C Boulton

Predicting 30-day mortality after hip fracture surgery: Evaluation of the National Hip Fracture Database case-mix adjustment model

Objectives 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. Methods 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. Results The 30-day mortality rate was 5.36% in the validation dataset (n = 3861), slightly lower than the 6.40% in the development dataset (n = 4044). The NHFD and Nottingham models showed a slightly lower discrimination in the validation dataset compared with the development dataset, but both still displayed moderate discriminative power (c-statistic for NHFD = 0.71, 95% confidence interval (CI) 0.67 to 0.74; Nottingham model = 0.70, 95% CI 0.68 to 0.75). Both models defined similar ranges of predicted mortality risk (1% to 18%) in assessment of calibration. Conclusions Both models have limitations in predicting mortality for individual patients after hip fracture surgery, but the NHFD risk adjustment model performed as well as the widely-used Nottingham prognostic tool and is therefore a reasonable alternative for risk adjustment in the United Kingdom hip fracture population. Cite this article: Bone Joint Res 2017;6:550–556

Understanding mortality rates after hip fracture repair using ASA physical status in the National Hip Fracture Database

Hip fracture is the most common reason for older patients to need emergency anaesthesia and surgery. Up to one‐third of patients die in the year after hip fracture, but this view of outcome may encourage therapeutic nihilism in peri‐operative decisions and discussions. We used a multicentre national dataset to examine relative and absolute mortality rates for patients presenting with hip fracture, stratified by ASA physical status. We analysed ASA physical status, dates of surgery, death and hospital discharge for 59,369 out of 64,864 patients in the 2015 National Hip Fracture Database; 3914 (6.6%) of whom died in hospital. Rates of death in hospital were 1.8% in ASA 1–2 patients compared with 16.5% in ASA 4 patients. Survival rates for ASA 4 patients on each of the first three postoperative days were: 98.8%, 99.1% and 99.1% (compared with figures of > 99.9% in ASA 1–2 patients over these days). Survival on postoperative day 6 was 99.4% for ASA 4 patients. Nearly half (48.6%) of the 1427 patients who did not have surgery died in hospital. Although technically sound, a focus on cumulative and relative risk of mortality may frame discussions in an unduly negative fashion, discouraging surgeons and anaesthetists from offering an operation, and deterring patients and their loved ones from agreeing to it. A more optimistic and pragmatic explanation that over 98% of ASA 4 patients survive both the day of surgery and the day after it, may be more appropriate.

Variations in care quality occur across the whole week, not just at weekends

The “weekend effect” is an oversimplification.1 Attempting to address it is a distraction because hospital mortality is not a good measure of quality of care and weekends are not the only times when quality is compromised by the way in which services are organised. What we need to know is, firstly, are there variations in quality of care depending on the time of day or the day of the week that emergency patients are admitted? Secondly, are these variations clinically important? Thirdly, if they are important, what are the underlying causes and, fourthly, does the NHS want to make the changes and investment that are necessary to deal with the causes? We think that we can answer the first and second questions, at least for some groups of patients, using data from national clinical audits. Patients with stroke receive high …