2] Jama Hosp Med Ctr JHMC, Queens, NY USA
[3] McGill Univ, Douglas Res Ctr, Dept Psychiat, Montreal, PQ, Canada
[4] Weill Cornell Med Coll, Ambulatory Care & Populat Hlth & Palliat Care Serv, New York, NY USA
[5] St Johns Univ, Dept Psychol, 8000 Utopia Pkwy,Room 411A,Marillac Hall, Queens, NY 11439 USA
关键词:
Alcohol use disorders;
Andersen model;
Typology;
Latent class analysis;
Health outcomes;
Health service utilization;
EMERGENCY-DEPARTMENT VISITS;
LATENT CLASS ANALYSIS;
POPULATION;
SUBTYPES;
CARE;
D O I:
10.1016/j.drugalcdep.2023.109825
中图分类号:
R194 [卫生标准、卫生检查、医药管理];
学科分类号:
摘要:
Background: Patients with alcohol-use disorders (AUDs) are highly heterogenous and account for an increasing proportion of general medical hospital visits. However, many patients with AUDs do not present with severe medical or psychiatric needs requiring immediate attention. There may be a mismatch between some patients' needs and the available services, potentially driving re-admissions and re-encounters. The current study aims to identify subgroups of AUD patients and predict differences in patterns of healthcare service use (HSU) over time. Methods: Latent class analysis (LCA) was conducted using hospital data incorporating sociodemographic, health behavior, clinical, and service use variables to identify subtypes of AUD patients, then class membership was used to predict patterns of HSU. Results. Four classes were identified with the following characteristics: (1) Patients with acute medical injuries (30 %); (2) Patients with socioeconomic and psychiatric risk factors, (11 %); (3) Patients with chronic AUD with primarily non-psychiatric medical needs (18 %); and (4) Patients with primary AUDs with low medical-treatment complexity (40 %). Negative binomial models showed that Class 4 patients accounted for the highest frequency of service use, including significantly higher rates of emergency department reencounters at 30 days and 12 months. Conclusions: The profile and patterns of HSU exhibited by patients in class 4 suggest that these patients have needs which are not currently being addressed in the emergency department. These have implications for how resources are allocated to meet the needs of patients with AUDs, including those who make frequent visits to the emergency department without high acuity medical needs.
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