A bespoke data linkage of an IVF clinical quality registry to population health datasets; methods and performance
Introduction Assisted reproductive technologies (ART), such as in-vitro fertilisation (IVF), have revolutionised the treatment of infertility, with an estimated 8 million babies born worldwide. However, the long-term health outcomes for women and their offspring remain an area of concern. Linking IV...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Swansea University
2021-09-01
|
| Series: | International Journal of Population Data Science |
| Subjects: | |
| Online Access: | https://ijpds.org/article/view/1679 |
| _version_ | 1797430739190415360 |
|---|---|
| author | Georgina M Chambers Stephanie K.Y. Choi Katie Irvine Christos Venetis Katie Harris Alys Havard Robert J Norman Kei Lui William Ledger Louisa R Jorm |
| author_facet | Georgina M Chambers Stephanie K.Y. Choi Katie Irvine Christos Venetis Katie Harris Alys Havard Robert J Norman Kei Lui William Ledger Louisa R Jorm |
| author_sort | Georgina M Chambers |
| collection | DOAJ |
| description | Introduction
Assisted reproductive technologies (ART), such as in-vitro fertilisation (IVF), have revolutionised the treatment of infertility, with an estimated 8 million babies born worldwide. However, the long-term health outcomes for women and their offspring remain an area of concern. Linking IVF treatment data to long-term health data is the most efficient method for assessing such outcomes.
Objectives
To describe the creation and performance of a bespoke population-based data linkage of an ART clinical quality registry to state-based and national administrative datasets.
Methods
The linked dataset was created by deterministically and probabilistically linking the Australia and New Zealand Assisted Reproduction Database (ANZARD) to New South Wales (NSW) and Australian Capital Territory (ACT) administrative datasets (performed by NSW Centre for Health Record Linkage (CHeReL)) and to national claims datasets (performed by Australian Institute of Health and Welfare (AIHW)). The CHeReL's Master Linkage Key (MLK) was used as a bridge between ANZARD's partially identifiable patient data (statistical linkage key) and NSW and ACT administrative datasets. CHeReL then provided personal identifiers to the AIHW to obtain national content data. The results of the linkage were reported, and concordance between births recorded in ANZARD and perinatal data collections (PDCs) was evaluated.
Results
Of the 62,833 women who had ART treatment in NSW or ACT, 60,419 could be linked to the CHeReL MLK (linkage rate: 96.2%). A reconciliation of ANZARD-recorded births among NSW residents found that 94.2% (95% CI: 93.9--94.4%) of births were also recorded in state/territory-based PDCs. A high concordance was found in plurality status and birth outcome (≥99% agreement rate, Cohen's kappa ranged: 0.78--0.98) between ANZARD and PDCs.
Conclusion
The data linkage resource demonstrates that high linkage rates can be achieved with partially identifiable data and that a population spine, such as the CHeReL's MLK, can be successfully used as a bridge between clinical registries and administrative datasets. |
| first_indexed | 2024-03-09T09:32:13Z |
| format | Article |
| id | doaj.art-5c2fcbe4c2ef4fd8a505679f00cc9d3a |
| institution | Directory Open Access Journal |
| issn | 2399-4908 |
| language | English |
| last_indexed | 2024-03-09T09:32:13Z |
| publishDate | 2021-09-01 |
| publisher | Swansea University |
| record_format | Article |
| series | International Journal of Population Data Science |
| spelling | doaj.art-5c2fcbe4c2ef4fd8a505679f00cc9d3a2023-12-02T03:27:01ZengSwansea UniversityInternational Journal of Population Data Science2399-49082021-09-016110.23889/ijpds.v6i1.1679A bespoke data linkage of an IVF clinical quality registry to population health datasets; methods and performanceGeorgina M Chambers0Stephanie K.Y. Choi1Katie Irvine2Christos Venetis3Katie Harris4Alys Havard5Robert J Norman6Kei Lui7William Ledger8Louisa R Jorm9Centre or Big Data Research in Health, Faculty of Medicine, University of New South Wales, Sydney, Australia; School of Women’s and Children’s Health, Faculty of Medicine, University of New South Wales, Sydney, AustraliaCentre or Big Data Research in Health, Faculty of Medicine, University of New South Wales, Sydney, Australia; School of Women’s and Children’s Health, Faculty of Medicine, University of New South Wales, Sydney, AustraliaCentre for Health Record Linkage, Ministry of Health, New South Wales, AustraliaCentre or Big Data Research in Health, Faculty of Medicine, University of New South Wales, Sydney, Australia; School of Women’s and Children’s Health, Faculty of Medicine, University of New South Wales, Sydney, AustraliaThe George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, AustraliaCentre or Big Data Research in Health, Faculty of Medicine, University of New South Wales, Sydney, Australia; National Drug and Alcohol Research Centre, Faculty of Medicine, University of New South Wales, Sydney, AustraliaThe Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, AustraliaSchool of Women’s and Children’s Health, Faculty of Medicine, University of New South Wales, Sydney, AustraliaSchool of Women’s and Children’s Health, Faculty of Medicine, University of New South Wales, Sydney, AustraliaCentre or Big Data Research in Health, Faculty of Medicine, University of New South Wales, Sydney, AustraliaIntroduction Assisted reproductive technologies (ART), such as in-vitro fertilisation (IVF), have revolutionised the treatment of infertility, with an estimated 8 million babies born worldwide. However, the long-term health outcomes for women and their offspring remain an area of concern. Linking IVF treatment data to long-term health data is the most efficient method for assessing such outcomes. Objectives To describe the creation and performance of a bespoke population-based data linkage of an ART clinical quality registry to state-based and national administrative datasets. Methods The linked dataset was created by deterministically and probabilistically linking the Australia and New Zealand Assisted Reproduction Database (ANZARD) to New South Wales (NSW) and Australian Capital Territory (ACT) administrative datasets (performed by NSW Centre for Health Record Linkage (CHeReL)) and to national claims datasets (performed by Australian Institute of Health and Welfare (AIHW)). The CHeReL's Master Linkage Key (MLK) was used as a bridge between ANZARD's partially identifiable patient data (statistical linkage key) and NSW and ACT administrative datasets. CHeReL then provided personal identifiers to the AIHW to obtain national content data. The results of the linkage were reported, and concordance between births recorded in ANZARD and perinatal data collections (PDCs) was evaluated. Results Of the 62,833 women who had ART treatment in NSW or ACT, 60,419 could be linked to the CHeReL MLK (linkage rate: 96.2%). A reconciliation of ANZARD-recorded births among NSW residents found that 94.2% (95% CI: 93.9--94.4%) of births were also recorded in state/territory-based PDCs. A high concordance was found in plurality status and birth outcome (≥99% agreement rate, Cohen's kappa ranged: 0.78--0.98) between ANZARD and PDCs. Conclusion The data linkage resource demonstrates that high linkage rates can be achieved with partially identifiable data and that a population spine, such as the CHeReL's MLK, can be successfully used as a bridge between clinical registries and administrative datasets.https://ijpds.org/article/view/1679Assisted Reproductive TechniquesInfertilityData LinkagePregnancy OutcomeAustralia |
| spellingShingle | Georgina M Chambers Stephanie K.Y. Choi Katie Irvine Christos Venetis Katie Harris Alys Havard Robert J Norman Kei Lui William Ledger Louisa R Jorm A bespoke data linkage of an IVF clinical quality registry to population health datasets; methods and performance International Journal of Population Data Science Assisted Reproductive Techniques Infertility Data Linkage Pregnancy Outcome Australia |
| title | A bespoke data linkage of an IVF clinical quality registry to population health datasets; methods and performance |
| title_full | A bespoke data linkage of an IVF clinical quality registry to population health datasets; methods and performance |
| title_fullStr | A bespoke data linkage of an IVF clinical quality registry to population health datasets; methods and performance |
| title_full_unstemmed | A bespoke data linkage of an IVF clinical quality registry to population health datasets; methods and performance |
| title_short | A bespoke data linkage of an IVF clinical quality registry to population health datasets; methods and performance |
| title_sort | bespoke data linkage of an ivf clinical quality registry to population health datasets methods and performance |
| topic | Assisted Reproductive Techniques Infertility Data Linkage Pregnancy Outcome Australia |
| url | https://ijpds.org/article/view/1679 |
| work_keys_str_mv | AT georginamchambers abespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT stephaniekychoi abespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT katieirvine abespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT christosvenetis abespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT katieharris abespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT alyshavard abespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT robertjnorman abespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT keilui abespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT williamledger abespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT louisarjorm abespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT georginamchambers bespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT stephaniekychoi bespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT katieirvine bespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT christosvenetis bespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT katieharris bespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT alyshavard bespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT robertjnorman bespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT keilui bespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT williamledger bespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance AT louisarjorm bespokedatalinkageofanivfclinicalqualityregistrytopopulationhealthdatasetsmethodsandperformance |