Geographic Disparity: Acute Stroke Treatment. Sergio Gonzáles, University of New Mexico Allison Willis, MD, MSCI, University of Pennsylvania

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1 Geographic Disparity: Acute Stroke Treatment Sergio Gonzáles, University of New Mexico Allison Willis, MD, MSCI, University of Pennsylvania

2 Background Acute Ischemic Stroke (AIS) Thrombus blocks blood vessels in brain Can be removed mechanically: thrombectomy Or dissolved with Kssue plasminogen ackvator (tpa): thrombolysis Introduced in 2001 Must be given 4 hours to prevent cerebral hemorrhaging NaKonal uklizakon rate is very low (2.4%) 1 Previous research: Many kinds of social determinates in stroke treatment & outcomes Racial/ethnic minorikes and low income people have higher incidence, higher mortality, and receive less thrombolysis 2,3 Geographic disparikes in mortality and thrombolysis have been observed between rural and urban hospitals; southern states have a higher incidence of stroke 4 Hospital size affects the rate of thrombolysis 5 Hospitals cerkficakon as Primary Stroke Centers (PSCs) by the Joint Commission began in 2004 Thrombolysis rates more than triple nakonal average in PSCs 1 Some social disparikes are reduced in PSCs 1,6 PSCs tend to be highly aggregated; issues of access 1 1 Mullen et al. Journal of the American Heart AssociaKon. 2:e Kimball et al. Journal of Stroke and Cerebrovascular Diseases. 23(1): Nasr et al. Journal of Stroke and Cerebrovascular Diseases. 22(2): Bray et al. Journal of the American Heart AssociaKon. 44: Kleindorfer et at. Journal of the American Heart AssociaKon. 40: Bhaeacharya et al. Journal of Stroke and Cerebrovascular Diseases, 22(4):

3 Project Overview & Aims Few studies have looked at Rural- Urban DispariKes in tpa uklizakon with serious depth Fewer studies have provided or looked for any significant suggeskons to mikgate disparikes in tpa uklizakon No studies have looked at the potenkal impact of PSC cerkficakon on Rural- DispariKes by Hospital Service Area Our study aims to provide a useful analysis of Rural- Urban disparikes in thrombolysis and the impact of PSC cerkficakon by HSA on these disparikes

4 Stroke is Bad Image taken from: hep:// stroke/ischemic- stroke/

5 Stroke is Bad but tpa is Good Image taken from: hep:// stroke/ischemic- stroke/

6 Stroke is Bad but tpa is Good Stroke is the 4 th leading cause of death 7 and one of the top 10 causes of disability 8 in the United States The direct costs to pakents due to stroke in 2012 was $71.6 billion and is expected to triple to $184.1 billion by NaKonal Vital StaKsKcs Report. Center for Disease Control. 62(6) Morbidity and Mortality Weekly Report. Center for Disease Control. 58(16) CirculaKon. Journal of the American Heart AssociaKon. 129:e28- e

7 Stroke is Bad but tpa is Good Stroke is the 4 th leading cause of death 7 and one of the top 10 causes of disability 8 in the United States The direct costs to pakents due to stroke in 2012 was $71.6 billion and is expected to triple to $184.1 billion by Thrombolysis the state of science treatment for AIS Reduces stroke symptom burden and improves post stoke dependency and mortality 10,11 Cost effeckve and provides net savings to pakent and Healthcare System 12 7 NaKonal Vital StaKsKcs Report. Center for Disease Control. 62(6) Morbidity and Mortality Weekly Report. Center for Disease Control. 58(16) CirculaKon. Journal of the American Heart AssociaKon. 129:e28- e Machumpurath et al. Journal of Cerebrovascular Diseases. 31: Marler et al. Neurology 55: Demaerschalk. Journal of Stroke and Cerebrovascular Diseases. 36:

8 Research Questions How have urban- rural disparikes in tpa uklizakon changed over Kme? Does PSC cerkficakon impact urban- rural disparikes in tpa uklizakon? Can PSCs help reduce disparikes?

9 Methods Used HCUP NaKonal InpaKent Sample (NIS) StraKfied sample of hospitals across US Isolated all cases of AIS and cases treated with tpa with ICD- 9 codes IdenKfied significant covariates PaKent CharacterisKcs and Hospital CharacterisKcs Added geocodes for PSCs and NIS hospital data by HSA Ran regressions to idenkfy predictors for tpa uklizakon and quankfy inequality between urban and rural hospitals Adjusted Odds RaKos for significant covariates Nested Hierarchical Regression Model to predict impact of PSCs in HSAs Gini Coefficient to measure inequality

10 WHAT DO YOU THINK MATTERS MOST? PaKent CharacterisKcs (e.g. Age, Sex, Race) Hospital CharacterisKcs (e.g. Size, LocaKon, Teaching Status) Something else?

11 Who You Are Matters Characteris7c Year (2001 to 2010) Age, years < Race White African American Hispanic Asian or Pacific Islander American Other Adjusted OR ǂ (95% CI) 1.2 ( )** Ref ( )** 0.72 ( )** 0.56 ( )** Ref ( )** 0.75 ( )** 0.92 ( ) 0.63 ( )* 0.98 ( ) tpa uklizakon has been increasing with each year The younger are more likely to receive tpa Racial/ethnic minorikes are less likely to receive tpa ** < * < ǂ Adjusted for Year, Age, Race, Hospital Bedsize, and CCI score

12 Zip Code Matters too PaKents in Urban Hospitals are nearly three Kmes as likely to receive tpa The best odds for thrombolysis are in Urban Teaching hospitals Characteris7c Hospital Loca7on Hospital Loca7on Rural Urban Rural Urban non- teaching Urban teaching Hospital Bedsize Small Medium Large Adjusted OR ǂ (95% CI) Ref ( )** Ref ( )** 3.47 ( )** Ref ( )** 2.32 ( )** ** < * < ǂ Adjusted for Year, Age, Race, Hospital Bedsize, and CCI score

13 Zip Code trumps Genetic Code Regardless of Race/ ethnicity odds for thrombolysis increase from rural to urban seqngs Increases in odds are comparable for all races/ethnicikes Hospital Loca7on White Rural Urban Rural Urban non- teaching Urban teaching African American Hispanic ** < * < ǂ Adjusted for Year, Age, Race, Hospital Bedsize, and CCI score Rural Urban Rural Urban non- teaching Urban teaching Rural Urban Rural Urban non- teaching Urban teaching Asian or Pacific Islander Rural Urban Rural Urban non- teaching Urban teaching Adjusted OR ǂ (95% CI) Ref ( )** Ref ( )** ( )** Ref ( )** Ref ( )** ( )** Ref ( )** Ref ( )* ( )** Ref ( ) Ref ( ) ( )*

14 Urban Rural Disparity Rural Urban tpa UKlizaKon Rate (%) YEAR

15 Urban Rural Disparity Since 2001, the rate of tpa uklizakon for urban hospitals more than quadrupled (1.17% to 4.87%) Rates in rural hospitals increased at a much slower rate; hasn t quite doubled (0.87% to 1.59%) The median percent growth for idenkfiable states from disparity: +120% Range of percent growth: 11% - 711% Only four states saw a reduced their disparity: HI, KS, NE & WA However skll notable disparity between urban & rural rate in WA

16 Rate Disparity

17 Rate Disparity is Growing

18 Lots of Inequity; Little Change Inequality was quankfied using a modificakon of the Gini Coefficient The Gini Coefficient compares distribukon of tpa rural hospital to to the distribukon of rural hospitals in each state We then looked at the data in terms of the theorekcal maximum amount of inequity possible for each state TheoreKcal Maximum would mean no thrombolysis in rural hospitals 15 of the 33 states with available data were found to have more than 75% of theorekcal maximum inequality for both years The number of states with 50% - 75% of maximum inequality grew from 7 to 10

19 Lots of Inequity; Little Change

20 Lots of Inequity; Little Change

21 But there s Hope! AddiKon of PSCs to HSAs improves likelihood of thrombolykc treatment PSCs can help reduce disparity rater than just be inefficient if distributed intenkonally Addi7onal PSCs per HSA Adjusted OR ǂ (95% CI) 0 Ref ( )** ( )** ( )** ( )** ( )** ( )** ( )** ** < * < ǂ Adjusted for Year, Age, Race, Hospital Bedsize, and CCI score

22 Hope for Rural Communities AddiKonal PSCs to rural HSAs have greater impact and are more efficient in increasing thrombolysis rates Addi7onal PSCs per HSA Adjusted OR ǂ (95% CI) 0 Ref ( )** ( )** ( )** ( )** ( )** Addi7onal PSCs per HSA Adjusted OR ǂ (95% CI) 0 Ref ( )** ( ) ( )** ( )** ( ) ( )** ( )** ** < * < ǂ Adjusted for Year, Age, Race, Hospital Bedsize, and CCI score

23 Limitations Factors we couldn t control or measure Emergency Medical Systems roukng protocol Pre- hospital communicakon Non- random data sample

24 Conclusions Treatment for Acute Ischemic Stroke is geqng beeer but disparity is geqng worse Thrombolysis rates are growing in urban and rural hospitals but much faster in Urban hospitals Inequality is a persistent problem despite increases in tpa uklizakon in rural hospitals Zip code trumps genekc code Hospital characteriskcs such as locakon and teaching status have the largest impact on odds for thrombolysis for all racial/ethnic groups Rural communikes can potenkally see more benefit from an addikonal PSC in their HSAs when compared to urban HSAs

25 ReVlections My Roles Background Research DescripKve StaKsKcal Analysis Rate Disparity Analysis Inequality Analysis Making the Maps Preparing the manuscript for publicakon Lessons Learned ArcGIS 10.1 WriKng regressions in R Experience as a health services and health disparikes researcher Framing of data for policy implicakons

26 Acknowledgements Dr. Allison Willis Dylan Thibault Ola Aboukhsawian Leonard Davis InsKtute of Health Economics Friends & Family

27 Questions?

28 Rate Disparity is Growing

29 Rate Disparity is Growing

30 Growth in Inequity

31 Growth in Inequity