Understanding Amputations for Diabetes and Vascular Disease in a Rural Population

1. Understanding Amputations for Diabetes and Vascular Disease in a Rural Population Samantha D Minc, MD, MPH, FSVS, FACS Assistant Professor Division of Vascular and Endovascular Surgery Department of Cardiovascular and Thoracic Surgery West Virginia University Authors: Samantha Danielle Minc, MD, MPH, Brian Hendricks, MS, PhD, Ranjita Misra, PhD, Yue Ren, MS, Luke Marone, MD, Gordon Stephen Smith, MB, ChB, MPH

2. Disclosures • The authors have no conflicts of interest to report • This work was supported by a grant from the Society for Vascular Surgery Foundation and in part by the following awards: • National Institute of General Medical Sciences (2U54GM104942) • National Institute of Drug Abuse (R21DA040187 and 1UG3DA044825)

3. Amputation is a devastating, but preventable complication of diabetes and vascular disease

4. Diabetic Foot Complications: A Prognosis Worse than Cancer? Armstrong DG, Wrobel J, Robbins JM. Guest Editorial: are diabetes-related wounds and amputations worse than cancer? Int Wound J. 2007;4(4):286-287.

5. Amputation is a marker for significant systemic cardiovascular disease Aulivola B, Hile CN, Hamdan AD, et al. Major lower extremity amputation: outcome of a modern series. Arch Surg. 2004;139(4):395-399; discussion 399.

6. Decreasing diabetes-related lower extremity amputations is an objective for healthy people 2020

7. Amputation disparities related to race and socioeconomic status are well documented https://www.healthypeople.gov/2020/data/disparities/summary/Chart/4121/3

8. Where you live matters

9. Rural disparities in amputation rates have not been well studied

12. Cardiovascular death rates in WV are significantly higher than the US average (371.2 vs 324.3*) *per 100,000 (2014-2016) https://nccd.cdc.gov/DHDSPAtlas/Default.aspx?state=WV

13. WV has the highest prevalence of diabetes in the continental US (~13%) https://nccd.cdc.gov/DHDSPAtlas/Default.aspx?state=WV

14. Deaths of Despair(drugs, alcohol, suicide and violence) https://jamanetwork.com/journals/jama/fullarticle/2674665

15. Understanding amputations for diabetes and vascular disease in a rural population • Quantitative data collection and analysis: • State inpatient database (2011-2016) • Hospital systems database (2011-2016) • Geographic systems analysis • Qualitative data collection and analysis • Focus groups • Amputees • High-risk patients • Providers • Vascular Surgeons/Podiatrists

16. Results – State inpatient database http://www.dartmouthatlas.org/data/bar.aspx?ind=307 • 459,464 hospital admissions with diabetes and/or PAD • 5679 amputations occurred • 3530 (60.5%) minor • 2248 (39.5%) major WV Amputation Prevalence Major Amputation: 5/1000 Minor Amputation: 7/1000 Any Amputation: 12/1000

19. Spatial epidemiology has unique considerations • Rural and rarer diseases = small counts • Traditional methods aggregate numbers • Bayesian methods allow for a more granular picture • Current literature focuses on descriptive data, rather than inferential • Choropleth maps • Spatial outliers • Standard deviation • Controlling for covariates/model building

20. Rossen LM, Hedegaard H, Khan D, Warner M. County-Level Trends in Suicide Rates in the U.S., 2005-2015. Am J Prev Med. 2018;55(1):72-79.

21. Figure 1. County and zip code level choropleth maps

23. Figure 2. Choropleth maps of raw rate per 1,000 of comorbid conditions and percent rural census tracts at the county level

24. Figure 3. County and zip code level model-fitted relative risk estimates for major and minor amputation, adjusting for covariates.

25. Discussion • WVs with diabetes and/or PAD are at high risk for amputation • Significant geographic variation in amputation risk exists across the state, even after controlling for potential confounders • Bayesian modeling provided a better model and much higher level of granularity than traditional methods

26. There are both access and utilization issues surrounding diabetic and vascular care in rural areas • Access to care: • Physical/geographic barriers • 91% of counties medically underserved • Utilization of care: • Behavioral barriers • Cultural barriers • Disparities in the social determinants of health

27. Limitations • Database-related • Multiple readmissions • Coding, under reporting • PO Boxes • “Patient Leakage”/Edge effect

28. Next steps • Deeper quantitative analysis of local data • Amputation Dashboard • Focus groups in progress • Inform WV communities of their risks and empower them to create a community-based intervention to reduce rates of amputation in WV • Create a model that can be applied to other rural communities across the country Long-term goals

29. VQI at VAM special edition! • What are the most significant barrier you face in trying to prevent amputation in your practice? • Patient awareness and education • Patient “apoplexy” • Patient access to care • Patient adherence to recommendations • Care coordination • Social and cultural barriers

30. VQI at VAM special edition! • If you could be given anything you wanted to prevent amputation, what would it be? • Patient education • Smoking cessation • Provider education • Better communication between providers, and providers and patients • Celebrity endorsement/improved awareness

31. Conclusions • Amputation is a preventable, and contextual complication of diabetes and vascular disease • Disparities in amputation are a marker for other health and SDOH disparities • High-resolution spatial analysis identifies geographic variation in risk and should be used to direct resources and prevention programs

32. Acknowledgements • Luke Marone, MD: Vascular mentorship • Ranjita Misra, PhD: Public health mentorship • Gordon Smith, MB, ChB, MPH: Epidemiology mentorship and analysis • Brian Hendricks, PhD: Spatial epidemiology methods and analysis • Yue Ren, MS: Biostatistical methods and analysis • Dylan Thibault, MS: Biostatistical methods and analysis

33. Questions?