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These issues lead to real world implications. For example, a health plan is going bankrupt because their assumptions in pricing risk did not generalize to the MA population they enrolled .. https://www.mercurynews.com/2020/10/11/thousands-of-local-seniors-left-scrambling-as-financial-woes-strike-medicare-advantage-plan/

~10,000 seniors in Santa Clara and San Joaquin counties scrambling for health care coverage because their MA plan went bankrupt failing to price risk correctly

Happened to most ACA marketplace plans early on as well

we are developing real world algorithms at Sutter and have encountered all of the coding issues and risk bias that you have so well articulated. do you have a standardized approach that you use when approaching a project that involves common diagnoses such as COPD or CHF as far finding the real population

thank you for a great talk. should be required listening for anyone doing real world clinical research

yep that’s what we are doing

text is where it’s at

Local tool building is not considered “publishable” even in clinical journals.

thanks!! keep up the good work. your aim is true.