This study aims to determine factors associated with psychiatric hospitalisation of patients treated for an acute psychiatric crisis who had access to intensive home treatment (IHT). This study was performed using data from a randomised controlled trial. Interviews, digital health records and eight internationally validated questionnaires were used to collect data from patients on the verge of an acute psychiatric crisis enrolled from two mental health organisations. Thirty-eight factors were assigned to seven risk domains. The seven domains are "sociodemographic", "social engagement", "diagnosis and psychopathology", "aggression", "substance use", "mental health services" and "quality of life". Multiple logistic regression analysis (MLRA) was conducted to assess how much pseudo variance in hospitalisation these seven domains explained. Forward MLRA was used to identify individual risk factors associated with hospitalisation. Risks were expressed in terms of relative risk (RR) and absolute risk difference (ARD). Data from 183 participants were used. The mean age of the participants was 40.03 (SD 12.71), 57.4% was female, 78.9% was born in the Netherlands and 51.4% was employed. The range of explained variance for the domains related to "psychopathology and care" was between 0.34 and 0.08. The "aggression" domain explained the highest proportion ( = 0.34) of the variance in hospitalisation. "Quality of life" had the lowest explained proportion of variance ( = 0.05). The forward MLRA identified four predictive factors for hospitalisation: previous contact with the police or judiciary (OR = 7.55, 95% CI = 1.10-51.63; ARD = 0.24; RR = 1.47), agitation (OR = 2.80, 95% CI = 1.02-7.72; ARD = 0.22; RR = 1.36), schizophrenia spectrum and other psychotic disorders (OR = 22.22, 95% CI = 1.74-284.54; ARD = 0.31; RR = 1.50) and employment status (OR = 0.10, 95% CI = 0.01-0.63; ARD = -0.28; RR = 0.66). IHT teams should be aware of patients who have histories of encounters with the police/judiciary or were agitated at outset of treatment. As those patients benefit less from IHT due to the higher risk of hospitalisation. Moreover, type of diagnoses and employment status play an important role in predicting hospitalisation.