Growth of linked hospital data use in Australia: a systematic review
Michelle Tew A , Kim M. Dalziel A , Dennis J. Petrie A B and Philip M. Clarke A
+ Author Affiliations
- Author Affiliations
A The University of Melbourne, Centre for Health Policy, Melbourne School of Population and Global Health, Level 4, 207 Bouverie Street, Carlton, Vic. 3053, Australia. Email: michelle.tew@unimelb.edu.au; kim.dalziel@unimelb.edu.au; philip.clarke@unimelb.edu.au
B Corresponding author. Email: dennis.petrie@unimelb.edu.au
Australian Health Review 41(4) 394-400 https://doi.org/10.1071/AH16034
Submitted: 5 February 2016 Accepted: 5 June 2016 Published: 22 July 2016
Journal Compilation © AHHA 2017 Open Access CC BY-NC-ND
Abstract
Objective The aim of the present study was to quantify and understand the utilisation of linked hospital data for research purposes across Australia over the past two decades.
Methods A systematic review was undertaken guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 checklist. Medline OVID, PsycINFO, Embase, EconLit and Scopus were searched to identify articles published from 1946 to December 2014. Information on publication year, state(s) involved, type of data linkage, disease area and purpose was extracted.
Results The search identified 3314 articles, of which 606 were included; these generated 629 records of hospital data linkage use across all Australian states and territories. The major contributions were from Western Australia (WA; 51%) and New South Wales (NSW; 32%) with the remaining states and territories having significantly fewer publications (total contribution only 17%). WA’s contribution resulted from a steady increase from the late 1990s, whereas NSW’s contribution is mostly from a rapid increase from 2010. Current data linkage is primarily used in epidemiological research (73%).
Conclusion More than 80% of publications were from WA and NSW, whereas other states significantly lag behind. The observable growth in these two states clearly demonstrates the underutilised opportunities for data linkage to add value in health services research in the other states.
What is known about the topic? Linking administrative hospital data to other data has the potential to be a cost-effective method to significantly improve health policy. Over the past two decades, Australia has made significant investments in improving its data linkage capabilities. However, several articles have highlighted the many barriers involved in using linked hospital data.
What does this paper add? This paper quantitatively evaluates the performance across all Australian states in terms of the use of their administrative hospital data for research purposes. The performance of states varies considerably, with WA and NSW the clear stand-out performers and limited outputs currently seen for the other Australian states and territories.
What are the implications for practitioners? Given the significant investments made into data linkage, it is important to continue to evaluate and monitor the performance of the states in terms of translating this investment into outputs. Where the outputs do not match the investment, it is important to identify and overcome those barriers limiting the gains from this investment. More generally, there is a need to think about how we improve the effective and efficient use of data linkage investments in Australia.
References
[1] Moore HC, Guiver T, Woollacott A, de Klerk N, Gidding HF. Establishing a process for conducting cross-jurisdictional record linkage in Australia. Aust N Z J Public Health 2015; 40 159–64.| Establishing a process for conducting cross-jurisdictional record linkage in Australia.Crossref | GoogleScholarGoogle Scholar | 26559155PubMed |
[2] Gibson A, Jorm L, McIntyre P. Using linked birth, notification, hospital and mortality data to examine false-positive meningococcal disease reporting and adjust disease incidence estimates for children in New South Wales, Australia. Epidemiol Infect 2015; 143 2570–9.
| Using linked birth, notification, hospital and mortality data to examine false-positive meningococcal disease reporting and adjust disease incidence estimates for children in New South Wales, Australia.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC2MvltFClsw%3D%3D&md5=a6cf57ca57f63cad02adeb4349e54d4eCAS | 25573266PubMed |
[3] Hall SE, Holman CDJ, Hendrie DV, Spilsbury K. Unequal access to breast-conserving surgery in Western Australia 1982–2000. ANZ J Surg 2004; 74 413–19.
| Unequal access to breast-conserving surgery in Western Australia 1982–2000.Crossref | GoogleScholarGoogle Scholar | 15191470PubMed |
[4] Clarke P, Leal J, Kelman C, Smith M, Colagiuri S.. Estimating the cost of complications of diabetes in Australia using administrative health-care data. Value Health 2008; 11 199–206.
| Estimating the cost of complications of diabetes in Australia using administrative health-care data.Crossref | GoogleScholarGoogle Scholar | 18380631PubMed |
[5] Katzenellenbogen JM, Vos T, Somerford P, Begg S, Semmens JB, Codde JP. Burden of stroke in Indigenous Western Australians: a study using data linkage. Stroke 2011; 42 1515–21.
| Burden of stroke in Indigenous Western Australians: a study using data linkage.Crossref | GoogleScholarGoogle Scholar | 21493909PubMed |
[6] Katzenellenbogen JM, Sanfilippo FM, Hobbs MS, Knuiman MW, Bessarab D, Durey A, Thompson SC. Voting with their feet – predictors of discharge against medical advice in Aboriginal and non-Aboriginal ischaemic heart disease inpatients in Western Australia: an analytic study using data linkage. BMC Health Serv Res 2013; 13 330
| Voting with their feet – predictors of discharge against medical advice in Aboriginal and non-Aboriginal ischaemic heart disease inpatients in Western Australia: an analytic study using data linkage.Crossref | GoogleScholarGoogle Scholar | 23962275PubMed |
[7] McCallum LK, Liu B, McIntyre P, Jorm LR. Estimating the burden of pertussis in young children on hospitals and emergency departments: a study using linked routinely collected data. Epidemiol Infect 2014; 142 695–705.
| Estimating the burden of pertussis in young children on hospitals and emergency departments: a study using linked routinely collected data.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC3snjs1enug%3D%3D&md5=ce232a5f9a341cc134c9eabf74afb959CAS | 23672837PubMed |
[8] Wilson CL, Cohn RJ, Johnston KA, Ashton LJ. Late mortality and second cancers in an Australian cohort of childhood cancer survivors. Med J Aust 2010; 193 258–61.
| 20819041PubMed |
[9] Williams TA, Dobb GJ, Finn JC, Knuiman M, Lee KY, Geelhoed E, Webb SA. Data linkage enables evaluation of long-term survival after intensive care. Anaesth Intensive Care 2006; 34 307–15.
| 1:STN:280:DC%2BD28zos1antw%3D%3D&md5=36916978b13c296d24366a370764d5ecCAS | 16802482PubMed |
[10] Kinner SA, Degenhardt L, Coffey C, Hearps S, Spittal M, Sawyer SM, Patton GC. Substance use and risk of death in young offenders: a prospective data linkage study. Drug Alcohol Rev 2015; 34 46–50.
| Substance use and risk of death in young offenders: a prospective data linkage study.Crossref | GoogleScholarGoogle Scholar | 25066461PubMed |
[11] Rotermann M, Sanmartin C, Trudeau R, St-Jean H. Linking 2006 census and hospital data in Canada. Health Rep 2015; 26 10–20.
| 26488823PubMed |
[12] Hobbs MS, McCall MG. Health statistics and record linkage in Australia. J Chronic Dis 1970; 23 375–81.
| Health statistics and record linkage in Australia.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaE3M%2FnvFOlsQ%3D%3D&md5=4670459fd46277525eeea20f0aea63f3CAS | 5492967PubMed |
[13] Holman CD, Bass AJ, Rosman DL, Smith MB, Semmens JB, Glasson EJ, Brook EL, Trutwein B, Rouse IL, Watson CR, de Klerk NH, Stanley FJ. A decade of data linkage in Western Australia: strategic design, applications and benefits of the WA data linkage system. Aust Health Rev 2008; 32 766–77.
| A decade of data linkage in Western Australia: strategic design, applications and benefits of the WA data linkage system.Crossref | GoogleScholarGoogle Scholar | 18980573PubMed |
[14] Banks E, Redman S, Jorm L, Armstrong B, Bauman A, Beard J, Beral V, Byles J, Corbett S, Cumming R, Harris M, Sitas F, Smith W, Taylor L, Wutzke S, Lujic S. Cohort profile: the 45 and Up Study. Int J Epidemiol 2008; 37 941–7.
| Cohort profile: the 45 and Up Study.Crossref | GoogleScholarGoogle Scholar | 17881411PubMed |
[15] Jorm L, Walter S, Lujic S, Mealing N, Byles J, Kendig H. The 45 and Up Study: exploring the health of home and community care clients in New South Wales. Sydney: Operational Performance Directorate Ageing, Disability and Home Care Department of Family and Community Services NSW; 2012.
[16] Population Health Research Network. Annual report 2013–14. Perth: Population Health Research Network Program Office; 2015. Available at: http://www.phrn.org.au/media/80709/annual-report-2013-2014_final.pdf [verified 1 February 2016].
[17] Roder DM, Fong KM, Brown MP, Zalcberg J, Wainwright CE. Realising opportunities for evidence-based cancer service delivery and research: linking cancer registry and administrative data in Australia. Eur J Cancer Care (Engl) 2014; 23 721–7.
| Realising opportunities for evidence-based cancer service delivery and research: linking cancer registry and administrative data in Australia.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC2M7jsVGgtg%3D%3D&md5=425d3ecb1b3ac18b37e6a2e82bc3ef2eCAS |
[18] Olver IN. Linking data to improve health outcomes. Med J Aust 2014; 200 368–9.
| Linking data to improve health outcomes.Crossref | GoogleScholarGoogle Scholar | 24794653PubMed |
[19] Kelman CW, Bass AJ, Holman CDJ. Research use of linked health data: a best practice protocol. Aust N Z J Public Health 2002; 26 251–5.
| Research use of linked health data: a best practice protocol.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD38zpt1Oitg%3D%3D&md5=0902bd682de4e7fcae9eadb484f0f30aCAS | 12141621PubMed |
[20] Glasson EJ, Hussain R. Linked data: opportunities and challenges in disability research. J Intellect Dev Disabil 2008; 33 285–91.
| Linked data: opportunities and challenges in disability research.Crossref | GoogleScholarGoogle Scholar | 19039688PubMed |
[21] Mitchell RJ, Cameron CM, Bambach MR. Data linkage for injury surveillance and research in Australia: perils, pitfalls and potential. Aust N Z J Public Health 2014; 38 275–80.
| Data linkage for injury surveillance and research in Australia: perils, pitfalls and potential.Crossref | GoogleScholarGoogle Scholar | 24890486PubMed |
[22] Whop LJ, Cunningham J, Condon JR. How well is the National Cervical Screening Program performing for Indigenous Australian women? Why we don’t really know, and what we can and should do about it. Eur J Cancer Care (Engl) 2014; 23 716–20.
| How well is the National Cervical Screening Program performing for Indigenous Australian women? Why we don’t really know, and what we can and should do about it.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC2M7jtVCltQ%3D%3D&md5=b04590a0d06fa87221cff86019f63cceCAS |
[23] Mitchell RJ, Cameron CM, McClure RJ, Williamson AM. Data linkage capabilities in Australia: practical issues identified by a Population Health Research Network ‘proof of concept project’. Aust N Z J Public Health 2015; 39 319–25.
| Data linkage capabilities in Australia: practical issues identified by a Population Health Research Network ‘proof of concept project’.Crossref | GoogleScholarGoogle Scholar | 25716143PubMed |
[24] Xafis V, Thomson C, Braunack-Mayer AJ, Duszynski KM, Gold MS. Legal impediments to data linkage. J Law Med 2011; 19 300–15.
| 1:STN:280:DC%2BC383hvF2gtA%3D%3D&md5=06e897c35c77c6b02997146dc58e5aafCAS | 22320005PubMed |
[25] Nadathur SG. Maximising the value of hospital administrative datasets. Aust Health Rev 2010; 34 216–23.
| Maximising the value of hospital administrative datasets.Crossref | GoogleScholarGoogle Scholar | 20497736PubMed |
[26] Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 2009; 151 264–9.
| Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.Crossref | GoogleScholarGoogle Scholar | 19622511PubMed |
[27] Population Health Research Network. Annual review 2011/2012. Perth: Population Health Research Network Program Office; 2013. Available at: http://www.phrn.org.au/media/80633/annual-report-2011v10.pdf [verified 1 February 2016].
[28] Population Health Research Network. Annual review 2012/2013. 2014. Available at: http://www.phrn.org.au/media/80631/annual-report-201213v2.pdf [verified 1 February 2016].
[29] Davies SB, Hofer A, Reeve C. Mortality attributable to rheumatic heart disease in the Kimberley: a data linkage approach. Intern Med J 2014; 44 1074–80.
| Mortality attributable to rheumatic heart disease in the Kimberley: a data linkage approach.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC2cbmsleqtA%3D%3D&md5=fc8c5adc47dcde11c2517085001d3461CAS | 25070793PubMed |
[30] Sundararajan V, Thrift AG, Phan TG, Choi PM, Clissold B, Srikanth VK. Trends over time in the risk of stroke after an incident transient ischemic attack. Stroke 2014; 45 3214–18.
| Trends over time in the risk of stroke after an incident transient ischemic attack.Crossref | GoogleScholarGoogle Scholar | 25256181PubMed |
[31] Moore HC, de Klerk N, Keil AD, Smith DW, Blyth CC, Richmond P, Lehmann D. Use of data linkage to investigate the aetiology of acute lower respiratory infection hospitalisations in children. J Paediatr Child Health 2012; 48 520–8.
| Use of data linkage to investigate the aetiology of acute lower respiratory infection hospitalisations in children.Crossref | GoogleScholarGoogle Scholar | 22077532PubMed |
[32] Howell SC, Wills RA, Johnston TC. Should diagnosis codes from emergency department data be used for case selection for emergency department key performance indicators? Aust Health Rev 2014; 38 38–43.
| Should diagnosis codes from emergency department data be used for case selection for emergency department key performance indicators?Crossref | GoogleScholarGoogle Scholar | 24308873PubMed |
[33] Mai Q, Holman CDAJ, Sanfilippo FM, Emery JD, Stewart LM. Do users of mental health services lack access to general practitioner services? Med J Aust 2010; 192 501–6.
| 20438420PubMed |
[34] Havard A, Jorm LR, Lujic S. Risk adjustment for smoking identified through tobacco use diagnoses in hospital data: a validation study. PLoS One 2014; 9 e95029
| Risk adjustment for smoking identified through tobacco use diagnoses in hospital data: a validation study.Crossref | GoogleScholarGoogle Scholar | 24736621PubMed |
[35] Lee YYC, Roberts CL, Jane Y, Dobbins T. Using hospital discharge data to identify incident pregnancy-associated cancers: a validation study. BMC Pregnancy Childbirth 2013; 13 37
| Using hospital discharge data to identify incident pregnancy-associated cancers: a validation study.Crossref | GoogleScholarGoogle Scholar |
[36] Chamberlain C, Fredericks B, McLean A, Davis B, Eades S, Stewart K, Reid CM. Gestational diabetes mellitus in far north Queensland, Australia, 2004 to 2010: midwives’ perinatal data most accurate source. Aust N Z J Public Health 2013; 37 556–61.
| Gestational diabetes mellitus in far north Queensland, Australia, 2004 to 2010: midwives’ perinatal data most accurate source.Crossref | GoogleScholarGoogle Scholar | 24892154PubMed |
[37] Australian Bureau of Statistics (ABS). NSW perinatal data collection (PDC). Canberra: ABS; 2011. Available at: http://www.abs.gov.au/ausstats/abs@.nsf/7d12b0f6763c78caca257061001cc588/43487e1fe03beaaeca25732c00192874!OpenDocument [verified 1 February 2016].
[38] Leigh A, Neill C. Do gun buybacks save lives? Evidence from panel data. Am Law Econ Rev 2010; 12 509–57.
| Do gun buybacks save lives? Evidence from panel data.Crossref | GoogleScholarGoogle Scholar |
[39] McKeon R, Alexander E, Brodaty H, Ferris B, Frazer I, Little M. Strategic review of health and medical research in Australia: better health through research. 2013. Available at: http://www.mckeonreview.org.au/downloads/Strategic_Review_of_Health_and_Medical_Research_Feb_2013-Final_Report.pdf [verified 1 February 2016].
[40] Victorian Auditor-General. Access to public sector information. 2015. Available at: http://www.audit.vic.gov.au/publications/20151210-Public-Sector-Info/20151210-Public-Sector-Info.pdf [verified 28 January 2016].
[41] Australian Government. Australian public service big data strategy. 2013. Available at: https://www.finance.gov.au/sites/default/files/Big-Data-Strategy.pdf [verified 1 February 2016].
