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hello data
I visualize data buried in non-proprietary healthcare databases
https://unsplash.com/@winstonchen

What exactly are you measuring?

11/21/2015

 
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High value, low value, patient-centered value--all terms that depending on the stakeholder or context convey authority and evidence for improving patient outcomes--unless they don't.

Make no mistake. Healthcare is a gargantuan profit generating enterprise. The free market influences care algorithms, clinical publications, health policy, and public health decisions.

First, in case you aren't familiar with my perspective, it is only fair that I put it all out on the table. In my defense I most certainly feel objective when I tackle a topic or story. My inclination both personally and professionally is to look to the data. I am even developing a guide to help decipher the medical literature--Improving Numeracy in Medicine.
...most of the news that people have, they have from media that they select for compatibility with their prior belief, then people are not looking to be surprised. They are looking for news that fits their view of the world. They want news that tells them that villains behave badly and good people behave well. Those are the kinds of things that people are asking for.--How to Lean Against Your Biases
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I recommend Daniel Kahneman's book Thinking Fast and Slow for a compelling look at how our biases influence our behavior and perception of fact vs. opinion. Especially (or should I say surprisingly) clinicians may be informed by independent data but how that information is filtered and interpreted at the point of care is also informed by personal heuristics or rules of thumb.

There is a strong temptation for journalists to tell people what people want to hear, both in terms of opinion but even in terms of facts. So when you’re talking about accuracy, it means really stressing the facts. The facts are going to be the most difficult to assimilate for the public, the things they don’t want to hear or ideas they don’t want to understand because they don’t fit their conception of the world.--How to Lean Against Your Biases
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The majority of my writing career was spent ghost writing articles, developing learning strategies, gap analyses, and medical education content as well as manuscripts in peer-reviewed journals. Over the years I gained extensive experience writing reports from major advisory council meetings. What had historically been strategic bidirectional information exchange was now confrontational.

​Well respected and accomplished leaders in their therapeutic areas began fighting back. They were rejecting clinical trial endpoints that failed the patients, demanding better research, and they were not backing down. One meeting (not too long ago) I was sitting in a room of pharmaceutical stakeholders as they discussed health economics and outcomes research and effective strategies for gaining market access and remaining competitive across product lifespans and beyond. 

Something began to click. I decided to focus my research and attention from the perspective of the medical societies and healthcare provider populations. Rigorous analyses and data modeling belonged outside of the walls of the well-funded medical affairs departments and available in unbiased reporting.

I quickly met likeminded colleagues in Choosing Wisely discussions, Lown Conferences, Preventing Overdiagnosis, How to Stay at the Cutting Edge of Medical Investigations (BMJ), Care that Matters, National Institutes of Health meetings, Inspiring the Future of American Health Care (NCQA), health policy issues live from the Brookings Institution and National Press Club, even the White House--there is a shift evolving in healthcare. No longer feeling like the "sound of one hand clapping" I found a "tribe".

A recent publication, Care That Matters: Quality Measurement in Healthcare is a powerful awakening for the new value-based algorithms on the horizon. It is important to have a core. A set of truths not amenable to distortion as business models transition from fee-for-service to fee-for value is needed.

​Here are summary points from the article:



  • There is limited evidence that many “quality” measures—including those tied to incentives and those promoted by health insurers and governments—lead to improved health outcomes.
  • Despite the lack of evidence, these measures and comparative “quality ratings” are used increasingly.
  • These measures are often based on easily measured, intermediate endpoints such as risk-factor control or care processes, not on meaningful, patient-centered outcomes; their use interferes with individualized approaches to clinical complexity and may lead to gaming, overtesting, and overtreatment.
  • Measures used for financial incentives and public reporting should meet higher standards.
  • We propose a set of core principles for the implementation of quality measures with greater validity and utility.​

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What can you do?

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Here is a link to a report card for Blue Cross Blue Shield quality measures. What are your thoughts? How do you score? I encourage you to sign the Quality Metrics open-letter to patients commiting to improving care. Access member only (free) resources for content and education development.

I think it is important to support writers and educators with like-minded goals and values. Many that follow the data&donuts blog are also medical writers. If you want to be informed about upcoming online courses or targeted publications that bring conference highlights please send a comment. I am creating transmedia access based on your needs and questions.

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.
https://www.rebelmouse.com/dataanddonuts/
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  • Data & Donuts (thinky thoughts)
  • COLLABORATor
  • Data talks, people mumble
  • Cancer: The Brand
  • Time to make the donuts...
  • donuts (quick nibbles)
  • Tools for writers and soon-to-be writers
  • datamonger.health
  • The "How" of Data Fluency