Updates from the BTSD Data for Quality Project Right Care Initiative Annual Summit, November 14, 2016 Allen Fremont, MD. Ph. D 1
Data for Quality Project (DQP) 2
Brief history and assessment of San Diego Data Group (2011-2015) Established to create safe venue for data sharing and foster collaboration on efforts to make SD a heart attack & stroke free zone Traditional focus on improving performance within individual organizations Equal emphasis on trends in combined data across organizations and collective action toward reducing cardiovascular risks throughout the region’s population. By fostering collaboration among health care organizations that collectively serve a large portion of population DFQ Group helped form foundation for a growing number of novel, innovative initiatives in San Diego. 3
Data Group Quickly Picked Up Steam 200,000 180,000 Group 8 Group 7 160,000 Group 6 140,000 Group 5 Group 4 120,000 Group 3 100,000 80,000 60,000 40,000 Group 2 20,000 Group 1 0 2010 2011 2012 2013 2014 BTSD SD Data Group Begins 4
Potential Impact BP Control in Hypertensives 200,000 74 percent of the 180,000 176,000 hypertensives had 160,000 BP controlled in 46, 100 2014 BP uncontrolled 140,000 Each 1 percentage point improvement = 120,000 1,760 more hypertensives with BP 129, 814 100,000 BP Uncontrolled control in SD BP controlled BP Controlled 80,000 60,000 40,000 20,000 0 2010 2011 2012 2013 2014 5
Projected Overall BP Control Rate in Hypertensives to 2018 100% 90% 2015-2016 rate 80% 84% 83% 82% 82% 80% 78% 76% Percentage with BP Controlled 70% 74% 72% 60% Drop in rate due to Goal is for 2 percent per year 50% several large groups improvement in overall rate of with lower rates 40% BP Control through 2018 (and increasing DQP population to 30% >200k) 20% 10% 0% 2010 (n=2) 2011 (n=2) 2012 (n=4) 2013 (n=7) 2014 (n=8) 2015 (n=8) 2016 (n=8) 2017 (n=8) 2018 (n=8) 6
Examples Areas of Focus 2016
Interactive Tableau files are now available for use by provider groups participating in DQP 8
Potential Focus on Gender Differences in CVD Risk Reduction Men Women 5.0% 4.1% 4.0% 3.0% 2.0% 0.5% 1.0% 0.0% -1.0% -0.6% -2.0% -3.0% -4.0% -4.0% -5.0% DM: BP <140/90 DM: LDL <100 Source: 2015 BTSD DQP Group Data 9
In contrast to gender gaps for most measures which are small or favor women, gaps in LDL control relatively large and favor men 10
Interactive maps show combined counts and HTN BP control rates by zip code 11
BP control rates may vary by local area (zipcode) served Group E HTN control rates Group F HTN control rates Darker shades of blue better performance; darker red shades worse performance. Source: 2015-16 BTSD DQP data. 12
DQP participants can also highlight potential “hotspots” where quality across DQP Group’s lower than other areas Cluster of zip codes around Escondido area with lower than expected DM LDL control rates 13
Are DM LDL control rates lower than expected for all groups or just some? Difference (percentage pts) in LDL control rate between each Group’s zip code and SD rate Count groups >30 in zip code group A group B group C group D group E group F group G combined area avg 41 60 N/A 58 68 51 40 57 Difference 92025 N/A 0 N/A -10.7 0.5 N/A -0.4 -12.6 4 92026 N/A -2.1 N/A 5.7 -10.6 -7.7 -2.4 -8.4 5 92027 N/A -4.1 N/A 1.3 -2.4 -4.3 3.3 -8.7 5 92029 N/A 1.7 N/A -10 3.2 N/A 2 -1.4 4 92082 N/A 1.2 N/A -6.2 N/A N/A -5.7 -14.2 3 In Escondido area, several but not all group’s LDL control rates are below their expected rate. The gap varies by specific zip code within the hotspot and some groups performing better than their expected rate. 14
DM LDL Control by Poverty (2015, Q4, Zip Code rates) DM LDL Control Rates (%) % households < poverty level Data source: LDL control data reported by 6 medical groups to the Be There San Diego Data group for Q4 of 2015. Rates are not presented for ZIP codes that include fewer than 30 individuals with hypertension (n=95). Percent of population with household income below poverty level derived from 5-year ACS estimates (2010- 2014) . Denominator size and number of groups serving area shown for selected zip codes. 15
Relationship between DM LDL Control rate and poverty rate across zip codes differed for some DQP Groups Overall Correlation coefficient=-0.34 (p=0.01) 10 20 30 40 50 60 70 80 90 100 Group G Correlation coefficient= 0.20 (p=0.09) Fitted values Group D Correlation coefficient= 0.26 (p=0.07) 0 0 10 20 30 40 pct_lthpov Fitted values pct_ldlcontrol_G Fitted values 10 20 30 40 50 60 70 80 90 100 Group F Correlation coefficient= -0.37 (p=0.01) Fitted values Group E Correlation coefficient= -0.22 (p=0.09) 0 0 10 20 30 40 pct_lthpov Fitted values pct_ldlcontrol_F Fitted values Data source: Blood pressure control data reported for Q4 of 2015. Observations entail percent adequately controlled BP for a given zip code and Group so that multiple observations are observed for each zipcode (N=85). Percent of population with household income below poverty level derived from 5-year ACS estimates (2010-2014) 16
Several zip codes in Escondido area with notably lower LDL control rates than expected across low and high poverty levels Expected Rate DM LDL Control Rates (%) Negative outliers % households < poverty level 17
San Diego Trends in AMI and HTN Control San Diego Trends in AMI and HTN control 180 80 79% 160 76% 74% 75 County AM I hospitalization rate (per 100K) 140 72% 71% % Patients with controlled BP 71% 120 70 100 65 80 60 60 40 55 20 0 50 2010 2011 2012 2013 2014 2015 SD County AMI hospitalization rate % Patients with HTN and controlled BP %Patients with DM and controlled BP Data sources: Data for Quality Group reporting and AMI data from Hospital Discharge Data, (CA OSHPD), County of San Diego, Health & Human Services Agency, Epidemiology & Immunization Services Branch 18
How do Patterns of AMI Hospitalization Rates vary by Zip Code and Year? 19
AMI hospitalization Rate Trends by SRA (2010-2014)
Questions and Discussion 21
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