Dataset Information

The effect of socio-demographic factors on mental health and addiction high-cost use: a retrospective, population-based study in Saskatchewan.

ABSTRACT: OBJECTIVE:A small proportion of the population accounts for the majority of healthcare costs. Mental health and addiction (MHA) patients are consistently high-cost. We aimed to delineate factors amenable to public health action that may reduce high-cost use among a cohort of MHA clients in Saskatoon, Saskatchewan. METHODS:We conducted a population-based retrospective cohort study. Administrative health data from fiscal years (FY) 2009-2015, linked at the individual level, were analyzed (n?=?129,932). The outcome of interest was ??90th percentile of costs for each year under study ('persistent high-cost use'). Descriptive analyses were followed by logistic regression modelling; the latter excluded long-term care residents. RESULTS:The average healthcare cost among study cohort members in FY 2009 was ~?$2300; for high-cost users it was ~?$19,000. Individuals with unstable housing and hospitalization(s) had increased risk of persistent high-cost use; both of these effects were more pronounced as comorbidities increased. Patients with schizophrenia, particularly those under 50 years old, had increased probability of persistent high-cost use. The probability of persistent high-cost use decreased with good connection to a primary care provider; this effect was more pronounced as the number of mental health conditions increased. CONCLUSION:Despite constituting only 5% of the study cohort, persistent high-cost MHA clients (n?=?6455) accounted for ~?35% of total costs. Efforts to reduce high-cost use should focus on reduction of multimorbidity, connection to a primary care provider (particularly for those with more than one MHA), young patients with schizophrenia, and adequately addressing housing stability.

SUBMITTER: Anderson M

PROVIDER: S-EPMC6267642 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The effect of socio-demographic factors on mental health and addiction high-cost use: a retrospective, population-based study in Saskatchewan.

Anderson Maureen M Revie Crawford W CW Quail Jacqueline M JM Wodchis Walter W de Oliveira Claire C Osman Meriç M Baetz Marilyn M McClure J J Stryhn Henrik H Buckeridge David D Neudorf Cordell C

Canadian journal of public health = Revue canadienne de sante publique 20180628 5-6

<h4>Objective</h4>A small proportion of the population accounts for the majority of healthcare costs. Mental health and addiction (MHA) patients are consistently high-cost. We aimed to delineate factors amenable to public health action that may reduce high-cost use among a cohort of MHA clients in Saskatoon, Saskatchewan.<h4>Methods</h4>We conducted a population-based retrospective cohort study. Administrative health data from fiscal years (FY) 2009-2015, linked at the individual level, were ana ...[more]

PMID: 29981109

Similar Datasets

Project description:ObjectivesTo estimate the attributable costs of multimorbidity and assess whether the association between the level of multimorbidity and health system costs varies by socio-demographic factors in young (<65 years) and older (?65 years) adults living in Ontario, Canada.DesignA population-based, retrospective cohort study SETTING: The province of Ontario, Canada PARTICIPANTS: 6 639 089 Ontarians who were diagnosed with at least one of 16 selected medical conditions on 1 April 2009.Main outcome measuresFrom the perspective of the publicly funded healthcare system, total annual healthcare costs were derived from linked provincial health administrative databases using a person-level costing method. We used generalised linear models to examine the association between the level of multimorbidity and healthcare costs and the extent to which socio-demographic variables modified this association.ResultsAttributable total costs of multimorbidity ranged from C$377 to C$2073 for young individuals and C$1026 to C$3831 for older adults. The association between the degree of multimorbidity and healthcare costs was significantly modified by age (p<0.001), sex (p<0.001) and neighbourhood income (p<0.001) in both age groups, and the positive association between healthcare costs and levels of multimorbidity was statistically stronger for older than younger adults. For individuals aged 65 years or younger, the increase in healthcare costs was more gradual in women than in their male counterparts, however, for those aged 65 years or older, the increase in healthcare costs was significantly greater among women than men. Lastly, we also observed that the positive association between the level of multimorbidity and healthcare costs was significantly greater at higher levels of marginalisation.ConclusionSocio-demographic factors are important effect modifiers of the relationship between multimorbidity and healthcare costs and should therefore be considered in any discussion of the implementation of healthcare policies and the organisation of healthcare services aimed at controlling healthcare costs associated with multimorbidity.

Project description:Introduction: Population health concerns have been raised about negative impacts from overuse of digital technologies. We examine patterns of online activity predictive of Digital Overuse and Addictive Traits (DOAT). We explore associations between DOAT and mental well-being and analyse how both relate to self-reported changes in self-esteem, perceived isolation, and anxiety about health when individuals use the internet for health purposes. Methods: A cross-sectional nationally representative household survey of adults using stratified random sampling (compliance 75.4%, n = 1,252). DOAT was measured using self-reported questions adapted from a social media addiction scale (failure to cut down use, restlessness when not using, and impact on job/studies and home/social life in the last year), combined into a single DOAT score. Higher DOAT score was defined as >1 standard deviation above population mean. The Short Warwick-Edinburgh Mental Well-being Scale was used to measure mental well-being. Analyses were limited to those with internet access (n = 1,003). Results: Negative impacts of digital technology use on work and home/social lives were reported by 7.4% of respondents. 21.2% had tried but failed to cut down use in the past year. Higher DOAT was associated with higher social media and internet use but also independently associated with greater risks of low mental well-being. Higher DOAT was associated with both improvement and worsening of self-esteem, perceived isolation and anxiety about health when using the internet for health reasons, with no change in these outcomes most likely in those with lower DOAT. Lower mental well-being was associated with a similar bi-directional impact on perceived isolation and was also associated with worsening self-esteem. Conclusions: Substantial proportions of individuals report negative impacts on home, social and working lives from digital technology use, with many trying but failing to cut down use. Individuals with higher DOAT may experience improvements or worsening in self-esteem and other measures of mental well-being when using the internet for health purposes. From a public health perspective, a greater understanding of risk factors for digital overuse, its impacts on well-being and how to reasonably limit use of technology are critical for a successful digital revolution.

Project description:Questionnaires are among the most basic and widespread tools to assess the mental health of a population in epidemiological and public health studies. Their most obvious advantage (firsthand self-report) is also the source of their main problems: the raw data requires interpretation, and are a snapshot of the specific sample's status at a given time. Efforts to deal with both issues created a bi-dimensional space defined by two orthogonal axes, in which most of the quantitative mental health research can be located. Methods aimed to assure that mental health diagnoses are solidly grounded on existing raw data are part of the individual validity axis. Tools allowing the generalization of the results across the entire population compose the collective validity axis. This paper raises a different question. Since one goal of mental health assessments is to obtain results that can be generalized to some extent, an important question is how robust is a questionnaire result when applied to a different population or to the same population at a different time. In this case, there is deep uncertainty, without any a priori probabilistic information. The main claim of this paper is that this task requires the development of a new robustness to deep uncertainty axis, defining a three-dimensional research space. We demonstrate the analysis of deep uncertainty using the concept of robustness in info-gap decision theory. Based on data from questionnaires collected before and during the Covid-19 pandemic, we first locate a mental health assessment in the space defined by the individual validity axis and the collective validity axis. Then we develop a model of info-gap robustness to uncertainty in mental health assessment, showing how the robustness to deep uncertainty axis interacts with the other two axes, highlighting the contributions and the limitations of this approach. The ability to measure robustness to deep uncertainty in the mental health realm is important particularly in troubled and changing times. In this paper, we provide the basic methodological building blocks of the suggested approach using the outbreak of Covid-19 as a recent example.

Dataset Information

The effect of socio-demographic factors on mental health and addiction high-cost use: a retrospective, population-based study in Saskatchewan.

Publications

The effect of socio-demographic factors on mental health and addiction high-cost use: a retrospective, population-based study in Saskatchewan.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets