External validation of the Hospital Frailty Risk Score in France.

BACKGROUND: The Hospital Frailty Risk Score (HFRS) has made it possible internationally to identify subgroups of patients with characteristics of frailty from routinely collected hospital data. OBJECTIVE: To externally validate the HFRS in France. DESIGN: A retrospective analysis of the French medical information database. SETTING: 743 hospitals in Metropolitan France. SUBJECTS: All patients aged 75 years or older hospitalised as an emergency in 2017 (n = 1,042,234). METHODS: The HFRS was calculated for each patient based on the index stay and hospitalisations over the preceding 2 years. Main outcome measures were 30-day in-patient mortality, length of stay (LOS) >10 days and 30-day readmissions. Mixed logistic regression models were used to investigate the association between outcomes and HFRS score. RESULTS: Patients with high HFRS risk were associated with increased risk of mortality and prolonged LOS (adjusted odds ratio [aOR] = 1.38 [1.35-1.42] and 3.27 [3.22-3.32], c-statistics = 0.676 and 0.684, respectively), while it appeared less predictive of readmissions (aOR = 1.00 [0.98-1.02], c-statistic = 0.600). Model calibration was excellent. Restricting the score to data prior to index admission reduced discrimination of HFRS substantially. CONCLUSIONS: HFRS can be used in France to determine risks of 30-day in-patient mortality and prolonged LOS, but not 30-day readmissions. Trial registration: Reference ID on clinicaltrials.gov: ID: NCT03905629.

Are the needs of people with multiple long-term conditions being met? Evidence from the 2018 General Practice Patient Survey.

OBJECTIVES: To investigate individual, practice and area level variation in patient-reported unmet need among those with long-term conditions, in the context of general practice (GP) appointments and support from community-based services in England. DESIGN: Cross-sectional study using data from 199 150 survey responses. SETTING: Primary care and community-based services. PARTICIPANTS: Respondents to the 2018 English General Practice Patient Survey with at least one long-term condition. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcomes were the levels of unmet need in GP and local services among patients with multiple long-term conditions. Secondary outcomes were the proportion of variation explained by practice and area-level factors. RESULTS: There was no relationship between needs being fully met in patients' last practice appointment and number of long-term conditions once sociodemographic characteristics and health status were taken into account (5+conditions-OR=1.04, 95% CI 0.99 to 1.09), but there was a relationship for having enough support from local services to manage conditions (5+conditions-OR=0.84, 95% CI 0.80 to 0.88). Patients with multimorbidity that were younger, non-white or frail were less likely to have their needs fully met, both in GP and from local services. Differences between practices and local authorities explained minimal variation in unmet need. CONCLUSIONS: Levels of unmet need are high, particularly for support from community services to manage multiple conditions. Patients who could be targeted for support include people who feel socially isolated, and those who have difficulties with their day-to-day living. Younger patients and certain ethnic groups with multimorbidity are also more likely to have unmet needs. Increased personalisation and coordination of care among these groups may help in addressing their needs.

Frailty, hospital use and mortality in the older population: findings from the Newcastle 85+ study.

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.

Area level impacts on emergency hospital admissions of the integrated care and support pioneer programme in England: difference-in-differences analysis.

OBJECTIVE: To examine whether any differential change in emergency admissions could be attributed to integrated care by comparing pioneer and non-pioneer populations from a pre-pioneer baseline period (April 2010 to March 2013) over two follow-up periods: to 2014/2015 and to 2015/2016. DESIGN: Difference-in-differences analysis of emergency hospital admissions from English Hospital Episode Statistics. SETTING: Local authorities in England classified as either pioneer or non-pioneer. PARTICIPANTS: Emergency admissions to all NHS hospitals in England with local authority determined by area of residence of the patient. INTERVENTION: Wave 1 of the integrated care and support pioneer programme announced in November 2013. PRIMARY OUTCOME MEASURE: Change in hospital emergency admissions. RESULTS: The increase in the pioneer emergency admission rate from baseline to 2014/2015 was smaller at 1.93% and significantly different from that of the non-pioneers at 4.84% (p=0.0379). The increase in the pioneer emergency admission rate from baseline to 2015/2016 was again smaller than for the non-pioneers but the difference was not statistically significant (p=0.1879). CONCLUSIONS: It is ambitious to expect unequivocal changes in a high level and indirect indicator of health and social care integration such as emergency hospital admissions to arise as a result of the changes in local health and social care provision across organisations brought about by the pioneers in their early years. We should treat any sign that the pioneers have had such an impact with caution. Nevertheless, there does seem to be an indication from the current analysis that there were some changes in hospital use associated with the first year of pioneer status that are worthy of further exploration.

Outcomes of hospital admissions among frail older people: a 2-year cohort study.

BACKGROUND: 'Frailty crises' are a common cause of hospital admission among older people and there is significant focus on admission avoidance. However, identifying frailty before a crisis occurs is challenging, making it difficult to effectively target community services. Better longer-term outcome data are needed if services are to reflect the needs of the growing population of older people with frailty. AIM: To determine long-term outcomes of older people discharged from hospital following short (<72 hours) and longer hospital admissions compared by frailty status. DESIGN AND SETTING: Two populations aged ≥70 years discharged from hospital units: those following short 'ambulatory' admissions (<72 hours) and those following longer inpatient stays. METHOD: Data for 2-year mortality and hospital use were compared using frailty measures derived from clinical and hospital data. RESULTS: Mortality after 2 years was increased for frail compared with non-frail individuals in both cohorts. Patients in the ambulatory cohort classified as frail had increased mortality (Rockwood hazard ratio 2.3 [95% confidence interval {CI} = 1.5 to 3.4]) and hospital use (Rockwood rate ratio 2.1 [95% CI = 1.7 to 2.6]) compared with those patients classified as non-frail. CONCLUSION: Individuals with frailty who are discharged from hospital experience increased mortality and resource use, even after short 'ambulatory' admissions. This is an easily identifiable group that is at increased risk of poor outcomes. Health and social care systems might wish to examine their current care response for frail older people discharged from hospital. There may be value in a 'secondary prevention' approach to frailty crises targeting individuals who are discharged from hospital.

Re-admission patterns in England and the Netherlands: a comparison based on administrative data of all hospitals.

BACKGROUND: Examining variation in patterns of re-admissions between countries can be valuable for mutual learning in order to reduce unnecessary re-admissions. The aim of this study was to compare re-admission rates and reasons for re-admissions between England and the Netherlands. METHODS: We used data from 85 Dutch hospitals (1 355 947 admissions) and 451 English hospitals (5 260 227 admissions) in 2014 (96% of all Dutch hospitals and 100% of all English NHS hospitals). Re-admission data from England and the Netherlands were compared for all hospital patients and for specific diagnosis groups: pneumonia, urinary tract infection, chronic obstructive pulmonary disease, coronary atherosclerosis, biliary tract disease, hip fracture and acute myocardial infarction. Re-admissions were categorized using a classification system developed on administrative data. The classification distinguishes between potentially preventable re-admissions and other reasons for re-admission. RESULTS: England had a higher 30-day re-admission rate (adjusted for age and gender) compared to the Netherlands: 11.17% (95% CI 11.14-11.20%) vs. 9.83% (95% CI 9.77-9.88%). The main differences appeared to be in re-admissions for the elderly (England 17.2% vs. the Netherlands 10.0%) and in emergency re-admissions (England 85.3% of all 30-day re-admissions vs. the Netherlands 66.8%). In the Netherlands, however, more emergency re-admissions were classified as potentially preventable compared to England (33.8% vs. 28.8%). CONCLUSIONS: The differences found between England and the Netherlands indicate opportunities to reduce unnecessary re-admissions. For England this concerns more expanded palliative care, integrated social care and reduction of waiting times. In the Netherlands, the use of treatment plans for daily life could be increased.

Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study.

BACKGROUND: Older 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. METHODS: A 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. FINDINGS: In 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). INTERPRETATION: The 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. FUNDING: National Institute for Health Research.