A systematic review of the predictors of health service utilisation by adults with mental disorders in the UK

ObjectivesTo identify variables that predict health service utilisation (HSU) by adults with mental disorders in the UK, and to determine the evidence level for these predictors.DesignA narrative synthesis of peer-reviewed studies published after the year 2000. The search was conducted using four databases (ie, PsycINFO, CINAHL Plus with full text, MEDLINE and EMBASE) and completed on 25 March 2014.SettingThe majority of included studies were set in health services across primary, secondary, specialist and inpatient care. Some studies used data from household and postal surveys.ParticipantsIncluded were UK-based studies that predicted HSU by adults with mental disorders. Participants had a range of mental disorders including psychotic disorders, personality disorders, depression, anxiety disorders, eating disorders and dementia.Primary outcomeA wide range of HSU outcomes were examined, including general practitioner (GP) contacts, medication usage, psychiatrist contacts, psychotherapy attendances, inpatient days, accident and emergency admissions and ‘total HSU’.ResultsTaking into account study quality, 28 studies identified a range of variables with good preliminary evidence supporting their ability to predict HSU. Of these variables, comorbidity, personality disorder, age (heterogeneous age ranges), neurotic symptoms, female gender, a marital status of divorced, separated or widowed, non-white ethnicity, high previous HSU and activities of daily living, were associated with increased HSU. Moreover, good preliminary evidence was found for associations of accessing a primary care psychological treatment service and medication use with decreased HSU.ConclusionsThe findings can inform decisions about which variables might be used to derive mental health clusters in ‘payment by results’ systems in the UK. The findings also support the need to investigate whether combining broad diagnoses with care pathways is an effective method for mental health clustering, and the need for research to further examine the association between mental health clusters and HSU.