Sarah C. Shih

Effect of pay-for-performance incentives on quality of care in small practices with electronic health records: A randomized trial

IMPORTANCE Most evaluations of pay-for-performance (P4P) incentives have focused on large-group practices. Thus, the effect of P4P in small practices, where many US residents receive care, is largely unknown. Furthermore, whether electronic health records (EHRs) with chronic disease management capabilities support small-practice response to P4P has not been studied. OBJECTIVE To assess the effect of P4P incentives on quality in EHR-enabled small practices in the context of an established quality improvement initiative. DESIGN, SETTING, AND PARTICIPANTS A cluster-randomized trial of small (<10 clinicians) primary care clinics in New York City from April 2009 through March 2010. A city program provided all participating clinics with the same EHR software with decision support and patient registry functionalities and quality improvement specialists offering technical assistance. INTERVENTIONS Incentivized clinics were paid for each patient whose care met the performance criteria, but they received higher payments for patients with comorbidities, who had Medicaid insurance, or who were uninsured (maximum payments:

Measuring Practice Systems for Chronic Illness Care: Accuracy of Self-Reports from Clinical Personnel

200/patient;

Tracking the delivery of prevention-oriented care among primary care providers who have adopted electronic health records

100,000/clinic). Quality reports were given quarterly to both the intervention and control groups. MAIN OUTCOMES AND MEASURES Comparison of differences in performance improvement, from the beginning to the end of the study, between control and intervention clinics for aspirin or antithrombotic prescription, blood pressure control, cholesterol control, and smoking cessation interventions. Mixed-effects logistic regression was used to account for clustering of patients within clinics, with a treatment by time interaction term assessing the statistical significance of the effect of the intervention. RESULTS Participating clinics (n = 42 for each group) had similar baseline characteristics, with a mean of 4592 (median, 2500) patients at the intervention group clinics and 3042 (median, 2000) at the control group clinics. Intervention clinics had greater adjusted absolute improvement in rates of appropriate antithrombotic prescription (12.0% vs 6.1%, difference: 6.0% [95% CI, 2.2% to 9.7%], P = .001 for interaction term), blood pressure control (no comorbidities: 9.7% vs 4.3%, difference: 5.5% [95% CI, 1.6% to 9.3%], P = .01 for interaction term; with diabetes mellitus: 9.0% vs 1.2%, difference: 7.8% [95% CI, 3.2% to 12.4%], P = .007 for interaction term; with diabetes mellitus or ischemic vascular disease: 9.5% vs 1.7%, difference: 7.8% [95% CI, 3.0% to 12.6%], P = .01 for interaction term), and in smoking cessation interventions (12.4% vs 7.7%, difference: 4.7% [95% CI, -0.3% to 9.6%], P = .02 for interaction term). Intervention clinics performed better on all measures for Medicaid and uninsured patients except cholesterol control, but no differences were statistically significant. CONCLUSIONS AND RELEVANCE Among small EHR-enabled clinics, a P4P incentive program compared with usual care resulted in modest improvements in cardiovascular care processes and outcomes. Because most proposed P4P programs are intended to remain in place more than a year, further research is needed to determine whether this effect increases or decreases over time. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00884013.

Patient-Centered Medical Home Among Small Urban Practices Serving Low-Income and Disadvantaged Patients

BACKGROUND Purchasers, plans, and clinical practices involved in quality improvement initiatives are increasingly interested in measuring practice systems, particularly in relation to clinical quality and as part of pay-for-quality initiatives. The validity of self-reports of the use of practice systems was examined. METHODS In 11 medical groups in Minnesota, the Physician Practice Connections Readiness Survey, which was developed on the basis of the concepts and evidence base of the Chronic Care Model, was used to survey office practice personnel about practice systems. Participation rates by medical group ranged from 61% to 94%, with a mean of 76%, yielding surveys from 32 lead physicians and 241 other personnel. Survey results were compared with an on-site audit by trained surveyors. RESULTS Overall agreement with the on-site audit ranged from 40.9% to 96.7% among lead physicians and from 33.9% to 81.9% among other personnel. Mean agreement was high for quality improvement (96.7% for lead physicians and 81.9% for other personnel), moderate for clinical information systems (71.2% for lead physicians and 66.0% for others), and low for the use of care management (less than 50% for both groups). Mean positive predictive value ranged from 55.2% to 100% among lead physicians and from 49.6% to 100% among other personnel. Both the presence of systems and the accuracy of reporting varied across medical groups. DISCUSSION The accuracy of self-reports of practice systems varies by type of system being assessed and by type of respondent. Although self-assessment may be useful for quality improvement purposes, self-reported information on clinical practices systems should not be used for accountability purposes, including pay-for-quality efforts or public reporting unless additional documentation is required to ensure fair comparisons.

The intended and unintended consequences of quality improvement interventions for small practices in a community-based electronic health record implementation project.

The Primary Care Information Project is a New York City initiative aimed at improving population health through the improved delivery of preventive care. It has assisted with the adoption of a fully functional electronic health record (EHR) in over 300 primary care practices. Practices with EHRs automatically transmit summary data that can be used to track population health indicators for recommended preventive care. Early analysis, focusing on small practices with fewer than 10 providers serving Medicaid and uninsured populations, showed increases in the delivery of recommended services of 0.1-2.4% per month (p ≤ 0.05). However, measurement of preventive care across this population is limited by some inconsistency of data transmission. This study shows that EHRs can be used to track the delivery of recommended preventive care across small primary care practices serving lower income communities in which few data are generally available for assessing population health.

Health IT–Enabled Care Coordination: A National Survey of Patient-Centered Medical Home Clinicians

PURPOSE Research on the patient-centered medical home (PCMH) model and practice redesign has not focused on the unique challenges and strengths of very small primary care practices serving disadvantaged patient populations. We analyzed the practice characteristics, prior experiences, and dimensions of the PCMH model that exist in such practices participating in the Primary Care Information Project (PCIP) of the New York City Department of Mental Health and Hygiene. METHODS We obtained descriptive data, focusing on PCMH, for 94 primary care practices with 5 or fewer clinicians serving high volumes of Medicaid and minority patient populations in New York City. Data included information extracted from PCIP administrative data and survey data collected specifically for this study. RESULTS Survey results indicated substantial implementation of key aspects of the PCMH among small practices serving disadvantaged patient populations, despite considerable potential challenges to achieving PCMH implementation. Practices tended to use few formal mechanisms, such as formal care teams and designated care or case managers, but there was considerable evidence of use of informal team-based care and care coordination nonetheless. It appears that many of these practices achieved the spirit, if not the letter, of the law in terms of key dimensions of PCMH. CONCLUSIONS Small practices can achieve important aspects of the PCMH model of primary care, often with informal rather than formal mechanisms and strategies. The use of flexible, less formal strategies is important to keep in mind when considering implementation and assessment of PCMH-like initiatives in small practices.

Sustained Improvement in Clinical Preventive Service Delivery Among Independent Primary Care Practices After Implementing Electronic Health Record Systems

Background:Despite the rapid rise in the implementation of electronic health records (EHR), commensurate improvements in health care quality have not been consistently observed. Objectives:To evaluate whether the implementation of EHRs and complementary interventions—including clinical decision support, technical assistance, and financial incentives—improved quality of care. Research Design:The study included 143 practices that implemented EHRs as part of the Primary Care Information Project—a long-standing community-based EHR implementation initiative. A total of 71 practices were randomized to receive financial incentives and quality feedback and 72 were randomized to feedback alone. All practices received technical assistance and had clinical decision support in their EHR. Using data from 2009 to 2011, we estimated measure-level fixed effects models to evaluate the association between exposure to clinical decision support, technical assistance, financial incentives, and quality of care. Associations were estimated separately for 4 cardiovascular measures that were rewarded by the financial incentive program and 4 measures that were not rewarded by incentives. Results:Financial incentives for quality were consistently associated with higher performance for the incentivized measures [+10.1 percentage points at 18 mo of exposure (approximately +22%), P<0.05] and lower performance for the unincentivized measures [−8.3 percentage points at 12 mo of exposure (approximately −20%), P<0.05]. Technical assistance was associated with higher quality for the unincentivized measures, but not for the incentivized measures. Conclusions:Technical assistance and financial incentives—alongside EHR implementation—can improve quality of care. Financial incentives for quality may not result in similar improvements for incentivized and unincentivized measures.

Patient Characteristics Associated With Smoking Cessation Interventions and Quit Attempt Rates Across 10 Community Health Centers With Electronic Health Records

PURPOSE Health information technology (IT) offers promising tools for improving care coordination. We assessed the feasibility and acceptability of 6 proposed care coordination objectives for stage 3 of the Centers for Medicare and Medicaid Services electronic health record incentive program (Meaningful Use) related to referrals, notification of care from other facilities, patient clinical summaries, and patient dashboards. METHODS We surveyed physician-owned and hospital/health system–affiliated primary care practices that achieved patient-centered medical home recognition and participated in the Meaningful Use program, and community health clinics with patient-centered medical home recognition (most with certified electronic health record systems). The response rate was 35.1%. We ascertained whether practices had implemented proposed objectives and perceptions of their importance. We analyzed the association of organizational and contextual factors with self-reported use of health IT to support care coordination activities. RESULTS Although 78% of the 350 respondents viewed timely notification of hospital discharges as very important, only 48.7% used health IT systems to accomplish this task. The activity most frequently supported by health IT was providing clinical summaries to patients, in 76.6% of practices; however, merely 47.7% considered this activity very important. Greater use of health IT to support care coordination activities was positively associated with the presence of a nonclinician responsible for care coordination and the practice’s capacity for systematic change. CONCLUSIONS Even among practices having a strong commitment to the medical home model, the use of health IT to support care coordination objectives is not consistent. Health IT capabilities are not currently aligned with clinicians’ priorities. Many practices will need financial and technical assistance for health IT to enhance care coordination.

Factors Related to Clinical Quality Improvement for Small Practices Using an EHR

Introduction Studies showing sustained improvements in the delivery of clinical preventive services are limited. Fewer studies demonstrate sustained improvements among independent practices that are not affiliated with hospitals or integrated health systems. This study examines the continued improvement in clinical quality measures for a group of independent primary care practices using electronic health records (EHRs) and receiving technical support from a local public health agency. Methods We analyzed clinical quality measure performance data from a cohort of primary care practices that implemented an EHR at least 3 months before October 2009, the study baseline. We assessed trends for 4 key quality measures: antithrombotic therapy, blood pressure control, smoking cessation intervention, and hemoglobin A1c (HbA1c) testing based on monthly summary data transmitted by the practices. Results Of the 151 practices, 140 were small practices and 11 were community health centers; average time using an EHR was 13.7 months at baseline. From October 2009 through October 2011, average rates increased for antithrombotic therapy (from 58.4% to 74.8%), blood pressure control (from 55.3% to 64.1%), HbA1c testing (from 46.4% to 57.7%), and smoking cessation intervention (from 29.3% to 46.2%). All improvements were significant. Conclusion During 2 years, practices showed significant improvement in the delivery of several key clinical preventive services after implementing EHRs and receiving support services from a public health agency.

Quality Measure Performance in Small Practices Before and After Electronic Health Record Adoption

OBJECTIVES We used electronic health record (EHR) data to determine rates and patient characteristics in offering cessation interventions (counseling, medications, or referral) and initiating quit attempts. METHODS Ten community health centers in New York City contributed 30 months of de-identified patient data from their EHRs. RESULTS Of 302 940 patients, 40% had smoking status recorded and only 34% of documented current smokers received an intervention. Women and younger patients were less likely to have their smoking status documented or to receive an intervention. Patients with comorbidities that are exacerbated by smoking were more likely to have status documented (82.2%) and to receive an intervention (52.1%), especially medication (10.8%). Medication, either alone (odds ratio [OR] = 1.9; 95% confidence interval [CI] = 1.5, 2.3) or combined with counseling (OR = 1.8; 95% CI = 1.5, 2.3), was associated with higher quit attempts compared with no intervention. CONCLUSIONS Data from EHRs demonstrated underdocumentation of smoking status and missed opportunities for cessation interventions. Use of data from EHRs can facilitate quality improvement efforts to increase screening and intervention delivery, with the potential to improve smoking cessation rates.