Correlates for the risk of specialist ID hospital admission for people with intellectual disabilities: development of the LDNAT inpatient index

PAINTER, Jon, INGHAM, Barry, TREVITHICK, Liam, HASTINGS, Richard P. and ROY, Ashok (2018). Correlates for the risk of specialist ID hospital admission for people with intellectual disabilities: development of the LDNAT inpatient index. Tizard Learning Disability Review, 23 (1), 42-50. [Article]

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Abstract
Purpose: The aim of this study was to analyse ratings data from the recently developed Learning Disability Needs Assessment Tool (LDNAT) to identify factors associated with specialist intellectual disability (ID) hospital admissions. Design/methodology/approach: Ratings from 1,692 individuals were analysed and the LDNAT items differing significantly between inpatients and non-inpatients were identified. Statistical analyses on total scores derived from these items were used to calculate an optimal cut-off. This LDNAT Inpatient Index score was also confirmed via an alternative statistical technique.. Findings: On average, 18 of the 23 LDNAT item ratings were significantly higher in people with ID assessed as inpatient compared to those rated in community settings. Using the total of these items, the resulting LDNAT Inpatient Index was analysed. A cut-off score of 22.5 was calculated to be the optimal balance between sensitivity (.833) and specificity (.750). This was confirmed by calculating the Youden index (j= .583). At this level 68% of inpatients and 81% of non-inpatient cases were correctly identified. Practical implications: Currently there is a national (UK) programme to radically reduce the amount of specialist inpatient care for people ID. This will necessitate early identification of individuals most at risk of admission together with investment in improved, proactive community services if admissions to a diminishing bed-base are to remain manageable. Originality/value: This study confirms the associations between mental health difficulties, challenging behaviour and specialist hospital admissions for people with ID, extending existing research by translating these findings into a clinically usable risk index.
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