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IntroductionAging populations with increasing frailty have major implications for health services internationally, and evidence-based treatment becomes increasingly important. The development of an electronic Frailty Index (eFI) using routine primary care data facilitates implementation of evidence-based interventions. However, the eFI does not account for time restrictions regarding when information was recorded.
Objectives and ApproachOur aim is to implement and further validate the eFI using the Secure Anonymised Information Linkage (SAIL) databank, introducing refinements based on time restrictions.
Our implementation of the eFI identifies frailty based on 1574 Read codes, which are mapped amongst 36 categories known as deficits. The eFI is based on the internationally established cumulative deficit model, and each deficit contributes equally to the eFI value.
However, although each deficit is equally weighted, only one of them is currently time dependent. We therefore analyse the time at which each deficit is identified, and propose time dependent cut-points based on our findings.
ResultsWe were able to successfully implement the eFI using data from over 400,000 individuals from the Welsh population using data held in the SAIL databank. Our results agree with the baseline characteristics and distributions of frailty found in the original development of the eFI.
We also found that the percentage of individuals identified as frail increased as the number of years of records included was increased. Furthermore, the increase in percentage year by year was almost linear for a number of the deficits. This led to the identification of time bounds for particular deficits, which could help to refine future implementations of the eFI.
Conclusion/ImplicationsOur work validates and refines the eFI, which is a particularly useful resource as it uses existing primary care data to identify frailty, meaning no additional resources are required. Furthermore, our implementation is readily available, meaning that future research related to frailty is easily reproducible and achievable by others.

BackgroundAging populations with increasing frailty have major implications for health services, and evidence-based treatment becomes increasingly important. The development of the electronic Frailty Index (eFI) using routine primary care data facilitatesthe implementation of evidence-based interventions and care.
MethodOur implementation of the eFI in the Secure Anonymised Information Linkage (SAIL) databank identifies frailty based on 1574 Read codes, which are mapped amongst 36 categories known as deficits. The eFI is based on a cumulative deficitmodel, and each deficit contributes equally to the eFI value.
FindingsAlthough each deficit is equally weighted, only one is currently time dependent. We therefore analysed the cumulative prevalence of each deficit on a year-by-year basis. This led to the identification of time bounds for particular deficits, which willhelp to refine future implementations of the eFI. We also further validated the eFI using data from over 400,000 individuals held in SAIL.
ConclusionThe eFI is particularly useful as it uses existing data to identify frailty, meaning no additional resources are required. Furthermore, our implementation is readily available, meaning that future research related to frailty is easily achievable by others.

AbstractBackgroundMainstream economic evaluations methods may not be appropriate to capture the range of effects triggered by interventions for people with intellectual disabilities. In this systematic review, we aimed to identify, assess and synthesise the arguments in the literature on how the effects of interventions for people with intellectual disabilities could be measured in economic evaluations.MethodWe searched for studies providing relevant arguments by running multi‐database, backward, forward citation and grey literature searches. Following title/abstract and full‐text screening, the arguments extracted from the included studies were summarised and qualitatively assessed in a narrative synthesis.ResultsOur final analysis included three studies, with their arguments summarised in different methodological areas.ConclusionsBased on the evidence, we suggest the use of techniques more attuned to the population with intellectual disabilities, such sensitive preference‐based instruments to collect health states data, and mapping algorithms to obtain utility values.

AbstractBackgroundFalls are common among people with intellectual disabilities. Many falls happen within the home. Our scoping review aimed to identify evidence for falls‐risk factors and falls‐prevention interventions for this population.MethodWe conducted a multi‐database search to identify any type of published study that explored falls‐risk factors or falls‐prevention interventions for people with intellectual disabilities. Following a process of (i) title & abstract and (ii) full‐text screening, data was extracted from the included studies and described narratively.ResultsForty‐one studies were included. Risks are multifactorial. There was limited evidence of medical, behavioural/psychological, or environmental interventions to address modifiable risk factors, and no evidence of the interventions' cost‐effectiveness.ConclusionsClinically and cost effective, acceptable and accessible falls‐prevention pathways should be available for people with intellectual disabilities who are at risk of falls from an earlier age than the general population.

IntroductionAround a third of people aged 65+, and around half of people aged 80+ fall at least once a year in the United Kingdom. Homes may be adapted to try to prevent falls, but evidence on the effectiveness of home adaptations is limited.
Objectives and ApproachOur objective was to determine if proactive (Care&Repair service) and reactive (rapid response) home adaptations provided by Care&Repair Cymru resulted in a reduced risk of a fall for older people aged 60+ in Wales.
We constructed a longitudinal dataset from the Secure Anonymised Information Linkage Databank. We created quarterly intervals for 5-years pre and post the date a home adaptation was received, or a randomly assigned date for the comparator. Per quarter, we created a binary indicator of whether someone had a fall at home that was recorded in either the emergency department or hospital admission data sources for Wales. We included key demographic variables as covariates. We analysed the data using logistic regression and a difference-in-difference approach.
ResultsWe analysed 634,046 individuals, of whom 60,794 received the proactive Care&Repair service, and 47,244 received the reactive rapid response service. People receiving proactive or reactive home adaptations from Care & Repair were at around a two-fold increased risk of falling, compared to those who did not receive home adaptation with Odds Ratios (ORs) of 2.13 [95%CI: 2.07, 2.20] and 2.73 [2.64,2.81] respectively. Falls risk increased per quarter for all individuals, but after intervention delivery, the rate of increase fell in the intervention groups.
ConclusionPeople receiving home adaptations from Care&Repair had a higher chance of a fall, indicating the service was successfully identifying those in need. Falls risk increased for everyone over time, but this was counteracted for people receiving an intervention.

The incidence of stroke in India is one of the largest worldwide. With this scoping review, we assessed the evidence on the costs of stroke, which is essential to evaluate whether stroke care interventions are cost-effective. We adopted a healthcare sector and broader societal perspective and searched electronic databases for records including stroke cost estimates (up to 2020). Following deduplication and screening of 2,510 records, we extracted the data (converted into 2020 Indian rupees [INR]) and assessed the quality of eight eligible studies. These studies, published between 2011 and 2020, covered the whole of India and specific localities and were: cost-of-illness studies (n = 3); economic evaluations (n = 2); cross-sectional costing study (n = 1); simulated costing study (n = 1); and policy/clinical review (n = 1). Among the extracted estimates, the mean total costs of stroke care per patient for the period up to six months post admission ranged from ₹19,428.86 in a government hospital in Punjab to ₹118,040.15 in a private tertiary care centre in Ludhiana. The median total out-of-pocket (OOP) payments for cardiovascular disease-related expenditures ranged from ₹18,148.88 to ₹68,464.39 across different income groups. Despite methodological limitations, the data from our scoping review will help in designing economic evaluations of stroke care interventions in India.JEL Codes: C18, C80, D61, I15, I19