Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Similar to Ibd intersectionality
Similar to Ibd intersectionality (20)
More from soder145
More from soder145 (20)
Recently uploaded
Recently uploaded (20)
Ibd intersectionality
- 1. The Intersection of Structural Risk Factors and Insurance-based Discrimination on Healthcare Access Inequities Kathleen Thiede Call, Rhonda Jones-Webb, Brooke Cunningham, Giovann Alarcon, Sarah Hagge, Alisha Simon AcademyHealth Annual Research Meeting June 25, 2018 Seattle, Washington
- 2. Intersectionality “Intersectionality is a theoretical framework for understanding how multiple social identities such as race, gender, sexual orientation, SES, and disability intersect at the micro level of individual experience to reflect interlocking systems of privilege and oppression (i.e., racism, sexism, heterosexism, classism) at the macro social/structural level.” (Bowleg. AJPH, 2012, p. 1267) 2
- 3. Insurance-based discrimination Unfair treatment that patients receive from health care providers because of the type of insurance they have or because they do not have insurance. 3
- 4. Summary of prior research • Insurance-based discrimination (IBD) is higher among those who have public insurance or who lack health insurance • Experiences of IBD are higher among racial and ethnic minorities • Experiences of IBD constrain access to healthcare 4
- 5. Our goals 1. Describe experiences of IBD across a range of structural risk factors (gender, race and ethnicity, income) - independently and combined 2. Examine the effects of IBD and structural risk factors on access to healthcare services –independently and synergistically. 5
- 6. 2015 Minnesota Health Access Survey • Biennial statewide telephone survey • Stratified sample: • Dual frame telephone (75% cell; 25% landline) • Knowledgeable adult answers for household • Participants: • Over 11,000 completed interviews • Field period: • August-November 2015 • Response rate: • 35% (29% cell, 41% landline) • Restricted analysis sample: • Non-elderly adult respondents -- answering for themselves • Approximately 3,800 6
- 7. Analysis strategy • Descriptive analysis comparing experiences of IBD across structural factors • Separate logistic regressions (contrasting those who do and do not report IBD) to understand the synergistic effects of structural risk factors and IBD on access to healthcare services • All analyses weighted and accounted for complex survey design 7
- 8. Insurance based discrimination (classism) If insured: “How often do health care providers treat you unfairly because of the type of health insurance you have?” If uninsured: “How often do health care providers treat you unfairly because you don’t have health insurance?” CODING: sometimes, usually, always (1) and never (0) 8
- 9. Other structural risk factors Gender (proxy for sexism) • “What is your gender?” CODING: Male, female other (omitted due to small sample size) Race/ethnicity (proxy for racism) • “Are you Mexican, Puerto Rican, Cuban or another Hispanic or Latino group?” • “Which of the following race or races do you consider yourself to be? CODING: Latinx, non-Latinx American Indian, Asian or Pacific Islander, Black/African American, White, some other race Income as % of FPG (proxy for classism) • “Approximately what was your household’s income from all sources in 2014, before taxes?” CODING: <138% FPG, 138-400% FPG, >400% FPG 9
- 10. Access Measures • Usual source of care • “Is there a regular place that you go for medical care? CODING: “Yes” and place of care NOT emergency room • Confidence getting needed care • “How confident are you that you can get the health care you need? Are you…” CODING: Very, somewhat confident (1) a little or not confident at all (0) 10
- 11. RESULTS Goal 1 Describe experiences of IBD across a range of structural risk factors - independently and combined 11
- 12. IBD varies by structural risk factors 12 3% 18% 25% 6% 5% 27% 11% 13% 3% 7% 24% 7% 2% 0% 5% 10% 15% 20% 25% 30% Private Public Uninsured Male Female White Black Asian American Indian Other/Multiple Latinx <138% FPG 138-400% FPG >400% FPG 8% * Indicates significant difference in IBD compared to all adults at p < .05 * * * * * * ALL ADULTS: 7%
- 13. 15% 38% 17% 7% 5% 14% 0% 10% 20% 30% 40% 50% 60% White Black Asian American Indian Other/Multiple Latinx Among public insured IBD varies by race/ethnicity 13 ALL ADULTS: 18% * * * Indicates significant difference in IBD compared to all adults at p < .05
- 14. RESULTS Goal 2 Describe synergistic effects of structural risk factors and IBD on access to healthcare services 14
- 15. 15 * * * * 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Public vs Private Uninsured vs Private Male vs Female Black vs White Asian vs White American Indian vs White Other/Multiple vs White Latinx vs White 138-400% vs >400% FPG <138% FPG vs >400% FPG No IBD Regressions adjust for US born, age, education, marital status, urban residence and health status. * Indicates significant odds ratio at p < .05 Lower odds Higher odds Structural risk factors, IBD, and likelihood of access to a usual source of care
- 16. Structural risk factors, IBD, and likelihood of access to a usual source of care 16 * * * * * * * * 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Public vs Private Uninsured vs Private Male vs Female Black vs White Asian vs White American Indian vs White Other/Multiple vs White Latinx vs White 138-400% vs >400% FPG <138% FPG vs >400% FPG No IBD IBD Regressions adjust for US born, age, education, marital status, urban residence and health status. * Indicates significant odds ratio at p < .05 Lower odds Higher odds
- 17. * * * * * * * * * * * * 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Public vs Private Uninsured vs Private Male vs Female Black vs White Asian vs White American Indian vs White Other/Multiple vs White Latinx vs White 138-400% vs >400% FPG <138% FPG vs >400% FPG No IBD IBD Structural risk factors, IBD, and likelihood of access to a usual source of care 17 Regressions adjust for US born, age, education, marital status, urban residence and health status. * Indicates significant odds ratio at p < .05 Lower odds Higher odds
- 18. * * * 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Public vs Private Uninsured vs Private Male vs Female Black vs White Asian vs White American Indian vs White Other/Multiple vs White Latinx vs White 138-400% vs >400% FPG <138% FPG vs >400% FPG No IBD Structural risk factors, IBD, and likelihood of confidence in getting needed care 18 Regressions adjust for US born, age, education, marital status, urban residence and health status. * Indicates significant odds ratio at p < .05 Lower odds Higher odds
- 19. * * * * 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Public vs Private Uninsured vs Private Male vs Female Black vs White Asian vs White American Indian vs White Other/Multiple vs White Latinx vs White 138-400% vs >400% FPG <138% FPG vs >400% FPG No IBD IBD Structural risk factors, IBD, and likelihood of confidence in getting needed care 19 Regressions adjust for US born, age, education, marital status, urban residence and health status. * Indicates significant odds ratio at p < .05 Lower odds Higher odds
- 20. * * * * * 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Public vs Private Uninsured vs Private Male vs Female Black vs White Asian vs White American Indian vs White Other/Multiple vs White Latinx vs White 138-400% vs >400% FPG <138% FPG vs >400% FPG No IBD IBD Structural risk factors, IBD, and likelihood of confidence in getting needed care 20 39.41 18.47 * Regressions adjust for US born, age, education, marital status, urban residence and health status. * Indicates significant odds ratio at p < .05 Lower odds Higher odds
- 21. Limitations and challenges • Cross-sectional data • Unfair treatment does not specify time referent • Only one measure of structural discrimination is experience based – specifically IBD; remaining are proxies. • Methods for exploring intersectionality are not well developed • Quantitative analysis alone may be antithetical to understanding intersectionality • Challenging to analyze, display and interpret intersectional influences 21
- 22. Summary of results Some structural risk factors are associated with higher IBD • Uninsured and public insured • Blacks • Low income • Structural risk factors combine to create a greater sense of IBD • Blacks with public insurance • Structural risk factors and IBD combine to create barrier to access which in turn, may exacerbate health inequities • Especially true for usual source of care • Black, LatinX, lower income people who also report IBD have likelihood of having a USC • Reports of IBD amplify lower likelihood of USC for those who are uninsured, Asian, other or multiple races • Less so for confidence in getting needed care • Black adults reporting IBD are much less confident than those reporting NO IBD 22
- 23. Implications • Reducing inequities in healthcare access requires attention to the convergence of structural risk factors • Best to intervene at multiple levels • Policy: • Incentivize patient-centered or whole person care; reduce financial disincentive to provide care to uninsured, public insured; promote culture of health – reduce structural barriers; broaden primary care workforce; diversify policymaking and healthcare workforce/leadership; monitor IBD as quality measure • Clinical/provider: • Adopt, enforce CLAS standards; promote structural competency training, continue implicit bias training; diversify workforce/leadership; include CHWs on care team • Individual: • Patient bill of rights, patient advocates, CHWs • Research: • Grapple with methodological approaches to intersectionality research • Measure and monitor IBD • OTHER IDEAS ARE WELCOME! 23
- 24. Acknowledgements This research was supported by the Minnesota Department of Health, Minnesota Department of Human Services, and SHADAC through a grant from the Robert Wood Johnson Foundation 24
- 25. Contact Information Kathleen Thiede Call, PhD SHADAC callx001@umn.edu 612-624-3922
Editor's Notes
- First a few definitions to ground us and set stage.
- Here defined as…
- What we know thus far about IBD is…
- …hypothesizing that the effects of these structural risk factors are correlated and that their impact on healthcare access are synergistic.
- Biennial dual frame telephone survey providing state of MN estimates insurance coverage and access Sampling designed to results for specific geographic regions, ages, race and ethnic groups Knowledgeable adults answers for household members Over 11K completes BUT we restrict analysis to adults answering questions for themselves about themselves: 3800 AAPOR RR3 Starting in 2013 also used list assisted data to screen out 65 plus households. Starting in 2015, included an age screener for the cell frame. 2015: 75% cell phone, 25% landline Limit to ADULTS RESPONDENTS only –reporting their experience of discrimination.
- First looked at correlation between SRFs and IBD Separate logistic regressions to understand combined influence of SRF and IBD on access to care
- Question asks: “How often do health care providers treat you unfairly because of the type of health insurance you have?” – or “because you don’t have health insurance” People reporting sometimes, usually and always are coded as experiencing IBD View as form of classism given that the US system tends to view health care as a privilege rather than a right and the association between income and enrollment in private vs public forms of insurance This measure describes experiences of discrimination whereas the other measures of structural risk factors are based on descriptive experiences and are proxies of experiences of oppression.
- Consistent with intersectionality lit we look at R/E and gender. Although survey participants are allowed to opt out of binary gender labels very few did; omitted due to small numbers. We also look at income. Again, this is highly correlated with type of insurance as we hit income threshholds for Medicaid, for MNCare or subsidized marketplace and those not eligible for any government assistance R/E = OMB questions
- Interested in how multiple systems of oppression impact access to health care. Two measures pretty standard measure where those who name a USC other than ED are coded as 1 those reporting very or somewhat confident in getting needed care are coded as 1 Confidence = 1 if Very or Somewhat confident, 0 if A little or Not at all confident (missing if not asked, refused, or DK)
- Goal would be to have 0% reporting unfair treatment based on type of insurance or lack of insurance – average for non-elderly adults is 7% (orange bar) Varies by structural factors, with exception of gender Public, uninsured signif higher prevalence of IBD and private signif lower prev of IBD than adults overall Reports of IBD is significantly higher for black adults IBD also higher for low income HH and much lower for high income HH Note that income pattern resembles insurance type given that eligibility for public is income based as is affordability of private insurance for many people.
- Looked at relationship between race/ethnicity and IBD among those with public and private insurance and the uninsured Again 0 is the goal As shown here, American Indian adults and adults reporting other or multiple races are less likely to report IBD than adults overall. 38% of Black adults with public insurance report IBD compared to 15% of white adults.
- Turn to exploration of interaction effects
- Separate regressions (contrasting those who do and do not report IBD) to understand the synergistic effects of structural risk factors and IBD on reports of having a USC Start with OR for those reporting No IBD Even those reporting NO IBD experience constraints to access: uninsured are less likely to have USC than private, males less likely than females Asian American, Other, multiple race adults less likely than whites
- Teal bars represent OR for those reporting IBD – These results respresent the most straightforward evidence of intersectionality: The lower likelihood of having a USC is only significant for Black, LatinX, low income adults who report IBD – not those who do not report IBC R/e, income and IBD combine to restrict access to care.
- Last 4 teal lines provide additional evidence of intersectionality: For some structural risk factors there is a lower likelihood of USC whether reporting IBD or not yet the odds are signif lower for those reporting IBD than not. True for those who are uninsured, Asian, other or multiple races. Orange arrow - Males report lower odds of USC than females. period. Reporting IBD does not amplify this disparity.
- Turning to second access measure: confidence in getting needed care. Again start with OR for those reporting No IBD Even those reporting NO IBD experience lower confidence: uninsured are less likely to have USC than private, Black, Other, multiple race adults less likely than whites
- For black adults, this impact is amplified when adding experiences of IBD– significantly less likely to be confident in getting needed care. Teal arrow: While the likelihood of lacking confidence in getting care is not signif for adults in low income compared to high income HHs, the OR for those who do and do not report IBD are significantly different.
- Finally, see again that uninsured less likely to be confident than privately insured, and that uninsured adults reporting IBD have even lower confidence – but the difference between the ORs is not signif. Very few other ORs reach significance We have small numbers challenges here so the OR for Asian and American Indian are quite large, and have large variance. Results are also in an unexpected direction: American Indians reporting IBD are more likely to be confident…. Perhaps seeking care with providers they trust…. IHS, FQHCs designed to serve their needs.
- Can’t confidently talk about causal relationships between IBD and diminished use of HC Unfair treatment has no time referent – could be interpreted as any experiences of unfair treatment which could lead to an overestimation of prevalence. Good thing is measure is specific to HC As stated earlier, only one measure of oppression asks about experiences: IBD The rest – gender, R/E and income are proxies for sexism, racism and classism Finally, to the best of my knowledge, methods for exploring intersectionality are not well developed – at least not quantitative methods It is even possible the quantitative analysis may be viewed as antithetical to understanding intersectionality There are interesting challenges involved in analyzing, displaying and interpreting intersectional influences – quantitatively.
- Before turning to implications, a quick summary of key results. Prevalence of IBD is higher among Uninsured and public insured Black and low income adults In addition – some structural factors combine to amplify reports of IBD True for Black adults with public insurance AND these structural factors and IBD combine OR intersect to creates barriers to access; which in turn may exacerbate health inequities. Contrasting the two measures of access, there is more evidence of intersecting sources of oppression for USC than true for confidence in getting needed care Makes sense as people are more likely to forgo preventive care than acute care
- So, what does this all mean… Reducing inequities in healthcare access requires attention to the convergence of structural risk factors Doing this well mean intervening at multiple levels Policy: Continue to create incentives for patient-centered or whole person care; reduce financial disincentive to provide care to uninsured, public insured; understand role in promoting culture of health – reduce structural barriers to good health and wellbeing; E.g., Medicaid ACOs paying for housing, nutritious food, etc. broaden primary care workforce; diversify policymaking and healthcare workforce – have people in leadership positions that have lived experience with oppression who can lead for change monitor IBD as quality measure Clinical/provider: Adopt, enforce CLAS standards; promote structural competency training; continue implicit bias training; diversify workforce/leadership; include CHWs on care team – often share common experiences of oppression yet can navigate complex and challenging health care system Individual: Patient bill of rights, patient advocates, CHWs Research Field needs to grapple with methodological approaches to intersectionality research Promote measuring and monitoring IBD as a vital quality metric.