Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Health Services Research
Published in: BMC Health Services Research 1/2015

Open Access 01-12-2015 | Research article

Accuracy and completeness of patient pathways – the benefits of national data linkage in Australia

Authors: James H. Boyd, Sean M. Randall, Anna M. Ferrante, Jacqueline K. Bauer, Kevin McInneny, Adrian P. Brown, Katrina Spilsbury, Margo Gillies, James B. Semmens

Published in: BMC Health Services Research | Issue 1/2015

Login to get access

Abstract

Background

The technical challenges associated with national data linkage, and the extent of cross-border population movements, are explored as part of a pioneering research project. The project involved linking state-based hospital admission records and death registrations across Australia for a national study of hospital related deaths.

Methods

The project linked over 44 million morbidity and mortality records from four Australian states between 1st July 1999 and 31st December 2009 using probabilistic methods. The accuracy of the linkage was measured through a comparison with jurisdictional keys sourced from individual states. The extent of cross-border population movement between these states was also assessed.

Results

Data matching identified almost twelve million individuals across the four Australian states. The percentage of individuals from one state with records found in another ranged from 3-5 %. Using jurisdictional keys to measure linkage quality, results indicate a high matching efficiency (F measure 97 to 99 %), with linkage processing taking only a matter of days.

Conclusions

The results demonstrate the feasibility and accuracy of undertaking cross jurisdictional linkage for national research. The benefits are substantial, particularly in relation to capturing the full complement of records in patient pathways as a result of cross-border population movements.
The project identified a sizeable ‘mobile’ population with hospital records in more than one state. Research studies that focus on a single jurisdiction will under-enumerate the extent of hospital usage by individuals in the population. It is important that researchers understand and are aware of the impact of this missing hospital activity on their studies.
The project highlights the need for an efficient and accurate data linkage system to support national research across Australia.
Literature
1.
Virnig BA, McBean M. Administrative data for public health surveillance and planning. Annu Rev Public Health. 2001;22(1):213–30.CrossRefPubMed
2.
Sibthorpe B, Kliewer E, Smith L. Record linkage in Australian epidemiological research: health benefits, privacy safeguards and future potential. Aust J Public Health. 1995;19(3):250–6.CrossRefPubMed
3.
Holman D, Bass A, Rouse I, Hobbs M. Population-based linkage of health records in Western Australia: Development of a health services research linked database. Aust N Z J Public Health. 1999;23.
4.
Holman CDAJ, Bass AJ, Rosman DL, Smith MB, Semmens JB, Glasson EJ, et al. A decade of data linkage in Western Australia: Strategic design, applications and benefits of the WA data linkage system. Aust Health Rev. 2008;32(4):766–77.CrossRefPubMed
5.
Newcombe H, Kennedy J. Record linkage: making maximum use of the discriminating power of identifying information. Commun ACM. 1962;5(11):563–6.CrossRef
6.
Ferrante A, Boyd J. A transparent and transportable methodology for evaluating Data Linkage software. J Biomed Inform. 2012;45(1):165–72.CrossRefPubMed
7.
8.
9.
Kendrick SW, Clarke JA. The Scottish Medical Record Linkage System. Health Bulletin (Edinburgh). 1979;51:72–9.
10.
Gill LE. OX-LINK: The Oxford Medical Record Linkage System. In: Record Linkage Techniques. Oxford: University of Oxford; 1997. p. 19.
11.
Roos LL, Wajda A. Record Linkage Strategies: Part 1: Estimating Information and Evaluating Approaches. Winnipeg: University of Manitoba; 1990. p. 28.
12.
Field K, Kosmider S, Johns J, Farrugia H, Hastie I, Croxford M, et al. Linking data from hospital and cancer registry databases: should this be standard practice? Internal medicine journal. 2010;40(8):566–73.CrossRefPubMed
13.
Lawrence G, Dinh I, Taylor L. The Centre for Health Record Linkage: A New Resource for Health Services Research and Evaluation. Health Information Management Journal. 2008;37(2):60–2.CrossRef
14.
NCRIS. Funding Agreement for the National Collaborative Research Infrastructure Strategy’s Research Capability known as ‘Population Health Research Network’. Canberra: Commonwealth Department of Education Science and Training; 2009.
15.
Frommer PM, Madronio C, Kemp S, Jenkin R, Reitano R. NCRIS Capability 5.7: Population Health and Data Linkage. Sydney: University of Sydney; 2007. p. 8.
16.
Boyd JH, Ferrante AM, O’Keefe CM, Bass AJ, Randall SM, Semmens JB. Data linkage infrastructure for cross-jurisdictional health-related research in Australia. BMC Health Serv Res. 2012;12.
17.
Kelman C, Bass A, Holman D. Research use of linked health data: A best practice protocol. Aust N Z J Public Health. 2002;26:5.CrossRef
18.
Newcombe HB. Handbook for Record Linkage: Methods for Health and Statistical Studies, Administration and Business. New York: Oxford University Press; 1988.
19.
20.
Jaro MA. "UNIMATCH: A record linkage system: User’s manual", Technical Report, US Bureau of the Census, Washington D.C. 1976.
21.
Christen P, Goiser K. Assessing Deduplication and Data Linkage, Quality: What to Measure. In: Proceedings of the Fourth Australasian Data Mining Conference Sydney; 2005: 16.
22.
Christen P, Goiser K. Quality and Complexity Measures for Data Linkage and Deduplication. In. Canberra: Department of Computer Science, Australian National University; 2004.
23.
Bishop G, Khoo J. Methodology of Evaluating the Quality of Probabilistic Linking. Canberra: Australian Bureau of Statistics, Analytical Services Branch; 2007. p. 20.
24.
Christen P, Goiser K. Quality and complexity measures for data linkage and deduplication. Quality Measures in Data Mining. Berlin Heidelberg: Springer; 2007. 127–151.
25.
Karmel R, Anderson P, Gibson D, Peut A, Duckett S, Wells Y. Empirical aspects of record linkage across multiple data sets using statistical linkage keys: the experience of the PIAC cohort study. 2010.
26.
Campbell KM, Deck D, Krupski A. Record linkage software in the public domain: a comparison of Link Plus, The Link King and a ‘basic’ deterministic algorithm. Health Informatics. 2008;14(1):5–15.CrossRef
27.
Harron K, Wade A, Gilbert R, Muller-Pebody B, Goldstein H. Evaluating bias due to data linkage error in electronic healthcare records. BMC Med Res Methodol. 2014;14(1):36.CrossRefPubMedPubMedCentral
28.
Harron K, Wade A, Muller-Pebody B, Goldstein H, Gilbert R. Opening the black box of record linkage. J Epidemiol Community Health. 2012;66(12):1198–8.CrossRefPubMed
Metadata
Title
Accuracy and completeness of patient pathways – the benefits of national data linkage in Australia
Authors
James H. Boyd
Sean M. Randall
Anna M. Ferrante
Jacqueline K. Bauer
Kevin McInneny
Adrian P. Brown
Katrina Spilsbury
Margo Gillies
James B. Semmens
Publication date
01-12-2015
Publisher
BioMed Central
Published in
BMC Health Services Research / Issue 1/2015
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/s12913-015-0981-2

Other articles of this Issue 1/2015

BMC Health Services Research 1/2015 Go to the issue

Research article

Determinants of the intention to use e-Health by community dwelling older people

Research article

Healthcare utilization and costs associated with S. aureus and P. aeruginosa pneumonia in the intensive care unit: a retrospective observational cohort study in a US claims database

Research article

Who pays for home care? A study of nationally representative data on disabled older Americans

Research article

Excess length of stay and economic consequences of adverse events in Dutch hospital patients

Research article

Successful collaboration in dementia care from the perspectives of healthcare professionals and informal carers in Germany: results from a focus group study

Research article

An organizational perspective on the long-term sustainability of a nursing best practice guidelines program: a case study