Every industry stands to benefit from the savvy use of business intelligence (BI), but few have as much at stake as healthcare.
Healthcare providers leverage the insights they gain by applying BI tools to traditional financial and operational processes as well as clinical processes that affect patient health. Evidence-based insight into such processes can significantly improve patient protocols, treatment outcomes and disease management across large populations.
For instance, data-fueled insights, based on predictive and actionable analytics, can enable hospitals to medically intervene before patient situations reach crisis mode.
Based on real-time analysis of scenarios built on predictive models, some hospitals can predict the onset of serious infections well in advance of any symptoms. Nurses armed with mobile devices receive alerts from patient monitors, based on patterns that indicate impending infection about 24 hours earlier than a physical exam might detect it. Caregivers can begin treatment well before symptoms would have emerged, possibly saving a patient’s life or preventing an outbreak.
Leveraging predictive models allows providers to act rather than react. However, they can only deliver on that potential if predictive algorithms are embedded in operational systems. Although analysts may see some benefit from building predictive models and then waiting for new data to emerge before running another model to test prediction accuracy, this approach is limited. When predictive algorithms are embedded, tools can make prescriptive recommendations that are more likely to improve treatments and deliver better outcomes.
Self-service access also improves end-user productivity. Newer offerings, such as web-based portals, allow less technical staff to use dashboards and generate reports without interfering with database or application functions. Meanwhile, specialists can still enjoy direct access to data sources and run the ad hoc queries necessary for their jobs.
That single-point-of-access approach allows more employees to delve into data and to share findings in ways that resonate with varied audiences. Access to more data sources — from warehouses to spreadsheets to email archives — combined with the ability to process data using ultrafast, in-memory database techniques means that data specialists and general business users can quickly turn insights into actionable intelligence.
From TCO to ACOs, ROI Ramps Up
Beyond the inherent value derived from productivity and faster decision-making, healthcare providers also see other returns on investments (ROI) from BI initiatives. In ROI case studies, Nucleus Research found that organizations with well-executed BI programs see an average return of more than $10 for every dollar spent on analytics applications.
Those returns manifest in improved operational efficiencies and lower total cost of ownership (TCO) as well as through direct ROI related to cash flow from the revenue-generation and cost-reduction opportunities identified through analytics.
Depending on the BI deployment model, healthcare providers can further reduce costs by choosing cloud-based analytics options, avoiding capital expenses and creating economies of scale across partner organizations.
Providers in North America are partnering on initiatives designed to leverage analytics to create “lean” operations, just as healthcare providers in accountable care organizations (ACOs) use shared analytics to coordinate better care delivery at reduced costs. Likewise, there’s a connection between analytics and patient engagement — a key factor in improving patient health. With electronic health records (EHRs) and other sources of information providing cohesive views of patient data, providers can personalize and promote wellness plans to encourage patients to take part in managing their own health.
- How BI has evolved since its early days
- What today’s BI encompasses
- What to look for in a BI technology
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