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Business Intelligence in Healthcare Today

Building Business Intelligence

There are emboldened changes affecting the way the healthcare industry provides its services, and it's all about business intelligence (BI). Recently, the field has become extremely competitive and analytics have emerged as important pieces of "evidence" as providers attempt to demonstrate their ability to improve care delivery efficiently as well as engage their clients with value-added information delivery.

Healthcare outcome metrics are the cornerstone of data emphasis today. Purchasers of healthcare require outcome metrics tied to provider performance and cost. They want to know the healthcare organization is able to keep their workers healthy and viewing their healthcare as a strong benefit. The same information is required, though for different reasons, by quality standards bodies and government agencies. While these interests are "auditing" in nature, they also generate macro environmental study data.

Evidence-based cultures must emerge from the siloed and reactive practices of the past. Information must be incorporated into care provisioning, clinical research, organization, compensation and care-related decisioning. BI is the strategy to achieve an evidence-based culture. Perhaps in no other industry, at any other time, was there such a need for BI as there is in healthcare today.

The state of healthcare data today makes this a fairly large challenge with non-integrated, siloed systems and a legacy of failed integration attempts (for mostly cultural reasons). Consider a typical hospital. It is not unusual to have a patient's record recorded in a specialist's paper-based system according to an internal interpretation of industry coding "standards." Patient procedures are then disseminated to multiple systems including billing. Another set of encoding is performed. Outpatient and other follow-up visits are not always well-linked to the original procedures or billing.

National registry registration of outcomes has forced some structure into the coding at this point, but such coding is often done in a standalone system, which periodically uploads files to the national registrar. Internal operations often do not have access to this data, which is perhaps of the highest quality in the entire care cycle. It's not hard to see why caregivers and healthcare administration alike struggle to solve problems with data and driving improved performance. By the time the data is collated from the disparate systems to meet a need, there is little time left to analyze the data and put the complete information together to make improvements for the next encounter, or the next patient.

BI has been used as the common, shared, systemic repository of data for all of these systems, whether it supports the operational aspects or not (usually not). It can encompass all of the following subjects: provider care capabilities, locations, track record, cost and availability; encounter results, follow-ups, effectiveness, cost, time lines; conditions and treatment plans; patients, conditions, billing; and labs and caregiving locations.

Achieving healthcare BI today means understanding cause/effect relationships such as the relationship between patient health, recovery and follow-up after the execution of alterative treatments for similar conditions. It means optimizing emergency room staffing. Solving issues such as these will achieve the overall goals of efficient and effective care delivery. This is where many healthcare organizations are today.

The ability to continue a BI program into predictive analysis, provider rankings and referral program analysis would provide more ROI. BI is no longer considered proactive; it's a current and glaring need in healthcare. The information BI can provide will not only serve these functions within a healthcare organization, but will also drive operational enhancements.

The future holds a transition to health savings accounts and individual, not employer, responsibility, only exacerbating the need to broadly disseminate quality data in a usable form. The stakes are now so high that those healthcare entities that do not get a handle on the management of their information should anticipate a rapid negative consequence.


William McKnight is partner, Information Management, at Lucidity Consulting Group. William functions as strategist, lead enterprise information architect and program manager for complex, high-volume full life-cycle implementations worldwide utilizing the disciplines of data warehousing, master data management, business intelligence, data quality and operational business intelligence. Many of his clients have gone public with their success story. McKnight is a Southwest Entrepreneur of the Year Finalist, a frequent best practices judge, has authored more than 150 articles and white papers and given over 150 international keynotes and public seminars. His team’s implementations from both IT and consultant positions have won Best Practices awards. He is a former IT VP of a Fortune company, a former engineer of DB2 at IBM and holds an MBA. He can be reached at wmcknight@luciditycg.com

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