Cardiovascular Disease Preventive Services Among Smaller Primary Care Practices

Perspective: Leveraging Electronic Health Record Data Within Food Is Medicine Program Evaluation: Considerations and Potential Paths Forward

Government, health care systems and payers, philanthropic entities, advocacy groups, nonprofit organizations, community groups, and for-profit companies are presently making the case for Food is Medicine (FIM) nutrition programs to become reimbursable within health care services. FIM researchers are working urgently to build evidence for FIM programs' cost-effectiveness by showing improvements in health outcomes and health care utilization. However, primary collection of this data is costly, difficult to implement, and burdensome to participants. Electronic health records (EHRs) offer a promising alternative to primary data collection because they provide already-collected information from existing clinical care. A few FIM studies have leveraged EHRs to demonstrate positive impacts on biomarkers or health care utilization, but many FIM studies run into insurmountable difficulties in their attempts to use EHRs. The authors of this commentary serve as evaluators and/or technical assistance providers with the United States Department of Agriculture's Gus Schumacher Nutrition Incentive Program National Training, Technical Assistance, Evaluation, and Information Center. They work closely with over 100 Gus Schumacher Nutrition Incentive Program Produce Prescription FIM projects, which, as of 2023, span 34 US states and territories. In this commentary, we describe recurring challenges related to using EHRs in FIM evaluation, particularly in relation to biomarkers and health care utilization. We also outline potential opportunities and reasonable expectations for what can be learned from EHR data and describe other (non-EHR) data sources to consider for evaluation of long-term health outcomes and health care utilization. Large integrated health systems may be best positioned to use their own data to examine outcomes of interest to the broader field.

Differences in Use of Clinical Decision Support Tools and Implementation of Aspirin, Blood Pressure Control, Cholesterol Management, and Smoking Cessation Quality Metrics in Small Practices by Race and Sex

Importance

Practice-level evidence is needed to clarify the value of population-based clinical decision support (CDS) tools in reducing racial and sex disparities in cardiovascular care.

Objective

To evaluate the association between CDS tools and racial and sex disparities in the aspirin use, blood pressure control, cholesterol management, and smoking cessation (ABCS) care quality metrics among smaller primary care practices.

Design, Setting, and Participants

This cross-sectional study used practice-level data from the Agency for Healthcare Research and Quality-funded EvidenceNOW initiative. The national initiative from May 1, 2015, to April 30, 2021, spanned 12 US states and focused on improving cardiovascular preventive care by providing quality improvement support to smaller primary care practices. A total of 576 primary care practices in EvidenceNOW submitted both survey data and electronic health record (EHR)-derived ABCS data stratified by race and sex.

Main Outcomes and Measures

Practice-level estimates of disparities between Black and White patients and between male and female patients were calculated as the difference in proportions of eligible patients within each practice meeting ABCS care quality metrics. The association between CDS tools (EHR prompts, standing orders, and clinical registries) and disparities was evaluated by multiply imputed multivariable models for each CDS tool, adjusted for practice rurality, ownership, and size.

Results

Across the 576 practices included in the analysis, 219 (38.0%) had patient panels that were more than half White and 327 (56.8%) had panels that were more than half women. The proportion of White compared with Black patients meeting metrics for blood pressure (difference, 5.16% [95% CI, 4.29%-6.02%]; P < .001) and cholesterol management (difference, 1.49% [95% CI, 0.04%-2.93%] P = .04) was higher; the proportion of men meeting metrics for aspirin use (difference, 4.36% [95% CI, 3.34%-5.38%]; P < .001) and cholesterol management (difference, 3.88% [95% CI, 3.14%-4.63%]; P < .001) was higher compared with women. Conversely, the proportion of women meeting practice blood pressure control (difference, -1.80% [95% CI, -2.32% to -1.28%]; P < .001) and smoking cessation counseling (difference, -1.67% [95% CI, -2.38% to -0.95%]; P < .001) metrics was higher compared with men. Use of CDS tools was not associated with differences in race or sex disparities except for the smoking metric. Practices using CDS tools showed a higher proportion of men meeting the smoking counseling metric than women (coefficient, 3.82 [95% CI, 0.95-6.68]; P = .009).

Conclusions and Relevance

The findings of this cross-sectional study suggest that practices using CDS tools had small disparities that were not statistically significant, but CDS tools were not associated with reductions in disparities. More research is needed on effective practice-level interventions to mitigate disparities.

Priorities for improvement across cancer and non-cancer related preventive services among rural and non-rural clinicians

Introduction

It is not realistic for most clinicians to perform the multitude of recommended preventive primary care services. This is especially true in low resource and rural settings, creating challenges to delivering high-quality care. This study collected stakeholder input from clinicians on which services they most need to improve.

Methods

The authors conducted a survey of primary care physicians 9–12/2021, with an emphasis on rural practices, to assess areas in which clinicians felt the greatest needs for improvement. The survey focused on primary prevention (behavior change counseling) and cancer screening, and contrasted needs for improvement for these services vs. other types of screening, and between clinicians in rural vs. non-rural practices.

Results

There were 326 respondents from 4 different practice-based research networks, a wide range of practice types, 49 states and included 177 clinicians in rural settings. Respondents rated the need to improve delivery of primary prevention counseling services highest, with needs for nutrition and dietary assessment and counseling rated highest followed by physical activity and with almost no differences between rural and nonrural. Needs for improvement in cancer screenings were rated higher than non-cancer screenings, except for blood pressure screening.

Conclusions

Both rural and nonrural primary care clinicians feel a need for improvement, especially with primary prevention activities. Although future research is needed to replicate these findings with different populations and other types of preventive service activities, greater priority should be given to development of practical, stakeholder informed assistance and resources for primary care to conduct primary prevention.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-022-01845-1.

Effective Facilitator Strategies for Supporting Primary Care Practice Change: A Mixed Methods Study

PURPOSE

Practice facilitation is an evidence-informed implementation strategy to support quality improvement (QI) and aid practices in aligning with best evidence. Few studies, particularly of this size and scope, identify strategies that contribute to facilitator effectiveness.

METHODS

We conducted a sequential mixed methods study, analyzing data from EvidenceNOW, a large-scale QI initiative. Seven regional cooperatives employed 162 facilitators to work with 1,630 small or medium-sized primary care practices. Main analyses were based on facilitators who worked with at least 4 practices. Facilitators were defined as more effective if at least 75% of their practices improved on at least 1 outcome measure-aspirin use, blood pressure control, smoking cessation counseling (ABS), or practice change capacity, measured using Change Process Capability Questionnaire-from baseline to follow-up. Facilitators were defined as less effective if less than 50% of their practices improved on these outcomes. Using an immersion crystallization and comparative approach, we analyzed observational and interview data to identify strategies associated with more effective facilitators.

RESULTS

Practices working with more effective facilitators had a 3.6% greater change in the mean percentage of patients meeting the composite ABS measure compared with practices working with less effective facilitators (P <.001). More effective facilitators cultivated motivation by tailoring QI work and addressing resistance, guided practices to think critically, and provided accountability to support change, using these strategies in combination. They were able to describe their work in detail. In contrast, less effective facilitators seldom used these strategies and described their work in general terms. Facilitator background, experience, and work on documentation did not differentiate between more and less effective facilitators.

CONCLUSIONS

Facilitation strategies that differentiate more and less effective facilitators have implications for enhancing facilitator development and training, and can assist all facilitators to more effectively support practice changes.