1. WORKING DRAFT Last Modified Printed Trend of quality measures following implementation of electronic health record systems amongst practices in underserved urban areas Jason Wang, Ph.D. Sr. Director of Program Evaluation and Analysis Primary Care Information Project NYC Department of Health & Mental Hygiene Primary Care Information Project APHA 140 th Annual Meeting San Francisco, CA October 30, 2012

2. 2 Primary Care Information Project Objective: Assess the overall trend for some key quality measures for practices in underserved urban areas after implementation of EHR. Background: In transforming primary care, studies showing sustained improvements in the delivery of clinical preventive services are limited. Fewer demonstrate sustained improvements among independent practices that are not affiliated with hospital or integrated health systems. This study examines the continued improvement in clinical quality measures for a group of practices using electronic health records and receiving technical support from a local public health agency. Methods: Clinical quality measure performance data were analyzed from a cohort of primary care practices that implemented an electronic health record (EHR) at least three months before baseline (October 2009). Trends were observed for four key quality measures: antithrombotic therapy, blood pressure control, smoking cessation intervention, and A1c testing based on monthly summary data transmitted by the practices over a two-years period. INTRODUCTION 2

3. 3 Primary Care Information Project Advancing NYC’s Health Priorities 3 Large burden, killing thousands of NYers and causing hundreds of thousands of preventable illnesses or disabilities each year Proven amenable to intervention Best addressed through coordinated action by City agencies, public-private partnerships, health care providers, businesses, individuals Important and winnable battles that affect every New Yorker 1)Have a Regular Doctor or Other Health Care Provider 2)Be Tobacco-Free 3)Keep Your Heart Healthy 4)Know Your HIV Status 5)Get Help for Depression 6)Live Free of Dependence on Alcohol and Drugs 7)Get Checked for Cancer 8)Get the Immunizations You Need 9)Make Your Home Safe and Healthy 10)Have a Healthy Baby

4. 4 Primary Care Information Project Primary Care Information Project (PCIP) PCIP started as a mayoral initiative in 2005 Mission Improve the quality of care in medically underserved areas through health information technology (HIT) Success Over 6,200 providers receiving EHR and Meaningful Use assistance 915 small practices, 23 large practices 50 community health centers 54 hospitals & outpatient clinics

5. 5 Primary Care Information Project MeasureEligible patients (denominator)Patient Goal (numerator) A1c TestingPatients 18-75 years with diabetes Hemoglobin A1c test recorded in the past 6 months Antithrombotic Therapy Patients 18+ years with ischemic vascular disease or 40+ with diabetes Taking Antithrombotic/other Antithrombotic therapy Blood Pressure Control Patients 18-75 years with hypertension and no diagnosis of ischemic vascular disease or diabetes Systolic <140 mmHg and Diastolic <90 mmHg Smoking Cessation Intervention Patients 18+ years with a "current smoker" smoking status Smoking cessation intervention (Rx or Counseling) received in the past 12 months Table 1. Description of quality measures

6. 6 Primary Care Information Project Table 2. Baseline Practice Characteristics Mean Practice Values for Small Practices (SP) and Community Health Centers (CHC) 6 Characteristic All PracticesSPCHC (n=151)(n=140)(n=11) Sites1.41.23.1 Providers4.52.629.3* Encounters per month9257493169 Unique Patients per month7426122392 % of Medicaid/ Self-insured >=20% (Practice self-reported) (T1)33%29.3%81.8%** Months using EHR up to Oct 2009 (T1)13.713.813.0 *p=0.03 **p=0.0004

7. 7 Primary Care Information Project Graph 1. Overall Progress in PCIP – 2 year trend 7 TimeAntithrombotic therapy Blood pressure control Hemoglobin A1c Testing Smoking Cessation Intervention Oct 2009 (T1)58.455.346.429.3 Oct 2010 (T2)66.758.550.634.5 Oct 2011 (T3)74.864.157.746.2 Difference between T1 and T28.3*3.14.25.2 Difference between T2 and T38.1*5.5*7.1*11.7* Difference between T1 and T316.4**8.8*11.3*16.9**

8. 8 Primary Care Information Project Table 3. Improved Quality Measure Performance over Time Stratified by Various Practice Characteristics 8 Antithrombotic TherapyBP ControlHemoglobin A1c TestingSmoking Cessation Practice Characteristics nT1T3p valuenT1T3p valuenT1T3p valuenT1T3p value Organization SP9358.973.1<.000110256.664.30.002914856.1NS8130.145.10.0006 Type CHC1154.2720.021143.2620.006113372.50.0041123.656.90.003 p value NS 0.01NS 0.003 NS Adoption time Early6161.875.9<.00016557.362.4NS6152.358.2NS5234.950.40.001 Later4353.673.3<.00014852.666.20.00024137.6570.005402241.10.004 p value NS 0.02NS 0.01NS % Medicaid <20%6756.875.7<.0001745763.90.0176644.455.40.0496126.739.30.008 and selfpay >=20%3761.373.50.005395264.30.0023650.160.7NS3134.556.90.002 p value NS 0.003 No. of providers Single4259.476.40.00054855.866.80.00084150.956.8NS3432.6480.04 Multiple6257.773.5<.00016554.961.70.036143.358.30.0075827.444.90.0001 p value NS

9. 9 Primary Care Information Project Table 4. Results of Generalized Estimating Equation (GEE) Model 9 Quality MeasuresAntithrombotic TxBP Control Hemoglobin A1c Testing Smoking Cessation Intervention Practice CharacteristicsOR (CI)p valueOR (CI)p valueOR (CI)p valueOR (CI)p value Months Since EHR 1.03 (1.02, 1.04) <.0001 1.006 (1.0008, 1.01) 0.0243 1.03 (1.01, 1.04) <.0001 1.04 (1.02, 1.05) <.0001 CHC 0.84 ( 0.43, 1.63) 0.6027 0.56 (0.38, 0.81) 0.0022 1.13 (0.32, 3.98) 0.8444 0.58 (0.28, 1.20) 0.1414 Months Since EHR*CHC 1.003 (0.98, 1.02) 0.7628 1.01 (1.002, 1.02) 0.016 1.02 (0.99, 1.06) 0.1447 1.006 (0.96, 1.05) 0.7975 Medicaid/Selfpay > 20% 1.21 (0.89, 1.66) 0.231 1.08 (0.89, 1.31) 0.4647 1.21 (0.83, 1.78) 0.3212 1.78 (1.13, 2.82) 0.0135 Practice has more than one provider 1.24 (0.83, 1.85) 0.28650.93 (0.76, 1.13) 0.45921.12 (0.74, 1.70) 0.57980.70 (0.45. 1.08) 0.1043

10. 10 Primary Care Information Project Two year trends of 151 independent practices show significant gains on four quality measures. Our findings suggest that independent small practices and community health centers, with the assistance from a community EHR extension program such as PCIP, can achieve clinical quality gains similar to those observed in larger, well-resourced integrated delivery systems. Our findings are particularly relevant to independent practices serving resource-challenged urban areas. Of the practice characteristics we analyzed, none accounted for consistent differences in the increases observed with the exception of duration using an EHR. In this study we observed increases of several percentage points per year, suggesting that long- term improvement can also occur. This continued progress supports the idea that urban independent practices can drive long-term improvements in population health, a finding that is especially promising since inner-city independent practices like those served by PCIP tend to see a larger than average number of patients who are both uninsured and suffering from more severe health issues. Continued support is needed to help independent primary care practices get the most from health IT as an investment to improve health care and focus on patient-centered, outcomes driven care and coordination.. DISCUSSION 1010

11. 11 Primary Care Information Project Several practices that adopted an EHR in the timeframe eligible for inclusion in the analyses were not able to transmit data and their performance on the indicators in this study are unknown, though practices with missing data have similar characteristics as those represented in the study. Providers working with PCIP represent a group of EHR users who have received a variety of assistance from PCIP staff, including training and guidance on quality improvement strategies, technical support on EHR software (upgrades, patches, and configuration), and connection for health information exchange. Comparable data are not available to ascertain whether providers who do not have access to the same types of assistance would experience similar improvement trends. Improvement due to better documentation alone in the EHR was not tested in this study. For lab tests where an electronic lab interface was not available and the practice does not routinely enter results into the patient’s record, practice rates on these tests will be under reported. Factors such as incentives, availability of CDSS alert, number of QI visits, PCMH recogization, etc. will be put into the analysis to detect significant driving forces for the quality measures improvement. LIMITATION and NEXT STEPS 1111

12. 12 Primary Care Information Project OTHER PCIP STUDIES (1). Health Information Systems in Small Practices: Improving the Delivery of Clinical Preventive Services. AJPM. November 2011.

13. 13 Primary Care Information Project OTHER PCIP STUDIES (2). Validity of EHR Derived Quality Measurement for Monitoring Population Health & Clinical Quality. JAMIA. Feb 2012.

14. 14 Primary Care Information Project OTHER PCIP STUDIES (3). Decline and Rebound: Population Trends in Performance on Clinical Quality Measures in Small Practices Adopting Electronic Health Records. Academy Health Annual Meeting, Orlando, FL. June 2012.

15. 15 Primary Care Information Project OTHER PCIP STUDIES (4). Two year quality trends for independent practices adopting an EHR and achieving PCMH recognition. AHRQ Annual Meeting, Washington DC, September 2012. 1515

16. 16 Primary Care Information Project Acknowledgments 1616 Authors: Jason J. Wang PhD, Kimberly M. Sebek MPH, Colleen M. McCullough BA, Sam C. Amirfar MD, Amanda S. Parsons MD, MBA, Jesse Singer DO, MPH, Sarah C. Shih MPH Contact: Jason Wang, Ph.D., Sr. Director of Program Evaluation and Analysis Primary Care Information Project, NYC Department of Health and Mental Hygiene Long Island City (Queens), NY 11101. Tel: (347) 396-4859, Email: jwang5@health.nyc.govjwang5@health.nyc.gov Acknowledgments: The authors would like to acknowledge Dr. Thomas Farley, Commissioner of the New York City Department of Health for the valuable input on this study. The authors also wish to thank the PCIP staff for their tremendous dedication and participating practices’ commitment to improving health in New York City. Funding: A portion of this study was supported by the Agency for Healthcare Research and Quality (grant #s R18HS17059 and 17294). The funder played no role in the study design, in the collection, analysis and interpretation of data, in the writing of the report or in the decision to submit the paper for publication