Practice Facilitation and Clinical Performance Feedback Using the Electronic Health Record Improved Blood Pressure and Cholesterol Management in Small Primary Care Practices in New York City.

Cardiovascular disease (CVD) disproportionately affects people of color and those with lower household income. Improving blood pressure (BP) and cholesterol management for those with or at risk for CVD can improve health outcomes. The New York City Department of Health implemented clinical performance feedback with practice facilitation (PF) in 134 small primary care practices serving on average over 84% persons of color. Facilitators reviewed BP and cholesterol management data on performance dashboards and guided practices to identify and outreach to patients with suboptimal BP and cholesterol management. Despite disruptions from the COVID-19 pandemic, practices demonstrated significant improvements in BP (68%-75%, P < .001) and cholesterol management (72%-78%, P = .01). Prioritizing high-need neighborhoods for impactful resource investment, such as PF and data sharing, may be a promising approach to reducing CVD and hypertension inequities in areas heavily impacted by structural racism.

Practice facilitation for scale up of clinical decision support for hypertension management: study protocol for a cluster randomized control trial.

BACKGROUND: Only half of patients with hypertension have adequately controlled blood pressure. Clinical decision support (CDS) has the potential to overcome barriers to delivering guideline-recommended care and improve hypertension management. However, optimal strategies for scaling CDS have not been well established, particularly in small, independent primary care practices which often lack the resources to effectively change practice routines. Practice facilitation is an implementation strategy that has been shown to support process changes. Our objective is to evaluate whether practice facilitation provided with hypertension-focused CDS can lead to improvements in blood pressure control for patients seen in small primary care practices. METHODS/DESIGN: We will conduct a cluster randomized control trial to compare the effect of hypertension-focused CDS plus practice facilitation on BP control, as compared to CDS alone. The practice facilitation intervention will include an initial training in the CDS and a review of current guidelines along with follow-up for coaching and integration support. We will randomize 46 small primary care practices in New York City who use the same electronic health record vendor to intervention or control. All patients with hypertension seen at these practices will be included in the evaluation. We will also assess implementation of CDS in all practices and practice facilitation in the intervention group. DISCUSSION: The results of this study will inform optimal implementation of CDS into small primary care practices, where much of care delivery occurs in the U.S. Additionally, our assessment of barriers and facilitators to implementation will support future scaling of the intervention. CLINICALTRIALS: gov Identifier: NCT05588466.

Medication Nonuse and Hospital Utilization: Medicaid Participants With Type 2 Diabetes in New York City.

INTRODUCTION: This study assesses the proportion of New York City Medicaid participants diagnosed with type 2 diabetes who did not have any claims for diabetes medication for an entire year and the association between nonuse of diabetes medication and subsequent hospitalizations. METHODS: The 2014‒2016 New York State Medicaid claims data were used for this cohort study. Two types of hospitalizations were examined: all-cause hospitalizations and preventable diabetes hospitalizations. A potential association between medication nonuse and the number of hospitalizations in the following year was assessed using the negative binomial regression model, adjusting for individual- and neighborhood-level factors. The study was conducted in 2019‒2020. RESULTS: Among the 117,183 individuals included in this study, 27.5% did not use any diabetes medication for an entire year. Compared with individuals using oral hypoglycemic medication only, the crude rate of all-cause hospitalizations among individuals who used no medication was approximately twice as high (37,111 vs 19,209 per 100,000 population), and the crude rate of preventable diabetes hospitalizations was almost 3 times as high (1,488 vs 537 per 100,000 population). Adjusting for individual- and neighborhood-level characteristics, medication nonuse was still associated with higher levels of all-cause hospitalizations (incidence rate ratio=1.26; 95% CI=1.21, 1.31) and preventable diabetes hospitalizations (incidence rate ratio=1.66; 95% CI=1.39, 1.99). CONCLUSIONS: Medication use and adherence are important for managing diabetes. However, almost 30% of New York City Medicaid participants with type 2 diabetes had no claims for diabetes medication for an entire year. Significantly higher hospitalization rates among this group warrant attention from providers and policy makers.

Using a Customer Relationship Management System to Manage a Quality Improvement Intervention.

HealthyHearts New York City (HHNYC), one of 7 cooperatives funded through the Agency for Healthcare Research and Quality's EvidenceNOW initiative, evaluated the impact of practice facilitation on implementation of the Million Hearts guidelines for cardiovascular disease prevention and treatment. Tracking the intervention required a system to facilitate process data collection that was also user-friendly and flexible. Coupled with protocols and training, a strategically planned and customizable customer relationship management system (CRMS) was implemented to support the quality improvement intervention with 257 small independent practices. Features of the CRMS and implementation protocols were customized to optimize program management, practice facilitation tracking and supervision, and data collection for performance feedback to practices and research. The CRMS was a valuable tool for tracking and managing the intervention systematically. Successful implementation of the HHNYC protocol also required an articulated implementation plan and adoption process.

Effect of Physician Participation in a Multi-element Health Information and Data Exchange Program on Chronic Illness Medication Adherence.

BACKGROUND: The Primary Care Information Project (PCIP) includes a network of more than 10,000 physicians across New York City focusing on improving the quality of patient care through the use of health information technology and data exchange. METHODS: We assessed adherence, defined as the percentage with a medication possession ratio (MPR) ≥80%, across 2 time periods for union members whose primary care providers participated in the PCIP compared with those whose providers did not participate. Using prescription claims data from 2008 and 2011, the MPR was calculated for disease-specific categories of drugs among patients with diabetes, hypertension, and both conditions. RESULTS: Greater improvements in the number of adherent members were observed for the PCIP patients with diabetes who were taking diabetes-specific medications (odds ratio [OR], 2.03; 95% confidence interval [CI], 1.08-3.83 for PCIP, versus OR, 1.14; 95% CI, 0.81-1.60 for non-PCIP) and patients with diabetes who are taking lipid-controlling medications (OR, 1.64; 95% CI, 0.73-3.65 for PCIP versus OR, 0.85; 95% CI, 0.55-1.32 for non-PCIP). However, the magnitude and significance of these associations were diminished when practices providing reduced prescription co-pays were excluded from the analyses. CONCLUSION: Access to primary care providers participating in a public health initiative was associated with some improvement in medication adherence. However, reducing prescription co-pays may be a stronger factor for higher medication adherence among union members.

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: $200/patient; $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.

Early assessment of health care utilization among a workforce population with access to primary care practices with electronic health records.

This study assesses the health care costs and utilization among labor union members from 2008 to 2010 and compares whether members accessing primary care providers participating in a public health city program, the Primary Care Information Project (PCIP), had different health care usage or cost patterns. Using claims data, the number of hospital inpatient services utilized decreased by 16 per 100 members among those with chronic conditions accessing PCIP providers, whereas members seeing non-PCIP providers increased by 15 per 100 members. Access to providers participating in a population health initiative was associated with lower utilization of inpatient services and overall costs.

Patient experiences at primary care practices using electronic health records.

We assessed patient experiences before and one year after electronic health record (EHR) implementation among primary care practices in New York City. These practices represented an ethnically diverse population in lower-income, urban communities. Surveys, available in English, Spanish, and Chinese languages, were administered at 10 sites. Generally, patients reported positive responses during both periods. After EHR implementation, patients were more likely to want e-mail communication with their doctors' office. The 70% of patients with Internet access were generally more satisfied with their experience and more likely to recognize benefits of EHRs. However, older patients and those with lower education levels or chronic diseases were significantly less likely than their counterparts to use the Internet. Therefore, disparities in Internet access could potentially lead to unequal access and use of healthcare if not addressed. Practices should routinely record patient communication preferences within the EHR, to tailor communications and improve patient experiences.

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

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.

The business end of health information technology. Can a fully integrated electronic health record increase provider productivity in a large community practice?

Electronic health records (EHRs) are expected to transform and improve the way medicine is practiced. However, providers perceive many barriers toward implementing new health information technology. Specifically, they are most concerned about the potentially negative impact on their practice finances and productivity. This study compares the productivity of 75 providers at a large urban primary care practice from January 2005 to February 2009, before and after implementing an EHR system, using longitudinal mixed model analyses. While decreases in productivity were observed at the time the EHR system was implemented, most providers quickly recovered, showing increases in productivity per month shortly after EHR implementation. Overall, providers had significant productivity increases of 1.7% per month per provider from pre- to post-EHR adoption. The majority of the productivity gains occurred after the practice instituted a pay-for-performance program, enabled by the data capture of the EHRs. Coupled with pay-for-performance, EHRs can spur rapid gains in provider productivity.

Associations between ozone and daily mortality: analysis and meta-analysis.

BACKGROUND: There is ample evidence that short-term ozone exposure is associated with transient decrements in lung functions and increased respiratory symptoms, but the short-term mortality effect of such exposures has not been established. METHODS: We conducted a review and meta-analysis of short-term ozone mortality studies, identified unresolved issues, and conducted an additional time-series analysis for 7 U.S. cities (Chicago, Detroit, Houston, Minneapolis-St. Paul, New York City, Philadelphia, and St. Louis). RESULTS: Our review found a combined estimate of 0.39% (95% confidence interval = 0.26-0.51%) per 10-ppb increase in 1-hour daily maximum ozone for the all-age nonaccidental cause/single pollutant model (43 studies). Adjusting for the funnel plot asymmetry resulted in a slightly reduced estimate (0.35%; 0.23-0.47%). In a subset for which particulate matter (PM) data were available (15 studies), the corresponding estimates were 0.40% (0.27-0.53%) for ozone alone and 0.37% (0.20-0.54%) with PM in model. The estimates for warm seasons were generally larger than those for cold seasons. Our additional time-series analysis found that including PM in the model did not substantially reduce the ozone risk estimates. However, the difference in the weather adjustment model could result in a 2-fold difference in risk estimates (eg, 0.24% to 0.49% in multicity combined estimates across alternative weather models for the ozone-only all-year case). CONCLUSIONS: Overall, the results suggest short-term associations between ozone and daily mortality in the majority of the cities, although the estimates appear to be heterogeneous across cities.

Monitor-to-monitor temporal correlation of air pollution in the contiguous US.

Numerous studies have reported short-term associations between ambient air pollution concentrations and mortality and morbidity. Particulate matter (PM) was often implicated as the most significant predictor of the health outcomes among the various air pollutants. However, a question remains as to the potential role played by the relative error of exposure estimation associated with each pollutant in defining their relative strengths of association. While most of the recent studies on PM exposure measurements have focused on the temporal correlation between personal exposures and the concentrations observed at ambient air quality monitors (within a few miles from the subjects), there have been few studies that systematically evaluated spatial uniformity of temporal correlation of air pollution within the scale of a city (several tens of miles) for which mortality or morbidity outcomes are aggregated in time-series studies. In this study, spatial uniformity of temporal correlation was examined by computing monitor-to-monitor correlation using available multiple monitors for PM(10) and gaseous criteria pollutants (NO(2), SO(2), CO, and O(3)) in the nationwide data between 1988 and 1997. For each monitor, the median of temporal correlation with other monitors within the Air Quality Control Region (AQCR) was computed. The resulting median monitor-to-monitor correlation was modeled as a function of qualitative site characteristics (i.e., land-use, location-setting, and monitoring-objective) and quantitative information (median separation distance, longitude/latitude or regional indicators) for each pollutant. Generalized additive models (GAM) were used to fit the smooth function of the separation distance and regional variation. The intercepts of the models across pollutants showed the overall rankings in monitor-to-monitor correlation on the average to be: O(3), NO(2), and PM(10), (r approximately 0.6 to 0.8)>CO (r<0.6)>SO(2) (r<0.5). Both the separation distance and regional variation were important predictors of the correlation. For PM(10), for example, the correlation for the monitors along the East Coast was higher by approximately 0.2 than western regions. The qualitative monitor characteristics were often significant predictors of the variation in correlation, but their impacts were not substantial in magnitude for most categories. These results suggest that the apparent regional heterogeneity in PM effect estimates, as well as the differences in the significance of health outcome associations across pollutants, may in part be contributed to by the differences in monitor-to-monitor correlations by region and across pollutants.

Contribution of respiratory disease to nonrespiratory mortality associations with air pollution.

Many time series studies have found that individuals with primary cardiac conditions were susceptible to the adverse effects associated with increased ambient particle levels. However, the mechanism(s) of these associations is not yet understood. In this study, we evaluate whether individuals with nonrespiratory primary causes of death who also had contributing respiratory causes listed on their death certificates were more affected by air pollution, as compared with those not having contributing respiratory conditions. Short-term associations between ambient particulate matter (10 microm or less in aerodynamic diameter) and mortality were modeled in New York City for the years 1985-1994. It was observed that among those 75 years or more, those with contributing respiratory disease had higher relative risks (95% confidence intervals) calculated per interquartile range, as compared with those without contributing respiratory disease for both circulatory deaths (relative risk = 1.066 [1.027-1.106] versus 1.022 [1.008-1.035]) and cancer deaths (relative risk = 1.129 [1.041-1.225] versus 1.025 [1.000-1.050]). However, this pattern of association was not observed for those who were less than 75 years old. The results of this study suggest that past studies may have underestimated the role of respiratory disease in pollution-mortality associations, especially among older adults.