Health analytics : gaining the insights to transform health by Jason Burke

By Jason Burke

"A hands-on, analytics street map for overall healthiness leadersThe industry-wide transformation occurring around the well-being and lifestyles sciences surroundings is mandating that enterprises undertake new decision-making functions, in keeping with technological know-how and real-world details. Analytics may be a required competency for the fashionable healthiness firm; this booklet is ready how you can "cross the chasm." the last word analytics advisor for  Read more...

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Extra info for Health analytics : gaining the insights to transform health care

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How good is it? is there enough of it? is it ready for analysis? can it answer the questions we are asking? , etc. It is ironic that executives can be intimidated by the math of advanced analytics; the people who actually do the work are usually happy to get to the math stage of a project. And the challenges are often never even visible to leaders. I asked Candice, a biostatistician at a pharmaceutical company, how much of her time was actually related to performing statistics of some kind. “That’s one of the most frustrating things for my team,” she said.

For example, analysts might build out a desktop application that models patient health risks using both clinical and nonclinical sources of data. A mobile application on the iPad might use the same risk models to prompt a nurse practitioner to ask some further probing questions during a highrisk patient interview. It might also be a service called by other software to implement a new disease management campaign targeting high-risk patients of a particular profile. As the analytical models improve over time, all three uses can benefit from the same investment.

Due to the volume of data and the increasing number of source data providers, the actuarial team was routinely devoting 70–80% of its time preparing data for analysis. ” Yet the data work was so significant that individual analysts were developing data management specializations as opposed to analytical specializations and insights. The organization initiated an internal project focused on developing a modernized approach to just three of the seven information management vectors: data integration, data aggregation, and data structuring.

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