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SummaryThis study uses NHS waiting times and osteoporosis medication community prescription datasets to assess the impact of COVID-19 on DXA waits and osteoporosis medication patterns in England. Results show significant increases in DXA waiting list times and variation in prescription rates. Investment is needed to improve waiting list times.PurposeThis study investigates the impact of COVID-19 on DXA scan waiting lists, service recovery and osteoporosis medication prescriptions in the NHS following the March 2020 national lockdowns and staff redeployment.MethodsData from March 2019 to June 2023, including NHS digital diagnostics waiting times (DM01) and osteoporosis medication prescriptions from the English Prescribing Dataset (EPD), were analysed. This encompassed total waiting list data across England’s seven regions and prescribing patterns for various osteoporosis medications. Analyses included total activity figures and regression analysis to estimate expected activity without COVID-19, using R for all data analysis.ResultsIn England, DXA waiting lists have grown significantly, with the yearly mean waiting list length increasing from 31,851 in 2019 to 65,757 in 2023. The percentage of patients waiting over 6 weeks for DXA scans rose from 0.9% in 2019 to 40% in 2020, and those waiting over 13 weeks increased from 0.1% in 2019 to 16.7% in 2020. Prescription trends varied, with increases in denosumab, ibandronic acid and risedronate sodium and decreases in alendronic acid, raloxifene hydrochloride and teriparatide. A notable overall prescription decrease occurred in the second quarter of 2020.ConclusionCOVID-19 has significantly increased DXA scan waiting lists with ongoing recovery challenges. There is a noticeable disparity in DXA service access across England. Osteoporosis care, indicated by medication prescriptions, also declined during the pandemic. Addressing these issues requires focused investment and effort to improve DXA scan waiting times and overall access to osteoporosis care in England.

The Health Foundation this week presented an analysis saying that surgical hubs could significantly increase treatment volumes, by around 11%, and were having systemwide effects on elective care that supported their continued expansion.1 Tim Mitchell, president of the Royal College of Surgeons of England, said, “With the budget on the horizon, we hope these findings encourage the government to turbocharge the expansion of surgical hubs nationwide, ensuring that every patient, regardless of location, can benefit from this proven initiative to receive faster treatment.” The Health Foundation’s NHS commissioned evaluation, which has not been peer reviewed, estimated the changes in elective activity in trusts with hubs relative to a control group of trusts without hubs, using a generalised synthetic control method. 1 Co M Marks T Tracey F Conti S Clarke G. The impact of elective surgical hubs on elective activity in acute hospital trusts in England: a generalised synthetic control study.

More than 40% of patients awaiting a kidney transplant in the UK are sensitised with human leucocyte antigen (HLA) antibodies. Median time to transplantation for such patients is double that of unsensitised patients at about 74 months. Removing antibody to perform an HLA-incompatible (HLAi) living donor transplantation is perceived to be high risk, although patient survival data are limited. We compared survival of patients opting for an HLAi kidney transplant with that of similarly sensitised patients awaiting a compatible organ. From the UK adult kidney transplant waiting list, we selected crossmatch positive living donor HLAi kidney transplant recipients who received their transplant between Jan 1, 2007, and Dec 31, 2013, and were followed up to Dec 31, 2014 (end of study). These patients were matched in a 1:4 ratio with similarly sensitised patients cases listed for a deceased-donor transplant during that period. Data were censored both at the time of transplantation (listed only), and at the end of the study period (listed or transplant). We used Kaplan-Meier curves to compare patient survival between HLAi and the matched cohort. Of 25 518 patient listings, 213 (1%) underwent HLAi transplantation during the study period. 852 matched controls were identified, of whom 41% (95% CI 32–50) remained without a transplant at 58 months after matching. We noted no difference in survival between patients who were in the HLAi group compared with the listed only group (log rank p=0·446), or listed or transplant group (log rank p=0·984). Survival of sensitised patients undergoing HLAi in the UK is comparable with those on dialysis awaiting a compatible organ, many of whom are unlikely to be have a transplant. Choosing a direct HLAi transplant has no detrimental effect on survival, but offers no survival benefit, by contrast with similar patients studied in a North American multicentre cohort. UK National Health Service Blood & Transplant and Guy's & St Thomas' National Institute for Health Research Biomedical Research Centre.

BackgroundIn the last decades, we have experienced an increase in the prevalence of obesity in western countries with a higher demand for bariatric surgery and consequently prolonged waiting times. Currently, in many public hospitals, the only criterion that establishes priority for bariatric surgery is waiting time regardless of obesity severity.MethodsWe propose a new, simple, and homogeneous clinical prioritization system, the Obesity Surgery Score (OSS), which takes into account simultaneously and equitably the time on surgical waiting list and the obesity severity based on three variables: body mass index, obesity-related comorbidities, and functional limitations. We have reviewed the current literature related to obesity clinical staging systems, and we have carried out an analysis of our patients in waiting list and divided their characteristics according to their degree of severity (A, B, or C) in the OSS. Patients with OSS grade C have a higher mean BMI, greater severity in comorbidities, and greater socio-labor impact. The current surgery waiting time of our series is of 26 months. Currently, 27 patients (51.9%) with OSS grade B and 15 patients (51.7%) with OSS grade C have been on our waiting list for more than 1 year.ConclusionSince the obesity severity, the waiting time and its clinical consequences are associated with an increase in morbidity and mortality, it is important to apply a structured prioritization system for bariatric surgery waiting list. This allows prioritization of patients at greater risk, improves patient prognosis, and optimizes costs and available health resources.

Background It is globally agreed that a well-designed health system deliver timely and convenient access to health services for all patients. Many interventions aiming to reduce waiting times have been implemented in Chinese public tertiary hospitals to improve patients’ satisfaction. However, few were well-documented, and the effects were rarely measured with robust methods. Methods We conducted a longitudinal study of the length of waiting times in a public tertiary hospital in Southern China which developed comprehensive data collection systems. Around an average of 60,000 outpatients and 70,000 prescribed outpatients per month were targeted for the study during Oct 2014-February 2017. We analyzed longitudinal time series data using a segmented linear regression model to assess changes in levels and trends of waiting times before and after the introduction of waiting time reduction interventions. Pearson correlation analysis was conducted to indicate the strength of association between waiting times and patient satisfactions. The statistical significance level was set at 0 . 05. Results The monthly average length of waiting time decreased 3 . 49 min ( P  = 0 . 003) for consultations and 8 . 70 min ( P  = 0 . 02) for filling prescriptions in the corresponding month when respective interventions were introduced. The trend shifted from baseline slight increasing to afterwards significant decreasing for filling prescriptions ( P  =0.003). There was a significant negative correlation between waiting time of filling prescriptions and outpatient satisfaction towards pharmacy services ( r  = −0 . 71, P  = 0 . 004). Conclusions The interventions aimed at reducing waiting time and raising patient satisfaction in Fujian Provincial Hospital are effective. A long-lasting reduction effect on waiting time for filling prescriptions was observed because of carefully designed continuous efforts, rather than a one-time campaign, and with appropriate incentives implemented by a taskforce authorized by the hospital managers. This case provides a model of carrying out continuous quality improvement and optimizing management process with the support of relevant evidence.

The COVID-19 pandemic resulted in extensive disruption to the delivery of elective health services. Official figures of NHS waiting lists in England do not account for patients on the hidden waiting list (ie, patients who have symptoms or disease requiring elective procedures who have not been placed on the waiting list due to pandemic-related disruption). The aim of this study was to model the elective procedure backlog in England, including the hidden waiting list. We used publicly available activity data from NHS Digital to estimate procedure-level backlogs in England for the pandemic period (from Jan 1, 2020, to Dec 31, 2022) compared with expected population need for elective procedures based on pre-pandemic trends, adjusting for population growth and ageing, as well as patient deaths while on the waiting list. The primary outcome was the elective procedure backlog. Elective procedures were defined as including surgery, endoscopy, interventional radiology, and interventional cardiology. The secondary outcome was the procedural hidden waiting list. The elective procedure backlog was reported by specialty and procedure. The total elective procedure backlog in England on Dec 31, 2022, was modelled to be 4 519 467 procedures. The hidden waiting list was 3 621 423, comprising 80·3% of the total backlog. Half the total backlog (2 228 348, 49·3%) was in people aged 16–59 years. The largest backlogs were in general surgery (1 463 423, 32·4%), orthopaedics (1 001 850, 22·2%), and urology (510 649, 11·3%). Overall, 84·7% (3 827 687 procedures) of the backlog were for day-case procedures. The procedures with the greatest total backlog were sigmoidoscopy and colonoscopy (546 930, 12·1%), gastroscopy (376 089, 8·3%), cataract surgery (238 912, 5·3%), and lower limb joint replacement (209 976, 4·6%). NHS waiting lists are an unreliable guide to the true population need for elective procedures. Initiatives are needed to identify and prioritise patients requiring urgent treatment. Most need is for low-complexity high-volume day-case surgery. Sustained, ring-fenced funding is required to invest in scaling up the operative workforce and facilities, and to increase the resilience of surgical services to avoid existing backlogs being compounded by future external pressures. This modelling study is based on an assumption that over the course of the pandemic the incidence of surgical disease did not change. None.

Stopping smoking can reduce complications by 50%.7 Increased physical activity, such as going for a daily brisk walk, reduces complications by 30-80%.8 Patients need to be supported in making active choices. Since optimisation for surgery involves simple measures, the waiting list should be thought of as a preparation list.9 Using this “teachable moment”10 may also help people with their future health. Sharing skills across the whole perioperative pathway is shown to reduce complications by 50% and to shorten hospital stays by 1-2 days, reducing the need for postoperative critical care as well as short notice cancellations, healthcare costs, and patient dissatisfaction.8 Preparation for surgery must start early in the care pathway.

Background The results of liver transplantation are excellent, with survival rates of over 90 and 80% at 1 and 5 years, respectively. The success of liver transplantation has led to an increase in the indications for liver transplantation. Generally, priorities are given to cirrhotic patients with a high Model for End-Stage Liver Disease (MELD) score on the principle of the sickest first and to patients with hepatocellular carcinoma (HCC) on the principle of priority points according to the size and number of nodules of HCC. These criteria can lead to a ‘competition’ on the waiting list between the above patients and those who are cirrhotic and have an intermediate MELD score or with life-threatening liver diseases not well described by the MELD score. For this latter group of patients, ‘MELD exception’ points can be arbitrarily given. Discussion The management of patients on the waiting list is of prime importance to avoid death and drop out from the waiting list as well as to improve post-transplant survival rates. For the more severe cases who may swiftly access liver transplantation, it is essential to rapidly determine whether liver transplantation is indeed indicated, and to organise a fast workup ahead of this. It is also essential to identify the ideal timing for liver transplantation in order to minimise mortality rates. For patients with HCC, a bridge therapy is frequently required to avoid progression of HCC and to maintain patients within the criteria of liver transplantation as well as to reduce the risk of post-transplant recurrence of HCC. For patients with cirrhosis and intermediate MELD score, waiting time can exceed 1 year; therefore, regular follow-up and management are essential to maintain the patient alive on the waiting list and to achieve a good survival after liver transplantation. Conclusion There is a diversity of patients on the waiting list for transplantation and equity should be preserved between those with cirrhosis of high and intermediate severity and those with HCC. The management of patients on the waiting list is an essential component of the success of liver transplantation.

Waiting lists are big news, but what’s really happening? John Appleby presents the most recent data in elective and emergency care—and the effect on patients

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