Poor Attendance for bone densitometry in patients at high risk of subsequent fragility fractures.

Fracture Liaison Services (FLS) are considered the most effective model for the prevention of subsequent fractures however, the uptake of these services has shown to be suboptimal. 6,528 patients were identified and referred on for bone densitometry assessment over a 6 yr period, however, 21% of these patients did not attend, with a trend towards a higher re-fracture rate in those that did not attend compared to those that did. The presence of a fragility fracture increases the risk of further fractures. Fracture Liaison Services (FLS) are considered the most effective model for the prevention of subsequent fractures, although the uptake amongst patients invited for bone densitometry assessment has shown to be suboptimal. The UK has one of the most comprehensive numbers of FLS, however the proportion and characteristics of patients identified through the FLS that do not respond to bone densitometry invitation, in the UK, remains unclear. We report the 6 yr. findings from the Nottingham FLS. The Nottingham Fracture Liaison Service (N-FLS) systematically identifies those adults aged 50 yr. and older with fragility fractures presenting to the fracture clinic and where appropriate, arranges referral for bone densitometry assessment. Routine clinical data is collected onto the N-FLS database. Patient characteristics, between January 2012 and December 2017, were examined of those referred for bone densitometry examination, comparing those that attended to those that did not attend (DNA). Deprivation scores for each patient were calculated using the English indices of deprivation 2015 (1-Most deprived; 5- Least deprived). Follow up data was available for those attending from 2016 onwards, which allowed an assessment of re-fracture. Over the 6 yr period, 6,528 patients as identified by the N-FLS were referred on for bone densitometry assessment. 1,386 patients (21%) did not attend (DNA) for bone densitometry assessment. The proportion was similar for each of the years. High prevalence of non-attendance was in females [1032 patients (74%)] and the most deprived individuals [398 patients (29%), which were significant when compared to those that did attend, p=0.042]. 826 patients were referred in 2016. Median follow-up time was 2.46 yr. (IQR 0.16-3.00 yr.). 52 (7%) patients, in this group, sustained a subsequent fracture (35 patients in the group that did not attend for bone density assessment and 17 in those that attend, p=0.092). Nottingham FLS have identified patients with fragility fractures that are at high-risk of further fractures. Despite a dedicated FLS, 21% of those invited for bone densitometry assessment, did not attend for their appointment, over the 6 yr. period, similar proportion each year. There was a significantly higher proportion of those identified as 'most deprived' not attending for a bone densitometry, compared to those who attended. Sub-analysis in those aged 75 yr. and over, showed a high non-attendance in this group. Further qualitative studies are necessary to explore this patient group in detail, who remain at high risk of re-fracture.

The cost of diagnostic uncertainty: a prospective economic analysis of febrile children attending an NHS emergency department.

BACKGROUND: Paediatric fever is a common cause of emergency department (ED) attendance. A lack of prompt and definitive diagnostics makes it difficult to distinguish viral from potentially life-threatening bacterial causes, necessitating a cautious approach. This may result in extended periods of observation, additional radiography, and the precautionary use of antibiotics (ABs) prior to evidence of bacterial foci. This study examines resource use, service costs, and health outcomes. METHODS: We studied an all-year prospective, comprehensive, and representative cohort of 6518 febrile children (aged < 16 years), attending Alder Hey Children's Hospital, an NHS-affiliated paediatric care provider in the North West of England, over a 1-year period. Performing a time-driven and activity-based micro-costing, we estimated the economic impact of managing paediatric febrile illness, with focus on nurse/clinician time, investigations, radiography, and inpatient stay. Using bootstrapped generalised linear modelling (GLM, gamma, log), we identified the patient and healthcare provider characteristics associated with increased resource use, applying retrospective case-note identification to determine rates of potentially avoidable AB prescribing. RESULTS: Infants aged less than 3 months incurred significantly higher resource use than any other age group, at £1000.28 [95% CI £82.39-£2993.37] per child, (p < 0.001), while lesser experienced doctors exhibited 3.2-fold [95% CI 2.0-5.1-fold] higher resource use than consultants (p < 0.001). Approximately 32.4% of febrile children received antibiotics, and 7.1% were diagnosed with bacterial infections. Children with viral illnesses for whom antibiotic prescription was potentially avoidable incurred 9.9-fold [95% CI 6.5-13.2-fold] cost increases compared to those not receiving antibiotics, equal to an additional £1352.10 per child, predominantly resulting from a 53.9-h increase in observation and inpatient stay (57.1 vs. 3.2 h). Bootstrapped GLM suggested that infants aged below 3 months and those prompting a respiratory rate 'red flag', treatment by lesser experienced doctors, and Manchester Triage System (MTS) yellow or higher were statistically significant predictors of higher resource use in 100% of bootstrap simulations. CONCLUSION: The economic impact of diagnostic uncertainty when managing paediatric febrile illness is significant, and the precautionary use of antibiotics is strongly associated with increased costs. The use of ED resources is highest among infants (aged less than 3 months) and those infants managed by lesser experienced doctors, independent of clinical severity. Diagnostic advances which could increase confidence to withhold antibiotics may yield considerable efficiency gains in these groups, where the perceived risks of failing to identify potentially life-threatening bacterial infections are greatest.