Dataset:
Evidence-based Processes and Outcomes of Care (EPOC): Improving services and outcomes for joint replacement patients

dc.date.accessioned 2021-11-26T10:34:11Z
dc.date.available 2021-11-26T10:34:11Z
dc.date.issued 2021 en_US
dc.description.abstract Dataset includes REDCap database and extract of this including compliance data generated using R code. Variables include 1681 variables for the broader study including details re site, surgeon, patient demographic and co-morbid health information, dates of surgery and follow up, surgical care data, antibiotic and VTE chemical and mechanical prophylaxis data, patient reported measures, details re surgical complications up to one year post surgery and health services utilisation data. en_US
dc.identifier.uri http://hdl.handle.net/1959.4/resource/collection/resdatac_521/1
dc.language English
dc.language.iso EN en_US
dc.rights CC-BY-ND en_US
dc.rights.uri https://creativecommons.org/licenses/by-nd/4.0/ en_US
dc.subject.other arthroscopy en_US
dc.subject.other joint replacement surgery en_US
dc.subject.other venous thromboembolism en_US
dc.subject.other infection en_US
dc.subject.other prophylaxis en_US
dc.subject.other clinical guidelines en_US
dc.title Evidence-based Processes and Outcomes of Care (EPOC): Improving services and outcomes for joint replacement patients en_US
dc.type Dataset en_US
dcterms.accessRights metadata only access
dcterms.accrualMethod Data were collected prospectively from patients and sites at key points prior to and following surgery. Data collected at sites were sent to the primary researchers via email, post or transported by the primary investigators (for some local sites). Paper data was stored in locked cabinets at the sites and offices of the investigators which are in a secure research facility. Electronic data received via email were stored in password protected data systems on secure health systems. Data were initially entered password-protected Microsoft Excel spread sheets; however, the size and complexity of the data was too great for Excel so a project specific secure REDCap (Vanderbilt University, 2017) online database was established that was managed through University of New South Wales (UNSW). Data sent by sites were reviewed for completeness as they were received and site coordinators contacted if any data was missing. An audit by researchers of 100% of the medical records of participating patients was undertaken prior to analyses to ensure missing data were minimised and to verify accuracy and completeness of data. The audit focused ensuring data regarding prophylaxis, history of co-morbid conditions and other relevant factors relevant to VTE and infection including previous VTE or resistant infections, allergy to drugs and cardiac conditions. We also verified the accuracy of complications included in the composite outcome during audits or by contacting surgeons, GP and other health providers. Data were entered into REDCap project specific database supported by UNSW. R language for statistical analysis and reporting was used to automatically generate compliance data. Compliance data were calculated from care data reported at baseline, acute and follow-up. Compliance was rated against the following guidelines: i. Therapeutic Guidelines: Antibiotics (2010) for the prevention of infection ii. National Health and Medical Research Council (NHMRC) Clinical Practice Guideline for the prevention of venous thromboembolism (VTE) for patients admitted to Australian hospitals (2009) Algorithms were developed to make decisions regarding whether the prophylaxis (care data) was compliant or consistent with the definitions and were able to take patient indications and contraindications for prophylaxis into account. An extract from the REDCap database was run through the R programme to determine compliance data. From this an excel spreadsheet was created. There are two spreadsheets used for analyses: The first includes the extract from R with all cases entered. The second extract only includes those patients with any followup data for whom compliance was calculated. The first extract is used to describe the larger sample, the second addresses the primary research questions. Data were analysed using SAS and SPSS. See also http://www.clinicaltrials.gov/. The Clinical trials registration number is ClinicalTrials.gov Identifier: NCT01899443. en_US
dcterms.rightsHolder Copyright 2021, Helen Badge en_US
dspace.entity.type Dataset en_US
unsw.accessRights.uri http://purl.org/coar/access_right/c_14cb
unsw.contributor.leadChiefInvestigator Harris, Ian en_US
unsw.contributor.researchDataCreator Naylor, Justine en_US
unsw.contributor.researchDataCreator Xuan, Wei en_US
unsw.contributor.researchDataCreator Badge, Helen en_US
unsw.coverage.temporalFrom 2013-06-01 en_US
unsw.coverage.temporalText Sites collected data at different times. Post acute data collection complications data were verified. After this refinements to the R coding meant progressive iterations of compliance data. A final version of the study data has been produced in two Excel files: the first including all eligible participants. The second including only those participants who participated in follow up and for whom compliance data has been generated. en_US
unsw.coverage.temporalTo 2018-10-31 en_US
unsw.description.contact Contact Helen Badge helen.badgehawke@gmail.com or Professor Ian Harris at ia1harris@gmail.com to request permission to access. en_US
unsw.description.storageplace Orthopaedic Department, Ingham Institute en_US
unsw.identifier.doi https://doi.org/10.26190/mddw-by48 en_US
unsw.isPublicationRelatedToDataset https://doi.org/10.1371/journal.pone.0180090 en_US
unsw.isPublicationRelatedToDataset https://doi.org/10.5694/mja16.01362 en_US
unsw.isPublicationRelatedToDataset https://doi.org/10.1177/2309499018802493 en_US
unsw.isPublicationRelatedToDataset https://doi.org/10.1177/2309499021992605 en_US
unsw.isPublicationRelatedToDataset https://doi.org/10.1007/s00167-019-05804-9 en_US
unsw.isPublicationRelatedToDataset https://doi.org/10.1371/journal.pone.0159799 en_US
unsw.isPublicationRelatedToDataset Clinical practice guideline compliance in orthopaedic surgery
unsw.relation.OriginalPublicationAffiliation Harris, Ian, Clinical Sch-Swest Syd Area He, Medicine & Health, en_US
unsw.relation.OriginalPublicationAffiliation Naylor, Justine, Clinical Sch-Swest Syd Area He, Medicine & Health, en_US
unsw.relation.OriginalPublicationAffiliation Xuan, Wei, Clinical Sch-Swest Syd Area He, Medicine & Health, en_US
unsw.relation.OriginalPublicationAffiliation Badge, Helen, Clinical Sch-Swest Syd Area He, Medicine & Health, en_US
unsw.relation.faculty Medicine & Health
unsw.relation.fundingAgency HCF Health and Medical Research Foundation, Whitlam Orthopaedic Research Centre en_US
unsw.relation.projectDesc Despite strong evidence for prevention of effective prophylaxis for VTE and deep infection after THR and TKR, it is unknown to what extent private and public service providers comply with recommended care practices and whether compliance with guidelines is associated with lower costs or better clinical and patient-centred outcomes. The primary research question is: Are practices that are not compliant with current clinical guidelines regarding VTE and antimicrobial prophylaxes after primary total hip or knee joint replacement associated with higher risk of surgical complications or worse patient outcomes? The hypothesis is that patient level compliance is related to the prevalence of a subsequent complication. The study will also address secondary research questions including: • Are practices that are not compliant with current clinical guidelines regarding prevention of VTE after primary total hip or knee joint replacement associated with higher risk of VTE events? • Are practices that are not compliant with current clinical guidelines regarding prevention of infection after primary total hip or knee joint replacement associated with higher risk of postoperative infections? Patients gave informed written consent prior to undergoing total primary hip or knee joint replacement surgery. Patients provided demographic and patient reported measures at baseline. Sites included 19 public and private Australian hospitals. Sites provided details of surgery and acute care. Follow up was completed via telephone by the researchers at 35, 90 and 365 days post surgery. Details of complications were verified. Compliance with guidelines was calculated from raw care data using computerised algorithms. en_US
unsw.relation.projectEndDate 2018-10-31 en_US
unsw.relation.projectStartDate 2012-11-02 en_US
unsw.relation.projectTitle Helen Badge en_US
unsw.relation.school Clinical School South West Sydney Area Health Service
unsw.relation.school Clinical School South West Sydney Area Health Service
unsw.relation.school Clinical School South West Sydney Area Health Service
unsw.relation.school Clinical School South West Sydney Area Health Service
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