I don't have to tell you the rate of type 2 diabetes is ridiculous and continues to rise. Globally it is hard to agree on cohesive recommendations as geography informs adherence to HbA1c levels of varying control benchmarks and other metrics.
The learning objectives (LOs) I see don't reflect this context. What I see are industry pipeline reports and marketing opportunities. My role as a collaborative partner is to educate about health policy, economics, and the clinical perspective of the clinician. Where are the true gaps? Unfortunately they don't always sit in a pretty box with a bow at the intersection of successfully acquired request for proprosals (RFPs) and clinical necessity at the patient level.
My inbox this morning alone contains several programs on how to approach the global scurge. Because as you can imagine, there is "gold" in them there insulin deprived hills. Here are just a few of the LOs:
- Implement strategies for the timely initiation of insulin therapy to best achieve glycemic control in patients with type 2 diabetes. (We need a discussion about glycemic control as a worthwhile target before we begin to educate on initiating therapy--don't we?)
- Outline the pharmacokinetic/pharmacodynamics profiles and evidence for emerging basal insulins for the treatment of type 2 diabetes.(How will "outlining" lead to better patient outcomes?)
The problem, as I see it, is we have yet to have meaningful conversations about the scope of glycemic control, ongoing discussions of risk factor management and actual disease prevention, how tight control parameters should be, presence or absence of quality evidence. As you can imagine, a learning objective focused on "outlining data" that might be influenced by a billion dollar industry might leave one with an arched-eyebrow.
What do we know about "value" in diabetes care? What about cost effectiveness? Marginal increases in efficacy? What about lifestyle interventions?
One of the major limitations of descriptive cost analyses such as those conducted by the American Diabetes Association (ADA) is that they do not provide an indication of the value obtained for the money spent.
The first thing that came to mind while reviewing the latest findings about novel and emerging GLP-1 receptor agonists, DPP-4 inhibitors, SGLT2 inhibitors, and/or injectable fixed-dose combinations was that study designs, study populations, and variable outcomes would be impossible to decipher at the individual patient level for the majority of practicing clinicians.
Improving Numeracy in Medicine attempts to create an informed dialogue but I recognize the limitations as ongoing questions continue to surface. I discussed p-values and their limitations on clinical significance but I am now reminded that 2-tail tests, like the null value often simplify and ignore the importance of one-sided clinical signficance.
The problem is that we haven't described the distinction of the novel treatment as being better, on the one hand, or worse/harmful, on the other,compared to a standard of care or placebo. When performing “2-sided” tests of statistical significance, we know nothing of superiority and non-inferiority. We also frequently misinterpret failure to reject the null hypothesis (based on 2-sided p values >5%, or 95% confidence intervals that include zero) as negative instead of inconclusive.
“It is never correct to claim that treatments have no effect or that there is no difference in the effects of treatments. It is impossible to prove ... that two treatments have the same effect. There will always be some uncertainty surrounding estimates of treatment effects, and a small difference can never be excluded."--Alderson and Chalmers
Devoid of the clinical expertise of the physician recognizing the uncertainty of a small increase in HbA1c creating a patient with a diagnosis, EMRs won't suggest stages of treatment such as watchful waiting or less aggressive management. What has really happened is that a risk factor has been identified but a disease is being treated. If you are a physician in a quality improvement institution the ICD10 code now starts a cascade of interventions and most likely financial incentives.
Medical education in diabetes care demands driving down HbA1c levels, although other risk factors such as blood pressure and cholesterol level appear to be more effective targets for reducing cardiovascular risk. Care that Matters: Quality Measurement and Health Care reports that glycemic control with drugs other than metformin may actually cause harmful hypoglycemia but fail to appreciably reduce morbidity and mortality. Other diabetes medications are treating numbers and risk factors but not actual patients.
Thoughtful discussions about content development and outcomes analytics that apply the principles and frameworks of health policy and economics to persistent and perplexing health and health care problems.
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