Category
Supplementary Resource
Organisation
Type
Standard
Version
1.1
Access
Open
Status
Active
Created
Dec 2016
This document describes the analysis performed by the IT Infrastructure Technical Committee when selecting the optimal de-identification algorithms to fulfil the De-Identification for Family Planning use case published in Volume 4 of the IHE Quality, Research, and Public Health (QRPH) Family Planning Trial Implementation Supplement.
This use case required the de-identification of data for the purposes of health services research, for example in program planning and budgeting, basic monitoring of program performance and adherence to the scope of a funded project, clinical quality improvement initiatives and whether services are being delivered to the intended populations.
The document has two intended audiences:
· clinicians, researchers, data analysts, and others who seek to understand how and why the selected de-identification algorithms were chosen for each data element (the target audience for this document)
· developers who will implement the de-identification algorithms into their software (who should start with the IHE QRPH De-Identification for Family Planning supplement and consult this document for additional background information where needed).
Main sections:
· Purpose and intended audience
· De-identification goals for family planning data elements
· Problem description
· Definitions
· Conventions
· Use cases
· De-identification methods
· Data models
· De-identification algorithm analysis
· Appendix A: Sample FP CDA documents and their de-identified documents
· Appendix B: Usability analysis of de-identified data
This use case required the de-identification of data for the purposes of health services research, for example in program planning and budgeting, basic monitoring of program performance and adherence to the scope of a funded project, clinical quality improvement initiatives and whether services are being delivered to the intended populations.
The document has two intended audiences:
· clinicians, researchers, data analysts, and others who seek to understand how and why the selected de-identification algorithms were chosen for each data element (the target audience for this document)
· developers who will implement the de-identification algorithms into their software (who should start with the IHE QRPH De-Identification for Family Planning supplement and consult this document for additional background information where needed).
Main sections:
· Purpose and intended audience
· De-identification goals for family planning data elements
· Problem description
· Definitions
· Conventions
· Use cases
· De-identification methods
· Data models
· De-identification algorithm analysis
· Appendix A: Sample FP CDA documents and their de-identified documents
· Appendix B: Usability analysis of de-identified data
Access IHE IT Infrastructure (ITI) White Paper – Analysis of Optimal De-Identification Algorithms for Family Planning Data Elements
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