Complimentary from the publishers of Care Analytics News April 2019 | ||||||
"Our research indicates that in the context of population-based
predictive modeling, the new ML[machine learning] techniques do offer
some modest -- and likely useful in some cases -- advantages over more
traditional statistical and econometric techniques now in wider use.
Although more research would be welcome, we do not believe that ML
techniques will offer as much increased accuracy as some
super-enthusiasts and start-ups have advertised.” - Jonathan P. Weiner DrPH, Professor of Health Policy & Management and of Health Informatics, CPHIT Director, ACG Co-Developer and Director of the ACG R&D Team at Baltimore’s Johns Hopkins Bloomberg School of Public Health. |
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According to the
Ninth Annual Industry Pulse Survey of 185 healthcare leaders by
HealthCare Executive Group and Change Healthcare, the following
percentages of respondents thought healthcare data analytics was
"extremely" or "very" effective in the aspects listed below: * improving workflows: 30% * making providers more productive: 28% * reducing healthcare costs: 22% Excerpted from: HIT Infrastructure, March 18, 2019. |
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Health Catalyst: 5 Ways to Improve HCC Coding Accuracy and Risk Adjustment With Analytics1. Have an accurate problem list. Note: HCC coding is used in the Hierarchical Condition Category (HCC) risk adjustment model used by CMS to estimate predicted costs for Medicare Advantage beneficiaries. Source:
Health Catalyst, April 9, 2019 check out more lists on healthsprocket. "What's on your list?" |
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