The impact of mental illness on potentially preventable hospitalisations: a population-based cohort study

Abstract

Background: Emerging evidence indicates an association between mental illness and poor quality of physical health care. To test this, we compared mental health clients (MHCs) with non-MHCs on potentially preventable hospitalisations (PPHs) as an indicator of the quality of primary care received.

Methods: Population-based retrospective cohort study of 139,208 MHCs and 294,180 matched non-MHCs in Western Australia from 1990 to 2006, using linked data from electoral roll registrations, mental health registry (MHR) records, hospital inpatient discharges and deaths. We used the electoral roll data as the sampling frame for both cohorts to enhance internal validity of the study, and the MHR to separate MHCs from non-MHCs. Rates of PPHs (overall and by PPH category and medical condition) were compared between MHCs, category of mental disorders and non-MHCs. Multivariate negative binomial regression analyses adjusted for socio-demographic factors, case mix and the year at the start of follow up due to dynamic nature of study cohorts.

Results: PPHs accounted for more than 10% of all hospital admissions in MHCs, with diabetes and its complications, adverse drug events (ADEs), chronic obstructive pulmonary disease (COPD), convulsions and epilepsy, and congestive heart failure being the most common causes. Compared with non-MHCs, MHCs with any mental disorders were more likely to experience a PPH than non-MHCs (overall adjusted rate ratio (ARR) 2.06, 95% confidence interval (CI) 2.03-2.09). ARRs of PPHs were highest for convulsions and epilepsy, nutritional deficiencies, COPD and ADEs. The ARR of a PPH was highest in MHCs with alcohol/drug disorders, affective psychoses, other psychoses and schizophrenia.

Conclusions: MHCs have a significantly higher rate of PPHs than non-MHCs. Improving primary and secondary prevention is warranted in MHCs, especially at the primary care level, despite there may be different thresholds for admission in people with established physical disease that is influenced by whether or not they have comorbid mental illness.

Figure 1

Selection of study cohorts. Abbreviations: ER = electoral roll registrations, MHCs = mental health clients, MHR = mental health registry. * Non-MHCs matched 2:1 with MHCs by 5-year age group, sex and being a current elector at study entry. The final ratio of non-MHC to MHC was 2.11:1 after excluding MHCs with dementia.

Figure 2

Unadjusted (univariate analysis) and adjusted (multivariate analysis) rate ratios of potentially preventable hospitalisations (PPHs) from negative binomial regression analysis, stratified by PPH category and medical condition, 1 January 1990 to 30 June 2006. Abbreviations: PPHs = potentially preventable hospitalisations, URR = unadjusted rate ratio, ARR = adjusted rate ratio, MHCs = mental health clients, COPD = chronic obstructive pulmonary disease. Notes: URRs and ARRs for nutritional deficiencies and convulsions and epilepsy were eliminated from the figure because of the larger numbers, which can be found from Table 2. Multivariate regression model adjusted for 5-year age group, sex, Indigenous status, level of social disadvantage, level of residential remoteness, physical comorbidities and year at the start of follow up. The reference group was non-MHCs.

Figure 3

Unadjusted (univariate analysis) and adjusted (multivariate analysis) rate ratios of total potentially preventable hospitalisations (PPHs) from negative binomial regression analysis, stratified by category of mental disorders. Abbreviations: MHR = mental health registry, MH = mental health, Dx = diagnosis, URR = unadjusted rate ratio, ARR = adjusted rate ratio, MHCs = mental health clients. Note: URR for other psychoses was eliminated from the figure because of the large number (URR 6.42, 95% CI 6.02-6.85). The drop in other psychoses from an URR of 6.42 to an ARR of 2.47, mainly due to their older age and high level of physical comorbidities. Multivariate regression model adjusted for 5-year age group, sex, Indigenous status, level of social disadvantage, level of residential remoteness, physical comorbidities and year at the start of follow up. The reference group was non-MHCs.