Bridging the gap: Leveraging business intelligence tools in support of patient safety and financial effectiveness

Abstract

It is common knowledge that health care relies heavily on IT and the inflow of data has out- performed our ability to process and convert data into meaningful information and knowledge that can then be used to improve care and cost of care. With health informatics becoming a national priority for two presidents, a new approach to care and cost optimization needs to be undertaken through targeted analytics. The authors, through carefully chosen case studies demonstrate how this objective of care and cost optimization has been accomplished scientifically.

Background

While meaningful use is a commonly recognized term within the industry, the authors point out that the underlying key objective of meaningful use – “transformation of our care delivery system through care and cost optimization and patient engagement and their impact on technological and cultural shifts” is less well understood. Authors point out that through years of use of less flexible and hard to maintain legacy systems, financial , clinical and administrative data have been separated into their own silos and bringing them in a meaningful way to accomplish this objective is a serious undertaking, unless a thoughtful and systematic HIT services research is employed. While large hospitals as well as large plan sponsors have started engaging in analytics to uncover care gaps and medication errors and starting to share those at POC during encounters to optimize care and cost of care, authors think, we still have a long way to go. Authors show the way by documenting case studies chosen from Duke University Health System (DUHS) to demonstrate techniques employed and results obtained for others to use as their models.

Approach

Authors point out three aspects of their DUHS case study for this demonstration. A voluntary safety reporting system and automated adverse drug event surveillance for patient safety data Web based safety dashboard that can provide encounter specific, event specific drill downs to identify systemic issues for quick intervention. Use of DUHS’ DW to critically evaluate and implement improvements in revenue cycle to recover costs that otherwise would have been lost.

Conclusion

As our population ages, chronic diseases increases and our health care system faces serious challenges in the coming decades, careful allocation of Funding for HIT , making Predictive analytics a priority and developing more modern visualization techniques would be imperative in ensuring care and cost of care optimization and for a healthier nation.