Fitzpatrick T, Rosella L, Calzavara A, Petch J, Pinto A, Manson H, Goel V, Woodchis, WP. Looking Beyond Income and Education — Socioeconomic Status Gradients Among Future High-Cost Users of Health Care, American Journal of Preventive Medicine, 2015 (Article in press).

Available from:

doi:10.1016/j.amepre.2015.02.018

http://www.ajpmonline.org/article/S0749-3797(15)00082-3/pdf

Background

Healthcare systems across the country have been focusing on “high-cost users” (HCUs) — the 5 percent of the population who consume a disproportionately high share of health care resources, accounting for over 50 percent of healthcare expenditures. Although focusing on HCUs may result in better quality of care for some patients, this approach does not reveal the drivers that cause individuals to become HCUs. It fails to account for social determinants of health (SDOH) beyond the health care system itself — other social and economic factors — that contribute to poor health and healthcare system burden. This study is the first to apply a population health lens to high-cost users of the healthcare system, shedding light on a broad range of individual, household, and neighborhood socio-economic (SES) characteristics associated with HCU. Importantly, it applies a longitudinal perspective on HCUs which is lacking from most HCU research.

Methods

The Canadian Community Health Survey (CCHS) is a cross-sectional survey administered by Statistics Canada representative of 98% of Canadians ≥12 years of age. This study used data from two cycles (2003-2004 and 2005-2006) of the CCHS, and linked these to population-based health administrative data for Ontario, Canada. The health administrative database contains data from the Ontario Health Insurance Plan (OHIP), the single-payer insurance system that covers OHIP-eligible residents of Ontario.

Healthcare spending was calculated for key sources of healthcare spending, such as hospital admissions, same day surgery, emergency department visits, physician payments, rehabilitation, complex continuing care, and medications covered through the government insurance program. Annual cost per person was calculated for each of the 5 years following the CCHS interview. Individuals who ranked in the top 5% of cost were categorized as HCUs. Individuals who were HCUs at baseline (users in the top 5% in the year following the interview) were excluded, as the goal was to determine the factors associated with future high-cost use.

Data for prior healthcare utilization was obtained from administrative databases. Area-level socioeconomic status was obtained using the Ontario Marginalization Index, which is a census-based, geographically derived index. The Anderson-Newman Framework of individual determinants of health services utilization was used to provide a conceptual model for the study.

Limitations

Although the approach in this study was novel, there were several limitations in the work. The CCHS only applies to Canadians living in private dwellings, not to those living in institutions, Aboriginal reserves, full-time Canadian Forces members, or those residing in certain remote areas. The CCHS also does not include people who are homeless or First Nations people who live on reserve, two groups who may be at higher risk of higher healthcare use.

Health expenditure data was only available for items covered under Ontario’s health insurance plan. The majority of people in Ontario would not receive coverage under that plan for expenses such as dental care and prescription drug costs.

Results

The authors obtained a final sample of 55,734 Ontario adults. These individuals could be linked to administrative data and were not HCUs at baseline. Over the subsequent 5 years, 16.3% of the cohort were HCUs in at least 1 year.

The characteristics of those who became HCUs were as follows: They were typically older, white, female, had a lower household income, and education below a post-secondary level. Other factors that influenced use of healthcare included neighbourhood of residence, ethnicity, and home ownership. Importantly, the authors found that, “…the single strongest predictor – even stronger than income – of future high-cost use is someone’s access to sufficient, safe, nutritious food.” The odds of becoming an HCU within the next 5 years were 46% greater for those living with food insecurity as compared to those living in food-secure households (95% CI=1.24-1.71).

Comment

High-cost use of the health care system is rooted not only in chronic disease and sub-optimal healthcare, but also in the growing inequities in Canadian society. Equitable access to health services, income, and food security are among the social determinants of health that contribute to health status. There will always be a need for a healthcare system; however, to help ensure effective and sustainable healthcare, we must also focus resources on the other SDOH that prevent illness and promote health. Doing so would create a healthier population and allow healthcare dollars to be spent in a more effective manner, rather than struggling to only address preventable illnesses and disease.

The authors of this study contend that to minimize HCUs, policy-makers and others could consider actions such as reform of the food bank system in Canada, a guaranteed minimum income, or applying a “Housing First” model. These approaches go beyond the usually illness-oriented focus of healthcare, and could have profound beneficial impacts on the health care system and on population health.

This research provides a solid evidence-base of clear links between decisions made in the health care system and those made in other areas that impact health. It highlights the importance of collaborative, intersectoral policies and interventions that align health care and public health to mitigate high-cost users. Consistent with this research is the WHO’s Intersectoral Action for Health (ISA initiative, which promotes intersectoral efforts in public policy aimed at improving quality of life), and legislation, such as in Quebec, requiring health impact assessments. This study also provides a rich starting point for further research to better tease out which specific SDOH-related policy initiatives would have the greatest benefits on health and healthcare.