Quality Measures for Occupational Data: Difference between revisions

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Created page with "he QMOD (Quality Metrics for Occupational Data) profile profile will . __TOC__ ==Summary== TBD ==Benefits== TBD ==Details== TBD ==Systems Affected== TBD '''Actors &..."
 
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==Summary==
==Summary==
TBD
Communication and processing of quality metrics represents an emerging area within interoperability that will greatly enhance the ability to specify and execute logic for population health monitoring. Occupational Data for Health (ODH) has been identified as a framework containing key social history factors impacting patient health, the management of medical conditions, and identification of risk factors. There is also an opportunity for monitoring and improvement of healthcare delivery through quality measures of health outcomes, and to assess the effectiveness of mitigation strategies such as testing and education. This IHE profile will constrain quality reporting and measurement standards in the context of ODH to improve the ability to assess work-related risks and provide support for strategies to monitor and measure health impacts related to workplace conditions with specific content to support quality improvement efforts.


==Benefits==
==Benefits==
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==Details==
==Details==


TBD
Quality metrics are typically generated by and/or adapted from external parties. Examples of such metrics are related to compliance with clinical practice guidelines (e.g. establishing occupational risk factors for lead exposure under the WHO Guideline for Clinical Management of Exposure to Lead), and identification of populations of interest (e.g. specific employment groups outlined in A consensus report by the American Diabetes Association and the European Association for the Study of Diabetes). These metrics are generally manually configured and maintained in systems that support reporting. This profile will specify a human-readable and machine interpretable definition of such population metrics in the context of interoperable clinical summaries and laboratory reports to enable automated processing.  The value proposition for quality improvement and public health is in improved reporting rates, consistency in metrics, and reduced implementation costs.
    
    
==Systems Affected==
==Systems Affected==
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''<Insert an actor-transaction diagram, and or list of Content Definitions>''
''<Insert an actor-transaction diagram, and or list of Content Definitions>''
Actors:  
Actors:  
Data Responder - The Data Responder shall be responsible for the creation of content and the transmission of a QMOD document to an Data Consumer.  
Data Responder - TGenerates the requested ODH quality measure data and sends it to the ODH Quality Data Consumer.  
 
Data Consumer - Retrieves the ODH quality measure data.
Data Consumer - The Data Consumer is responsible for initiating a query to the Data Responder system for documents meeting certain criteria and can retrieve selected documents supplied by the Data Responder. Data Consumer is also responsible for receiving ODH quality data needed to compute ODH measures from the Data Sender.  
Data Sender - Sends the measurement data  
 
Data Sender - The Data Sender is responsible for sending ODH data needed to compute ODH measures to the Data Receiver.


Transactions:  
Transactions:  


Query for EMS Quality Data [QRPH-55] - The Data Consumer sends a query for an EMS Quality Data to the Data Responder.   
Query for ODH Quality Data [QMOD-xx] - Query request for ODH quality measure data.   


Send EMS Measure Report Data [QRPH-56] - The Data Sender sends quality measure report data to the Data Consumer.
Send Quality Measure Data [QMOD-yy] - Sends a Report with data needed to compute ODH Quality Measures


==Specification==
==Specification==


'''Profile Status:''' [Draft]   
'''Profile Status:''' [Draft]   


'''Documents:'''  
'''Documents:'''  
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'''Underlying Standards:'''
'''Underlying Standards:'''
:* HL7 HQMF: Health Quality Measures Format
:* HL7 eMeasure HL7 Version 3 Standard: Representation of the Health Quality Measure Format (eMeasure) Release 1
:* HL7 FHIR® R4 <https://www.hl7.org/fhir/>
:* HL7 FHIR CQF Quality Measure Implementation Guide
:* HL7 FHIR DEQM: Data Exchange for Quality Measures Implementation Guide
:* LOINC: Logical Observation Identifiers, Names and Codes


''<list all the standards on which the profile is based; if possible with links to sources>''
:* HL7 Version 3 Domain Analysis Model: Emergency Medical Services, Release 1 <http://www.hl7.org/implement/standards/product_brief.cfm?product_id=39>
:*HL7 Version 3 Domain Information Model; Emergency Medical Services, Release 1 <http://www.hl7.org/implement/standards/product_brief.cfm?product_id=302>
:*HL7 Version 3 Domain Analysis Model: Trauma Registry Data Submission, Release http://www.hl7.org/implement/standards/product_brief.cfm?product_id=363
:*HL7 FHIR standard STU3 http://hl7.org/fhir/STU3/index.html
:*eMeasures References: https://www.heart.org/HEARTORG/Professional/MissionLifelineHomePage/Recognition/Mission-Lifeline-EMS-Recognition_UCM_308047_Article.jsp


==FHIR Implementation Guide==
==FHIR Implementation Guide==

Latest revision as of 11:44, 6 February 2024

he QMOD (Quality Metrics for Occupational Data) profile profile will .

Summary

Communication and processing of quality metrics represents an emerging area within interoperability that will greatly enhance the ability to specify and execute logic for population health monitoring. Occupational Data for Health (ODH) has been identified as a framework containing key social history factors impacting patient health, the management of medical conditions, and identification of risk factors. There is also an opportunity for monitoring and improvement of healthcare delivery through quality measures of health outcomes, and to assess the effectiveness of mitigation strategies such as testing and education. This IHE profile will constrain quality reporting and measurement standards in the context of ODH to improve the ability to assess work-related risks and provide support for strategies to monitor and measure health impacts related to workplace conditions with specific content to support quality improvement efforts.

Benefits

TBD

Details

Quality metrics are typically generated by and/or adapted from external parties. Examples of such metrics are related to compliance with clinical practice guidelines (e.g. establishing occupational risk factors for lead exposure under the WHO Guideline for Clinical Management of Exposure to Lead), and identification of populations of interest (e.g. specific employment groups outlined in A consensus report by the American Diabetes Association and the European Association for the Study of Diabetes). These metrics are generally manually configured and maintained in systems that support reporting. This profile will specify a human-readable and machine interpretable definition of such population metrics in the context of interoperable clinical summaries and laboratory reports to enable automated processing. The value proposition for quality improvement and public health is in improved reporting rates, consistency in metrics, and reduced implementation costs.

Systems Affected

TBD

Actors & Transactions:

<Insert an actor-transaction diagram, and or list of Content Definitions> Actors: Data Responder - TGenerates the requested ODH quality measure data and sends it to the ODH Quality Data Consumer. Data Consumer - Retrieves the ODH quality measure data. Data Sender - Sends the measurement data

Transactions:

Query for ODH Quality Data [QMOD-xx] - Query request for ODH quality measure data.

Send Quality Measure Data [QMOD-yy] - Sends a Report with data needed to compute ODH Quality Measures

Specification

Profile Status: [Draft]

Documents: TBD

Underlying Standards:

  • HL7 HQMF: Health Quality Measures Format
  • HL7 eMeasure HL7 Version 3 Standard: Representation of the Health Quality Measure Format (eMeasure) Release 1
  • HL7 FHIR® R4 <https://www.hl7.org/fhir/>
  • HL7 FHIR CQF Quality Measure Implementation Guide
  • HL7 FHIR DEQM: Data Exchange for Quality Measures Implementation Guide
  • LOINC: Logical Observation Identifiers, Names and Codes


FHIR Implementation Guide

Using Resources at FMM Level 0-5:

TBD

See Also

Related Profiles

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