The objective of this study was to quantify the burden of musculoskeletal disorders (MSDs) on the Ontario health care system. Specifically, we examined the magnitude and costs of MSD-associated ambulatory physician care and hospital service use, considering different physician types (e.g. primary care, rheumatologists, orthopaedic surgeons) and hospital settings (e.g. emergency department (ED), day surgery, inpatient hospitalizations). Administrative health data were analyzed for fiscal year 2013/14 for adults aged 18+ years (N=10,841,302). Data sources included: Ontario Health Insurance Plan Claims History Database, which captures data on in- and out-patient physician services, Canadian Institute for Health Information (CIHI) Discharge Abstract Database, which records diagnoses and procedures associated with all inpatient hospitalizations, and CIHI National Ambulatory Care Reporting System, which captures data on all emergency department (ED) and day surgery encounters. Services associated with MSDs were identified using the single three digit International Classification of Diseases (ICD) version 9 diagnosis code provided on each physician service claim for outpatient physician visits and the “most responsible” ICD-10 diagnosis code recorded for hospitalizations, ED visits and day surgeries. Patient visit rates and numbers of patients and visits were tabulated according to care setting, patient age and sex, and physician specialty. Direct medical costs were estimated by care setting. Data were examined for all MSDs combined as well as specific diagnostic groupings, including a comprehensive list of both trauma and non-trauma related conditions. Overall, 3.1 million adult Ontarians (28.5%) made 8 million outpatient physician visits associated with MSDs in 2013/14. These included 5.6 million primary care visits, nearly 15% of all adult primary care visits in the province. MSDs accounted for 560,000, 12.3%, of all adult ED visits. Patient visit rates to the ED for non-trauma spinal conditions were the highest of all MSDs at 1032 per 100,000 population, accounting for 23% of all MSD-related ED visits. Osteoarthritis had the highest rate of inpatient hospitalization of all MSDs at 340 per 100,000 population, accounting for 42% of all MSD-related admissions. Total costs for MSD-related care were $1.6 billion, with 12.6% of costs attributed to primary care, 9.2% to specialist care, 8.6% to ED care, and 61.2% of total costs associated with inpatient hospitalizations. Costs due to ‘arthritis and related conditions’ as a group accounted for 40.1% of total MSD costs ($966 million). Costs due to non-trauma related spinal conditions accounted for 10.5% ($168 million) of total MSD costs. All trauma-related conditions (spine and non-spine combined) were responsible for 39.4% ($627 million) of total MSD costs. MSD-related imaging costs for patients who made physician visits for MSDs were $169 million. Including these costs yields a total of $1.8 billion. MSDs place a significant and costly burden on the health care system. As the population ages, it will be essential that health system planning takes into account the large and escalating demand for MSD care, both in terms of health human resources planning and the implementation of more clinically and cost effective models of care, to reduce both the individual and population burden

Although wait-times for hip fracture surgery have been linked to mortality and are being used as quality-of-care indicators worldwide, controversy exists about the duration of the wait that leads to complications. Our objective was to use new population-based wait-time data to emprically derive an optimal time window in which to conduct hip fracture surgery before the risk of complications increases. We used health administrative data from Ontario, Canada to identify hip fracture patients between 2009 and 2014. The main exposure was the time from hospital arrival to surgery (in hours). The primary outcome was mortality within 30 days. Secondary outcomes included a composite of mortality or other medical complications (MI, DVT, PE, and pneumonia) also within 30 days. Risk-adjusted cubic splines modeled the probability of each complication according to wait-time. The inflection point (in hours) when complications began to increase was used to define ‘early’ and ‘delayed’ surgery. To evaluate the robustness of this definition, outcomes amongst propensity-score matched early and delayed patients were compared using percent absolute risk differences (% ARDs, with 95% confidence intervals [CIs]). There were 42,230 patients who met entry criteria. Their mean age was 80.1 (±10.7) and the majority were female (70.5%). The risk of complications modeled by cubic splines consistently increased when wait-times were greater than 24 hours, irrespective of the complication considered. Compared to 13,731 propensity-score matched patients who received surgery earlier, 13,731 patients receiving surgery after 24 hours had a significantly higher risk of 30-day mortality (N=898 versus N=790, % ARD 0.79 [95% CI 0.23 to 1.35], p = .006) and the composite outcome (N=1,680 versus N=1,383, % ARD 2.16 [95% CI 1.43 to 2.89], p < .001). Overall, there were 14,174 patients (33.6%) who received surgery within 24 hours and 28,056 patients (66.4%) who received surgery after 24 hours. Increased wait-time was associated with a greater risk for 30-day mortality and other complications. The finding that a wait-time of 24 hours represents a threshold defining higher risk may inform existing hip fracture guidelines. Since two-thirds of patients did not receive surgery within this timeframe, performance improvement efforts that reduce wait-times are warranted

Purpose of Study. Discecomy is a common operation peformed for back pain at our hospital. We analysed the theatre register looking at demographic and health data for our patients to shed more light on this cases. Description of Methods. Entries in the spinal unit theatre registers from 2000–2012 were reviewed, and all patients undergoing discectomy for disc herniation recorded analysed regarding demographics and epidemiology. Summary Of Results. A total of 171 patients had operations in our theatres. Of these patients the large majority were females. The age distribution was 45 to 50 years. The lumbar spine was the commonest region operated, especially the lower lumbar spine. We had very low repeat operations from failed surgery or requiring herniation. Conclusion. Surgical registers are an important tool in understanding pathology in the communities we serve. We can track the type of patients treated and then plan appropriate intervention programmes. It also helps to follow-up patients and correlate outcomes, and we can use this data to correlate practices nationally and internationally. NO DISCLOSURES

Aims

Orthopaedic surgeries are complex, frequently performed procedures associated with significant haemorrhage and perioperative blood transfusion. Given refinements in surgical techniques and changes to transfusion practices, we aim to describe contemporary transfusion practices in orthopaedic surgery in order to inform perioperative planning and blood banking requirements.

Purpose. The prevention of a subsequent, contralateral hip fracture is targeted as an avoidable event in the elderly. Fall prevention and bone strengthening measures have met with limited success and the urgency of their effect is undetermined. Our objective was to evaluate the time to second hip fracture (the time between a first and a subsequent, contralateral fracture) in elderly patients, using a population-based administrative health data set. Method. The 58,286 records of persons older than 60 yrs and hospitalized for a hip fracture between 1985 and 2005 were obtained from a Provincial administrative health database. We excluded non-traumatic cases and identified the care episodes related to a subsequent hip fracture for each patient using unique identifiers. We used a 5 year “wash-out period” to avoid counting a second fracture as a first one. We calculated the proportion of first and second fractures and sex distribution over time (fiscal years) and quantified the time between first and second fracture, while correlating it to age, sex and fracture type. Results. Overall, 3,866 patients sustained a second hip fracture between 1990 and 2005; 3,119 (81%) were women, in contrast to 73% for primary fractures (chi-square =137.8, df=1, p<0.001). In 33% cases, the type of a subsequent fracture (transcervical vs pertrochanteric) was different from the first. The median time from first fracture was 3 years, 90% occurred by 9yrs. The age at the first fracture most influenced the time to second fracture. The median time (90th percentile in parentheses) between fractures decreased as patients got older and was 5 (13), 4 (10), 3 (7), 2 (5) years for patients who were correspondingly 60–69, 70–79, 80–89 and 90+ years old at first fracture. Conclusion. Among survivors of an initial hip fracture, the occurrence of a second hip fracture appears to affect a greater proportion of women than primary fractures. Our results identify the time frame which preventative interventions should target when aiming at reducing second hip fractures, that target being increasingly small (from 5 to 2 years) as patients age. This information identifies a time frame researchers must target as they seek new fracture prevention methods. In the shorter term however, these data could influence health administrators and policy makers as they decide to support one hip fracture prevention method over another

Aims

Healthcare systems have been rapidly restructured to meet COVID-19 demand. Clinicians are working to novel clinical guidelines, treating new patient cohorts and working in unfamiliar environments. Trauma and orthopaedics (T&O) has experienced cancellation of routine clinics and operating, with redistribution of the workload and human resources. To date, no studies have evaluated the mental health impact of these changes on the T&O workforce. We report the results of a novel survey on the impact of the pandemic on the mental health of our orthopaedic workforce and the contributory factors.