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 [1]. 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) [2].
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 [1]:
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 [3]. 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 [4]—by Shershneva,
Olson, and others [5]. The Joyner article noted the Shershneva team’s finding
that “process mapping led to improvement in [a majority of CVD] measures” [1].
References cited:
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://fullcirclece.blogspot.com/2015/09/todays-landmark-nhlbi-sprint-study.html]
MeSH “Major” Terms of Featured Article [1]: Education, Medical, Continuing/organization & administration; Metabolic Syndrome X/prevention & control; Models, Educational; Physicians, Family/education; Quality Improvement
