In an effort to reduce hospital length of stay (LoS) following total knee arthroplasty (TKA), patient management strategies have evolved over time. The aims of this study were threefold: first, to quantify the reduction in LoS for TKA in a regional hospital; second, to identify the patient, surgical and management factors associated with hospital LoS; and lastly, to assess the change in complications incidence and hospital readmission as a function of LoS. A retrospective chart review was conducted on a consecutive series of primary and revision TKAs from January 2012 to March 2018. Factors describing patient demographics, as well as preoperative, intraoperative, surgical, and postoperative management, were extracted from paper and electronic medical records by a team of reviewers. Multivariate linear regression was performed to assess the association between these factors and LoS. In total, 362 procedures were included, which were reduced to 329 admissions once simultaneous bilateral procedures were taken into account. Median LoS reduced significantly (p = 0.001) from 6 to 2 days over the period of review. A stepwise regression analysis identified patient characteristics (age, gender, comorbidities, discharge barriers), perioperative management (anesthesia type), surgical characteristics (approach, alignment method), and postoperative management (mobilization timing, postoperative narcotic use, complication prior to discharge) as factors explaining 58.3% of the variance in LoS. Representation to emergency (6%) and hospital readmission (3%) remained low for the reviewed period. Efforts to reduce hospital LoS following TKA within a regional hospital setting can be achieved over time without significant increases in the rate or severity of complications or representation to acute care and subsequent readmission. The findings establish the role of patient, surgical and management factors in the context of agreed discharge criteria between care providers.

Background The aim of this study was to demonstrate a novel method of assessing data quality for an orthopaedic registry and its effects on data quality metrics. Methods A quality controlled clinical patient registry was implemented, comprising six observational cohorts of shoulder and knee pathologies. Data collection procedures were co-developed with clinicians and administrative staff in accordance with the relevant dataset and organised into the registry database software. Quality metrics included completeness, consistency and validity. Data were extracted at scheduled intervals (3 months) and quality metrics reported to stakeholders of the registry. Results The first patient was enrolled in July 2017 and the data extracted for analysis over 4 quarters, with the last audit in August 2018 (N = 189). Auditing revealed registry completeness was 100% after registry deficiencies were addressed. However, cohort completeness was less accurate, ranging from 12 to 13% for height & weight to 90–100% for operative variables such as operating surgeon, consulting surgeon and hospital. Consistency and internal validation improved to 100% after issues in registry processes were rectified. Conclusions A novel method to assess data quality in a clinical orthopaedic registry identified process shortfalls and improved data quality over time. Real-time communication, a comprehensive data framework and an integrated feedback loop were necessary to ensure adequate quality assurance. This model can be replicated in other registries and serve as a useful quality control tool to improve registry quality and ensure applicability of the data to aid clinical decisions, especially in newly implemented registries. Trial registration ACTRN12617001161314; registration date 8/08/2017. Retrospectively registered.