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Socio-economic Status Related to Self-Injury

Socio-economic Status Related to Self-Injury. Chantal Couris Manager, Indicator Research and Development. Background. Self-injury is the result of either suicidal or self-harming behaviour Self-injury is strongly associated with mental illness and/or poor mental health.

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Socio-economic Status Related to Self-Injury

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  1. Socio-economic Status Related to Self-Injury Chantal Couris Manager, Indicator Research and Development

  2. Background • Self-injury is the result of either suicidal or self-harming behaviour • Self-injury is strongly associated with mental illness and/or poor mental health. • Monitoring self-injury hospitalization rates may gain some insight into the effectiveness of the mental health system in reducing these types of injuries. • Besides other significant predictors, at-risk populations for self-injury include persons living in less affluent neighbourhoods.

  3. Objectives • The objective of this analysis was to address the magnitude of SES-related disparity for self-injury hospitalization and provincial variations across the country and provide summary measures to help quantify the impact of SES disparity.

  4. Methods • Individuals discharged from a general hospital with a diagnosis code for intentional external cause of injury were identified. • Only individuals 15 years and older were included. • Rates of self-injury hospitalizations were calculated by neighbourhood income quintile. Two summary measures (Potential rate reduction and Disparity rate ratio) were calculated at provincial and national level to capture the magnitude of health disparities. • Rates are expressed per 100,000 population and are age-standardized to the 1991 Canadian population. • For more information on the methodology, please refer to the Health indicators Technical Notes available at www.cihi.ca

  5. How do we categorize socio-economic status (SES)?

  6. Disparity in the Health Indicators project • Neighbourhood income quintile to measure SES • Patient’s place of residence (postal code), available in administrative data • Categorizes small geographic areas into 5 roughly equal population groups • Quintile 1 = least affluent neighbourhoods • Quintile 5 = most affluent neighbourhoods • Research has demonstrated correlations between place of residence and social determinants of health such as income, education, quality of community services, etc

  7. How do we quantify SES-related disparity? • Disparity Rate Ratio • Potential Rate Reduction

  8. Disparity Rate Ratio (DRR) Magnitude of socio-economic disparities Ratio

  9. Potential Rate Reduction (PRR)%

  10. Socio-Economic Status Related to Self-Injury Hospitalization

  11. Self-Injury Hospitalization Rates and Potential Rate Reductions by Province, Canada, 2011–2012 Sources Discharge Abstract Database, National Ambulatory Care Reporting System and Ontario Mental Health Reporting System, Canadian Institute for Health Information; Fichier des hospitalisations MED-ÉCHO, ministère de la Santé et des Services sociaux du Québec; 2006 Census, Statistics Canada.

  12. Key findings: Self-injury hospitalization rate • Hospitalization rates for self-injury could potentially be significantly lower • Provincial variations range from highs in NL and NB to lows in QC, ON and AB • If all Canadians experienced the same rate as those living in the most-affluent neighbourhoods, the national hospitalized self-injury rate would be 27% lower • Disparities by socio-economic status provide a fuller picture for targeted improvement • Ontario, Alberta and Quebec had self-injury hospitalization rates below the national average • When examined by socio-economic status, each of these provinces could further reduce their rates by more than 25% if all of their residents lived in the most-affluent neighbourhoods

  13. Limitations • Many self-injuries do not result in a hospitalization. • Self-injury may also result in death before care can be sought. • Reporting self-injury might be underestimated because of the manner in which intent is captured in the data sources available: there may be uncertainty when differentiating between unintentional and intentional motives.

  14. Conclusion • This analysis highlights that considerable health system disparity exist. • Providing this type of information will allow jurisdictions to take a closer look at disparities by SES across the many dimension of health of their particular population and their health systems.

  15. Policy Implications • SES-disparity summary measures can be used to inform health policy, manage the health system, enhance our understanding of the broader determinants of heath and identify gaps in health status and outcomes for specific populations. • These measures can also act as screening tools to identify differences over time and between jurisdictions

  16. Thank you! ccouris@cihi.ca

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