Baseline Analysis of Patients Presenting for Surgical Review of Anterior Cruciate Ligament Rupture Reveals Heterogeneity in Patient-Reported Outcome Measures.

Despite the establishment of successful surgical techniques and rehabilitation protocols for anterior cruciate ligament (ACL) reconstruction, published return to sport rates are less than satisfactory. This has led orthopaedic surgeons and researchers to develop more robust patient selection methods, and investigate prognostic patient characteristics. No previous studies have integrated baseline characteristics and responses to patient-reported outcome measures (PROMs) of patients with ACL rupture presenting for surgical review. Patients electing to undergo ACL reconstruction under the care of a single orthopaedic surgeon at a metropolitan public hospital were enrolled in a clinical quality registry. Patients completed Veterans RAND 12-item Health Survey (VR-12) Physical Component Summary and Mental Component Summary scores, Tegner activity scale, and International Knee Documentation Committee (IKDC) questionnaires at presentation. Total scores were extracted from the electronic registry, and a machine learning approach (k-means) was used to identify subgroups based on similarity of questionnaire responses. The average scores in each cluster were compared using analysis of variance (ANOVA; Kruskal-Wallis) and nominal logistic regression was performed to determine relationships between cluster membership and patient age, gender, body mass index (BMI), and injury-to-examination delay. A sample of 107 patients with primary ACL rupture were extracted, with 97 (91%) available for analysis with complete datasets. Four clusters were identified with distinct patterns of PROMs responses. These ranged from lowest (Cluster 1) to highest scores for VR-12 and IKDC (Cluster 4). In particular, Cluster 4 returned median scores within 6 points of the patient acceptable symptom state for the IKDC score for ACL reconstruction (70.1, interquartile range: 59-78). Significant (p < 0.05) differences in PROMs between clusters were observed using ANOVA, with variance explained ranging from 40 to 69%. However, cluster membership was not significantly associated with patient age, gender, BMI, or injury-to-examination delay. Patients electing to undergo ACL reconstruction do not conform to a homogenous group but represent a spectrum of knee function, general physical and mental health, and preinjury activity levels, which may not lend itself to uniform treatment and rehabilitation protocols. The factors driving these distinct responses to PROMs remain unknown but are unrelated to common demographic variables.

Implementation and quality assessment of a clinical orthopaedic registry in a public hospital department.

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.