SummaryBackgroundOlder people are increasing users of health care globally. We aimed to establish whether older people with characteristics of frailty and who are at risk of adverse health-care outcomes could be identified using routinely collected data.MethodsA three-step approach was used to develop and validate a Hospital Frailty Risk Score from International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) diagnostic codes. First, we carried out a cluster analysis to identify a group of older people (≥75 years) admitted to hospital who had high resource use and diagnoses associated with frailty. Second, we created a Hospital Frailty Risk Score based on ICD-10 codes that characterised this group. Third, in separate cohorts, we tested how well the score predicted adverse outcomes and whether it identified similar groups as other frailty tools.FindingsIn the development cohort (n=22 139), older people with frailty diagnoses formed a distinct group and had higher non-elective hospital use (33·6 bed-days over 2 years compared with 23·0 bed-days for the group with the next highest number of bed-days). In the national validation cohort (n=1 013 590), compared with the 429 762 (42·4%) patients with the lowest risk scores, the 202 718 (20·0%) patients with the highest Hospital Frailty Risk Scores had increased odds of 30-day mortality (odds ratio 1·71, 95% CI 1·68–1·75), long hospital stay (6·03, 5·92–6·10), and 30-day readmission (1·48, 1·46–1·50). The c statistics (ie, model discrimination) between individuals for these three outcomes were 0·60, 0·68, and 0·56, respectively. The Hospital Frailty Risk Score showed fair overlap with dichotomised Fried and Rockwood scales (kappa scores 0·22, 95% CI 0·15–0·30 and 0·30, 0·22–0·38, respectively) and moderate agreement with the Rockwood Frailty Index (Pearson's correlation coefficient 0·41, 95% CI 0·38–0·47).InterpretationThe Hospital Frailty Risk Score provides hospitals and health systems with a low-cost, systematic way to screen for frailty and identify a group of patients who are at greater risk of adverse outcomes and for whom a frailty-attuned approach might be useful.FundingNational Institute for Health Research.

we confirm a widely used definition of CGA. Key outcomes are death, disability and institutionalisation. The main beneficiaries in hospital are older people with acute illness. The presence of frailty has not been widely examined as a determinant of CGA outcome.

Background The aim of this study was to provide high-quality evidence on delivering hospital-wide Comprehensive Geriatric Assessment (CGA). Objective(s) (1) To define CGA, its processes, outcomes and costs in the published literature, (2) to identify the processes, outcomes and costs of CGA in existing hospital settings in the UK, (3) to identify the characteristics of the recipients and beneficiaries of CGA in existing hospital settings in the UK and (4) to develop tools that will assist in the implementation of hospital-wide CGA. Design Mixed-methods study combining a mapping review, national survey, large data analysis and qualitative methods. Participants People aged ≥ 65 years in acute hospital settings. Data sources Literature review – Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, MEDLINE and EMBASE. Survey – acute hospital trusts. Large data analyses – (1) people aged ≥ 75 years in 2008 living in Leicester, Nottingham or Southampton (development cohort, n = 22,139); (2) older people admitted for short stay (Nottingham/Leicester, n = 825) to a geriatric ward (Southampton, n = 246) or based in the community (Newcastle, n = 754); (3) people aged ≥ 75 years admitted to acute hospitals in England in 2014–15 (validation study, n = 1,013,590). Toolkit development – multidisciplinary national stakeholder group (co-production); field-testing with cancer/surgical teams in Newcastle/Leicester. Results Literature search – common outcomes included clinical, operational and destinational, but not patient-reported, outcome measures. Survey – highly variable provision of multidisciplinary assessment and care across hospitals. Quantitative analyses – in the development cohort, older people with frailty diagnoses formed a distinct group and had higher non-elective hospital use than older people without a frailty diagnosis. Patients with the highest 20% of hospital frailty risk scores had increased odds of 30-day mortality [odds ratio (OR) 1.7], long length of stay (OR 6.0) and 30-day re-admission (OR 1.5). The score had moderate agreement with the Fried and Rockwood scales. Pilot toolkit evaluation – participants across sites were still at the beginning of their work to identify patients and plan change. In particular, competing definitions of the role of geriatricians were evident. Limitations The survey was limited by an incomplete response rate but it still provides the largest description of acute hospital care for older people to date. The risk stratification tool is not contemporaneous, although it remains a powerful predictor of patient harms. The toolkit evaluation is still rather nascent and could have meaningfully continued for another year or more. Conclusions CGA remains the gold standard approach to improving a range of outcomes for older people in acute hospitals. Older people at risk can be identified using routine hospital data. Toolkits aimed at enhancing the delivery of CGA by non-specialists can be useful but require prolonged geriatrician support and implementation phases. Future work could involve comparing the hospital-based frailty index with the electronic Frailty Index and further testing of the clinical toolkits in specialist services. Funding The National Institute for Health Research Health Services and Delivery Research programme.

Background Frailty is a significant determinant of health care utilisation and associated costs, both of which also increase with proximity to death. What is not known is how the relationships between frailty, proximity to death, hospital use and costs develop in a population aged 85 years and over. Methods This study used data from a prospective observational cohort, the Newcastle 85+ Study, linked with hospital episode statistics and death registrations. Using the Rockwood frailty index (cut off <0.25), we analysed the relationship between frailty and mortality, proximity to death, hospital use and hospital costs over 2, 5 and 7 years using descriptive statistics, Kaplan–Meier survival curves, Cox’s proportional hazards and negative binomial regression models. Results Baseline frailty was associated with a more than two-fold increased risk of mortality after 7 years, compared to people who were non-frail. Participants classified as frail spent more time in hospital over 7 years than the non-frail, but this difference declined over time. Baseline frailty was not associated with increased time spent in hospital during the last 90 days of life. Conclusion Evidence continues to accrue on the impact of frailty on emergency health care use. Hospital and community services need to adapt to meet the challenge of introducing new proactive and preventative approaches, designed to achieve benefits in clinical and/or cost effectiveness of frailty management.

ObjectivesTo develop a method for calculating age-specific hospital catchment populations (HCPs) for children and young people (CYP) in England. To show how these methods allow geographical variation in hospital activity to be investigated and addressed more effectively.DesignRetrospective, secondary analysis of existing national datasets.SettingInpatient care of CYP (0-18 years) in England.ParticipantsHospital Episode Statistics (HES) data were accessed for all inpatient admissions (elective and emergency) for CYP from birth to 18 years, 364 days, for 2011/2012–2014/2015. In 2014/2015, 857 112 admissions were analysed, from an eligible population of approximately 11.9 million CYP.Outcome measuresFor each hospital Trust, the catchment population of CYP was calculated; Trust-level admission rates per thousand per year were then calculated for admissions due to (1) any diagnostic code, (2) primary diagnosis of epilepsy and (3) epilepsy listed as primary diagnosis or comorbidity.ResultsEstimated 2014/2015 HCPs for CYP ranged from 268 558 for Barts Health NHS Trust to around 30 000 for the smallest acute general paediatric services and below 10 000 for many Trusts providing specialist services. As expected, the composition of HCPs was fairly consistent for age breakdown but levels of deprivation varied widely. After standardising for population characteristics, admission rates with a primary diagnosis of epilepsy ranged from 14.3 to 157.7 per 100 000 per year (11.0-fold variation) for Trusts providing acute general paediatric services. All-cause admission rates showed less variation, ranging from 4033 to 11 681 per 100 000 per year (2.9-fold variation).ConclusionsUse of age-specific catchment populations allows variation in hospital activity to be linked to specific teams and care pathways. This provides an evidence base for initiatives to tackle unwarranted variation in healthcare activity and health outcomes.