Reporting of Aboriginal people in health data collections in NSW

Abstract Background Aboriginal people are under-reported on administrative health data in Australia. Various approaches have been used or proposed to improve reporting of Aboriginal people using linked records. This cross-sectional study used self-reported Aboriginality from the NSW Patient Survey Program (PSP) as a reference standard to assess the accuracy of reporting of Aboriginal people on NSW Admitted Patient (APDC) and Emergency Department Data Collections (EDDC), and compare the accuracy of selected approaches to enhance reporting Aboriginality using linked data. Methods Ten PSP surveys were linked to five administrative health data collections, including APDC, EDDC, perinatal, and birth and death registration records. Accuracy of reporting of Aboriginality was assessed using sensitivity, specificity, and positive and negative predictive values (PPVs and NPVs) and F score for the EDDC and APDC as baseline and four enhancement approaches using linked records: “Most recent linked record”, “Ever reported as Aboriginal”, and two approaches using a weight of evidence, “Enhanced Reporting of Aboriginality (ERA) algorithm” and “Multi-stage median (MSM)”. Results There was substantial under-reporting of Aboriginality on APDC and EDDC records (sensitivities 84 and 77% respectively) with PPVs of 95% on both data collections. Overall, specificities and NPVs were above 98%. Of people who were reported as Aboriginal on the PSP, 16% were not reported as Aboriginal on any of their linked records. Record linkage approaches generally increased sensitivity, accompanied by decrease in PPV with little change in overall F score for the APDC and an increase in F score for the EDDC. The “ERA algorithm” and “MSM” approaches provided the best overall accuracy. Conclusions Weight of evidence approaches are preferred when record linkage is used to improve reporting of Aboriginality on administrative health data collections. However, as a substantial number of Aboriginal people are not reported as Aboriginal on any of their linked records, improvements in reporting are incomplete and should be taken into account when interpreting results of any analyses. Enhancement of reporting of Aboriginality using record linkage should not replace efforts to improve recording of Aboriginal people at the point of data collection and addressing barriers to self-identification for Aboriginal people.

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Improving Data Quality in Health Care

Encyclopedia of Information Science and Technology, Second Edition ◽

10.4018/978-1-60566-026-4.ch295 ◽

2010 ◽

pp. 1877-1881

Author(s):

Karolyn Kerr ◽

Tony Norris

Keyword(s):

Health Care ◽

New Zealand ◽

Data Quality ◽

Good Practice ◽

Health Data ◽

Strategic Approach ◽

The Right ◽

Data Collections ◽

And Control ◽

Care Demands

The increasingly information intensive nature of health care demands a proactive and strategic approach to data quality to ensure the right information is available to the right person at the right time in the right format. The approach must also encompass the rights of the patient to have their health data protected and used in an ethical way. This article describes the principles to establish good practice and overcome practical barriers that define and control data quality in health data collections and the mechanisms and frameworks that can be developed to achieve and sustain quality. The experience of a national health data quality project in New Zealand is used to illustrate the issues.

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Improving Data Quality in Health Care

Health Information Systems ◽

10.4018/978-1-60566-988-5.ch015 ◽

2011 ◽

pp. 218-225 ◽

Cited By ~ 1

Author(s):

Karolyn Kerr ◽

Tony Norris

Keyword(s):

Health Care ◽

New Zealand ◽

Data Quality ◽

Good Practice ◽

Health Data ◽

Strategic Approach ◽

The Right ◽

Data Collections ◽

And Control ◽

Care Demands

The increasingly information intensive nature of health care demands a proactive and strategic approach to data quality to ensure the right information is available to the right person at the right time in the right format. The approach must also encompass the rights of the patient to have their health data protected and used in an ethical way. This article describes the principles to establish good practice and overcome practical barriers that define and control data quality in health data collections and the mechanisms and frameworks that can be developed to achieve and sustain quality. The experience of a national health data quality project in New Zealand is used to illustrate the issues.

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The Norwegian Twin Registry

Twin Research and Human Genetics ◽

10.1017/thg.2019.59 ◽

2019 ◽

Vol 22 (6) ◽

pp. 647-650

Author(s):

Thomas Nilsen ◽

Ingunn Brandt ◽

Jennifer R. Harris

Keyword(s):

Record Linkage ◽

Potential Benefit ◽

Data Access ◽

Health Data ◽

Research Use ◽

Twin Data ◽

Physical And Mental Health ◽

Twin Registry ◽

Other Information ◽

Data Collections

AbstractThe Norwegian Twin Registry (NTR) is maintained as a research resource that was compiled by merging several panels of twin data that were established for research into physical and mental health, wellbeing and development. NTR is a consent-based registry. Where possible, data that were collected in previous studies are curated for secondary research use. A particularly valuable potential benefit associated with the Norwegian twin data lies in the opportunities to expand and enhance the data through record linkage to nationwide registries that cover a wide array of health data and other information, including socioeconomic factors. This article provides a brief description of the current NTR sample and data collections, information about data access procedures and an overview of the national registries that can be linked to the NTR for research projects.

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If you build it, they will come: unintended future uses of organised health data collections

BMC Medical Ethics ◽

10.1186/s12910-016-0137-x ◽

2016 ◽

Vol 17 (1) ◽

Cited By ~ 19

Author(s):

Kieran C. O’Doherty ◽

Emily Christofides ◽

Jeffery Yen ◽

Heidi Beate Bentzen ◽

Wylie Burke ◽

...

Keyword(s):

Health Data ◽

Data Collections

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Study protocol for One Health data collections, analyses and intervention of the Sino-Swedish integrated multisectoral partnership for antibiotic resistance containment (IMPACT)

BMJ Open ◽

10.1136/bmjopen-2017-017832 ◽

2018 ◽

Vol 8 (1) ◽

pp. e017832 ◽

Cited By ~ 14

Author(s):

Qiang Sun ◽

Yang Wang ◽

Anette Hulth ◽

Yonghong Xiao ◽

Lennart E Nilsson ◽

...

Keyword(s):

Antibiotic Resistance ◽

Study Protocol ◽

One Health ◽

Health Data ◽

Data Collections

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Identifying Indigenous People in Health Data Collections

Health Information Management ◽

10.1177/183335839702600412 ◽

1996 ◽

Vol 26 (4) ◽

pp. 209-211 ◽

Cited By ~ 1

Author(s):

Mary-Ellen Vidgen

Keyword(s):

Indigenous People ◽

Health Data ◽

Data Collections

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Generating knowledge on data collection methods and the availability of health information in Europe

European Journal of Public Health ◽

10.1093/eurpub/ckz185.816 ◽

2019 ◽

Vol 29 (Supplement_4) ◽

Author(s):

B Unim ◽

E Mattei ◽

F Carle ◽

E Bernal-Delgado ◽

P Achterberg ◽

...

Keyword(s):

Data Collection ◽

Policy Making ◽

Health Data ◽

Data Sources ◽

Research Networks ◽

Data Collection Methods ◽

Eu Countries ◽

Health System Performance Assessment ◽

Data Collections ◽

Collection Methods

Abstract Background Data collection methods, metadata-reporting standards and usage of data for health monitoring (HM) and health system performance assessment (HSPA) are not uniform in Europe. Moreover, the evidence produced by research are not always available, comparable or usable for research purposes and policy making. The aim is to summarize health data collection methods, quality assessment, availability and accessibility procedures covering different data sources for HM and HSPA across EU countries. Methods The study is conducted through a multidimensional approach, which includes: i) a review of institutional websites (OECD, Eurostat, WHO-Europe); ii) a review of EU research networks; and iii) a multi-national survey addressing epidemiologists, health data managers and researchers that have played leading roles in EU projects. Currently, the survey instrument is being piloted. A qualitative data analysis to describe and compare the identified data sources for HM and HSPA will be performed. Results As part of the work within the Joint Action ‘Information for Action’ (InfAct), the study will generate knowledge on standardized health data collections and related metadata, used methods and procedures for HM and HSPA in EU. It will also facilitate the identification of national or sub-national health data collected through standardized procedures but not included in international databases or research networks. Conclusions The lack of infrastructures for health data sharing in EU limits data usage and comparability within and between countries. This study, as part of InfAct, will facilitate the assessment of health inequalities across EU countries in terms of quality, availability, accessibility and comparability of health data and information. It will also facilitate sharing and dissemination of standardized and comparable health data collections, which are essential for research and evidence-based policy-making.

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Identification of Australians from culturally and linguistically diverse backgrounds in national healthdata collections

Australian Health Review ◽

10.1071/ah050455 ◽

2005 ◽

Vol 29 (4) ◽

pp. 455 ◽

Cited By ~ 7

Author(s):

Ilse Blignault ◽

Abbas Haghshenas

Keyword(s):

National Health ◽

Linguistic Diversity ◽

Health Sector ◽

Community Services ◽

Health Data ◽

Service Development ◽

Data Sets ◽

National Data ◽

Cultural And Linguistic Diversity ◽

Data Collections

In multicultural Australia, comprehensive and upto- date information on ethnicity and health is essential to guide policy and service development in the health sector. Data collected for purposes other than research are a potentially important source of information. This study explored the extent to which indicators of cultural and linguistic diversity are currently included in national health and welfare service data collections, and the data standards employed. We identified and reviewed 44 relevant bodies of work: 7 national data dictionaries, 15 national data sets, 10 national health data collections and 12 national surveys. Each of the large data dictionaries (health, community services and housing assistance) contained several ethnicity-related variables. Immigrant Australians were identified (usually by country of birth, sometimes by language, and occasionally by period of residence or year of arrival) in all the major national health and community data sets, health data collections and surveys. Australian Bureau of Statistics standards and classifications relating to cultural and linguistic diversity were widely used. Researchers, health policy makers and planners should fully exploit these secondary data sources, as well as undertaking or commissioning primary research.

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Using linked administrative health data for palliative and end of life care research in Ireland: potential and challenges

HRB Open Research ◽

10.12688/hrbopenres.13215.1 ◽

2021 ◽

Vol 4 ◽

pp. 17

Author(s):

Maria Kelly ◽

Katie O'Brien ◽

Ailish Hannigan

Keyword(s):

Palliative Care ◽

Health System ◽

End Of Life ◽

Data Protection ◽

End Of Life Care ◽

Data Access ◽

Health Data ◽

Life Care ◽

Administrative Health Data ◽

Data Collections

Background: This study aims to examine the potential of currently available administrative health data for palliative and end-of-life care (PEoLC) research in Ireland. Objectives include to i) identify administrative health data sources for PEoLC research ii) describe the challenges and opportunities of using these and iii) estimate the impact of recent health system reforms and changes to data protection laws. Methods: The 2017 Health Information and Quality Authority catalogue of health and social care datasets was cross-referenced with a recognised list of diseases with associated palliative care needs. Criteria to assess the datasets included population coverage, data collected, data dictionary and data model availability and mechanisms for data access. Results: Eight datasets with potential for PEoLC research were identified, including four disease registries, (cancer, cystic fibrosis, motor neurone and interstitial lung disease), death certificate data, hospital episode data, community prescription data and one national survey. The ad hoc development of the health system in Ireland has resulted in i) a fragmented information infrastructure resulting in gaps in data collections particularly in the primary and community care sector where much palliative care is delivered, ii) ill-defined data governance arrangements across service providers, many of whom are not part of the publically funded health service and iii) systemic and temporal issues that affect data quality. Initiatives to improve data collections include introduction of i) patient unique identifiers, ii) health entity identifiers and iii) integration of the eircode postcodes. Recently enacted general data protection and health research regulations will clarify legal and ethical requirements for data use. Conclusions: With appropriate permissions, detailed knowledge of the datasets and good study design currently available administrative health data can be used for PEoLC research. Ongoing reform initiatives and recent changes to data privacy laws will facilitate future use of administrative health data for PEoLC research.

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