Detection and diagnosis of delirium: a study of the application of computer-assisted technologies

Delirium is a common, severe and life threatening neuropsychiatric disorder. Encountered in all healthcare settings, delirium affects approximately one in five general hospital inpatients (Ryan et al., 2013, Siddiqi et al., 2006) with delirium incidence and prevalence rates likely to rise substantially in the coming years as healthcare services provide for our increasingly aged society. Delirium impacts negatively upon morbidity, length of stay in hospital, cognitive impairment and mortality (Witlox et al., 2010), along with substantial social and healthcare costs (Leslie and Inouye, 2011). Despite its clinical importance in terms of frequency and impact, delirium is underdiagnosed and inadequately treated. This may be related to factors such as the complex and heterogenous clinical presentation of delirium, as well as the frequent mis-assumption that cognitive impairment is an expected and normal state for older inpatients, thus missing out on opportunities to identify potentially reversible and modifiable causative factors. This is further compounded by the lack of brief, objective and effective bed-side tests that are acceptable to patients and healthcare workers alike. At a service-planning level, the importance of delirium and cognitive friendly hospital initiatives are frequently neglected (O'Connell et al., 2014). Prior to DSM III (APA, 1980) and ICD10 (WHO, 1992), the lack of operationalized diagnostic criteria for delirium hampered detection and diagnosis: the emphasis in DSM 5 (APA, 2013) on the critical importance of attentional deficits, especially deficits in sustained attention, has brought clarity to the area of delirium screening, diagnosis and assessment.