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Data Linkage: A powerful research tool with potential problems
Open accessAbstract
BACKGROUND: Policy makers, clinicians and researchers are demonstrating increasing interest in using data linked from multiple sources to support measurement of clinical performance and patient health outcomes. However, the utility of data linkage may be compromised by sub-optimal or incomplete linkage, leading to systematic bias. In this study, we synthesize the evidence identifying participant or population characteristics that can influence the validity and completeness of data linkage and may be associated with systematic bias in reported outcomes. METHODS: A narrative review, using structured search methods was undertaken. Key words "data linkage" and Mesh term "medical record linkage" were applied to Medline, EMBASE and CINAHL databases between 1991 and 2007. Abstract inclusion criteria were; the article attempted an empirical evaluation of methodological issues relating to data linkage and reported on patient characteristics, the study design included analysis of matched versus unmatched records, and the report was in English. Included articles were grouped thematically according to patient characteristics that were compared between matched and unmatched records. RESULTS: The search identified 1810 articles of which 33 (1.8%) met inclusion criteria. There was marked heterogeneity in study methods and factors investigated. Characteristics that were unevenly distributed among matched and unmatched records were; age (72% of studies), sex (50% of studies), race (64% of studies), geographical/hospital site (93% of studies), socio-economic status (82% of studies) and health status (72% of studies). CONCLUSION: A number of relevant patient or population factors may be associated with incomplete data linkage resulting in systematic bias in reported clinical outcomes. Readers should consider these factors in interpreting the reported results of data linkage studies.
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“Data describing linkage methods and evaluating their success are critical to permit the reader to assess the impact of any linkage error and related bias [51].”
From The Reporting of Studies Conducted Using Observational Routinely-Collected Health Data (RECORD) statement. (2015) · cites this paper as [51]
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von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040296 · Cited by 23,020
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2007) · The Lancet · doi:10.1016/s0140-6736(07)61602-x · Cited by 21,320
Crossing the Quality Chasm: A New Health System for the 21st Century
Baker, A. (2001) · BMJ · doi:10.1136/bmj.323.7322.1192 · Cited by 10,779
Crossing the Quality Chasm: A New Health System for the 21st Century
Committee on Quality of Health Care in America (2002) · Journal for Healthcare Quality · doi:10.1111/j.1945-1474.2002.tb00463.x · Cited by 8,508
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2007) · Preventive Medicine · doi:10.1016/j.ypmed.2007.08.012 · Cited by 2,698
Teasdale, G. M. (2002) · British Journal of Neurosurgery · doi:10.1080/02688690220148815 · Cited by 1,063
Holman, C. D. J., Bass, A. J., Rouse, I. L., & HOBBS, M. S. T. (1999) · Australian and New Zealand Journal of Public Health · doi:10.1111/j.1467-842x.1999.tb01297.x · Cited by 1,037
A framework for evaluation of secondary data sources for epidemiological research
SØRENSEN, H. T., SABROE, S., & OLSEN, J. (1996) · International Journal of Epidemiology · doi:10.1093/ije/25.2.435 · Cited by 455
Research use of linked health data — a best practice protocol
Kelman, C., Bass, A. J., & Holman, C. D. J. (2002) · Australian and New Zealand Journal of Public Health · doi:10.1111/j.1467-842x.2002.tb00682.x · Cited by 434
The Scottish Record Linkage System.
Kendrick, S. W., & Clarke, J. (1993) · PubMed · Cited by 377
Research works printed but not linked: 4
- Canadian Institute for Health Information: Health Care In Canada 2004. 2004, Ottawa, CA: CIHI
- Winglee M, Valliant R, Scheuren F: A case study in record linkage. Survey Methodology. 2005, 31 (1): 3-11.
- National Community Services Information Management Group: Statistical Data Linkage in Community Services Data Collection. 2004, Canberra Australian Institute of Health and Welfare
- Young AF, Dobson AJ, Byles JE: Health services research using linked records: who consents and what is the gain?[see comment]. Aust N Z J Public Health. 2001, 25 (5): 417-420. · DOI
Cited by
Sorted by citations
Items 101–200 of 235
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McIsaac, K. E., MacDonald, S. F., Chong, N., Moser, A. L., Moineddin, R., Colantonio, A., Nathens, A. B., & Matheson, F. I. (2016) · PLoS ONE · doi:10.1371/journal.pone.0161173 · Cited by 10
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Haque, S., Mengersen, K. L., & Stern, S. (2021) · Journal Of Big Data · doi:10.1186/s40537-020-00394-7 · Cited by 10
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Baghal, T. A., Knies, G., & Burton, J. (2014) · RePEc: Research Papers in Economics · Cited by 10
Meta-research: bird’s eye views of primary care research
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Ranchon, F., Chanoine, S., Lambert‐Lacroix, S., Bosson, J., Moreau–Gaudry, A., & Bedouch, P. (2023) · Journal of Medical Internet Research · doi:10.2196/41048 · Cited by 8
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Hoffmann, S., Morris, T. P., Herrmann, M., Heinze, G., Wynants, L., CALSTER, B. V., Bischl, B., Schmid, M., Shaw, P. A., Mathes, T., et al. (2026) · BMJ · doi:10.1136/bmj-2025-087812 · Cited by 8
Lim, F. J., Blyth, C. C., de Klerk, N. H., Valenti, B., Rouhiainen, O., Wu, D. Y.-A., Jansz, C. S., & Moore, H. C. (2015) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.08.003 · Cited by 7
Blake, H. A., Sharples, L. D., Harron, K. L., van der Meulen, J., & Walker, K. (2022) · International Journal of Epidemiology · doi:10.1093/ije/dyac130 · Cited by 7
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de Paula, A. A., Pires, D. R. F., Filho, P. A., de Lemos, K. R. V., Barçante, E., & Pacheco, A. G. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.03.005 · Cited by 7
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Bunting, D., Endo, T., Watt, K., Daniel, R., & Bosley, E. (2022) · Prehospital Emergency Care · doi:10.1080/10903127.2022.2108179 · Cited by 6
Karystianis, G., Cabral, R. C., Adily, A., Lukmanjaya, W., Schofield, P., Buchan, I. E., Nenadić, G., & Butler, T. G. (2022) · JMIR Formative Research · doi:10.2196/39373 · Cited by 6
Lloyd, L., Nicholson, C., Strange, G. A., & Celermajer, D. S. (2023) · Australian Health Review · doi:10.1071/ah23185 · Cited by 6
Sharifian, A., Pourhoseingholi, M. A., Baghestani, A. R., Hajizadeh, N., & Gholizadeh, S. (2016) · Gastroenterology and hepatology from bed to bench. · Cited by 6
Zhao, M., Hoek, G., Strak, M., Grobbee, D. E., Graham, I. M., Klipstein‐Grobusch, K., & Vaartjes, I. C. H. (2020) · Global Heart · doi:10.5334/gh.877 · Cited by 6
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Cacoub, P., Sbaï, A., Benhamou, Y., Godeau, P., & Pietté, J. C. (2000) · PubMed · Cited by 6
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Moore, J. C., Smith, P. W. F., & Durrant, G. B. (2017) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12342 · Cited by 6
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Pluchart, H., Bailly, S., Fauconnier, J., Delafosse, P., Chanoine, S., Dumas, I., Bedouch, P., & Toffart, A. (2021) · Respiratory Medicine and Research · doi:10.1016/j.resmer.2021.100861 · Cited by 6
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Peycheva, D., Ploubidis, G. B., & Calderwood, L. (2021) · Wiley series in probability and statistics · doi:10.1002/9781119376965.ch7 · Cited by 6
Trick, W. E., Doshi, K., Ray, M. J., & Angulo, F. R. (2019) · ACI Open · doi:10.1055/s-0039-1693129 · Cited by 5
Choi, H., Mok, J., Kang, Y. A., Jeong, D., Kang, H., Kim, H. J., Kim, H.-S., & Jeon, D. (2023) · ERJ Open Research · doi:10.1183/23120541.00135-2023 · Cited by 5
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van Brug, H. E., Rosendaal, F. R., van Steenbergen, L. N., Nelissen, R. G. H. H., & Gademan, M. G. J. (2023) · PLoS ONE · doi:10.1371/journal.pone.0282519 · Cited by 5
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Leray, E., Drézen, E., Casey, R., & Vukusic, S. (2025) · Revue Neurologique · doi:10.1016/j.neurol.2025.05.002 · Cited by 4
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Smith, S., Drummond, K. J., DOWLING, A. J., Bennett, I. E., Campbell, D. C., Freilich, R. J., Phillips, C., Ahern, E. S., Reeves, S., Campbell, R., et al. (2024) · JCO Clinical Cancer Informatics · doi:10.1200/cci.24.00025 · Cited by 4
Lee, B., Lee, Y., Kim, S., Oh, H., Won, S., Jang, S., Jeon, Y. J., Yoo, B., & Bak, J. K. (2024) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-024-02586-0 · Cited by 4
Phan, H., He, V. Y., Clifford, S., Jackson, W., & Guthridge, S. L. (2024) · Children and Youth Services Review · doi:10.1016/j.childyouth.2024.107828 · Cited by 4
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Dasylva, A., & Goussanou, A. (2022) · Japanese Journal of Statistics and Data Science · doi:10.1007/s42081-022-00153-3 · Cited by 4
Buhr, L., & Schicktanz, S. (2022) · Big Data & Society · doi:10.1177/20539517221092653 · Cited by 4
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Weissman, J. D., Parker, J. D., Miller, D., Miller, E. A., & Gindi, R. M. (2016) · Survey Practice · doi:10.29115/sp-2016-0028 · Cited by 4
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Wang, W., Aseltine, R. H., Chen, K., & Yan, J. (2020) · The Annals of Applied Statistics · doi:10.1214/19-aoas1287 · Cited by 4
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Scheider, S., & Mallick, M. K. (2025) · JMIR Formative Research · doi:10.2196/63396 · Cited by 3
Nepomuceno, T. C., Junior, P. C. M. L., Zhu, J., Yi, F., Martin, R. H., Lupu, D. S., Peterson, L., Peres, L. C., Berry, A. B., Iversen, E. S., et al. (2024) · JCO Clinical Cancer Informatics · doi:10.1200/cci.23.00251 · Cited by 3
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Wilson, C., Harley, C., & Steels, S. (2020) · Journal of Paramedic Practice · doi:10.12968/jpar.2020.12.11.445 · Cited by 3
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Vincent, K. S., Far, S. S., & Papathomas, M. (2020) · Crime & Delinquency · doi:10.1177/0011128720981900 · Cited by 3
Kelly, M., O’Brien, K. M., & Hannigan, A. (2021) · HRB Open Research · doi:10.12688/hrbopenres.13215.2 · Cited by 3
Glock, B., Endel, F., & Endel, G. (2017) · Cited by 3
Duszynski, K. M., Pratt, N. L., Lynch, J. W., Berry, J. G., & Gold, M. S. (2018) · Vaccine · doi:10.1016/j.vaccine.2018.11.025 · Cited by 3
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Wickersham, A., & Downs, J. M. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-91709-4.00005-6 · Cited by 3
Jennings, E., de Lusignan, S., Michalakidis, G., Krause, P., Sullivan, F., Liyanage, H., & Delaney, B. C. (2018) · BMJ Health & Care Informatics · doi:10.14236/jhi.v25i4.964 · Cited by 3
Emnet: A System for Privacy-preserving Statistical Computation on Distributed Health Data
Hailemichael, M. A. (2015) · NORA - Norwegian Open Research Archives · Cited by 3
Varhol, R., Robinson, S., Lee, C., Randall, S. M., & Boyd, J. (2025) · Health Information Management Journal · doi:10.1177/18333583251329533 · Cited by 3
Endo, T., & Clemens, S. (2026) · Quality of Life Research · doi:10.1007/s11136-026-04173-4 · Cited by 2
Giesinger, I., Li, J., Takemoto, E. E., Brackbill, R. M., Cone, J. E., Qiao, B., & Farfel, M. R. (2020) · Annals of Epidemiology · doi:10.1016/j.annepidem.2020.10.010 · Cited by 2
Herbert, D., Kalbasi, S., Heriot, N., Allan, D., Garduce, P., Pourghaderi, A. R., McInnes, S., & Ahern, S. (2025) · Health Information Management Journal · doi:10.1177/18333583251352621 · Cited by 2
Rico, R. D., Nambiar, D., Gabbe, B. J., Stoove, M. A., & Dietze, P. (2020) · BMC Medical Research Methodology · doi:10.1186/s12874-020-01163-z · Cited by 2
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Banati, P., & Lerner, R. M. (2021) · Bristol University Press eBooks · doi:10.47674/9781529204834 · Cited by 2
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Koornneef, D. J. M., Brinkman, S., Termorshuizen, F., & de Keizer, N. F. (2024) · Studies in health technology and informatics · doi:10.3233/shti240345 · Cited by 2
Harron, K. L., Grath-Lone, L. M., Mason, S. J., & Gilbert, R. E. (2016) · Staff Publications Online (The Tavistock and Portman) · Cited by 2
Big data approaches to investigating Child Mental Health disorder outcomes
Downs, J. M. (2018) · Research Portal (King's College London) · Cited by 2
Sallakh, M. A. A. (2018) · doi:10.23889/suthesis.48569 · Cited by 2
Ghebreab, L., Kool, B., Lee, A. C.-L., & Morton, S. (2023) · BMC Medical Research Methodology · doi:10.1186/s12874-023-01900-0 · Cited by 1
Digitalstrategie und Health Data Management im Krankenhaus
Henke, V., Hülsken, G., Schneider, H., & Varghese, J. (2024) · Springer eBooks · doi:10.1007/978-3-658-43236-2_21 · Cited by 1
Jaswal, H., Ialomiteanu, A., Hamilton, H., Rehm, J. T., Wells, S. L., & Shield, K. D. (2024) · BMC Public Health · doi:10.1186/s12889-024-20769-2 · Cited by 1
Djajadisastra, F. W. (2024) · Journal of Preventive Medicine and Public Health · doi:10.3961/jpmph.24.448 · Cited by 1
Selukar, S., Yin, V., & Othus, M. K. D. (2025) · Blood Reviews · doi:10.1016/j.blre.2025.101324 · Cited by 1
Detecting Fake People in Historical Records
Duzett, N., Hepps, T., Otterstrom, A., & Price, J. (2025) · Social Science History · doi:10.1017/ssh.2025.10115 · Cited by 1
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Moon, J. D., Bohensky, M. A., & Galea, M. P. (2016) · International Journal of Big Data and Analytics in Healthcare · doi:10.4018/ijbdah.2016010102 · Cited by 1
Self-citationFarr, I. W., Cowley, L., Broadhurst, K., Odd, D., Jones, C., Bailey, G. A., Alrouh, B., Abouelenin, M., Cusworth, L., Doebler, S., et al. (2024) · International Journal for Population Data Science · doi:10.23889/ijpds.v9i1.2362 · Cited by 1
Conel: Contrastive Neural Link Discovery Leveraging Literal Similarities
Becker, A., Ngomo, A.-C. N., & Sherif, M. A. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-25156-5_9 · Cited by 1
Meinecke, A., Diaz-Decaro, J. D., Gavin, K. M., Sun, T., Strom, J. B., Gabarró, M. S., Li, H., Teltsch, D. Y., Najafzadeh, M., Panozzo, C. A., et al. (2026) · Frontiers in Pharmacology · doi:10.3389/fphar.2026.1887249 · Cited by 1
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Khurshid, A. (2021) · doi:10.7566/jpscp.36.011005 · Cited by 1
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Bradfield, O. (2021) · Research Ethics · doi:10.1177/17470161211058311 · Cited by 1
Silverwood, R. J., Rajah, N., Calderwood, L., Stavola, B. L. D., Harron, K. L., & Ploubidis, G. B. (2024) · International Journal for Population Data Science · doi:10.23889/ijpds.v9i1.2137 · Cited by 1
Evaluating Linkage Quality of Population-Based Administrative Data for Health Service Research
Kim, J., Choi, H., Lim, H. J., Oh, M., & Ahn, J. J. (2024) · Journal of Korean Medical Science · doi:10.3346/jkms.2024.39.e127 · Cited by 1
Green, H., Fabrianesi, B., Carolan, L., & Braunack‐Mayer, A. (2024) · JBI Evidence Synthesis · doi:10.11124/jbies-23-00317 · Cited by 1
Marcellis, L. H. M., Sinnige, A., van Bergen, A. G. E., Spruijt, S., Kittelson, A. J., Teijink, J. A. W., van der Wees, P. J., & Hoogeboom, T. J. (2025) · BMJ Open Quality · doi:10.1136/bmjoq-2024-002920 · Cited by 1
Denz, R., Meiszl, K., Ihle, P., Oberle, D., Drechsel‐Bäuerle, U., Scholz, K., Meyer, I., & Timmesfeld, N. (2025) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918.2025.2488942 · Cited by 2
Benchimol, E. I., Smeeth, L. L., Guttmann, A., Harron, K. L., Moher, D., Petersen, I., Sørensen, H. T., Januel, J., von Elm, E. B., & Langan, S. (2019) · Canadian Medical Association Journal · doi:10.1503/cmaj.181309 · Cited by 2
Andrew, N. E., Cadilhac, D. A.-M., Sundararajan, V., Thrift, A. G., Anderson, P., Lannin, N. A., & Kilkenny, M. F. (2021) · Australian and New Zealand Journal of Public Health · doi:10.1111/1753-6405.13079 · Cited by 1
Self-citationKelly, M., O’Brien, K. M., & Hannigan, A. (2021) · HRB Open Research · doi:10.12688/hrbopenres.13215.1 · Cited by 1
Sustainable Human Development Across the Life Course
(2021) · Bristol University Press eBooks · doi:10.56687/9781529204834 · Cited by 1
Tsang, G. (2022) · Cronfa (Swansea University) · doi:10.23889/suthesis.61814 · Cited by 1
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Self-citationNgundue, J. E. (2016) · ScholarWorks (Walden University)
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Rammon, J., He, Y., & Parker, J. D. (2018) · Health Services and Outcomes Research Methodology · doi:10.1007/s10742-018-0186-3
Metadata
- Authors
- Bohensky, M. A., Jolley, D., Sundararajan, V., Evans, S., Pilcher, D. V., Scott, I., & Brand, C. A.
- Affiliations
- Monash University (AU)
- Australian and New Zealand Intensive Care Society (AU)
- Princess Alexandra Hospital (AU)
- Corresponding author
- Bohensky, Megan A
- Venue
- BMC Health Services Research
- Published
- 2010-12
- Volume
- 10
- Issue
- 1
- Pages
- 346-346
- ISSN
- 1472-6963 (ISSN-L)
- PMC
- PMC3271236
- OpenAlex
- W1975356361
- Cited by
- 234
- References
- 61
- Citations by year
- 2026: 8 · 2025: 19 · 2024: 24 · 2023: 16 · 2022: 27 · 2021: 25 · 2020: 18 · 2019: 16 · 2018: 20 · 2017: 16 · 2016: 13 · 2015: 7 · 2014: 10 · 2013: 4 · 2012: 5
- FWCI
- 5.65
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Health Services Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Monash University
- Topics
- Physical Sciences › Computer Science › Information Systems › Data Quality and Management
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- data linkage, medical record linkage, systematic bias, patient characteristics, socioeconomic status, health status, clinical outcome measurement
- MeSH terms
- Data Collection, Health Services Research, Health Status, Hospitals, Humans, Outcome and Process Assessment, Health Care, Quality Assurance, Health Care, Research Design, Sensitivity and Specificity, Databases, Bibliographic, Information Storage and Retrieval, Empirical Research, Clinical Audit
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