Method for the brokerage of benchmarks in healthcare pathways

• US 20070299703A1
• Filed: 06/26/2006
• Published: 12/27/2007
• Est. Priority Date: 06/26/2006
• Status: Abandoned Application

• Current Assignee: Siemens AG
• Original Assignee: Siemens AG
• Inventors: Laumann, Susanne, Lang, Martin
• Application Number:
  US11/474,881
• Publication Number:
  US 20070299703A1
• Time in Patent Office: Days
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 10/06395 Quality analysis or management
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

A method is provided for sharing healthcare benchmarks in which event data, status information, and measures from process instances of information systems of a local healthcare institution are monitored. The event data and measures are assigned into groups of process types and key measurements of the process instances into quality or performance indicators for each group of processes of a same type are aggregated, thereby creating combined process data. This combined process data of the local healthcare institution is provided to a globally accessible benchmark broker who stores the combined process data along with similarly processed combined process data other healthcare institutions. This data can be accessed by the local and other healthcare institutions. A user viewable comparison is produced between the combined process data of the local healthcare institution and the combined process data of the other healthcare institution.

Claims

1. A method for sharing healthcare benchmarks, comprising:

monitoring event data, status information, and measures from process instances of information systems of a local healthcare institution;

assigning the event data and measures into groups of process types and aggregating key measurements of the process instances into quality or performance indicators for each group of processes of a same type, thereby creating combined process data;

providing the combined process data of the local healthcare institution to a globally accessible benchmark broker;

storing, by the benchmark broker, the combined process data of the local healthcare institution;

storing, by the benchmark broker, similarly processed combined process data of another healthcare institution;

accessing, by the local healthcare institution, the stored combined process data of the other healthcare institution; and

producing a user viewable comparison between the combined process data of the local healthcare institution and the combined process data of the other healthcare institution.

2. The method according to claim 1, wherein the comparison is provided in a form selected from the group consisting of a chart, a graph, and a report.

3. The method according to claim 1, wherein the monitored data is stored in a raw data repository.

4. The method according to claim 1, wherein the assigning comprises implementing reverse engineering of existing process models in a reverse engineering, aggregation and assessment service (RAA).

5. The method according to claim 4, further comprising:

inputting the event data and measures at an input of the RAA;

enriching process models with the input event data and measures by the RAA; and

outputting the enriched process models by the RAA.

6. The method according to claim 5, further comprising enriching the process models with additional information.

7. The method according to claim 6, wherein the additional information is selected from the group consisting of executing role, organizational unit, and hospital-wide patient identifier.

8. The method according to claim 5, further comprising:

utilizing a process mining component for reconstructing process models based on pre-processed event data and storing computed process models together with corresponding process instance graphs in a temporary process repository.

9. The method according to claim 8, wherein the process mining component utilized an algorithm selected from the group consisting of an alpha mining algorithm and a genetic mining algorithm.

10. The method according to claim 4, wherein the RAA aggregates events from the monitoring service to provide a homogeneous level of data or event granularity.

11. The method according to claim 4, further comprising enriching the process models with additional information and subsequently calculating basic measures.

12. The method according to claim 11, wherein the basic measures are selected from the group consisting of:

a) duration of a workflow task based on its start and end timestamp, and b) costs for a task, based on a personal working timer per task and corresponding personal costs.

13. The method according to claim 1, wherein the combined process data comprises parameters of medical quality assurance and healthcare pathways, parameters of general process capabilities, and financially relevant indicators.

14. The method according to claim 1, wherein the event data and measures comprise identifiers related to case, system, event, and measures.

15. The method according to claim 14, wherein the event data further comprises a timestamp.

16. The method according to claim 1, further comprising:

detecting at least one of differences and deviations in the processes; and

providing a representation of these detected aspects as a part of the viewable comparison.

17. The method according to claim 1, further comprising:

finding and classifying, with data mining algorithms, interdependencies of measures and specific classes of processes, process partitions or process courses regarding measures and process knowledge from different sites.

18. The method according to claim 1, further comprising:

detecting at least one of dependencies, trends, and continuous process changes from process-related measures obtained from the other healthcare institution; and

producing a user-viewable chart, graph, or other displayed output related to statistical information.