Kicking off the Health Data Management Healthcare Analytics Symposium, workshop organizer Peter Aiken noted that the majority of organizations today--healthcare included--lack an overarching data strategy.
As a result, much of the data gathered, he said, is of little value. During his three-hour primer on the basics of building an analytics program, Aiken, an associate professor of information systems at Virginia Commonwealth University, walked the audience through a number of terms and concepts used in the field.
Aiken broke healthcare analytics into three broad components: 1. Descriptive efforts that tell what happened; 2. Predictive data that forecast what might happen; and 3. Prescriptive analytics that answer the question: what should I do?
He noted that many IT projects suffer from cost overruns and missed deadlines, and fail to provide intended function. On the health care front, he cited the example of the National Health Service in England, which recently scrapped its long-standing clinical EHR project intended to connect all the hospitals in the country.
Sometimes with proper senior level management support, healthcare data projects can move forward more rapidly and meet their goals. Aiken cited the example of a project he assisted on with the Department of Defense in trying to reduce the number of military suicides. The work required pulling data from a variety of systems, but at a planning session, multiple systems administrators said their data was privileged. Finally, a senior level executive announced to the group, “This is my data,” and said any objections to sharing information needed to be routed through him.
Aiken reminded the audience that the information embedded in their clinical I.T. systems was valuable for both patient care and business intelligence purposes, such as figuring out how one organization stands in the marketplace in terms of competitive service line share. “Data is a durable asset,” he said.
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