Age-adjusted rate Age-adjusted rate Deaths Age-adjusted Rate Key Data for County Cardiovascular Disease and Diabetes Right Care Initiative The Right Care Initiative (RCI) is dedicated to improving cardiovascular and diabetes outcomes by catalyzing uptake of patient-centered, evidence-based practices using performance data to drive improvement among health systems, medical groups, clinics, and health plans. Based at UC Berkeley School of Public Health, this public-private partnership was launched in 2008 by the UC Berkeley and UCLA Schools of Public Health with the CA Department of Managed Health Care. RCI includes health system leaders, patients groups, the University of (multiple campuses), USC, Stanford, Health Services Advisory Group (CMS QIO), CA Chronic Care Coalition, and RAND. We collaborate intensively with local leaders in 3 major metro areas:,, and. Right Care s first University of Best Practices (UBP) launched in in February of 2011; the 2nd in 2012. UBP gathers health leaders for top performers to teach proven strategies, practices, and breakthrough ideas to prevent heart attacks, strokes, and diabetic complications. University of Best Practices: Right Care s Translational Model to Implement Evidence-Based Innovations Monthly 2-hour convenings are held with leaders from the major regional health care delivery systems. Leaders from successful organizations or experts present in the 1st hour. A break-out session or discussion involving all participants follows in the second hour to consider how to apply the speaker s ideas in the local setting and to problem-solve how to overcome barriers to better uptake of evidence-based protocols and practices. Trusted performance data is the bedrock of the UBP model. Key Statistics Mortality rates in County for diabetes, coronary heart disease, and stroke are higher compared to the state. Figure 1. has higher hospitalization rates for acute myocardial infarction (MI) and stroke compared with overall (OSHPD). County has the 2 nd worst rate of MIs in CA. There are large disparities by race for cardiovascular hospitalizations and risk factors. Figs. 4 and 6. Many counties are leading on lowering risks. Table 1. County Mortality Rates, 2013-2015 120 100 80 60 40 20 0 93.2 106 Coronary Heart Disease (CHD) 34.7 Stroke 40.8 20.6 24.6 Diabetes County Hospitalization Rates, 2014 25 15 185.42 207.36 178.46 132.43 5 Myocardial Infarction Stroke (without TIA) Figure 1: Average age-adjusted death rate (2013-2015). Source: Department of Public Health. County Health Status Profiles 2017 30 Myocardial Infarction Hospitalization Rate by Sex, 2014 245.87 179.31 Male 91.32 133.30 Female Figure 2: 2014 Age-adjusted hospitalization rate of myocardial infarction and stroke without TIA Source: Office of Statewide Health Planning and Development s Patient 25 15 5 Stroke (without TIA) Hospitalization Rate by Sex, 2014 201.59 228.63 Male 158.28 187.95 Female Figure 3: 2014 Age-adjusted MI Hospitalization rate in stratified by sex Source: Office of Statewide Health Planning and Development s Patient Figure 4: 2014 Age-adjusted Stroke Hospitalization rate in stratified by sex Source: Office of Statewide Health Planning and Development s Patient
Percent Age Adjusted Prevalence (%) Age-adjusted rate Age-adjusted rate 30 25 15 5 Myocardial Infarction Hospitalization Rates by Race, 2014 172.69 132.79 180.15 251.33 123.84 208.66 98.42 178.88 White Black Hispanic Asian/PI Stroke (without TIA) Hospitalization Rates by Race, 2014 40 30 192.09 168.76 302.38 314.07 206.59 209.71 171.11 145.68 White Black Hispanic Asian/PI Figure 5: 2014 Age-adjusted MI Hospitalization rate in stratified by race Source: Office of Statewide Health Planning and Development s Patient Figure 6: 2014 Age-adjusted Stroke Hospitalization rate in stratified by race Source: Office of Statewide Health Planning and Development s Patient 35.00 Self-Reported Risk Factors - Health Interview Survey, 2011-2014 3 25.00 2 15.00 1 5.00 Hypertension Obese (BMI>30) Smoking Diabetes (type I and II) Diabetes (type II) Heart Disease Heart Failure 27.20 25.22 12.98 8.38 7.05 6.09 1.82 29.47 29.41 16.29 8.82 7.74 5.18 1.65 Figure 7: Self-reported Cardiovascular Risk Factors from 2011-2014 publicly available data ( Health Interview Survey). Source: Dingbaum, Darsie, Ivey et al., Department of Public Health Analysis, 2016 (CHIS 2011-2014 Adult Public Use File). Self-Reported Risk Factors by Race/Ethnicity, CHIS, 2013-2014 50 45 40 35 30 25 20 15 10 5 0 Hypertension Obesity (BMI>30) Smoking Diabetes Type II Diabetes African American Only, non-hispanic 44.09 32.41 17.21 4.97 3.69 Asian only 36.76 17.47 3.49 11.23 11.23 Hispanic 30.05 39.19 12.63 14.59 14.59 White, non Hispanic 28.71 27.36 17.76 6.88 5.62 Figure 8: Self-reported Cardiovascular Risk Factors by race from 2013-2014 publicly available data ( Health Interview Survey). Source: Dingbaum, Darsie, Ivey et al., CA Department of Public Health Analysis, 2016 (CHIS 2011-2014 Adult Public Use File).
Table 1: Data are age adjusted from pooled CHIS 2011-2014. Ranks are from 1-44 with 1 having the lowest prevalence, and 44 having the highest; small counties were pooled to create stable estimates. All estimates reported are stable. Source: Dingbaum, Darsie, Ivey et al., CA Department of Public Health Analysis, 2016 (CHIS 2011-2014 Adult Public Use File). Age-Adjusted Prevalence of Self-Reported Cardiometabolic and Other Risk Factors for Adults in Counties (Percent (rank)) County Calaveras (grouped) Diabetes Obesity Hypertension Heart Disease Smoking Status 5.36 (5) 22.25 (14) 25.22 (12) 5.19 (6) 16.10 (29) Alameda 6.41 (8) 20.87 (9) 25.52 (14) 5.49 (7) 11.97 (12) Placer 6.66 (11) 20.87 (9) 20.83 (2) 6.75 (29) 10.03 (6) Contra Costa 6.79 (12) 22.06 (13) 25.38 (13) 4.58 (2) 14.10 (22) Yolo 6.97 (13) 21.36 (10) 26.48 (19) 6.83 (31) 7.59 (1) El Dorado 7.10 (15) 21.39 (11) 24.47 (9) 5.77 (12) 18.15 (38) 7.40 (22) 23.06 (16) 26.18 (17) 5.86 (14) 12.51 (16) Colusa (grouped) 7.79 (23) 26.34 (24) 33.86 (43) 7.90 (34) 18.56 (39) State Rate 8.38 25.22 27.20 6.09 12.98 8.82 (26) 29.41 (31) 29.47 (31) 5.18 (5) 16.29 (31) San Joaquin 9.05 (29) 33.85 (35) 32.04 (35) 9.83 (41) 16.97 (35) Sutter 10.25 (34) 31.61 (32) 32.73 (40) 8.92 (39) 15.01 (24) Solano 11.76 (37) 28.74 (29) 33.99 (44) 8.43 (37) 15.44 (27) Stanislaus 13.12 (42) 33.86 (36) 29.19 (30) 6.27 (23) 15.11 Comparing Counties Coronary Heart Disease Three Year Averaged, Age-adjusted Mortality Rates (2013-2015) County Age-adjusted 95% Confidence Interval Death Rate Lower Upper Santa Clara 62.1* 58.5 65.6 State Rate *Statistically Significant 85.9* 82.7 89.0 93.2 92.2 94.1 106.0* 100.7 111.2 109.7* 107.7 111.7 Comparing Counties Stroke Three Year Averaged, Age-adjusted Mortality Rates (2013-2015) County Age-adjusted 95% Confidence Interval Death Rate Lower Upper Santa Clara 26.1* 23.8 28.3 33.0 31.0 34.9 Table 2: Age-adjusted Mortality Rates for Coronary Heart Disease. Source: County Health Status Profiles 2017 Report, Department of Public Health Table 3: Age-adjusted Mortality Rates for Stroke. Source: County Health Status Profiles 2017 Report, Department of Public Health 33.1 31.9 34.2 State Rate 34.7 34.2 35.3 40.8* 37.5 44.1 *Statistically Significant
Age Adjusted Hospitalization Rate per 100,000 people Age Adjusted Hospitalization Rate per 100,000 people Age Adjusted Hospitalization Rate per 100,000 people 19 18 17 16 15 14 13 12 11 9 8 Comparing County Trends - Myocardial Infarction Hospitalization Rate, 2010-2014 2010 2011 2012 2013 2014 Statewide Figure 9: Age-Adjusted Hospitalization Rate for Myocardial Infarction (2010-2014 Office of Statewide Health Planning and Development) 26 255.00 25 245.00 24 235.00 23 225.00 22 215.00 21 205.00 195.00 19 Comparing County Trends - Stroke with TIA Hospitalization Rate, 2010-2014 2010 2011 2012 2013 2014 Statewide Figure 10: Age-Adjusted Hospitalization Rate for Stroke with TIA (2010-2014 Office of Statewide Health Planning and Development) 22 215.00 21 205.00 195.00 19 185.00 18 175.00 17 165.00 Comparing County Trends - Stroke without TIA Hospitalization Rate, 2010-2014 2010 2011 2012 2013 2014 Statewide Figure 11: Age-Adjusted Hospitalization Rate for Stroke without TIA (2010-2014 Office of Statewide Health Planning and Development)
Mortality Hot Spots for Diabetes, Heart Disease, Hypertension, and Stroke (2007-2011) Figure 12: County Hot Spots for Diabetes, Heart Disease, Hypertension and Stroke Mortality Rates (2007-2011) Source: Department of Public Health, Map 3,4,5,6. County Health Status Profiles 2017.
Proposed Action Plan for County County has: Higher rates of smoking than the state average o Encourage primary care physicians to ask about smoking as a vital sign during every visit. o Provide brief cessation counseling for smokers which can also help physicians meet meaningful use 1. Higher rates of obesity than the state average o Encourage measurement of BMI regularly in primary care; ensure patients are aware of obesity-related risks 2. o Develop a plan with patients for addressing obesity; provide solid evidence to promote diet and physical activity changes. o Work to ensure all communities have access to safe, affordable options for healthy diets and physical activity in their neighborhoods 3. Higher rates of hypertension than the state; high rates of uncontrolled hypertension, especially for African Americans o Ensure that the most recent medication protocols and guidelines for hypertension are actively being upheld by care teams including monitoring of quality indicators and promotion of evidence-based treatment. o Improve community outreach about hypertension as a silent killer targeting places where people meet churches, synagogues, barbershops, community and senior centers among others. o Improve medication adherence by utilizing health coaches to activate patients via motivational interviewing and evidencebased media messaging. o Consider having pharmacists more actively engaged on the care team 4. o Provide information about best practices for treating hypertension to local primary care providers. o Examine air pollution in relationship to cardiovascular disease in County 5 Disparities in hypertension among different race/ethnicities; African American, API and Hispanic rates of hypertension are much higher than the rest of the state while White rates are only a little higher. o Act to address key disparities in hypertension among different race/ethnicities, with African Americans, API and Hispanic rates of hypertension being much higher than the rest of while White rates are only a little higher. o Help physicians learn about, and learn to ask their patients about determinants of health including whether medication costs are within budget. o Provide medical practices information about how to use culturally aligned, linguistically appropriate health coaches to bridge the gaps in care, to enable better care for specific populations we serve. o Form connections between medical practices and community programs that can expand outreach and care (senior centers, community-based organizations, parish nurses) about hypertension and diabetes. o Apply evidence-based elements of the Right Care triangle in County. Bibliography 1. Maciosek MV, LaFrance AB, Dehmer SP, et al. Health benefits and cost-effectiveness of brief clinician tobacco counseling for youth and adults. The Annals of Family Medicine. 2017;15(1):37-47. 2. Cabodi J, Kelsberg G, Safranek S. Does brief physician counseling promote weight loss? J Fam Pract. 2011;60(9):548-550. 3. Laraia BA, Karter AJ, Warton EM, Schillinger D, Moffet HH, Adler N. Place matters: neighborhood deprivation and cardiometabolic risk factors in the Diabetes Study of Northern (DISTANCE). Social Science & Medicine. 2012;74(7):1082-1090. 4. Patient Safety and Clinical Pharmacy Services Collaborative (PSPC). U.S. Depatment of Health and Human Services; Health Resources and Services Administration. https://www.hrsa.gov/communitiesofpractice/ataglance/patientsafety.pdf Date Accessed: 6/30/17. 5. Lee, Byeong-Jae, Bumseok Kim, and Kyuhong Lee. Air Pollution Exposure and Cardiovascular Disease. Toxicological Research 30.2 (2014): 71 75. PMC. Web. 30 June 2017. 6. Office of Statewide Health Planning and Development. Patient. Merged dataset - 2010 to 2014. Analysis by Dingbaum, Darsie, Ivey, 2017. 7. Health Interview Survey. CHIS 2011-2014 Adult Public Use File., CA: UCLA Center for Health Policy Research, January 2015. Analysis by Dingbaum, Darsie, Ivey, 2017. 8. County Health Status Profiles 2017 Report. Department of Public Health. Created by the Right Care Initiative Research Team. Brief as of 6-30-17