1. Joyner J, Moore MA, Simmons DR, et al. Impact of performance improvement continuing medical education on cardiometabolic risk factor control: the COSEHC initiative. J Contin Educ Health Prof.2014;34(1):25-36. http://onlinelibrary.wiley.com/doi/10.1002/chp.21217/abstract. [Featured Article]
2. Moore DE, Green JS, Gallis HA. Achieving desired results and improved outcomes: integrating planning and assessment throughout learning activities. J Contin Educ Health Prof. 2009;29(1):1-15.
3. Boyle PJ, O’Neil KW, Berry CA, Stowell SA, Miller SC. Improving diabetes care and patient outcomes in skilled-care communities: successes and lessons from a quality improvement initiative. J Am Med Dir Assoc. 2013;14(5):340-344.
4. NHLBI. Landmark NIH study shows intensive blood pressure management may save lives: lower blood pressure target greatly reduces cardiovascular complications and deaths in older adults [press release]. NHLBI Website. http://www.nih.gov/news/health/sep2015/nhlbi-11.htm. Accessed September 11, 2015.
5. Shershneva MB, Mullikin EA, Loose A-S, Olson CA. Learning to collaborate: a case study of performance improvement CME. J Contin Educ Health Prof. 2008;28(3):140-147. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2782606/. [See blog post on this previously featured article at http://fullcircleclinicaleducation.com/todays-landmark-nhlbi-sprint-study-results-relate-to-this-2008-pi-cme-article-by-shershneva-olson-et-al/]
MeSH “Major” Terms of Featured Article : Education, Medical, Continuing/organization & administration; Metabolic Syndrome X/prevention & control; Models, Educational; Physicians, Family/education; Quality Improvement
Many of you who know me might recall that I moved from the Northeast to the Southeast U.S. some years back. As I learned about the people and culture of the Southeast, I commonly saw many dietary and lifestyle factors that would confer increased risks for cardiovascular diseases and diabetes—indeed, this part of the United States is known as “The Stroke Belt.” The Consortium for Southeastern Hypertension Control (COSEHC) initiative reported by Joyner et al sought to improve the control of these risk factors through a performance-improvement continuing medical education (PI-CME) activity . It somehow seems fated that I report this study because the lead author is based in the same North Carolina city where I have lived these many years, working at Wake Forest University. The PI-CME initiative itself was conducted with several primary care physician practices with designation as a COSEHC Cardiovascular Center of Excellence in Charleston, South Carolina; a comparable practice group served as a control. Results were reported to Moore’s Level 6 (patient health outcomes) .
The intervention included many overlapping and reinforcing elements that we would expect to see in a major initiative on a major health concern: using the plan-do-study-act (PDSA) model, researchers worked to “improve practice gaps by integrating evidence-based clinical interventions, physician-patient education, processes of care, performance metrics, and patient outcomes.” The intervention design included an action plan to include medical assistants and nurses in patient-level tasks and education, patient chart reminders, patient risk stratification, and sharing of physicians’ feedback on successful practice changes with other participating practices.
Because patient health outcome indicators were used to define educational effectiveness of the PI-CME initiative, the selection of measures is important to our understanding of study findings. The research team used cardiometabolic risk factor target treatment goals for 7 lab values as recommended by 3 sets of evidence-based guidelines (JNC-7, ATP-III, and ADA). The team set a more aggressive target for low-density lipoprotein cholesterol (LDL-C) because many patients had multiple risk factors for cardiometabolic diseases and coronary heart disease risk “can exist even in the absence of other risk factors.” Researchers investigated changes in patient subgroups: “diabetic, African American, the elderly (> 65 years), and female patient subpopulations and in patients with uncontrolled risk factors at baseline.” The authors note that the average patient in both intervention and control groups was clinically obese; other baseline health indicators were also similar.
Now to results, gathered at 6 months to assess changes in patients’ cardiometabolic risk factor values and control rates from baseline. The abstract summarizes findings as follows :
Only women receiving health care by intervention physicians showed a statistical improvement in their cardiometabolic risk factors as evidenced by a -3.0 mg/dL and a -3.5 mg/dL decrease in mean LDL cholesterol and non-HDL cholesterol, respectively, and a -7.0 mg/dL decrease in LDL cholesterol among females with uncontrolled baseline LDL cholesterol values. No other statistical differences were found.
I want to discuss some factors that could explain the little change seen in this study. First, the intervention was measured at just 6 months into the educational initiative; this is known to be barely adequate for assessing clinicians’ performance change, and even performance changes were not likely to produce significantly different lab values in patients with years of health-related practices that led to their higher risks. Interestingly, there was less room for improvement because patients in both groups had higher baseline risk-control rates than is seen at the U.S. national level, and the patients in the intervention group had even higher baseline risk-control rates than patients in the physician control group had.
The study did appear to improve noted performance gaps regarding gender disparities in care. The authors note 4 studies pointing out suboptimal treatment-intensification to control LDL-C in female vs. male patients and even physician bias or inaction for female patients. Thus the improved patient outcome data for LDL-C and non-HDL cholesterol among women treated by physicians in the intervention group indicates a narrowing of established gaps in attitude (Level 4) and/or performance (Level 5).
Here in “The Stroke Belt,” any effort to control cardiometabolic risk factors must include population-level initiatives and patient education, which I have seen state governments, public health departments, recreation centers, and schools undertake at many levels. Two items stand out as affecting the COSEHC report’s findings: that the study tried to measure changed patient health indicators too soon after intervention, and that the researchers tied themselves to the high standard of measuring Level 6 for a health concern that needs interventions among patients and the public that were not considered here. Indeed, because physicians’ feedback on successful changes during the initiative were shared across practices, we know that Level 4 – 5 competence and performance changes were achieved. The authors should be commended on their work to tackle this public health concern through a PI-CME initiative.
Finally, I want to mention that Joyner et al cite two studies by others I am humbled to name as colleagues. First, Sara Miller and others at Med-IQ (in a team often featured in Don Harting’s earlier posts in this Back to School campaign) published with PJ Boyle on improving diabetes care and patient outcomes in skilled-care (long-term-care) communities . Second, Joyner et al cite the article featured in this blog on September 11, 2015—which itself came up in my reporting on that day’s release of the landmark SPRINT study results of the NHLBI —by Shershneva, Olson, and others . The Joyner article noted the Shershneva team’s finding that “process mapping led to improvement in [a majority of CVD] measures” .