Jesse Singer, DO, MPH

To assess performance on quality measures among small primary care practices that recently adopted an electronic health record (EHR), and how performance differs between practices that have achieved patient-centered medical home (PCMH) recognition and those that have not.

Comparison of practice characteristics and performance on quality measures across 150 independent practices from 2009 to 2011 by recognition status for Physician Practice Connections—PCMH.

PCMH-recognized practices performed significantly better than nonrecognized practices on 5 out of 7 clinical quality measures at baseline, and the differences were maintained over the 2-year study period. Both groups improved on all clinical quality measures. Though the magnitude of differences was small, PCMHrecognized practices had a higher number of patients diagnosed with hypertension and proportionally more black patients. A significant difference in PCMH-recognized practices is that they received, on average, 4 additional quality improvement visits compared with nonrecognized practices.

Among small practices that have adopted EHRs, practices with PCMH recognition consistently outperformed practices without recognition on most clinical quality measures. With adequate assistance, small, resource-strapped practices can continue to have higher performance on clinical quality measures.

Patient-centered medical home (PCMH) recognition in small practices is associated with higher performance on quality measures over time.

		Small practices with PCMH recognition perform better on quality measures related to chronic conditions

		The differences observed between the practice groups appear to be sustainable over the 2-year study period.

		Quality measure performance is correlated with greater participation in a quality improvement program.

The patient-centered medical home (PCMH) concept has been widely promoted as a way to enhance primary care and deliver better care to patients with chronic conditions.

 This model of care has stimulated the attention of payers, Medicaid policy makers, physicians, and patient advocates, as it has the potential to address several of the shortcomings of the current healthcare system.

Components of the PCMH model include practice-based policies and processes intended to improve healthcare quality, patient experience, clinician satisfaction, and costs of care.

 Pilots and demonstration projects have yielded mixed results, but positive reports associate PCMHs in large practices and institutions with decreases in costs for patients enrolled in Medicaid; increased care of Medicaid patients; and positive patient and clinician experiences.

 Recently published studies have also shown that components of the medical home (eg, care coordination, pre-visit planning) are associated with positive effects on clinical outcomes for patients and quality of life for clinicians.

The process of transforming and achieving recognition as a medical home can be difficult, especially for small practices with few resources.

Additionally, small practices located in low income neighborhoods face challenges unique to their settings (eg, smaller panel size for quality measurement, lack of information systems, and lack of support staff) which can further exacerbate their ability to generate the documentation needed to demonstrate transformation and meet the standards for recognition.

 Promoting the adoption of PCMH standards in small primary care practices in lower income neighborhoods with a large proportion of chronically ill patients can be advantageous for reducing healthcare inequalities.

As part of a larger public health initiative, the Primary Care Information Project (PCIP), a bureau within the New York City Department of Health and Mental Hygiene, has offered assistance to small, independent practices in New York City to complete the application for the National Committee for Quality Assurance’s (NCQA’s) Physician Practice Connections—Patient Centered Medical Home (PPC-PCMH) recognition program.15 This study assesses the clinical quality outcomes of PCIP-participating practices that have achieved PPC-PCMH recognition from NCQA, and compares performance on quality measures from 2009 through 2011 in practices that have been PCMH-recognized with those that have not.

In an effort to transform primary care and improve population health, PCIP assists primary care practices in the adoption and use of electronic health records (EHRs). From its inception in 2005 through early 2012, PCIP assisted over 3000 primary care clinicians located in over 600 independently owned practices to adopt preventionoriented EHR systems. Collectively, PCIP participants represent over 20% of New York City’s primary care clinicians and serve approximately 2.6 million patients.

Recognizing that digitizing the information around healthcare alone would not bring about the changes needed to improve the delivery of clinical preventive services, PCIP offers additional support to address both technical needs and quality improvement (QI).

 PCIP employs a field team dedicated to assisting clinicians in optimizing work flows and leveraging data from their own EHR systems to track clinical quality performance. Much of the QI curriculum was modeled around the standards articulated by the NCQA’s PPC-PCMH program. This included an initial visit to identify practice leadership or champion for QI activities; follow-up meetings with the practice or provider to review progress on meeting QI objectives; using the functions within the EHR, such as the registry tool that generates lists of patients by selected characteristics (eg, diagnosis of hypertension with blood pressure over 140/90 mm Hg without a visit to practice in past 6 months and no scheduled visit in next 3 months); and reviewing the quality reporting tool—a specific feature within eClinical- Works co-developed with PCIP to display quality measures tied to the city’s health policy agenda.

 PCIP offered visits to practices every 4 to 6 weeks; staff were available by e-mail and phone to answer questions in addition to the on-site visits.

To encourage and facilitate the PPC-PCMH recognition process, PCIP established a multi-site application and offered to practices the ability to apply under the 2008 standards. Fees for the application were also subsidized by PCIP. Because some of the PCMH standards had been met across all PCIP practices, such as having an EHR with clinical decision support, clinicians did not have to repeat some of the standard documentation related to their EHRs in their NCQA applications. PCIP practices eligible to be included in the multi-site application were eligible to receive 36.75 points, which at the time was adequate for obtaining Level 1 recognition. However, all practices still needed to provide supporting documentation to demonstrate to NCQA their use of the systems; if practices wished to do so, they could work towards a higher recognition level by submitting additional documentation. NCQA then reviewed the documentation gathered by practices and submitted by PCIP to determine whether clinicians in the application met Level 1, 2, or 3 PPC-PCMH standards. By early 2012, PCIP had assisted roughly 25% of its member practices in achieving NCQA recognition, including 269 sites representing 169 practices and 657 clinicians to meet 2008 standards. Practices applying for PPC-PCMH recognition after July 1, 2012, are required to follow 2011 standards.

Primary care practices were included in this analysis if they had 5 or fewer clinicians and adopted the eClinicalWorks EHR system prior to October 2009. Pediatricfocused practices were excluded as the quality measures analyzed were limited to adult primary care. Practices were also excluded if data were unavailable for either of the 2 analysis periods: October 2009 and October 2011. Because the process of obtaining NCQA recognition can take between 6 to 12 months, practices were categorized into the PCMH-recognized group if they achieved NCQA recognition at any time up until February 2012.

As part of a contract negotiated with eClinicalWorks, PCIP established an automated monthly data transmission process to receive summarized data generated from each practice’s EHR. Practices receiving support from PCIP have agreed to provide data transmitted through this process. The data transmitted consisted of clinician-level aggregated counts of patients meeting numerator and denominator definitions for each of the quality measures, developed to be consistent with National Quality Forum measure definitions. 

 EHR utilization data are also received monthly, including number of labs reviewed, order sets used, number of monthly encounters per full-time equivalent (FTE), number of unique patients seen per month, as well as proportions of patients by age group, gender, race/ethnicity, or with a diagnosis of hypertension, diabetes, or both. PCIP staff used Salesforce, a commercially available, Webbased customer relationship management (CRM) application to monitor activities with the practices (eg, site visits with QI or other PCIP staff, attendance at classes or seminars hosted by PCIP or the vendor), maintain program administration and contact information, and track practice milestones such as initial contact for recruitment and date of EHR “go-live.”

Seven clinical quality measures of care and documentation were selected for analysis: (1) antithrombotic therapy for patients with diabetes or ischemic vascular disease; (2) blood pressure control in hypertensive patients with and without diabetes (2 separate measures); (3) body mass index (BMI) recorded; (4) glycated hemoglobin (A1C) testing in patients with diabetes; (5) smoking status recorded; and (6) smoking cessation intervention, including counseling, prescription drugs, and referrals to the New York State fax-to-quit hotline for identified smokers (

). These 7 measures were selected because they are indicators of clinical performance aimed at preventing and reducing smoking, diabetes, and cardiovascular disease, all of which are leading contributors to a large burden of morbidity and mortality within New York City and the United States.

 These chronic conditions are also frequently reported by PCIP field staff as some of the most common conditions among patients in practices seeking NCQA PCMH recognition.

Practices were grouped together based on whether they had an NCQA PCMH recognition status. We chose February 2012 as the cutoff date to categorize practices with or without an NCQA recognition status (Level 1, 2, or 3). Frequencies and descriptive statistics were generated and simple t tests and χ² tests were conducted to compare baseline practice characteristics for practices that did and did not receive PCMH recognition (

). To illustrate the time distribution of practices achieving PCMH recognition, we graphed NCQA recognition dates (

). Separately, we plotted the monthly cumulative average QI visits (on-site assistance provided to practices) by whether practices were PCMH-recognized or not from October 2009 to October 2011 (

We compared performance over time on quality measures over the same time period (October 2009-October 2011). Performance on each quality measure was constructed as a rate (numerator divided by denominator) for each practice for each month. To calculate meaningful rates and create stable comparisons, practices were excluded from individual measure analyses if their denominator for that measure was less than or equal to 10. Simple 

 tests were used to compare the performance on measures between practices with and without PCMH recognition at the baseline (October 2009) and current (October 2011) time points and to compare changes in quality measure performance within the groups (Table 1). Average rates of PCMH-recognized (solid lines) and nonrecognized practices (dashed lines) were graphed for each quality measure from October 2009 through October 2011 (

Mixed model regression was used to examine the differences in improvement between PCMH and non-PCMH practices over time for each quality measure, allowing each practice to have a different intercept to account for unexplained practice heterogeneity. 

shows the odds ratios (ORs) and 95% CIs generated from a general estimation model for the effects of PCMH recognition, time, and the interaction between the 2 variables across practices. All statistical analyses were conducted with SAS version 9.2 (SAS Institute Inc, Cary, North Carolina) and figures were drawn with R 2.15. For all statistical tests, a 2-tailed 

 value of less than .05 was considered statistically significant.

Out of 776 practices enrolled in PCIP as of July 2012, 349 were live on their system prior to October 2009. Of those, 150 practices met the selection criteria for inclusion in this analysis. Of the 150 included practices, 39.3% have achieved PCMH recognition from NCQA (Figure 1A), including 1 Level 2 and 12 Level 3 practices. The earliest practice to achieve PCMH recognition did so in February 2010, and the latest practice became PCMH-recognized in February 2012; half of practices gained recognition by December 2010.

PCMH-recognized and nonrecognized practices did not statistically differ at baseline in months using EHR, total encounters, number of clinicians, clinician FTE, or insurance type. PCMH-recognized practices had a slightly, though statistically significant, larger proportion of patients with hypertension (Table 2). A comparison of performance between practices by recognition level yielded no significant differences on any measure (data not shown).

At baseline, PCMH-recognized practices performed significantly better than nonrecognized practices on 5 of the 7 quality measures (Table 1). There was no difference in performance at baseline between PCMH-recognized and nonrecognized practices for the 2 blood pressure control measures. At the later time point (October 2011), PCMH-recognized practices outperformed nonrecognized practices on A1C testing, BMI recorded, blood pressure control in patients with both hypertension and diabetes, smoking status recorded, and smoking cessation intervention measures. There was no significant difference in performance between the practice groups on antithrombotic therapy and blood pressure control in patients with hypertension only.

Overall, both groups of practices improved on every measure over the 2-year period (Table 1). For 6 of the 7 measures, time using the EHR was a significant predictor of improvement (Table 3). For both of the blood pressure control measures, the interaction term was significant with an OR greater than 1, indicating that PCMH-recognized practices improved at a faster rate than nonrecognized practices. For the A1C testing measure and the BMI recorded measure, the interaction term was significant with an OR less than 1, suggesting that nonrecognized practices improved at a faster rate than PCMH-recognized practices. By the end of the study period, PCMH-recognized practices, on average, had received 4 more visits than nonrecognized practices with PCIP QI staff (Figure 1B).

Practices in both the PCMH-recognized and nonrecognized groups significantly improved performance on key clinical quality measures over the 2-year study period. At both the baseline and later time points, practices that had achieved PCMH recognition consistently performed better on process measures, including measures referring to in-office screenings or documentation proficiency, than practices that had not achieved PCMH recognition. PCMH-recognized practices performed about the same as nonrecognized practices at baseline on the blood pressure control measures in both diabetic and nondiabetic patients.

Time using the EHR was the most significant predictor of improvement on all quality measures, and the average time using the EHR was roughly the same for both groups of practices. Although both groups of practices improved on all measures over time, for some measures, PCMH recognition was associated with even greater improvement. PCMH-recognized practices improved at a faster rate than nonrecognized practices on both of the blood pressure control measures over the 2-year period, suggesting that PCMH recognition may have a positive effect on the quality of care for patients with multiple chronic conditions. Given that improved performance on these measures requires not only clinician intervention (eg, medication order) but also patient engagement (eg, medication compliance, lifestyle changes), it may be that practices that achieve recognition as a PCMH have learned to provide an enhanced level of care, enabling them to do better on these types of measures. There are different pathways of implementing the PCMH model and practices emphasize different components depending on their circumstances 

; however, PCMH pilots across the country have shown a similar correlation between component processes of the PCMH model and improvements in quality of care for patients with multiple morbidities.

Additionally, practice facilitator programs have been shown to have a positive impact on practice transformation; the PCIP QI curriculum may have had similar effects on the adoption of new processes or guidelines.

For other measures, PCMH recognition was not associated with a greater rate of improvement. Both groups improved at approximately the same rate on antithrombotic therapy and the 2 smoking measures, although a large gap remained in performance between PCMH-recognized and nonrecognized practices. Nonrecognized practices improved at a higher rate on BMI recorded and A1C testing. For both of these measures, nonrecognized practices performed significantly below PCMH-recognized practices at baseline, and our results indicated that over time, nonrecognized practices were able to reduce the initial gap in performance. Also worth noting is that the baseline rate of BMI recorded was quite high for PCMH-recognized practices (86%), and these practices may have reached a performance ceiling over the course of the study, whereas nonrecognized practices had more room to improve, leaving an opportunity to close the performance gap.

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