National hip fracture registries audit similar aspects of care but there is variation in the actual data collected; these differences restrict international comparison, benchmarking, and research. The Fragility Fracture Network (FFN) published a revised minimum common dataset (MCD) in 2022 to improve consistency and interoperability. Our aim was to assess compatibility of existing registries with the MCD. We compared 17 hip fracture registries covering 20 countries (Argentina; Australia and New Zealand; China; Denmark; England, Wales, and Northern Ireland; Germany; Holland; Ireland; Japan; Mexico; Norway; Pakistan; the Philippines; Scotland; South Korea; Spain; and Sweden), setting each of these against the 20 core and 12 optional fields of the MCD.Aims
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The aim of this study was to describe services available to patients with periprosthetic femoral fracture (PPFF) in England and Wales, with focus on variation between centres and areas for care improvement. This work used data freely available from the National Hip Fracture Database (NHFD) facilities survey in 2021, which asked 21 questions about the care of patients with PPFFs, and nine relating to clinical decision-making around a hypothetical case.Aims
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Patients with A1 and A2 trochanteric hip fractures represent a substantial proportion of trauma caseload, and national guidelines recommend that sliding hip screws (SHS) should be used for these injuries. Despite this, intramedullary nails (IMNs) are routinely implanted in many hospitals, at extra cost and with unproven patient outcome benefit. We have used data from the National Hip Fracture Database (NHFD) to examine the use of SHS and IMN for A1 and A2 hip fractures at a national level, and to define the cost implications of management decisions that run counter to national guidelines. We used the NHFD to identify all operations for fixation of trochanteric fractures in England and Wales between 1 January 2021 and 31 December 2021. A uniform price band from each of three hip fracture implant manufacturers was used to set cost implications alongside variation in implant use.Aims
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Hip fracture commonly affects the frailest patients, of whom many are care-dependent, with a disproportionate risk of contracting COVID-19. We examined the impact of COVID-19 infection on hip fracture mortality in England. We conducted a cohort study of patients with hip fracture recorded in the National Hip Fracture Database between 1 February 2019 and 31 October 2020 in England. Data were linked to Hospital Episode Statistics to quantify patient characteristics and comorbidities, Office for National Statistics mortality data, and Public Health England’s SARS-CoV-2 testing results. Multivariable Cox regression examined determinants of 90-day mortality. Excess mortality attributable to COVID-19 was quantified using Quasi-Poisson models.Aims
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The aim of this study was to explore current use of the Global Fragility Fracture Network (FFN) Minimum Common Dataset (MCD) within established national hip fracture registries, and to propose a revised MCD to enable international benchmarking for hip fracture care. We compared all ten established national hip fracture registries: England, Wales, and Northern Ireland; Scotland; Australia and New Zealand; Republic of Ireland; Germany; the Netherlands; Sweden; Norway; Denmark; and Spain. We tabulated all questions included in each registry, and cross-referenced them against the 32 questions of the MCD dataset. Having identified those questions consistently used in the majority of national audits, and which additional fields were used less commonly, we then used consensus methods to establish a revised MCD.Aims
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In UK there are around 76,000 hip fractures occur each year 10% to 15% of which are undisplaced intracapsular. There is considerable debate whether internal fixation is the most appropriate treatment for undisplaced fractures in older patients. This study describes cannulated hip screws survivorship analysis for patients aged ≥ 60 years with undisplaced intra-capsular fractures. This was a retrospective cohort study of consecutive patients aged ≥ 60 years who had cannulated screws fixation for Garden I and II fractures in a teaching hospital between March 2013 and March 2016. The primary outcome was further same-side hip surgery. Descriptive statistics were used and Kaplan-Meier estimates calculated for implant survival.Aims
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The aim of this study was to determine the impact of hospital-level service characteristics on hip fracture outcomes and quality of care processes measures. This was a retrospective analysis of publicly available audit data obtained from the National Hip Fracture Database (NHFD) 2018 benchmark summary and Facilities Survey. Data extraction was performed using a dedicated proforma to identify relevant hospital-level care process and outcome variables for inclusion. The primary outcome measure was adjusted 30-day mortality rate. A random forest-based multivariate imputation by chained equation (MICE) algorithm was used for missing value imputation. Univariable analysis for each hospital level factor was performed using a combination of Tobit regression, Siegal non-parametric linear regression, and Mann-Whitney U test analyses, dependent on the data type. In all analyses, a p-value < 0.05 denoted statistical significance.Aims
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The National Hip Fracture Database (NHFD) publishes hospital-level risk-adjusted mortality rates following hip fracture surgery in England, Wales and Northern Ireland. The performance of the risk model used by the NHFD was compared with the widely-used Nottingham Hip Fracture Score. Data from 94 hospitals on patients aged 60 to 110 who had hip fracture surgery between May 2013 and July 2013 were analysed. Data were linked to the Office for National Statistics (ONS) death register to calculate the 30-day mortality rate. Risk of death was predicted for each patient using the NHFD and Nottingham models in a development dataset using logistic regression to define the models’ coefficients. This was followed by testing the performance of these refined models in a second validation dataset.Objectives
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