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University of Utah Health strengthens referring partner relationships
Technology Category
- Functional Applications - Enterprise Resource Planning Systems (ERP)
- Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries
- Healthcare & Hospitals
Applicable Functions
- Business Operation
- Quality Assurance
Use Cases
- Remote Patient Monitoring
- Regulatory Compliance Monitoring
- Remote Collaboration
Services
- System Integration
- Data Science Services
The Challenge
As a tertiary medical center in a five-state referral area encompassing more than 10 percent of the continental United States, University of Utah Health has long been committed to building strategic alliances with referring physicians. Yet one unwelcome perception persisted. A lag in the consistency of patient follow-up often resulted in a lack of uniformity of care and a breakdown in efficient communications with physicians. The reason for the lag was that University of Utah Health often had to verify disparate and sometimes inaccurate provider discharge data. Two to three FTEs dedicated substantial time to sorting through and manually validating accurate provider names, locations, credentials and more every day, using MPI, Google and other publicly available resources. As a result of this time-consuming verification process, referring providers were left in the dark on treatments, interventions and medications conducted on behalf of their patients, which, in the worst of situations, led to redundancies in after-discharge treatment, and increasing frustration among referring providers.
About The Customer
University of Utah Health, the Mountain West’s only academic healthcare system, is staffed by more than 1,000 board-certified physicians trained in over 200 medical specialties and receives thousands of patient referrals each year in a five-state area. Facilitating seamless, secure patient transitions was crucially important, but without a means to promote accuracy and completeness of the provider directory, there were often breakdowns in communications with referring physicians. In an effort to elevate the all-important partnership between the medical center and physicians, the medical center leveraged LexisNexis® Provider Data MasterFile™ last year. Since choosing the comprehensive data solution, the medical center has witnessed a surge in satisfaction among physicians and patients, improved accuracy and efficiency, the elimination of redundancies and significant time and cost savings.
The Solution
University of Utah Health chose LexisNexis® Provider Data MasterFile™ to meet its goals of transitioning patients more efficiently and helping themselves and their referring partners meet Meaningful Use (MU) Transitions of Care objectives. These MU objectives state that Eligible Hospitals and Eligible Providers who transition their patients to another setting or provider of care, or who refer their patients, should provide a summary care record for targeted percentages of their patients. By linking the Provider Data MasterFile with its current Epic electronic hospital record (EHR) system, University of Utah Health was able to significantly improve the accuracy of provider data, which can change by as much as 25 percent in a single year. The powerful Provider Data MasterFile solution provides deep data coverage of more than 8.5 million U.S. health practitioners, with drill-down attributes such as name integrity (individual names, DBAs and Formerly Known As), addresses across all practice locations, billing locations, updated key data information, state license(s) and other credentials. The Provider Data MasterFile is continuously updated with billions of data points on every healthcare provider in the nation. As a result, University of Utah Health has made great strides in enhancing the care transition and strengthening its referrer alliances. On the front end, the patient’s physician information is entered into the Epic EPR provider dictionary. The data is then bumped against the Provider Data MasterFile and in nearly three-quarters of these instances, a match is provided with an 85 percent or higher accuracy rate. Now that verification isn’t forced to go through multiple people, the updated data is back in the system immediately, and the process has sped up significantly.
Operational Impact
Quantitative Benefit
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