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

Abstract

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.

Utility of functioning in predicting costs of care for patients with mood and anxiety disorders

“…On the basis of previous research showing their associations with mental health service costs (Durbin et al , 2015; Twomey et al , 2015a), initial adjustments were made for age, sex, marital status, ethnicity, employment status, area-level deprivation, general health comorbidity, psychiatric comorbidity, clinician-rated severity of illness, NHS costs incurred in the 3 months before baseline, functioning, depressive symptom severity and anxiety symptom severity. To safeguard statistical power, we subsequently removed several covariates that (a) were not associated with costs in exploratory analysis and (b) yielded P values more than 0.20 in this association.…”

“…(DSM-V), whereby it is rated alongside diagnostic severity (Gold, 2014; Lam et al , 2015). The utility of functioning in predicting costs of care in the general population was supported in a recent review (Hopfe et al , 2016), but its utility in predicting costs in mental disorders is unclear – there is mixed evidence from investigations that deployed various domain-specific operationalizations of functioning and uncosted healthcare use outcomes (Patel et al , 2006; Cooper et al , 2010; Twomey et al , 2015a, 2015b). …”

Utility of the Health of the Nation Outcome Scales (HoNOS) in Predicting Mental Health Service Costs for Patients with Common Mental Health Problems: Historical Cohort Study

“…Most data pertaining to comorbidity were missing and thus its effect could not be examined, albeit that comorbidity is closely associated with mental health service costs. [37] The modest PAFs for the contribution of exposures and covariates to high costs indicates that there are other determinants that have not been considered. The costs outcome did not capture the full range of health services typically accessed by people with common mental health problems (e.g.…”

“…The mental health clusters in the previous studies were partly defined using diagnosis. Diagnosis has been consistently found to be associated with costs [37] and accounted for a far greater amount of the variance in length of stay than any of the HoNOS items in a case-register study involving psychiatric inpatients. [20] Therefore, the contrasting absence of cost associations for the HoNOS in the current study may be attributable to our sole inclusion of patients with common mental health problems, which negated the potential confounding effect of diagnosis on examined associations.…”

“…HoNOS items were simultaneously entered into all relevant predictive models. Based on previous research showing their associations with mental health service costs,[37,38] additional adjustments were made for age, gender, marital status, ethnicity, area-level deprivation (Index of Multiple Deprivation, in quintiles, for the sample), and previous health service use (previous days in contact with a SLaM mental health service in the year before baseline). To account for possible differences in service configurations across locations, the borough where a SLaM mental health service was first accessed was an additional adjustment.…”