Factors associated with higher healthcare costs in a cohort of homeless adults with a mental illness and a general cohort of adults with a history of homelessness.

BACKGROUND: Healthcare costs are disproportionately incurred by a relatively small group of people often described as high-cost users. Understanding the factors associated with high-cost use of health services among people experiencing homelessness could help guide service planning. METHODS: Survey data from a general cohort of adults with a history of homelessness and a cohort of homeless adults with mental illness were linked with administrative healthcare records in Ontario, Canada. Total costs were calculated using a validated costing algorithm and categorized based on population cut points for the top 5%, top 6-10%, top 11-50% and bottom 50% of users in Ontario. Multinomial logistic regression was used to identify the predisposing, enabling, and need factors associated with higher healthcare costs (with bottom 50% as the reference). RESULTS: Sixteen percent of the general homeless cohort and 30% percent of the cohort with a mental illness were in the top 5% of healthcare users in Ontario. Most healthcare costs for the top 5% of users were attributed to emergency department and inpatient service costs, while the costs from other strata were mostly for physician services, hospital outpatient clinics, and medications. The odds of being within the top 5% of users were higher for people who reported female gender, a regular medical doctor, past year acute service use, poor perceived general health and two or more diagnosed chronic conditions, and were lower for Black participants and other racialized groups. Older age was not consistently associated with higher cost use; the odds of being in the top 5% were highest for 35-to-49-year year age group in the cohort with a mental illness and similar for the 35-49 and ≥ 50-year age groups in the general homeless cohort. CONCLUSIONS: This study combines survey and administrative data from two cohorts of homeless adults to describe the distribution of healthcare costs and identify factors associated with higher cost use. These findings can inform the development of targeted interventions to improve healthcare delivery and support for people experiencing homelessness.

Does Housing Improve Health Care Utilization and Costs? A Longitudinal Analysis of Health Administrative Data Linked to a Cohort of Individuals With a History of Homelessness.

BACKGROUND: Individuals who are homeless have complex health care needs, which contribute to the frequent use of health services. In this study, we investigated the relationship between housing and health care utilization among adults with a history of homelessness in Ontario. METHODS: Survey data from a 4-year prospective cohort study were linked with administrative health records in Ontario. Annual rates of health encounters and mean costs were compared across housing categories (homeless, inconsistently housed, housed), which were based on the percentage of time an individual was housed. Generalized estimating equations were applied to estimate the average annual effect of housing status on health care utilization and costs. RESULTS: Over the study period, the proportion of individuals who were housed increased from 37% to 69%. The unadjusted rates of ambulatory care visits, prescription medications, and laboratory tests were highest during person-years spent housed or inconsistently housed and the rate of emergency department visits was lowest during person-years spent housed. Following adjustment, the rate of prescription claims remained higher during person-years spent housed or inconsistently housed compared with the homeless. Rate ratios for other health care encounters were not significant (P>0.05). An interaction between time and housing status was observed for total health care costs; as the percentage of days housed increased, the average costs increased in year 1 and decreased in years 2-4. CONCLUSIONS: These findings highlight the effects of housing on health care encounters and costs over a 4-year study period. The rate of prescription medications was higher during person-years spent housed or inconsistently housed compared with the homeless. The cost analysis suggests that housing may reduce health care costs over time; however, future work is needed to confirm the reason for the reduction in total costs observed in later years.

Patterns and predictors of high-cost users of the health system: a data linkage protocol to combine a cohort study and randomised controlled trial of adults with a history of homelessness.

INTRODUCTION: Homelessness is a global issue with a detrimental impact on health. Individuals who experience homelessness are often labelled as frequent healthcare users; yet it is a small group of individuals who disproportionately use the majority of services. This protocol outlines the approach to combine survey data from a prospective cohort study and randomised controlled trial with administrative healthcare data to characterise patterns and predictors of healthcare utilisation among a group of adults with a history of homelessness. METHODS AND ANALYSIS: This cohort study will apply survey data from the Health and Housing in Transition study and the At Home/Chez Soi study linked with administrative healthcare databases in Ontario, Canada. We will use count models to quantify the associations between baseline predisposing, enabling, and need factors and hospitalisations, emergency department visits and physician visits in the following year. Subsequently, we will identify individuals who are high-cost users of the health system (top 5%) and characterise their patterns of healthcare utilisation. Logistic regression will be applied to develop a set of models to predict who will be high-cost users over the next 5 years based on predisposing, enabling and need factors. Calibration and discrimination will be estimated with bootstrapped optimism (bootstrap performance-test performance) to ensure the model performance is not overestimated. ETHICS AND DISSEMINATION: This study is approved by the St Michael's Hospital Research Ethics Board and the University of Toronto Research Ethics Board. Findings will be disseminated through publication in peer-reviewed journals, presentations at research conferences and brief reports made available to healthcare professionals and the general public. TRIAL REGISTRATION NUMBER: This is a secondary data analysis of a cohort study and randomized trial. The At Home/Chez Soi study has been registered with the International Standard Randomised Control Trial Number Register and assigned ISRCTN42520374.

Validation study of health administrative data algorithms to identify individuals experiencing homelessness and estimate population prevalence of homelessness in Ontario, Canada.

OBJECTIVES: To validate case ascertainment algorithms for identifying individuals experiencing homelessness in health administrative databases between 2007 and 2014; and to estimate homelessness prevalence trends in Ontario, Canada, between 2007 and 2016. DESIGN: A population-based retrospective validation study. SETTING: Ontario, Canada, from 2007 to 2014 (validation) and 2007 to 2016 (estimation). PARTICIPANTS: Our reference standard was the known housing status of a longitudinal cohort of housed (n=137 200) and homeless or vulnerably housed (n=686) individuals. Two reference standard definitions of homelessness were adopted: the housing episode and the annual housing experience (any homelessness within a calendar year). MAIN OUTCOME MEASURES: Sensitivity, specificity, positive and negative predictive values and positive likelihood ratios of 30 case ascertainment algorithms for detecting homelessness using up to eight health service databases. RESULTS: Sensitivity estimates ranged from 10.8% to 28.9% (housing episode definition) and 18.5% to 35.6% (annual housing experience definition). Specificities exceeded 99% and positive likelihood ratios were high using both definitions. The most optimal algorithm estimates that 59 974 (95% CI 55 231 to 65 208) Ontarians (0.53% of the adult population) experienced homelessness in 2016, a 67.3% increase from 2007. CONCLUSIONS: In Ontario, case ascertainment algorithms for identifying homelessness had low sensitivity but very high specificity and positive likelihood ratio. The use of health administrative databases may offer opportunities to track individuals experiencing homelessness over time and inform efforts to improve housing and health status in this vulnerable population.