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The Australian Orthopaedic Association National Joint Replacement Registry first began data collection on 1 September 1999 and full nationwide implementation commenced in January 2003. The purpose of the Registry is to improve the quality of care for individuals receiving joint replacement surgery. The Registry enables surgeons, academic institutions, governments and industry to request specific data that are not available in published annual reports. There is an established system for identifying prostheses with a higher than anticipated rate of revision (HTARR) which was introduced in 2004. The higher rate of revision for the ASR Hip Resurfacing System was first identified by this process in 2007. There has been a reduction in revision hip and knee replacement over the years that the Registry has been in operation, and the addition of Patient Reported Outcome Measures (PROMs) and data linkage will enable more extensive analysis of joint replacement surgery in the future. Cite this article: EFORT Open Rev 2019;4 DOI:10.1302/2058-5241.4.180071

IntroductionTo enhance the value of the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) we recently linked these data with administrative datasets including, Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Scheme (PBS). Understanding the validity of administrative data is important in establishing the reliability of these data for informing clinical practice and policy.
Objectives & ApproachThe study objective was to determine the validity of MBS data for capturing the occurrence of a joint replacement procedure. Using the AOANJRR procedures as the gold standard, we determined the sensitivity of the MBS data in correctly identifying hip joint replacement procedures.
ResultsOf the 178,047 patients with a single primary total hip replacement occurring in a private hospital setting and recorded in the AOANJRR, 76% had a same-day MBS service claim indicative of that procedure, 2% had MBS procedures within +/- 7 days of the procedure while 18% had no MBS procedure codes indicative of a total hip joint replacement procedure. Of the procedures with no total hip MBS codes, 2% had MBS procedures codes indicating a total knee procedure, 1.7% had MBS procedure codes indicating a revision hip on that day and 13% of procedures had an in-hospital MBS hip anaesthetic administration code claimed on that day.
Conclusion / ImplicationsGiven the increasing application of MBS data to describe health service use it is important to understand the validity of these data for identifying procedures undertaken in the private hospital setting. Using validated, gold standard data captured by the AOANJRR we identified that MBS data likely underestimate the occurrence of total hip replacement procedures. In addition, some MBS procedure codes are misattributed to other procedure types such as knee procedures and revision procedures.

IntroductionMonitoring of joint replacement (JR) data from the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) has reduced revision rates and improved surgical practice. Outcome assessment post-arthroplasty is limited however, to revision (reoperation) surgery and mortality outcomes. The AOANJRR National Data Linkage project seeks to broaden the scope of outcomes investigation in Australia by linking registry and health administrative datasets.
Objectives and ApproachUsing linked registry and administrative data, the project seeks to describe and quantify national/regional trends and variation in major complications (infection, dislocation, arthrofibrosis, chronic pain, venous thromboembolism, cardiac events), malignancy and health service utilisation (readmissions, emergency encounters and inpatient rehabilitation) following hip, knee and shoulder joint replacement surgery. Evidence will be generated on how these outcomes are associated with and vary according to patient, surgical, implant, hospital and pharmacological factors.
As Australia lacks a national identifier, seven linkage agencies are probabilistically linking AOANJRR hip, knee and shoulder replacement data (1999-2017) with 20 datasets. Datasets include government-subsidised health services, procedural and prescription data. Hospital separations and emergency attendance data from Australia's eight jurisdictions together with national cancer registry and rehabilitation service data are also planned for linkage. Linked data are maintained in a secure remote access computing environment.
ResultsTo date, national Medicare Benefits Schedule, Pharmaceutical Benefits Scheme and the Australian Cancer Database data have been linked with >900,000 AOANJRR patients, representing 607.6 million health service records (1999-2018), 467.7 million prescriptions (2002-2018) and 184,000 cancer records, respectively. Remaining linked data will be available in mid-2020. Some initial summary results across a selected range of studies will be presented.
Conclusion / ImplicationsThis national data-linkage program will identify areas for improvement in joint replacement surgery and modifiable risk factors contributing to poor patient outcomes.

IntroductionPatient comobidity at time of primary joint replacement (JR) impacts on outcomes including revision and mortality. Understanding changes in comorbidity profiles is important when assessing change in outcomes over time. Most arthroplasty registries have limited comorbidity information due to their minimum dataset. One approach to obtaining additional comorbidity data is linking registry data with national administrative data.
Objectives and ApproachObjectives were to quantify pre-operative comorbidity profile of patients undergoing primary total hip replacement (THR) and total knee replacement (TKR) for osteoarthritis. Also, to examine temporal trends in individual comorbidities for THR and TKR patients.
National pharmaceutical dispensing data were linked with THR and TKR arthroplasty patients. Medication dispensing histories in 12-months preceding JR (2003-2017) for 237,333 THR and 394,965 TKR patients, were mapped to 47 comorbidity classes using the Rx-Risk-V measure - a pharmacy-based measure of comorbidity. Comorbidity scores were calculated by summing comorbidity categories for individual patients. Trends in comorbidity scores/categories were described, with comorbidity information presented by PBS beneficiary category (concessional/general), stratified by age (<65/≥65 years).
ResultsMedian (interquartile range) comorbidity scores were higher in concessional patients ≥65y, THR:5(3-6), TKR:5(3-7); <65y,TKR:5(3-6) but not THR:4(2-6). Comparative scores for general patients (both ages) were THR:4(2-6) and TKR:3(2-5). Trends in median comorbidity scores were consistent across study period, THR:4- 5(concessional)/2-3(general) and TKR:4-5(concessional)/4(general). Commonly identified comorbidities in younger concessional THR patients were pain, measured by opioid use (62.4%), inflammation/pain, measured by use of non-steroidal anti-inflammatories (62.2%), GORD (36.2%) and hypertension (36.1%). Individual comorbidities remained generally stable over time. However, increased patient proportions were seen in THR concessionals <65y for opioid pain (59.1%-71.1%), depression (24.5-42.5%), whilst inflammation/pain (82.1-56.1%) and antiplatelet use (≥65y:23.5-9.2%) declined.
Conclusion / Implicationsn THR or TKR patients no appreciable change in comorbidity score or comorbidity profile occurred over time. This suggests that improving JR outcomes over time are unlikely due solely to variation in patient comorbidity profiles.

IntroductionInfection is a major complication following joint replacement (JR) surgery. However, little data exist on baseline use of antibiotics following primary JR and how use changes with subsequent revision surgery.
Objectives & ApproachOur study objectives were to describe community use of antibiotics before and after primary total hip replacement (THR) and change in use pre and post revision procedure.
Registry data were linked with national medication dispensing data using probabilistic record linkage. Patients with THR for osteoarthritis in a private hospital between 1999 and 2017 were included. Three groups were analysed: patients with primary procedures revised for infection, revised for non-infection reasons and those not revised. Rate of antibiotic dispensing/month was calculated as number of patients dispensed at least one antibiotic in a given month divided by number of patients at-risk.
ResultsThere were 102,577 patients included in the non-revised group, 3,156 revised for non-infection and 520 revised for infection. Prior to primary THR, baseline antibiotic dispensing rate was 9-11%/month in all groups. Post-primary rates were similar (10-11%) for non-revised and revised non-infection patients but higher (16-17%) for revised-infection patients. In 1, 6 and 12 months preceding revision for infection, antibiotic use was 55%, 27% and 22%, respectively. For patients revised for non-infection, antibiotic use was 21%, 14%, 13%, respectively. One-month following revision for infection, 82% of patients were dispensed antibiotics, remaining high (38%) at 6-months and 28% at 12-months. In the revision non-infection group, antibiotic use was 48% first month post-surgery, reducing rapidly to 15% at 6-months.
Conclusion / ImplicationsNon-revision and revision non-infection patients had similar antibiotic dispensing before and after surgery. Revision infection patients however, maintained higher antibiotic dispensing post-primary, pre and post revision. This may reflect either ongoing infection, need for long-term suppressive therapy or reluctance of treating physicians to terminate treatment.