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Analytics

By Tom Sullivan | 07:44 am | October 27, 2016
Health orgs trekking deeper into analytics should expect a new information wave, understand that crowdsourcing can pay off, know machine learning is real right now, buckle down on governance. And don’t hold out for perfection. 
By Eric Bailey | 07:25 am | October 27, 2016
Healthcare IT News interviewed several experts at the forum on a range of topics spanning cost, risk, technologies, challenges and successes. 
By Mike Miliard | 07:15 am | October 27, 2016
Panelists at the HIMSS and Healthcare IT News Big Data and Healthcare Analytics Forum shared advice about engaging clinicians and patients, persuading the C-suite to support analytics investments, bridging the gap between IT and business, and more.
By Jack McCarthy | 11:26 am | October 26, 2016
Critical success factors for making human capital management a strategic asset.
By Tom Sullivan | 01:16 pm | October 25, 2016
Yet the industry has more potential for care improvement and ROI than others that have already adopted the technologies. 
By Jack McCarthy | 09:19 am | October 25, 2016
Bank forges digital tech partnerships with Gem, PokitDok, and others on services for healthcare claims management. 
By Tom Sullivan | 05:47 pm | October 24, 2016
Predictive analytics are not going to be perfect. But that’s okay. Experts explain the sweet spot to target today.  
By Mike Miliard | 05:27 pm | October 24, 2016
Benson Hsu, MD, vice president of data and analytics at Sanford Health, explains how sharing data with 'smart people' from outside the health system has led to some innovative applications for population health management.
By Bernie Monegain | 02:13 pm | October 24, 2016
Peter Embi, MD, an internationally recognized expert in biomedical informatics, will leave his post as interim chair of the Department of Biomedical Informatics and associate dean for research informatics at Ohio State University’s College of Medicine, to join Regenstrief Institute as CEO.
By Tom Sullivan | 02:10 pm | October 24, 2016
Hospitals that haven't started making data actionable, explainable, trusted and contextualized should start now. Why the urgency? In two or three years, finding talented data scientists and other skilled workers is only going to get more difficult.