TKG Healthcare Technology Solutions


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VRfi

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TKG Solutions
VRfi
VRfi© - VERIFYING REVENUE INTEGRITY
VRfi is a web-based application developed for healthcare providers by The Kramer Group, Inc. (TKG) that provides a unique 100% QA solution for outpatient coding employee QA workflow and error identification.

VRfi combines technology -- through predictive software, coding analysis and charge capture -- with our expert healthcare consultants to provide our clients with the best possible outcome. Our consultants are equipped with comprehensive clinical coding, documentation, and reimbursement expertise. VRfi utilizes an unsurpassed proprietary rules engine and clinically based business rules to identify and eliminate virtually every error in coding, charge capture and documentation, insuring proper reimbursement and compliance. Overnight processing enables each claim to be evaluated before and after submission, and the detailed drill down reporting facilitates the immediate correction of errors detected by VRfi’s on-line web based system.

Benefits of VRfi:
  • Reviews 100% of all outpatient claims filed by clinical systems for services such as invasive radiology, cardiology, infusion, chemotherapy, GI, pain management, respiratory and other surgeries.
  • Utilizes clinical “rules based engine” and matrixes to identify critical billing errors and provides the hospital with specific reasons for the error, the origination of the error and the suggested corrective action.
  • Provides a web based work flow process to assign claims to specific individuals who may be charged with making corrections.
  • Identifies and filters all errors to eliminate most “false positives” and assign “absolute”, “possible” and “probable" status to facilitate ease of workflow and corrections.
  • Assigns net reimbursement impact to each error by individual account.
  • Provides extensive drill down capability and management reporting at all levels.

For more marketing information click on the link below to download a brochure.

Download VRfi PDF (221K)

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