Aims. Previous studies have reported an increased risk for postoperative complications in the Medicaid population undergoing total hip arthroplasty (THA). These studies have not controlled for the surgeon’s practice or patient care setting. This study aims to evaluate whether patient point of entry and Medicaid status plays a role in
Hip fracture is a global public health problem.
The National Hip Fracture Database provides a framework for service evaluation
in this group of patients in the United Kingdom, but does not collect
patient-reported outcome data and is unable to provide meaningful
data about the recovery of
Aims. To assess the variation in pre-fracture
We summarise and highlight the safety concerns
within the field of trauma and orthopaedic surgery with particular
emphasis placed on current controversies and reforms within the United
Kingdom National Health Service.
Aims. In this study, we aimed to determine whether designation as a
major trauma centre (MTC) affects the
Objectives. This study investigates the reporting of health-related
Aims. The health-related
A prospective cohort of 222 patients who underwent revision hip replacement between April 2001 and March 2004 was evaluated to determine predictors of function, pain and activity level between one and two years post-operatively, and to define
This study estimated trends in incidence of open fractures and the adherence to clinical standards for open fracture care in England. Longitudinal data collected by the Trauma Audit and Research Network were used to identify 38,347 patients with open fractures, and a subgroup of 12,170 with severe open fractures of the tibia, between 2008 and 2019 in England. Incidence rates per 100,000 person-years and 95% confidence intervals were calculated. Clinical care was compared with the British Orthopaedic Association Standards for Trauma and National Major Trauma Centre audit standards.Aims
Methods
Aims. The aim of this study was to assess the effect of multimorbidity
on improvements in health-related
The poor reporting and use of statistical methods in orthopaedic papers has been widely discussed by both clinicians and statisticians. A detailed review of research published in general orthopaedic journals was undertaken to assess the
We matched 78 patients with a loose cemented Charnley Elite Plus total hip replacement (THR) by age, gender, race, prosthesis and time from surgery with 49 patients with a well-fixed stable hip replacement, to determine if poor bone
We have evaluated the
In a prospective trial we studied 176 consecutive patients having a primary total hip arthroplasty to compare the
Aims. The aim of the study was to compare measures of the
Aims. Natural Language Processing (NLP) offers an automated method to extract data from unstructured free text fields for arthroplasty registry participation. Our objective was to investigate how accurately NLP can be used to extract structured clinical data from unstructured clinical notes when compared with manual data extraction. Methods. A group of 1,000 randomly selected clinical and hospital notes from eight different surgeons were collected for patients undergoing primary arthroplasty between 2012 and 2018. In all, 19 preoperative, 17 operative, and two postoperative variables of interest were manually extracted from these notes. A NLP algorithm was created to automatically extract these variables from a training sample of these notes, and the algorithm was tested on a random test sample of notes. Performance of the NLP algorithm was measured in Statistical Analysis System (SAS) by calculating the accuracy of the variables collected, the ability of the algorithm to collect the correct information when it was indeed in the note (sensitivity), and the ability of the algorithm to not collect a certain data element when it was not in the note (specificity). Results. The NLP algorithm performed well at extracting variables from unstructured data in our random test dataset (accuracy = 96.3%, sensitivity = 95.2%, and specificity = 97.4%). It performed better at extracting data that were in a structured, templated format such as range of movement (ROM) (accuracy = 98%) and implant brand (accuracy = 98%) than data that were entered with variation depending on the author of the note such as the presence of deep-vein thrombosis (DVT) (accuracy = 90%). Conclusion. The NLP algorithm used in this study was able to identify a subset of variables from randomly selected unstructured notes in arthroplasty with an accuracy above 90%. For some variables, such as objective exam data, the accuracy was very high. Our findings suggest that automated algorithms using NLP can help orthopaedic practices retrospectively collect information for registries and
There is little published information on the
health impact of frozen shoulder. The purpose of this study was
to assess the functional and health-related
We set out to determine the impact of surgery on
Public disclosure of outcome-orientated ranking of hospitals is becoming increasingly popular and is routinely used by Swedish health-care authorities. Whereas uncertainty about an outcome is usually presented with 95% confidence intervals, ranking’s based on the same outcome are typically presented without any concern for bias or statistical precision. In order to study the effect of incomplete registration of re-operation on hospital ranking we performed a simulation study using published data on the two-year risk of re-operation after total hip replacement. This showed that whereas minor registration incompleteness has little effect on the observed risk of revision, it can lead to major errors in the ranking of hospitals. We doubt whether a level of data entry sufficient to generate a correct ranking can be achieved, and recommend that when ranking hospitals, the uncertainties about data
Aims. The aim of this study was to evaluate health-related