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Childhood obesity rates have more than tripled in the past 30 years, an alarming public health development that is contributing about $150 billion a year to the overall cost of U.S. health care.
Almost one in five children aged six to eleven are seriously overweight, making them highly vulnerable to heart disease, diabetes and other serious illnesses. At the same time, Congress and the Department of Agriculture are spending more than $1.28 billion annually to subsidize the crops that are used as additives in manufacturing cookies, candies, soda pop and other highly popular junk food that arguably are among the primary contributors to childhood obesity. The sweet, fatty and calorie-rich Hostess Twinkies alone contain 14 ingredients made with highly subsidized processed ingredients, including corn syrup, high fructose corn syrup, corn starch and vegetable shortening--How Billions In Tax Dollars Subsidize The Junk Food Industry
The American Diabetes Association Applauds Major Funding Increase for DiabetesThe Consolidated Appropriations Act for Fiscal Year 2016 increased discretionary funding for the National Institute of Diabetes and Digestive and Kidney Diseases to $1.818 billion, an increase of over $68 million compared to FY2015. This robust funding will allow the institute to expand promising research toward improved treatments and move us closer to a cure for diabetes.
Why is this a problem? I noticed a trend in the percentage of adults with diabetes. The CDC data is clear. Start with 1995 and what do you notice? The heat map on the far right of the image is quite informative.
The story of our health, our populations, and disease needs a 360 perspective. Context is everything.
Coordinated Learning to Improve Evidence-based care: A model for Continuing Education for the New Healthcare Environment has created a much needed energized base in continuing education. On one hand, the industry as a whole is slow to respond to the evolving needs of healthcare providers outside of the watchful and financial resources of industry funded CME. On the other hand, many have debated the role of a Pharma company dictating how to evolve the CME framework. The article and framework is spearheaded by Genentech. Basically, if you hope to be funded, you will need to follow their articulated framework--drink the kool-aid so to speak--not necessarily a bad thing. My clients seem to fall into two camps. How do I follow the model or how can I create a model beyond TELMS that addresses many of the key points? I am not going to debate the model but I will weigh in on the vagueness of "how" these mechanisms can be implemented beyond the narrow scope of the article. Let me cast a wide net and share a bit of what I find problematic regarding claims to "Improve awareness, convert information, demonstrate engagement, and substantiate partnerships". I don't have the answer--I would at least like to create an important dialogue. Medical education as a whole is data poor. The quality of data collection and analysis by even CME industry leaders is laughable. Look. I am not trying to be confrontational or combative. Each time I post a critical review of the learning healthcare system I create a diaspora. That is all well and good. If you choose to join me in trying to make sense of what we can accomplish with strong and concise objectives, I welcome you. If you are a medical education company reporting learning outcomes, no matter how far up the food chain you think you are--I have seen your data, reports, and post-activity deliverables. Maybe not by you, but I assure you, your clients or colleagues are looking for guidance--especially when they are handed a low quality output and made to defend the spend to their finance committee. The data is compelling, confusing, and potentially influenced by industry and financial interests on a global scale. I am going to use T2D as an example. Lately I have been working with Oncology data but there is a whole other level of complexity there. Data on food nutrition, food policy, consensus data, and clinical patient databases are informative when discussing chronic diseases--specifically Type II Diabetes. The short audio below sets the tone from the preventative perspective. You don't need me to tell you healthcare costs are unsustainable. There are limits to out-innovating our biology. We need stronger and more robust policies upstream from disease. Added Sugar Intake and Cardiovascular Diseases Mortality Among US Adults provides an analysis of National Health and Nutrition Examination Survey Data. Continuing medical education laments about inviting voices outside of the bubble to the conversation about improving health outcomes through better education for providers. I agree. TELMS lacks the instructional granularity to guide toward data sources to add a full dimensional perspective on disease. A much needed guidance for healthcare providers responsible for the future outcomes of the healthcare they deliver. The Expanded Learning Model for Systems (TELMS), offers a framework for designing, implementing, and evaluating learning solutions that move both HCPs and patients through a series of learning stages to enable them to adopt evidence-based behaviors informed by quality and performance indicators, and which will help CE stakeholders to demonstrate how such changes lead to improvements in care coordination and quality of care. A total 360 degree look at care must include the cost and financial perspectives. The new administration has hinted at allowing cost to become part of care considerations. You will need to learn how to follow the dollar. Commercial companies typically follow the lead of Centers for Medicare and Medicaid. Many times we write about available interventions focused specifically on mechanism of action and potentially side-effect profiles--especially if those might be differentiators. If you rely on clinical literature, you will need to turn a keen eye on competitors selected in clinical trials. Will Cardiovascular Outcomes Data on Newer Diabetes Drugs Bury the Older Agents? is a timely article in JAMA Internal Medicine. Although the FDA has traditionally focused on the safety and efficacy of drugs relative to placebo, there are abundant good reasons for the agency to push industry and other study sponsors to use active controls in type 2 diabetes studies. The major clinical role of the new drugs is as alternative treatments, not as therapies for patients who otherwise would not be treated with drugs. ![]() I also like to look at Investor Reports accessible on the internet. We hear about "Innovation" being stifled if we lower drug costs. Shouldn't the drug pipeline show investments in innovation? How about record amounts of shareholder dividends or stock buy backs? When you neglect to look at data and understand the "patient/return on investment" of shareholder argument you become a PR machine--not an informed voice or part of the broader discussion of change in healthcare. What if I told you that many companies create revenue by cycling profits back to shareholders instead of capital investments like R&D? Obviously pharmaceutical companies are heterogeneous and have different practices and incentives but the demand for greater transparency is a bit ill-informed and ignorant. They are already transparent--If you know where to look.
-The industry affiliated model, TELMS highlights the cognitive overload of 27000 articles published every week but neglects the role of industry or low quality and poor statistical design of the large majority. Many decisions at the point of care are incentivized based on dubious claims or over-medicalization. We could do more by empowering providers with tools to improve numeracy. Here is a brief snapshot of industry influence from a Virtual Expert Roundtable where a panel of experts will "discuss strategies to set appropriate HbA1c targets, how to select guideline-based therapies, and how to engage and motivate patients to be fully invested in their treatment program to reach their HbA1c goals." Here are the industry payments to expert #1: The website Open Payment Data reported $272,023.63 in total general payments. Industry payments to expert #2: Open Payment Data reported $96,317.25 total in general payments. I am not here to demonize anyone but an educational program where the 3 "experts" are being paid ~ half of a million dollars by industry--is not trivial. Pharmaceutical Industry–Sponsored Meals and Physician Prescribing Patterns for Medicare Beneficiaries demonstrates an association (not causal) with increased brand-name prescribing following industry-sponsored meals. Addressing Unmet Basic Resource Needs as Part of Chronic Cardiometabolic Disease Management is an article describing social correlates of health. Discussions of basic resource needs as an interventional strategy are effective in directing care. Intensive Treatment and Severe Hypoglycemia Among Adults With Type 2 Diabetes helps to demonstrate the benefits or limits of treatment intensification in patients that do not benefit. The risk of hypoglycemia almost doubles in highly clinically complex patients. Join us at the Medical Affairs and Scientific Communications Forum. I will discuss "Data Talks, People Mumble"--new ways of presenting data in healthcare and medicine.
The table below summarizes the evidence supporting a systematic update of the 2008 U.S. Preventative Services Task Force (USPSTF) review on Type 2 diabetes in adults. You can scroll down on the right side of the document to see all the evidence (of varying quality). The actual update was published at the close of 2015.
I attend a lot of health policy and health system improvement conferences either in person or by remote access. So far, the focus is far downstream of the trigger. Have you spent time reading about social determinants of health? The data is strongest for prevention. Why is so much money directed "downstream"?
Jeff Iliff is a neuroscientist part of a team discovering the "glymphatic system"...An interesting listen if you ever considered how the brain moves waste across that relatively impermeable blood-brain barrier.
As a nation we watch the documentaries about how food policy impacts our options at the grocery store--and the quality of our health. Let's face it. There can be an argument made for the influence of zip code vs. genetic code as a determinant or correlate of health outcomes in the US.
Are you involved with the Patient-Centered Outcomes Research Institute (PCORI)? Today was day 1 of the Improving Healthcare Systems October Advisory Panel. There are many working diligently to improve patient outcomes but a common thread is a lack of high-quality initiatives for funding. Please join the discussions. How a national food policy could save millions of American lives-- Mark Bittman, Michael Pollan, Ricardo Salvador and Olivier De Schutter
Professor Tyrone Hayes discusses hormone disruptors and the downstream health consequences being played out without our consent or awareness.
Maptitude GIS and Mapping software simplifies the integration of population health data into many publically available datasets. Data & Donuts made a choice to invest in integrating population and community level data into disease state analyses. The ability to include Maptitude data in our Tableau Data Visualizations means more data informed insights for our collaborative projects.
Here are a few mapping examples from the public sphere demonstrating how a focused data strategy can expand the perspective of a story, business objective, or targeted research question. Click image for more details.
This final example from Vitality Institute describes a landmark study examining a connection between workforce health and the health of the surrounding communities.
What's in your data?
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...
![]() Observation is a skill. Discovering what is present and also what is absent requires focus, objectivity, and awareness. Van Gogh, The Starry Night. 1889 can be viewed at Museum of Modern Art in New York City. I like to use art as an interdisciplinary tool when working with clinical data and numeracy. I notice colleagues don't want to raise their hands to admit they don't understand hazard ratios or calculating number needed to treat (NNT)--but will scrunch up their faces and ask questions about what they observe in art. We can often look at works of art and create a story. If I was to describe the picture above to you and help you "see" it too, what should I say? Should the information be factual and objective or subjective? Would that influence how you visualized the facts? Cardiovascular Mortality in Patients With Type 2 Diabetes and Recent Acute Coronary Syndromes From the EXAMINE TrialRESULTS Rates of CV death were 4.1% for alogliptin and 4.9% for placebo (hazard ratio [HR] 0.85; 95% CI 0.66, 1.10). A total of 736 patients (13.7%) experienced a first nonfatal CV event (5.9% MI, 1.1% stroke, 3.0% HHF, and 3.8% UA). Compared with patients not experiencing a nonfatal event, the adjusted HR (95% CI) for death was 3.12 after MI (2.13, 4.58; P < 0.0001) 4.96 after HHF (3.29, 7.47; P < 0.0001), 3.08 after stroke (1.29, 7.37; P = 0.011), and 1.66 after UA (0.81, 3.37; P = 0.164). Mortality rates after a nonfatal event were comparable for alogliptin and placebo. CONCLUSIONS In patients with type 2 diabetes and a recent ACS, the risk of CV death was higher after a postrandomization, nonfatal CV event, particularly heart failure, compared with those who did not experience a CV event. The risk of CV death was similar between alogliptin and placebo. What is the story?
stay tuned... From the press office in New Orleans 76th American Diabetes Association Sessions New Orleans (June 11, 2016) – Health-related quality of life (HRQOL) is an important area of investigation that has gained increasing recognition and is a critical element of diabetes research, treatment and care, according to experts at the Symposium, “Beyond A1C—Why Quality of Life Matters,” presented on June 11, 2016, during the American Diabetes Association’s 76th Scientific Sessions®, June 10-14, 2016, at the Ernest N. Morial Convention Center in New Orleans.
I unofficially transitioned from a medical writer for hire, to a journalist curious about the intersection of health policy, health economics, clinical medicine and research. Unable to pick a favorite genre I slowly learned the impossibility of pulling on too many individual strings. The story was and is complex.
The most valuable lessons I learned were in the audience of policy meetings at the Brookings Insititution, National Press Club, and the White House. Discussions (often heated) about health economics and outcomes research led by the formal medical director of CMS at an advisory council meeting were eye opening. Once you learn--you can't go back. I can't pretend that diabetes is just diabetes and a pill or injection is the answer. I recently approached the mic at a session sponsored by the Johns Hopkins Institute for Basic Biomedical Sciences. Weighty Matters: Recent Advances in Metabolism, Obesity and Diabetes Research was targeted to journalists. Except there was limited or no data. No skill session on how to evaluate clinical data. I asked about a bariatric procedure and the risk of malabsorption of nutrients if indeed the digestive tract was abbreviated. You could hear crickets. My goal is to unpack the science. If we understand the evidence--both what we know and don't know--better decisions will be made. Better articles, education, and recommendations for patients at the point of care. Recommending gastric bypass as a national solution for our diabetes epidemic is bad medicine and bad economics.-- Mark Hyman, MD
I was scheduled to attend the 76th Scientific Sessions of the American Diabetes Association. Professionally I was filled with anticipation. It is no trivial matter to be granted media access as a digital media professional, a.k.a. blogger. I had to submit analytics from my web traffic, share data regarding site visitors and pages viewed etc. and be open to having the content reviewed and considered.
I was in... I did not attend. I will be staying up-to-date and writing about the sessions but not with my peers in a fully-staffed press room. Sometimes the personal over-rides the professional and you have to face the reality of the situation. A few client projects escalated requiring close oversight. I have been at conferences trying to juggle phone conversations, go-to-meetings, and deadlines and it isn't pretty. I made a tough call. Tough because I thrive for the live connection. Access is my secret sauce and I use it liberally. Lucky for me, I have been thinking about writing more specifically about diabetes. What a perfect time to slow down and create a narrative. But first, we need context. A level set of sorts to set the stage for how we think about clinical evidence. We also need to consider how we utilize surrogate measures to determine clinical efficacy and safety in clinical trials and what that means for the real world population (outside of a controlled clinical trial).
The figure below, highlights a comparison between agencies and their acceptance of surrogates --red for non-accepted surrogates, green for accepted surrogates.
Comparison of international agencies: concerns with surrogate outcomes. Y axis: Drug submission. X axis: Agency. *No: no (e2) = implicit no “evidence 2”; no (ref) = implicit no “reference”; no (e) = explicit no “evidence 1”; no (e1 + e2) = explicit no “evidence 1” and implicit no “evidence 2”; Yes: yes (e1) = implicit yes “evidence 1”; yes (e2) = implicit yes “evidence 2”; yes (used) = implicit yes “used before”; yes (ref) = implicit yes “reference”; yes (e) = explicit yes; Not identified: N/S = no statement; N/A = not applicable; Red shades = negative statements of surrogate acceptability; Green shade = positive statement of surrogate acceptability; HbA1c = hemoglobin A1c; 6MWD = 6 minute walk distance; composite = histology, virology, serology; SVR = sustained virological response; CDR = Common Drug Review; HC = Health Canada; FDA = Food and Drug Administration; EMA = European Medicines Agency; NICE = National Institute for Health and Clinical Excellence; PBS = Pharmaceutical Benefit Scheme; SMC = Scottish Medicines Consortium.v Surrogate outcomes are defined as a laboratory measurement or a physical sign used as a substitute for a clinically meaningful endpoint that measures directly how a patient feels, functions or survives, and that is expected to predict the effect of the therapy.
I am not suggesting that I have any answers. But I do have a lot of questions. I field dozens of calls within medical education about writing need assessments for diabetes funding of interventions. Everybody wants to do what they have always done. "Hey, write about this class of drugs because the funder is <<insert pharma>>". No thank you. There is too much to lose.
Looking at a therapeutic area pipe-line and deciding what the gaps should be is like locking the barn door after the cows have wandered off. You need to look at the data--be open to the bounty of freely available datasets. Be open to making a difference. Let's figure it out together... moo. 2016 Banting Medal for Scientific Achievement
I continue to be puzzled by the quote by ADA--"The numbers associated with diabetes make a strong case for devoting more resources to finding a cure."
The statistics (at least to me) point to need for population health interventions and prevention strategies. Health costs are unsustainable and the diversion of funds looking for cures downstream of deleterious social correlates leaves me gobsmacked. 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... Stay-tuned @graphemeconsult |
Why diabetes?Context is everything. Chronic diseases share common pathways -- metabolic derangements are seen in Alzheimer's Disease and a variety of other disease pathways. Archives
February 2017
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