Search

US-12620466-B1 - Computer-based tools and techniques for analyzing health care data in connection with medical procedures

US12620466B1US 12620466 B1US12620466 B1US 12620466B1US-12620466-B1

Abstract

Tools and techniques are provided for analyzing health care procedure related transactions of a health care entity. The method can include creating a linked data items file, by a transaction analysis computer system, derived from a combination of a charge description master (CDM) file containing CDM data items, an order entry system (OES) file containing OES data items, and a CDM-to-OES cross-reference data file. The linked data items file can be analyzed by reading linked line items, analyzing its CDM data portion, analyzing its OES data portion, and/or comparing the linked CDM data portion to the linked OES data portion for determining similarities or differences between the CDM and OES data portions.

Inventors

  • William A. Hunt
  • Ziwei Yi

Assignees

  • MEDCOM SOLUTIONS, INC.

Dates

Publication Date
20260505
Application Date
20240228

Claims (17)

  1. 1 . A computer-implemented method for analyzing health care procedure related transactions of a health care entity, the method comprising: importing, by a transaction analysis computer system including at least one electronic computer processor and at least one computer-readable medium, at least the following information: at least a portion of a charge description master (CDM) file containing multiple CDM healthcare data items, at least a portion of an order entry system (OES) file containing multiple OES healthcare data items, and at least a portion of a CDM-to-OES cross-reference data file; the transaction computer system programmed with at least one dynamic data engine configured for processing multiple data models adaptable to changes in data structures associated with the imported information; creating, by the transaction analysis system applying the CDM-to-OES cross-reference data file to the CDM data items file and the OES data items file, a linked data items file; analyzing, by the transaction analysis system, the linked data items file, wherein the analyzing comprises: reading at least one linked line item of the linked data items file, analyzing a CDM data portion of the linked line item, analyzing an OES data portion of the linked line item, and comparing the linked CDM data portion to the linked OES data portion of the linked line item for determining at least one similarity or difference between the CDM data portion and the OES data portion, wherein the comparing further comprises: analyzing the CDM data portion of the linked line item for determining an active or inactive status of a CDM data item, analyzing the CDM data portion of the linked line item for determining a chargeability status of a CDM data item, and generating a report in response to determining at least one similarity or difference between the OES data portion and the CDM data portion, the report including at least one indication of a discrepancy which needs to be corrected; and executing, by the transaction analysis system, at least one or more of: changing at least a portion of the OES data portion and/or at least a portion of the CDM data portion in response to determining at least one similarity or difference between the linked OES data portion and the linked CDM data portion; and/or mapping at least one CDM data item to at least one OES data item in response to identifying the CDM data item as unmapped to any OES data item.
  2. 2 . The method of claim 1 , further comprising analyzing the OES data portion of the linked line item for determining an active or inactive status of an OES data item.
  3. 3 . The method of claim 1 , further comprising analyzing the OES data portion of the linked line item for determining a chargeability status of an OES data item.
  4. 4 . The method of claim 1 , further comprising comparing the OES data portion to the CDM data portion of the linked line item for determining at least one similarity or difference between the linked OES data portion and the linked CDM data portion.
  5. 5 . The method of claim 1 , further comprising determining at least one similarity or difference between the linked CDM data portion and the linked OES data portion by comparing at least a portion of a description associated with the linked CDM data portion to at least a portion of a description associated with the linked OES data portion.
  6. 6 . The method of claim 1 , further comprising determining at least one similarity or difference between the linked CDM data portion and the linked OES data portion by comparing at least a portion of a unit of measure associated with the linked CDM data portion to at least a portion of a unit of measure associated with the linked OES data portion.
  7. 7 . The method of claim 1 , further comprising identifying at least one OES data item unmapped to any CDM data item.
  8. 8 . The method of claim 7 , further comprising determining an active or inactive status of the unmapped OES data item.
  9. 9 . The method of claim 7 , further comprising determining a chargeability status of the unmapped OES data item.
  10. 10 . The method of claim 1 , further comprising identifying at least one CDM data item unmapped to any OES data item.
  11. 11 . The method of claim 10 , further comprising determining an active or inactive status of the unmapped CDM data item.
  12. 12 . The method of claim 10 , further comprising determining a chargeability status of the unmapped CDM data item.
  13. 13 . The method of claim 1 , further comprising using an artificial intelligence module for analyzing the CDM data portion of the linked line item.
  14. 14 . The method of claim 1 , further comprising using an artificial intelligence module for analyzing the OES data portion of the linked line item.
  15. 15 . The method of claim 1 , further comprising using an artificial intelligence module for comparing the CDM data portion to the OES data portion of the linked line item for determining at least one similarity or difference between the linked CDM data portion and the linked OES data portion.
  16. 16 . The method of claim 15 , further comprising using an artificial intelligence module for comparing the OES data portion to the CDM data portion of the linked line item for determining at least one similarity or difference between the linked OES data portion and the linked CDM data portion.
  17. 17 . The method of claim 1 , further comprising communicating at least one electronic mail notification in response to generating the report, the notification including the at least one indication of a discrepancy which needs to be corrected.

Description

CROSS-REFERENCE TO RELATED APPLICATION/PRIORITY CLAIM This application claims the benefit of U.S. application Ser. No. 18/151,380, filed on Jan. 6, 2023, which claims priority to U.S. provisional patent application Ser. No. 63/297,181, filed on Jan. 6, 2022, the entirety of which is hereby incorporated by reference into the present application. FIELD OF THE INVENTION In various embodiments, the present invention generally relates to computer-based tools, devices, and processes for analyzing records and other information associated with administering health care treatments to patients at a health care facility. BACKGROUND In the health care industry, charging for clinical procedures, visits and services are highly governed by Medicare, Medicaid and other commercial payors. Clinical activity including various medical procedures must be appropriately charged to the responsible party using diagnostic codes and procedure codes. These body of code sets are the means to which an insurer will acknowledge the services provided and the basis for payment of such patient care. If such charging is performed incorrectly or inefficiently, this can negatively impact the ability of a health care facility to provide medically effective and cost effective health care. What are needed, therefore, are improved tools and techniques for analyzing data associated with performing medical procedures at health care facilities and their associated charges. This would lead to providing more efficient and effective medical procedures for patients who need health care. BRIEF DESCRIPTION OF THE FIGURES FIG. 1 schematically illustrates an example of a computing environment in which a transaction analysis system operates to analyze health care procedure related data. FIG. 2 is a process flow diagram illustrating examples of processes for performing the collection or aggregation of data from multiple sources. FIG. 3 includes a process flow diagram illustrating an example of creating a linked data item file. FIG. 4 includes a process flow diagram illustrating an example of comparing charge description master (CDM) data items to order entry system (OES) data items. FIG. 5 includes a process flow diagram illustrating an example of analyzing OES data items to CDM data items. FIG. 6 includes a process flow diagram illustrating an example of creating a file for the OES data items that are not linked to CDM data items. FIG. 7 includes a process flow diagram illustrating an example of determining if OES data items should be linked to CDM data items. FIG. 8 includes a process flow diagram illustrating an example of processing unmapped data items. FIG. 9A schematically illustrates examples of mapping CDM data items to OES data items. FIG. 9B schematically illustrates various specific examples of the results of the analysis performed by the transaction analysis system. FIG. 10 is a screen display illustrating an example of a dashboard view of navigator application configured for use in connection with a transaction analysis system. FIG. 11 through 14 include screen displays illustrating examples of a “Configurations” section of a navigator application configured for use in connection with a transaction analysis system software. FIG. 15 is a screen display illustrating an example of an Order Entry Data Import user interface. FIGS. 16 through 19 include screen displays demonstrating how various records linked to a CDM identification number can be displayed. FIG. 20 is a screen display showing a reporting section of a navigator application configured for use in connection with a transaction analysis system. FIG. 21 includes an example of an OE-not-mapped report. FIG. 22 is a screen display illustrating examples of order entry line items that have been mapped to a CDM but which have issues. FIG. 23 illustrates an example of a report of order entry items that appear to be mapped to a charge code but with charge codes which are considered invalid. FIG. 24 shows an example of a report called OE-implants-mapped-to-non-implements-revenue-codes which can be generated in connection with an OR Supply module. DESCRIPTION In developing the various embodiments of the invention described herein, the inventors have appreciated the need for advanced technology for analyzing health care clinical treatment data and the financial transactions associated with such treatment. Clinical services provided to patients are typically entered into specific software systems, Order Entry Systems, (OES) for a given clinical area, such as Cardiac Catheterizations, CT Scans or Laboratory testing. These IT systems are responsible for ordering the patient work, registering the clinical results and handing off the clinical charging data to the hospital or physicians finance IT system to subsequently be billed to the patient or patient's insurer. It is most critical that the charge data is accurately and efficiently transferred from the clinical area to the financial area for billing purpos