This article appears in the July 2012 issue of HealthLeaders magazine.
Decision-making in healthcare can be painfully slow, as any physician will tell you, because of complexity. Patient discharge, for example, can involve a coordination of gears that could make a clockmaker sweat, because of all the information that must be processed to coordinate care outside the walls of the hospital. But thanks to a flurry of innovation in real-time processing of data, many healthcare organizations, including physician group practices, are getting better—and quicker—at dealing with data.
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The problem is getting that data, which is often unstructured, into a format that allows clinicians to make decisions faster and in a more coordinated fashion. Leaders have long had difficulty with breaking down data silos and finding ways to use fragmented information. They strive to find ways to use leading, instead of trailing, indicators, so that interventions can be made not only in a more timely manner but with more predictive power behind them.
Healthcare delivery organizations are 10–15 years behind other industries in managing and capitalizing on the data they own, says Greg Tipsword, healthcare provider practice leader for West Monroe Partners, a Chicago-based healthcare consulting firm. The need to catch up is urgent. Being able to do predictive modeling is critical to risk-based contracting because to reduce waste, labor-intensive interventions need to be used on a distinct group of patients who are most likely to exhibit a complex web of behaviors that, left unchecked, will result in the need for expensive care. The trouble lies in predicting who those patients are before they encounter those complications so that interventions can be made.
Numerous stakeholders need to be involved in defining the type of information required. This depends on the mission of the organization and many other variables, and should begin with the deliberative process, he says.