‘Big data’ is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Billions of dollars have been spent on attempts to build predictive tools from large sets of poorly controlled healthcare metadata. Companies often sell reports at a physician or facility level based on various flawed data sources, and comparative websites of ‘publicly reported data’ purport to educate the public. Physicians should be aware of concerns and pitfalls seen in such data definitions, data clarity, data relevance, data sources and data cleaning when evaluating analytic reports from metadata in health care.

Cite this article: Bone Joint J 2017;99-B:1571–6.

Hip fracture patients are vulnerable to delirium. This study examined the associations between delirium and outcomes including mortality, length of stay, post-discharge care requirements, and readmission. This cohort study collected validated healthcare data for all hip fracture patients aged ≥50 years that presented to a high-volume centre between March 2020-November 2021. Variables included: demographics, delirium status, COVID-19 status, treatment factors, and outcome measures. Wilcoxon rank sum or Chi-squared tests were used for baseline differences, Cox proportional hazard regression for mortality, logistic regression for post-discharge care requirements and readmission, and linear regression for length of stay. Analyses were adjusted for age, sex, deprivation, pre-fracture residence type and COVID-19. There were 1822 patients (mean age 81 years; 72% female) of which 496/1822 (27.2%) had delirium (4AT score ≥4). Of 371/1822 (20.4%) patients that died within 180 days of admission, 177/371 (47.7%) had delirium during the acute stay. Delirium was associated with an increased 30- and 180-day mortality risk (adjusted HR 1.74 (95%CI 1.15-2.64; p=0.009 and 1.74 (1.36-2.22; p<0.001), respectively), ten day longer total inpatient stay [adj. B.coef 9.80 (standard error 2.26); p<0.001] and three-fold greater odds of higher care requirements on discharge [Odds Ratio 3.07 (95% Confidence Interval 2.27-4.15; p<0.001)]. More than a quarter of patients had delirium during the hip fracture stay, and this was independently associated with increased mortality, longer length of stay, and higher post-discharge care requirements. These findings are relevant for prognostication and service planning, and emphasise the importance of effective delirium screening and evidence-based interventions in this vulnerable population

Aims. The aims of this study were to investigate whether 1) multispecialist tertiary intervention for complex spinal pain lead to reductions in spine-related healthcare costs and 2) baseline characteristics are related to health care consuming costs. Patients and methods. A cost study in a natural prospective cohort was carried out to investigate healthcare data of patients admitted to the Groningen Spine Center (GSC) ranging from two years prior to referral until two year after discharge. GSC intervention consisted of a multi-professional and -specialist based diagnosis and treatment. Patients (18 and 80 years) were included, suffering from specific as well as multifactorial spinal pain. Clinical data was merged with Health Care Insurance data and included questionnaires on demographics, work, pain, disability, quality of life and psychosocial functioning. Univariable (paired sample t-tests) and multivariable analyses (pooled OLS Regression and fixed effects models) were carried out. Results. Included were 997 patients (mean age 52 years) filing a total of 700.533 health care declarations. The findings suggest that the intervention had a significant negative effect on spine-related healthcare costs (predominantly on medical specialist and allied care). Reduction in healthcare costs after treatment was predicted by lower age, lower duration, lower BMI, high education, high job satisfaction, low physical workload, high mental health, better coping, lower pain intensity, high EQ-5D score and low financial worries at baseline (all p<0.01). Conclusion. This observational study showed that spine-related healthcare consuming can be effectively reduced after tertiary multi-specialist intervention for patients with complex spinal pain. The results are robust when controlling for background characteristics and are unlikely to be driven by regression to the mean. No conflicts of interest. No funding obtained

Total hip arthroplasty (THA) is one of the most successful and effective treatments for advanced hip osteoarthritis (OA). Over the last 5 years, Canada has seen a 17.8% increase in the number of hip replacements performed annually, and that number is expected to grow along with the aging Canadian population. However, the rise in THA surgery is associated with an increased number of patients at risk for the development of an infection involving the joint prosthesis and adjacent deep tissue – periprosthetic joint infections (PJI). Despite improved hygiene protocols and novel surgical strategies, PJI remains a serious complication. No previous population-based studies has investigated PJI risk factors using a time-to-event approach and none have focused exclusively on patients undergoing THA for primary hip OA. The purpose of this study is to determine risk factors for PJI after primary THA for OA using a large population-based database collected over 15 years. Our secondary objective is to determine the incidence of PJI, the time to PJI following primary THA, and if PJI rates have changed in the past 15 years. We performed a population-based cohort study using linked administrative databases in Ontario, Canada in accordance with RECORD and STROBE guidelines. All primary total hip replacements performed for osteoarthritis in patients aged 55 or older between January 1st 2002 – December 31st 2016 in Ontario, Canada were identified. Periprosthetic joint infection as the cause for revision surgery was identified with the International Classification of Diseases, 10th Edition (ICD-10), Clinical Modification diagnosis code T84.53 in any component of the healthcare data set. Data were obtained from the Institute for Clinical Evaluative Sciences (ICES). Demographic data and outcomes are summarized using descriptive statistics. We used a Cox proportional hazards model to analyze the effect of surgical factors and patient factors on the risk of developing PJI. Surgical factors include the approach, use of bone graft, use of cement, and the year of surgery. Patient factors include sex, age at surgery, income quintile and rurality (community vs. urban). We compared the 1,2,5 and 10 year PJI rates for patients undergoing THA each year of our cohort with the Cochran-Armitage test. Less than 0.1% of data were missing from all fields except for rurality which was lacking 0.3% of data. A total of 100,674 patients aged 55 or older received a primary total hip arthroplasty for osteoarthritis from 2002–2016. We identified 1034 cases of revision surgery for prosthetic joint infection for an overall PJI rate of 1.03%. When accounting for patients censored at final follow-up, the cumulative incidence for PJI is 1.44%. Our Cox proportional hazards model revealed that male sex, Type II diabetes mellitus, discharge to convalescent care, and having both hips replaced during one's lifetime were associated with increased risk of developing PJI following primary THA. Importantly, the time adjusted risk for PJI was equal for patients operated within the past 5 years, 6–10 years ago, or 11–15 years ago. The surgical approach, use of bone grafting or cement were not associated with increased risk of infection. PJI rates have not changed significantly over the past 15 years. One, two, five and ten-year PJI rates were similar for patients undergoing THA in all qualifying years. Analysis of a population-based cohort of 100,674 patients has shown that the risk of developing PJI following primary THA has not changed over 15 years. The surgical approach, use of bone grafting or cement were not associated with increased risk of infection. Male sex, Type II diabetes Mellitus and discharge to a rehab facility are associated with increased risk of PJI. As the risk of PJI has not changed in 15 years, an appropriately powered trial is warranted to determine interventions that can improve infection rate after THA

Introduction. Machine learning is a relatively novel method to orthopaedics which can be used to evaluate complex associations and patterns in outcomes and healthcare data. The purpose of this study is to utilize 3 different supervised machine learning algorithms to evaluate outcomes from a multi-center international database of a single shoulder prosthesis to evaluate the accuracy of each model to predict post-operative outcomes of both aTSA and rTSA. Methods. Data from a multi-center international database consisting of 6485 patients who received primary total shoulder arthroplasty using a single shoulder prosthesis (Equinoxe, Exactech, Inc) were analyzed from 19,796 patient visits in this study. Specifically, demographic, comorbidity, implant type and implant size, surgical technique, pre-operative PROMs and ROM measures, post-operative PROMs and ROM measures, pre-operative and post-operative radiographic data, and also adverse event and complication data were obtained for 2367 primary aTSA patients from 8042 visits at an average follow-up of 22 months and 4118 primary rTSA from 11,754 visits at an average follow-up of 16 months were analyzed to create a predictive model using 3 different supervised machine learning techniques: 1) linear regression, 2) random forest, and 3) XGBoost. Each of these 3 different machine learning techniques evaluated the pre-operative parameters and created a predictive model which targeted the post-operative composite score, which was a 100 point score consisting of 50% post-operative composite outcome score (calculated from 33.3% ASES + 33.3% UCLA + 33.3% Constant) and 50% post-operative composite ROM score (calculated from S curves weighted by 70% active forward flexion + 15% internal rotation score + 15% active external rotation). 3 additional predictive models were created to control for the time required for patient improvement after surgery, to do this, each primary aTSA and primary rTSA cohort was subdivided to only include patient data follow-up visits >20 months after surgery, this yielded 1317 primary aTSA patients from 2962 visits at an average follow-up of 50 months and 1593 primary rTSA from 3144 visits at an average follow-up of 42 months. Each of these 6 predictive models were trained using a random selection of 80% of each cohort, then each model predicted the outcomes of the remaining 20% of the data based upon the demographic, comorbidity, implant type and implant size, surgical technique, pre-operative PROMs and ROM measures inputs of each 20% cohort. The error of all 6 predictive models was calculated from the root mean square error (RMSE) between the actual and predicted post-op composite score. The accuracy of each model was determined by subtracting the percent difference of each RMSE value from the average composite score associated with each cohort. Results. For all patient visits, the XGBoost decision tree algorithm was the most accurate model for both aTSA & rTSA patients, with an accuracy of ∼89.5% for both aTSA and rTSA. However for patients with 20+ month visits only, the random forest decision tree algorithm was the most accurate model for both aTSA & rTSA patients, with an accuracy of ∼89.5% for both aTSA and rTSA. The linear regression model was the least accurate predictive model for each of the cohorts analyzed. However, it should be noted that all 3 machine learning models provided accuracy of ∼85% or better and a RMSE <12. (Table 1) Figures 1 and 2 depict the typical spread and RMSE of the actual vs. predicted total composite score associated with the 3 models for aTSA (Figure 1) and rTSA (Figure 2). Discussion. The results of this study demonstrate that multiple different machine learning algorithms can be utilized to create models that predict outcomes with higher accuracy for both aTSA and rTSA, for numerous timepoints after surgery. Future research should test this model on different datasets and using different machine learning methods in order to reduce over- and under-fitting model errors. For any figures or tables, please contact the authors directly

Arthroplasty registries have played a key role in the treatment of patients with various joint diseases and conditions since their conception. Swedish hip and knee arthroplasty registries were initiated in late 1970's. The main aim of registries was to create feedback to surgeons. During the last two decades with introduction of patient reported outcomes, data from registries have been increasingly used to compare caregivers and to improve quality of health care. According to the Swedish Hip Arthroplasty Register (SHAR) Sahlgrenska University Hospital had been underperforming during years 2006–2012. In order to improve the outcomes a systematic data driven approach using local and national registries, based on value based management was undertaken. Representatives from all categories of healthcare staff and patients were invited to join a newly initiated group. The group was asked to define which measurement that contributed most to improve healthcare. Data from SHAR and local registries were used and seventeen different areas of improvement were identified. Several workgroups were initiated. Between years 2013 and 2017 there was an increase of 60% in the annual volume of elective THAs. The length of stay decreased from 6.4 days to 1.8 days. Satisfaction with outcome of surgery increased from 76% to 90%. Adverse events decreased from 28% to 10%. The risk of re-operations within 2 years decreased from 2.4% to 1.9%. Data from a national and a local registry were used to identify and implement changes in a large university hospital. Engaging member of staff and creating a graphical tool for continuous feedback drastically improved the quality of care whilst increasing the availability of hip replacements and reducing costs. This project demonstrates the power of registry data and a patient centered approach in engaging staff and improving healthcare

Cite this article: Bone Joint Res 2023;12(4):256–258.

Aims

This study aimed to describe practice variation in the use of total hip arthroplasty (THA) for older patients with femoral neck fracture and to determine the association between patient, surgeon, and institution factors and treatment with THA.

The February 2025 Hip & Pelvis Roundup³⁶⁰ looks at: Postoperative periprosthetic femoral fractures after hip arthroplasty: quantifying the other half of the picture; Hip arthroscopy in patients with borderline dysplasia: how do we know when it will not work?; The morbidly obese patient remains a challenge for arthroplasty surgeons; Unexpected positive cultures in aseptic revision hip and knee arthroplasty: does it make a difference?; Failed spinal anaesthesia in hip and knee arthroplasty surgery; Clinical failure of femoral neck fracture is associated with varus necks; Navigating the angles: how variations in femoral and acetabular versions influence hip pain and treatment; High-tech or hands-on? Similar outcomes in direct anterior total hip arthroplasty.

Aims

This study compares the re-revision rate and mortality following septic and aseptic revision hip arthroplasty (rTHA) in registry data, and compares the outcomes to previously reported data.

The February 2025 Wrist & Hand Roundup³⁶⁰ looks at: Delayed fixation of distal radial fractures beyond three weeks increases the odds of reoperation; A systematic review of management options for symptomatic scaphometacarpal impingement after trapeziectomy; Diagnosing occult scaphoid fractures: an art or science?; Dual-mobility trapeziometacarpal arthroplasty shows promising outcomes but lacks long-term evidence; 3D-printed titanium scaphoid implant offers a promising alternative for unreconstructable scaphoid nonunion; Lidocaine co-injection reduces pain intensity during corticosteroid injections in hand and wrist conditions; Long-term outcomes of PyroDisk arthroplasty for trapeziometacarpal osteoarthritis; Evaluating the impact of COVID-19 on hand surgery practices: adaptations and missed opportunities.

Aims

The Clavien-Dindo (CD) classification and Comprehensive Complication Index (CCI) have been validated primarily among general surgical procedures. To date, the validity of these measures has not been assessed in patients undergoing arthroplasty.

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It is unclear if a supportive bandage, removable splint, or walking cast offers the best outcome following low-risk ankle fractures in children. The aim of this study was to evaluate the feasibility of a randomized controlled trial to compare these treatments.

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The aim of this study was to evaluate the suitability, against an accepted international standard, of a linked hip fracture registry and routinely collected administrative dataset in England to embed and deliver randomized controlled trials (RCTs).

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Ankle fracture is one of the most common musculoskeletal injuries sustained in the UK. Many patients experience pain and physical impairment, with the consequences of the fracture and its management lasting for several months or even years. The broad aim of ankle fracture treatment is to maintain the alignment of the joint while the fracture heals, and to reduce the risks of problems, such as stiffness. More severe injuries to the ankle are routinely treated surgically. However, even with advances in surgery, there remains a risk of complications; for patients experiencing these, the associated loss of function and quality of life (Qol) is considerable. Non-surgical treatment is an alternative to surgery and involves applying a cast carefully shaped to the patient’s ankle to correct and maintain alignment of the joint with the key benefit being a reduction in the frequency of common complications of surgery. The main potential risk of non-surgical treatment is a loss of alignment with a consequent reduction in ankle function. This study aims to determine whether ankle function, four months after treatment, in patients with unstable ankle fractures treated with close contact casting is not worse than in those treated with surgical intervention, which is the current standard of care.

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To assess the cost-effectiveness of a two-layer compression bandage versus a standard wool and crepe bandage following total knee arthroplasty, using patient-level data from the Knee Replacement Bandage Study (KReBS).

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Registry studies on modified acetabular polyethylene (PE) liner designs are limited. We investigated the influence of standard and modified PE acetabular liner designs on the revision rate for mechanical complications in primary cementless total hip arthroplasty (THA).