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Embedding an Evidence-Based Model for Suicide Prevention in the National Health Service: A Service Improvement Initiative
被引:9
作者:
Brown, Sophie
[1
,2
]
Iqbal, Zaffer
[1
,2
]
Burbidge, Frances
[1
,2
]
Sajjad, Aamer
[2
]
Reeve, Mike
[2
]
Ayres, Victoria
[2
]
Melling, Richard
[2
]
Jobes, David
[3
]
机构:
[1] Univ Hull, Fac Hlth Sci, Dept Psychol, Kingston Upon Hull HU6 7RX, N Humberside, England
[2] NAViGO Hlth & Social Care Community Interest Co, Grimsby DN32 0QE, England
[3] Catholic Univ Amer, Clin Psychol Fac, Sch Arts & Sci, Dept Psychol, Washington, DC 20064 USA
关键词:
suicide prevention;
suicidality;
CAMS;
service improvement;
service model;
COLLABORATIVE ASSESSMENT;
SELF-HARM;
MANAGEMENT;
CARE;
PROFESSIONALS;
APPOINTMENT;
BEHAVIOR;
TRIAL;
D O I:
10.3390/ijerph17144920
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Despite the improved understanding of the determinants of suicide over recent decades, the mean suicide rate within the United Kingdom (UK) has remained at 10 per 100,000 per annum, with about 28% accessing mental health services in the 12 months prior to death. In this paper, we outlined a novel systems-level approach to tackling this problem through objectively differentiating the level of severity for each suicide risk presentation and providing fast-track pathways to care for all, including life-threatening cases. An additional operational challenge addressed within the proposed model was the saturation of local crisis mental health services with approximately 150 suicidality referrals per month, including non-mental health cases. This paper discussed a service improvement initiative undertaken within a National Health Service (NHS) secondary care mental health provider's open-access 24/7 crisis and home treatment service. An organisation-wide bespoke "suicide risk triage" system utilising the Collaborative Assessment and Management of Suicidality (CAMS) was implemented across all services. The preliminary impacts on suicidality, suicide rates and service user outcomes were described.
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页码:1 / 13
页数:13
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