Surgery (RMH) - Research Publications

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    Profile and Trends in Comorbidity for Patients Undergoing Hip and Knee Arthroplasty Using the Rx-Risk Measure with Pharmaceutical Dispensing Records
    Kerr, M ; Graves, SE ; Pratt, N ; Inacio, M ; Duszynski, K ; Gulyani, A ; De Steiger, R ; Harris, I ; Ackerman, I ; Jorm, L ; Lorimer, M (Swansea University, 2020-12-07)
    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.
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    Enhancing Joint Replacement Outcomes Through Registry Linkage with National Health Administrative Data in Australia
    Duszynski, K ; Graves, SE ; Pratt, N ; Inacio, M ; De Steiger, R ; Harris, I ; Ackerman, I ; Jorm, L ; Lorimer, M ; Gulyani, A (Swansea University, 2020-12-07)
    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.