Learn more about Jason Burke

Author Bio

Jason Burke brings over eight years of health care experience at University of Utah Healthcare to Health Catalyst. At the University of Utah, he spent over four years as a data architect on the Enterprise Data Warehouse and over four years as the business system administrator of the Enterprise Performance Management tool used to annually budget over $1.2 billion. He has also worked with a multitude of business intelligence tools and was responsible for executive level reports and dashboards. Mr. Burke holds a MBA with a Management of Technology certificate and a BS from the University of Utah.

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Insights

Lean Principles in Healthcare: 2 Important Tools Organizations Must Have

The transition from fee-for-service to value-based reimbursement is driving many healthcare systems to fine-tune processes and work waste out of the system. In the search for quality improvement tools there has been much buzz surrounding lean, touted for its ability to remove waste from processes. Many have tried lean and, failing to achieve any sustainable benefit, are learning that applying lean principles to healthcare can be quite difficult. The lean approach isn’t a magic potion. Sustainable change will never become real without a committed organization dedicated to making it a reality. Lean, or any quality improvement tool, works in healthcare only when it is part of a larger initiative driving real cultural change.

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Is That Data Valid? Getting Accurate Financial Data in Healthcare

A consolidated EDW is not a replacement or threat to the individual financial systems and reporting tools employed for general ledger, billing, payroll, or supply management. On the contrary, each of those systems is designed with sophisticated functionality that drives organizational efficiency. But alone, these systems realize only a portion of their true return on investment for the enterprise. As a consolidated data resource, these systems provide untold potential to address the underlying challenges to efficient, cost-effective health care.

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Master Data Management in Healthcare: 3 Approaches

Master data management is key for healthcare organizations looks to integrate different systems. The two types of master data are identity data and reference data. Master data management is the process of linking identity data and reference data. MDM is important for mergers and acquisitions and health information exchanges. The three approaches for MDM are: IT system consolidation, Upstream MDM implementation, and Downstream master data reconciliation in an enterprise data warehouse.

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Healthcare Analytics Applications: Why You Need an Out of Box Solution with Customizability

Providers throughout the U.S. are facing difficult choices for their healthcare analytics applications: should they use an out-of-the-box solution or put in the extra time, effort, and expense to develop a customized solution? Out-of-the-box healthcare analytics applications are just that — they’re applications most health systems can use as-is because the application is designed to work well with the popular source systems in the marketplace. To really gain a deep understanding of the organization and its patients, though, customization of the analytics application is necessary. Customization enables analysts to dig much deeper into the data — and not just after the initial implementation. Instead, the best type of customized healthcare analytics applications solutions can accommodate endless customizations time after time based on new definitions and rules. By selecting customized applications, health systems will get made-to-order analytics that will provide a return on investment — now and in the future.

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