Aims. Due to widespread cancellations in elective orthopaedic procedures, the number of patients on waiting list for surgery is rising. We aim to determine and quantify if disparities exist between inpatient and day-case orthopaedic waiting list numbers; we also aim to determine if there is a ‘hidden burden’ that already exists due to reductions in elective secondary care referrals. Methods. Retrospective data were collected between 1 April 2020 and 31 December 2020 and compared with the same nine-month period the previous year. Data collected included surgeries performed (day-case vs inpatient), number of patients currently on the orthopaedic waiting list (day-case vs inpatient), and number of new patient referrals from primary care and therapy services. Results. There was a 52.8% reduction in our elective surgical workload in 2020. The majority of surgeries performed in 2020 were day case surgeries (739; 86.6%) with 47.2% of these performed in the independent sector on a ‘lift and shift’ service. The total number of patients on our waiting lists has risen by 30.1% in just 12 months. As we have been restricted in performing inpatient surgery, the inpatient waiting lists have risen by 73.2%, compared to a 1.6% rise in our day-case waiting list. New patient referral from primary care and therapy services have reduced from 3,357 in 2019 to 1,722 in 2020 (49.7% reduction). Conclusion. This study further exposes the increasing number of patients on orthopaedic waiting lists. We observed disparities between inpatient and day-case waiting lists, with dramatic increases in the number of inpatients on the waiting lists. The number of new patient referrals has decreased, and we predict an influx of referrals as the pandemic eases, further adding to the pressure on inpatient waiting lists. Robust planning and allocation of adequate resources is essential to deal with this backlog. Cite this article: Bone Jt Open 2021;2(7):530–534

Data from the wait list management system and hospital databases was used to develop a computer model simulating the resource requirements required during patient flow into, through, and out of orthopaedic surgery for TKR, THR and knee arthroscopy. Results from the simulation model suggested that inpatient beds, rather than operating room time was the constraining resource and an extra twenty-five beds and 30% more OR time would stabilize and subsequently reduce the wait time at the institution. In addition, simulations suggested that pooling surgeon wait lists reduced patient wait time. Simulation models are an effective resource allocation decision-making tool for orthopaedic surgery. To develop and implement a wait list simulation model to analyze the existing system and guide resource allocation decision-making at the QEII Health Sciences Centre. The simulation model suggests an immediate increase in inpatient surgical beds from sixty-six to ninety-one followed by a 30% increase in OR time in thirty months to stabilize and subsequently reduce patient wait times. Simulations showed that pooling surgeon waiting lists reduced patient wait time, however, dividing orthopaedics resources among two facilities had little effect. Adding twenty-five beds reduced the wait time growth rate substantially, but not to zero, while adding fifty beds reduced the wait time growth rate to zero. Adding twenty-five beds and 30% more OR time had the same result as adding fifty beds. Simulation models can be effective for guiding resource allocation decisions for orthopaedic surgery. Recommendations based on the wait list simulation model results were immediately adopted by the provincial Department of Health. A simulation model of the orthopaedic surgery system at the institution was created using Arena simulation software. Empirical statistical distributions were developed based on Wait List Management System and administrative data to assign values to model variables: number of patient referrals seen per office session; proportion of patient referrals actually converting to a surgery booking; type of procedure required; admission status; time required for surgery; and length of stay. The model was tested, and validated. Several scenarios with adjusted levels of resources variables (OR time, number of surgeons, length of stay, inpatient bed availability) were simulated

A centralized wait list management system (WLMS) for TKR, THR and knee arthroscopy was developed to collect accurate data on parameters of patients’ wait for surgery. A priority metric rating patient priority was implemented. Data from hospital enterprise systems related to aspects of patients’ wait for surgery was collected and imported. Patients’ functional status was significantly worse than population norms, they were adversely affected while waiting and are unsatisfied with their access to surgery. Traffic ratios (ratio of booked to completed surgeries) exceed the maximum value for a stable wait list and the waits for surgery exceed national and international recommendations for maximum wait-times. To develop and implement a WLMS for TKR, THR and knee arthroscopy to enable the accurate and efficient collection of data on size of list, rate of list growth, rate surgeries are performed, health and functional status of patients, and surgeon rated priority. Patients are adversely affected while waiting and are unsatisfied with the length of their wait. Traffic ratios exceed the maximum value for a stable waitlist. The priority metric has face validity for rating patient acuity. SF36 and WOMAC scores were three to four standard deviations worse than the population norm, over 50% of patients felt wait time would negatively affect outcome, 80% felt waits should be twelve months or less, and over 50% were unsatisfied with access to surgery. VAS scores were normally distributed with good face validity. Wait times are one hundred and thirty to three hundred days for arthroplasty and ninety to four hundred days for arthroscopy. Traffic ratios are 0.9 for arthroplasty and 1.5 for arthroscopy. Prospective outcomes with respect to the wait list will allow determination of minimum acceptable wait times from administrative, surgeon and patient perspectives. Accurate and reliable collection of wait list data provides a sound basis for future decision-making. Surgery bookings were centralized. A priority metric based on a visual analog scale (VAS) with a single question asking the surgeon to rate the patient priority was implemented. A cross-sectional postal survey was conducted. Data from hospital enterprise systems related to aspects of patients’ wait for surgery was collected and imported into the WLMS

A centralized wait list management system (WLMS) for TKR, THR and knee arthroscopy was developed to collect accurate data on parameters of patients’ wait for surgery. A priority metric rating patient priority was implemented. Data from hospital enterprise systems related to aspects of patients’ wait for surgery was collected and imported. Patients’ functional status was significantly worse than population norms, they were adversely affected while waiting and are unsatisfied with their access to surgery. Traffic ratios (ratio of booked to completed surgeries) exceed the maximum value for a stable wait list and the waits for surgery exceed national and international recommendations for maximum wait-times. To develop and implement a WLMS for TKR, THR and knee arthroscopy to enable the accurate and efficient collection of data on size of list, rate of list growth, rate surgeries are performed, health and functional status of patients, and surgeon rated priority. Patients are adversely affected while waiting and are unsatisfied with the length of their wait. Traffic ratios exceed the maximum value for a stable waitlist. The priority metric has face validity for rating patient acuity. SF36 and WOMAC scores were three to four standard deviations worse than the population norm, over 50% of patients felt wait time would negatively affect outcome, 80% felt waits should be twelve months or less, and over 50% were unsatisfied with access to surgery. VAS scores were normally distributed with good face validity. Wait times are one hundred and thirty to three hundred days for arthroplasty and ninety to four hundred days for arthroscopy. Traffic ratios are 0.9 for arthroplasty and 1.5 for arthroscopy. Prospective outcomes with respect to the wait list will allow determination of minimum acceptable wait times from administrative, surgeon and patient perspectives. Accurate and reliable collection of wait list data provides a sound basis for future decision-making. Surgery bookings were centralized. A priority metric based on a visual analog scale (VAS) with a single question asking the surgeon to rate the patient priority was implemented. A cross-sectional postal survey was conducted. Data from hospital enterprise systems related to aspects of patients’ wait for surgery was collected and imported into the WLMS

Aims

The primary aim was to assess whether preoperative health-related quality of life (HRQoL) was associated with postoperative mortality following total hip arthroplasty (THA) and knee arthroplasty (KA). Secondary aims were to assess whether patient demographics/comorbidities and/or joint-specific function were associated with postoperative mortality.

Aims. The primary aim is to estimate the current and potential number of patients on NHS England orthopaedic elective waiting lists by November 2020. The secondary aims are to model recovery strategies; review the deficit of hip and knee arthroplasty from National Joint Registry (NJR) data; and assess the cost of returning to pre-COVID-19 waiting list numbers. Methods. A model of referral, waiting list, and eventual surgery was created and calibrated using historical data from NHS England (April 2017 to March 2020) and was used to investigate the possible consequences of unmet demand resulting from fewer patients entering the treatment pathway and recovery strategies. NJR data were used to estimate the deficit of hip and knee arthroplasty by August 2020 and NHS tariff costs were used to calculate the financial burden. Results. By November 2020, the elective waiting list in England is predicted to be between 885,286 and 1,028,733. If reduced hospital capacity is factored into the model, returning to full capacity by November, the waiting list could be as large as 1.4 million. With a 30% increase in productivity, it would take 20 months if there was no hidden burden of unreferred patients, and 48 months if there was a hidden burden, to return to pre-COVID-19 waiting list numbers. By August 2020, the estimated deficits of hip and knee arthroplasties from NJR data were 18,298 (44.8%) and 16,567 (38.6%), respectively, compared to the same time period in 2019. The cost to clear this black log would be £198,811,335. Conclusion. There will be up to 1.4 million patients on elective orthopaedic waiting lists in England by November 2020, approximate three-times the pre-COVID-19 average. There are various strategies for recovery to return to pre-COVID-19 waiting list numbers reliant on increasing capacity, but these have substantial cost implications. Cite this article: Bone Jt Open 2021;2(2):103–110

Aims. The aim of this study was to assess the quality of life of patients on the waiting list for a total hip (THA) or knee arthroplasty (KA) during the COVID-19 pandemic. Secondary aims were to assess whether length of time on the waiting list influenced quality of life and rate of deferral of surgery. Methods. During the study period (August and September 2020) 843 patients (THA n = 394, KA n = 449) from ten centres in the UK reported their EuroQol five dimension (EQ-5D) scores and completed a waiting list questionnaire (2020 group). Patient demographic details, procedure, and date when listed were recorded. Patients scoring less than zero for their EQ-5D score were defined to be in a health state “worse than death” (WTD). Data from a retrospective cohort (January 2014 to September 2017) were used as the control group. Results. The 2020 group had a significantly worse EQ-5D score compared to the control group for both THA (p < 0.001) and KA (p < 0.001). Over one-third (35.0%, n = 138/394) of patients waiting for a THA and nearly a quarter (22.3%, n = 100/449) for KA were in a health state WTD, which was significantly greater than the control group (odds ratio 2.30 (95% confidence interval (CI) 1.83 to 2.93) and 2.08 (95% CI 1.61 to 2.70), respectively; p < 0.001). Over 80% (n = 680/843) of the 2020 group felt that their quality of life had deteriorated while waiting. Each additional month spent on the waiting list was independently associated with a decrease in quality of life (EQ-5D: -0.0135, p = 0.004). There were 117 (13.9%) patients who wished to defer their surgery and the main reason for this was health concerns for themselves and or their family (99.1%, n = 116/117). Conclusion. Over one-third of patients waiting for THA and nearly one-quarter waiting for a KA were in a state WTD, which was approaching double that observed prior to the pandemic. Increasing length of time on the waiting list was associated with decreasing quality of life. Level of evidence: Level III retrospective case control study. Cite this article: Bone Joint J 2021;103-B(4):672–680

Aims. The aim of this study was to report health-related quality of life (HRQoL) and joint-specific function in patients waiting for total hip or knee arthroplasty surgery (THA or TKA) in Northern Ireland, compared to published literature and a matched normal population. Secondary aims were to report emergency department (ED) and out-of-hours general practitioner (OOH GP) visits, new prescriptions of strong opioids, and new prescriptions of antidepressants while waiting. Methods. This was a cohort study of 991 patients on the waiting list for arthroplasty in a single Northern Ireland NHS trust: 497 on the waiting list for ≤ three months; and 494 waiting ≥ three years. Postal surveys included the EuroQol five-dimension five-level questionnaire (EQ-5D-5L), visual analogue scores (EQ-VAS), and Oxford Hip and Knee scores to assess HRQoL and joint-specific function. Electronic records determined prescriptions since addition to the waiting list and patient attendances at OOH GP/EDs. Results. Overall, 712/991 (71.8%) responded at ≤ three months for THA (n = 164) and TKA (n = 199), and ≥ three years for THA (n = 88) and TKA (n = 261). The median EQ-5D-5L score in those waiting ≤ three months was 0.155 (interquartile range (IQR) -0.118 to 0.375) and 0.189 (IQR -0.130 to 0.377) for ≥ three years. Matched controls had a median EQ-5D-5L 0.837 (IQR 0.728 to 1.000). Compared to matched controls, EQ-5D-5L scores were significantly lower in both waiting cohorts (p < 0.001) with significant differences found in every domain. Negative scores, indicating a state “worse than death”, were present in 40% at ≤ three months and 38% at ≥ three years. Patients waiting ≥ three years had significantly more opioid (28.4% vs 15.2%; p < 0.001) and antidepressant prescriptions (15.2% vs 9.9%; p = 0.034) and significantly more joint-related attendances at unscheduled care (11.7% vs 0% with ≥ one ED attendance (p < 0.001) and (25.5% vs 2.5% ≥ one OOH GP attendance (p < 0.001)). Conclusion. Patients on waiting lists in Northern Ireland are severely disabled with the worst HRQoL and functional scores studied. The lack of deterioration in EQ-5D-5L and joint-specific scores between patients waiting ≤ three months and ≥ three years likely reflects floor effects of these scores. Prolonged waits were associated with increased dependence on strong opiates, depression, and attendances at unscheduled care. Cite this article: Bone Joint J 2023;105-B(7):783–794

Purpose/Background. More than 20 million UK citizens have MSK conditions, and post-pandemic the backlog awaiting access to MSK services has increased. The most prevalent MSK condition is low back pain (LBP), and getUBetter has been recommended by NICE as one of five digital health technologies for helping manage LBP. Purpose: Evaluate impact of getUBetter on a community MSK waiting list. Methods/Results. Mixed methods approach used. All patients on community MSK waiting list sent a postal invite for getUBetter. Number of downloads and frequency of use recorded, and users emailed questionnaire exploring outcomes and satisfaction. Rate users removed themselves from the waiting list compared with non-users. Of 14,500 invitations, 657(4.5%) patients downloaded getUBetter, 395(60.1%) used it once and 138(21%) ≥3 times. Seventeen (7%) of 239 patients canvassed responded to questionnaire, 17% reported improved pain, 21% reported improved confidence and had been helped back to work. Twenty-five percent better understood their condition and 43% needed no other treatment. Seventy-five percent were critical of limited content, with chronic osteoarthritis mentioned. 69.6% of users removed themselves from the waiting list. This was 29.6% above the rate for non-users. Conclusion. Sending postal invites for getUBetter to a MSK waiting list yielded limited uptake. However, despite some criticisms, patients using it reported improved pain, early return to usual activities, and improved confidence in self-management. Some patients recovered without the need for additional support and getUBetter shows some potential for reducing a MSK waiting list. Clearly further work is required to explore methods to increase patient uptake and maximise impact. Conflicts of interest. None. Sources of funding. None

Aim

Restarting elective services presents a challenge to restore and improve many of the planned patient care pathways which have been suspended during the response to the COVID-19 pandemic. A significant backlog of planned elective work has built up representing a considerable volume of patient need. We aimed to investigate the health status, quality of life, and the impact of delay for patients whose referrals and treatment for symptomatic joint arthritis had been delayed as a result of the response to COVID-19.

Aim. To investigate the impact of waiting for surgical treatment for bone and joint infection (BJI) on patient self-reported quality of life (QoL). Method. Patients presenting to clinic between January 2019 and February 2020 completed the EuroQol EQ-5D-5L questionnaire. Patients were divided into three groups: surgery performed; on the waiting list for surgery; or decision for non-operative management. All patients were followed-up for 2 years. The EQ-index score was calculated and change from presentation to 1-year and 2-year follow-up was compared across the 3 groups. Mortality at final follow-up was measured in all groups. Results. 188 patients were included. Of these, 98 had an operation performed, 50 were on the waiting list for surgery but did not receive an operation and 40 were treated non-operatively. At presentation, all three groups had similar EQ-5D-5L index scores (surgery:0.412 SD0.351; waiting list:0.510 SD0.320; non-operative management: 0.467 SD0.354; p=0.269). There was a significant improvement in QoL in patients who underwent surgery when compared to their pre-operative state (mean increase of EQ-index score +0.241 in the first year (SD0.333, p<0.001) and +0.259 (SD0.294, p<0.001) in the second year. Patients on the waiting list for surgery had a small time-dependent decrease in EQ-index score at 1 year (−0.077, SD0.282, p=0.188) and 2 years (−0.140, SD0.359, p=0.401). Patients treated non-operatively had similar changes in EQ-index scores at 1 year (−0.052, SD0.309, p=0.561) and 2 years (−0.146, SD 0.234, p=0.221). Patients who had surgery had significantly better QoL at 2-years after treatment compared to other groups (mean EQ-index scores: surgery performed 0.671 vs. waiting list 0.431, p<0.001; surgery performed vs. non-operative management 0.348, p<0.001). Mortality in the operated group was 3.1%, which was similar to patients who were on the waiting list for surgery (6.5%, p=0.394) but lower than patients who were non-operatively managed (14.7%, p=0.014). Conclusions. The Covid-19 pandemic created long waiting times for some patients. Selecting patients with BJI who can safely wait for surgery is difficult. QoL for patients with BJI deteriorates over time if surgery is delayed or not performed. When patients decline surgery, they should be counselled that their QoL is likely to be impaired over time. The relationship between waiting time and mortality merits further study

Aims. COVID-19 has compounded a growing waiting list problem, with over 4.5 million patients now waiting for planned elective care in the UK. Views of patients on waiting lists are rarely considered in prioritization. Our primary aim was to understand how to support patients on waiting lists by hearing their experiences, concerns, and expectations. The secondary aim was to capture objective change in disability and coping mechanisms. Methods. A minimum representative sample of 824 patients was required for quantitative analysis to provide a 3% margin of error. Sampling was stratified by body region (upper/lower limb, spine) and duration on the waiting list. Questionnaires were sent to a random sample of elective orthopaedic waiting list patients with their planned intervention paused due to COVID-19. Analyzed parameters included baseline health, change in physical/mental health status, challenges and coping strategies, preferences/concerns regarding treatment, and objective quality of life (EuroQol five-dimension questionnaire (EQ-5D), Generalized Anxiety Disorder 2-item scale (GAD-2)). Qualitative analysis was performed via the Normalization Process Theory. Results. A total of 888 patients responded. Better health, pain, and mood scores were reported by upper limb patients. The longest waiters reported better health but poorer mood and anxiety scores. Overall, 82% had tried self-help measures to ease symptoms; 94% wished to proceed with their intervention; and 21% were prepared to tolerate deferral. Qualitative analysis highlighted the overall patient mood to be represented by the terms ‘understandable’, ‘frustrated’, ‘pain’, ‘disappointed’, and ‘not happy/depressed’. COVID-19-mandated health and safety measures and technology solutions were felt to be implemented well. However, patients struggled with access to doctors and pain management, quality of life (physical and psychosocial) deterioration, and delay updates. Conclusion. This is the largest study to hear the views of this ‘hidden’ cohort. Our findings are widely relevant to ensure provision of better ongoing support and communication, mostly within the constraints of current resources. In response, we developed a reproducible local action plan to address highlighted issues. Cite this article: Bone Jt Open 2021;2(8):583–593

Aims. The overall aim of this study was to determine the impact of deprivation with regard to quality of life, demographics, joint-specific function, attendances for unscheduled care, opioid and antidepressant use, having surgery elsewhere, and waiting times for surgery on patients awaiting total hip arthroplasty (THA) and total knee arthroplasty (TKA). Methods. Postal surveys were sent to 1,001 patients on the waiting list for THA or TKA in a single Northern Ireland NHS Trust, which consisted of the EuroQol five-dimension five-level questionnaire (EQ-5D-5L), visual analogue scores (EQ-VAS), and Oxford Hip and Knee Scores. Electronic records determined prescriptions since addition to the waiting list and out-of-hour GP and emergency department attendances. Deprivation quintiles were determined by the Northern Ireland Multiple Deprivation Measure 2017 using postcodes of home addresses. Results. Overall, 707 postal surveys were returned, of which 277 (39.2%) reported negative “worse than death” EQ-5D scores and 219 (21.9%) reported the consumption of strong opioids. Those from the least deprived quintile 5 had a significantly better EQ-5D index (median 0.223 (interquartile range (IQR) -0.080 to 0.503) compared to those in the most deprived quintiles 1 (median 0.049 (IQR -0.199 to 0.242), p = 0.004), 2 (median 0.076 (IQR -0.160 to 0.277; p = 0.010), and 3 (median 0.076 (IQR-0.153 to 0.301; p = 0.010). Opioid use was significantly greater in the most deprived quintile 1 compared to all other quintiles (45/146 (30.8%) vs 174/809 (21.5%); odds ratio 1.74 (95% confidence interval 1.18 to 2.57; p = 0.005). Conclusion. More deprived patients have worse health-related quality of life and greater opioid use while waiting for THA and TKA than more affluent patients. For patients awaiting surgery, more information and alternative treatment options should be available. Cite this article: Bone Jt Open 2024;5(5):444–451

Aims. The COVID-19 pandemic has caused unprecedented disruption to elective orthopaedic services. The primary objective of this study was to examine changes in functional scores in patients awaiting total hip arthroplasty (THA), total knee arthroplasty (TKA), and unicompartmental knee arthroplasty (UKA). Secondary objectives were to investigate differences between these groups and identify those in a health state ‘worse than death’ (WTD). Methods. In this prospective cohort study, preoperative Oxford hip and knee scores (OHS/OKS) were recorded for patients added to a waiting list for THA, TKA, or UKA, during the initial eight months of the COVID-19 pandemic, and repeated at 14 months into the pandemic (mean interval nine months (SD 2.84)). EuroQoL five-dimension five-level health questionnaire (EQ-5D-5L) index scores were also calculated at this point in time, with a negative score representing a state WTD. OHS/OKS were analyzed over time and in relation to the EQ-5D-5L. Results. A total of 174 patients (58 THA, 74 TKA, 42 UKA) were eligible, after 27 were excluded (one died, seven underwent surgery, 19 non-responders). The overall mean OHS/OKS deteriorated from 15.43 (SD 6.92), when patients were added to the waiting list, to 11.77 (SD 6.45) during the pandemic (p < 0.001). There were significantly worse EQ-5D-5L index scores in the THA group (p = 0.005), with 22 of these patients (38%) in a health state WTD, than either the TKA group (20 patients; 27% WTD), or the UKA group (nine patients; 21% WTD). A strong positive correlation between the EQ-5D-5L index score and OHS/OKS was observed (r = 0.818; p < 0.001). Receiver operating characteristic analysis revealed that an OHS/OKS lower than nine predicted a health state WTD (88% sensitivity and 73% specificity). Conclusion. OHS/OKS deteriorated significantly among patients awaiting lower limb arthroplasty during the COVID-19 pandemic. Overall, 51 patients were in a health state WTD, representing 29% of our entire cohort, which is considerably worse than existing pre-pandemic data. Cite this article: Bone Jt Open 2023;4(3):138–145

Aims. Deprivation underpins many societal and health inequalities. COVID-19 has exacerbated these disparities, with access to planned care falling greatest in the most deprived areas of the UK during 2020. This study aimed to identify the impact of deprivation on patients on growing waiting lists for planned care. Methods. Questionnaires were sent to orthopaedic waiting list patients at the start of the UK’s first COVID-19 lockdown to capture key quantitative and qualitative aspects of patients’ health. A total of 888 respondents were divided into quintiles, with sampling stratified based on the Index of Multiple Deprivation (IMD); level 1 represented the ‘most deprived’ cohort and level 5 the ‘least deprived’. Results. The least deprived cohort were older (mean 65.95 years (SD 13.33)) than the most deprived (mean 59.48 years (SD 13.85)). Mean symptom duration was lower in the least deprived areas (68.59 months (SD 112.26)) compared to the most deprived (85.85 months (SD 122.50)). Mean pain visual analogue scores (VAS) were poorer in the most compared to the least deprived cohort (7.11 (SD 2.01) vs 5.99 (SD 2.57)), with mean mood scores also poorer (6.06 (SD 2.65) vs 4.71 (SD 2.78)). The most deprived areas exhibited lower mean quality of life (QoL) scores than the least (0.37 (SD 0.30) vs 0.53 (SD 0.31)). QoL findings correlated with health VAS and Generalized Anxiety Disorder 2-item (GAD2) scores, with the most deprived areas experiencing poorer health (health VAS 50.82 (SD 26.42) vs 57.29 (SD 24.19); GAD2: 2.94 (SD 2.35) vs 1.88 (SD 2.07)). Least-deprived patients had the highest self-reported activity levels and lowest sedentary cohort, with the converse true for patients from the most deprived areas. Conclusion. The most deprived patients experience poorer physical and mental health, with this most adversely impacted by lengthy waiting list delays. Interventions to address inequalities should focus on prioritizing the most deprived. Cite this article: Bone Jt Open 2022;3(10):777–785

There is a surge of patients on the waiting-list for primary total hip replacement (THR), due to unprecedented reduction of elective activity caused by COVID-19. A higher incidence of femoral head collapse (FC) and acetabular erosion (AE) leading to increase in pain and instability as well as requirement of more complex surgery and potentially higher risk to patients was noted in this period. Rapidly progressive Arthritis (RPA) of the hip is a known entity often described as progression of joint space narrowing greater than 2mm over one year time period. The study aims to identify any potential relationship between waiting time and establishment of femoral head collapse and/ or acetabular erosion. A retrospective review of arthroplasty surgeon's waiting list during COVID. Serial hip radiographs recorded between February 2020 and February 2022 were analysed. FC was quantified as a percentage of the femoral head radius, while AE was assessed by drawing two parallel lines, one through both tear drops and the other through superior most aspect of intact acetabulum, parallel to the inter tear-drop line and expressed as percentage of normal side. Only 105 patients out of 264 patients added to the waiting list had elective arthroplasty for hip/knee. Only 35 patients out of 90 listed for THR, had the surgery. 36 of 90 (40%) were found to have developed FC and fitted the criteria for RPA. Acetabular erosion was seen in 19 (21%). Therefore 53% (19 of 36) of those who developed FC progressed to AE. Incidence of collapse was higher in females (32%), with mean age of 62 (range 51–81), compared to 21% in males with mean age 59 (range 53–87). Mean extent of femoral head collapse was 20% (10 – 44%). A significant proportion of patients added to waiting list during COVID developed RPA of the hip with 40% having femoral head collapse and 21% progressing to acetabular erosion leading to a complex case-mix. Patients on long waiting lists need regular x-ray checks/PROMS since significant proportion progress to FC and Acetabular Erosion

Hip and knee joint arthroplasty wait list has been getting outrageously long in South Africa with some tertiary hospital reporting more than 5 years of waiting time. This has been further compounded by covid 19 pandemic. There is plateau of ideas on how best to address the backlogs in high volume tertiary centers, with catchup list, out reach program, private partnership seeming unsustainable. We sought to look for sustainable solution to the problem and we looked not far but inside the system. Method. Triggered by the fire that engulfed part of the hospital, we found ourself refuged at the sister tertiary hospital with no access to theatre time. We visited districts hospitals within the cluster and discovered state of the art facility underutilized. We presented a plan to establish a satellite arthroplasty center which was greatly embraced by the management. We partnered with the trade to setup an arthroplasty service in this district hospital. Employed 3 retired nurses and 2 parttime anaesthetist all on yearly contract. We developed pathways for patient selection according to American Society of Anaesthesiologist(ASA). 232 total joint arthroplasties were performed in 15-month, 33%Hips and 67%Knees. The average hospital stay was 2,3± 2days. We had 1 mortality(# NOF) and 2 cases of PJI treated successfully with debridement antibiotic and implant retention. We had 5 cases of intraoperative calcar femur fracture managed with cables and all stable at 6weeksand 3month. Over 76% of the cases were performed by fellows as the primary surgeons. Primary hip and knee total joint replacement can be safely performed in a district hospital. Employing motivated retired staff was key to the success of this project. Fellowship trainees performed most of the operations. We suggest that other academic hospitals with long waiting list can look at emulating this model within their district

Orthopaedic paediatric deformities, globally, are often corrected later than initial identification due to resource constraints (bed availability, investigative modalities, surgical skill set). The study aims to analyse experiences and challenges met with running a flagship scoliosis surgery week in a tertiary public health care facility, with the goal of reducing patient waiting time on the waiting list. In this retrospective study, patients from an existing deformity correction waiting list were selected for a 5 day scoliosis surgery week. Investigations relevant to clinical findings were carried out and patients were scheduled on a “one patient per day” surgery list. Inclusion criteria was any patient with adolescent idiopathic scoliosis of varying degree that was symptomatic. Exclusion criteria was any other deformity of any age. Outcomes measured include: Administrative hurdles (obtaining funding, organising ward and ICU beds, getting nursing staff), Surgical challenges (severity of the curve, intraoperative time, approach chosen) and perioperative management (anaesthesia, pain management, cost of equipment) will be looked at to better define the experiences and challenges. All scheduled surgeries were completed. This meant more cases were carried out than what was done in the last 2 years at the facility combined. Lack of Nursing staff availability and few ICU beds delayed starting cases. Anterior fusion took a shorter surgical time in comparison to posterior and cost far less to carry out owing to deformity severity. Intra and post operative management also varied due to daily changes in theatre staff and a lack of standardized protocols. Running a scoliosis surgery week helps to lower the waiting time for deformity correction in public health care facilities. Pre organising resources results in more successful outcomes and an increase in the number of cases done over a shorter period

Background. Frequency of primary total hip (THA) and total knee (TKA) arthroplasty procedures is increasing, with a subsequent rise in revision procedures. This study aims to describe timing and excess surgical mortality associated with revision THA and TKA compared to those on the waiting list. Methods. All patients from 2003–2013 in a single institution who underwent revision THA and TKA, or added to the waiting list for the same procedure were recorded. Mortality rates were calculated at cutoffs of 30- and 90-days post-operation or addition to the waiting list. Results. 561 and 547 patients were available for the survivorship analysis in the revision THA and TKA groups respectively. Following exclusion, 901 and 832 patients were available for the 30-day analysis and 484 and 568 patients for the 90-day analysis in the revision THA and revision TKA waiting list groups respectively. The 30- and 90-day mortality rate was significantly greater for the revision THA group compared to the waiting list group (excess surgical mortality of 0.357%, 95% confidence interval 0.098% to 0.866%; p=0.037) (odds ratio of 5.22, 95% confidence interval 0.626 to 43.524; excess surgical mortality of 0.863%, 95% confidence interval 0.455% to 1.153%; p=0.045). The 30- and 90-day mortality rate was not significantly greater for the revision TKA group compared to the waiting list group (excess surgical mortality of zero) (excess surgical mortality of 0.366%, 95% confidence interval 0.100% to 0.651%; p=0.075). Conclusions. Revision THA is associated with a significant excess surgical mortality rate at 30- and 90-days post operation when compared to the waiting list for the same procedure. However, we have been unable to quantify any increased risk after revision TKA. We would encourage other authors with access to larger samples to use our method to quantify excess mortality after revision TKA. Level of Evidence. III-Retrospective Cohort Study

Waiting times for arthroplasty surgery in Northern Ireland are among the longest in the National Health Service, which have been further lengthened by the onset of the SARS-CoV-19 global pandemic in March 2020. The Department of Health (DoH) in Northern Ireland has announced a new Elective Care Framework (ECF), with the framework proposing that by March 2026 no patient will wait more than 52 weeks for inpatient/day case treatment. We aimed to assess the feasibility of achieving this with reference to Total Hip Arthroplasty (THA). Waiting list information was obtained via a Freedom of Information request to the DoH (May 2021) and National Joint Registry data was used to determine baseline operative numbers. Mathematical modelling was undertaken to calculate the time taken to meet the ECF target and also to determine the time to clear the waiting lists for THA using the number of patients currently on the waiting list and percentage operating capacity relative to pre-Covid-19 capacity to determine future projections. As of May 2021, there were 3,757 patients awaiting primary THA in Northern Ireland. Prior to April 2020, there were a mean 2,346 patients/annum added to the waiting list for primary THA and there were a mean 1,624 primary THAs performed per annum. The ECF targets for THA will only be achieved in 2026 if operating capacity is 200% of pre COVID-19 pandemic capacity and will be achieved in 2030 if capacity is 170%. Surgical capacity must exceed pre-Covid capacity by at least 30% to meet ongoing demand. THA capacity was significantly reduced following resumption of elective orthopaedics post-COVID-19 (22% of pre-COVID-19 capacity – 355 THAs/annum post-COVID-19 versus 1,624/annum pre-COVID-19). This modelling demonstrates that, in the absence of major funding and reorganisation of elective orthopaedic care, the targets set out in the ECF will not be achieved with regards to hip arthroplasty. Waiting times for THA surgery in the NHS in Northern Ireland are likely to remain greater than 52 weeks for most of this decade