scholarly journals Construction and Validation of a Frailty Index in Primary Care in Italy: The Health-Search Frailty Index

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 533-534
Author(s):  
Davide Vetrano ◽  
Alberto Zucchelli ◽  
Graziano Onder ◽  
Roberto Bernabei ◽  
Laura Fratiglioni ◽  
...  
Keyword(s):  
Primary Care ◽  
Frailty Index ◽  
External Validation ◽  
Geographical Area ◽  
Population Level ◽  
Survival Models ◽  
National Study ◽  
Personalized Care ◽  
Primary Care Data ◽  
Data Driven Approach

Abstract Recognizing frailty in primary care is important to implement personalized care pathways and for prognostication. The aim of this study was to build and validate a frailty index based on routinely collected primary care data in Italy. We used clinical data from 308,280 Italian primary care patients 60+ with at least 5 years of follow-up, part of the Health Search Database. A heuristic algorithm was used to select the deficits to be included in a highly performant frailty index. The fitness of the index was assessed through the c-statistics derived by survival models. Results were externally validated using the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K). After testing 3.4 million of deficits combinations, 25 deficits were selected to be included in the Health Search Frailty Index (HS-FI). After adjusting by sex, age and geographical area, the HS-FI was associated with 5-year mortality (HR per 0.1 increase 1.99; 95%CI 1.95-2.02) and hospitalization rate (HR per 0.1 increase 1.25; 95%CI 1.23-1.27). In the external validation cohort, HS-FI independently predicted mortality, hospitalization, incident disability, incident dementia, and incident falls. This is the first frailty index built following a data-driven approach, using national representative primary care data. The implementation of such tool – derived by routinely collected data – in primary care software will ease the prompt, comparable and reliable recognition of frailty at the population level.

scholarly journals External validation of the electronic Frailty Index using the population of Wales within the Secure Anonymised Information Linkage Databank

2019 ◽  
Vol 48 (6) ◽  
pp. 922-926 ◽  
Author(s):  
Joe Hollinghurst ◽  
Richard Fry ◽  
Ashley Akbari ◽  
Andy Clegg ◽  
Ronan A Lyons ◽  
...  
Keyword(s):  
Cox Regression ◽  
Care Home ◽  
Frailty Index ◽  
External Validation ◽  
Care Services ◽  
Primary Care Data ◽  
Hazard Ratios ◽  
Health And Social Care ◽  
National Implementation ◽  
Transition Times

Abstract Background frailty has major implications for health and social care services internationally. The development, validation and national implementation of the electronic Frailty Index (eFI) using routine primary care data has enabled change in the care of older people living with frailty in England. Aims to externally validate the eFI in Wales and assess new frailty-related outcomes. Study design and setting retrospective cohort study using the Secure Anonymised Information Linkage (SAIL) Databank, comprising 469,000 people aged 65–95, registered with a SAIL contributing general practice on 1 January 2010. Methods four categories (fit; mild; moderate and severe) of frailty were constructed using recognised cut points from the eFI. We calculated adjusted hazard ratios (HRs) from Cox regression models for validation of existing outcomes: 1-, 3- and 5-year mortality, hospitalisation, and care home admission for validation. We also analysed, as novel outcomes, 1-year mortality following hospitalisation and frailty transition times. Results HR trends for the validation outcomes in SAIL followed the original results from ResearchOne and THIN databases. Relative to the fit category, adjusted HRs in SAIL (95% CI) for 1-year mortality following hospitalisation were 1.05 (95% CI 1.03-1.08) for mild frailty, 1.24 (95% CI 1.21-1.28) for moderate frailty and 1.51 (95% CI 1.45-1.57) for severe frailty. The median time (lower and upper quartile) between frailty categories was 2,165 days (lower and upper quartiles: 1,510 and 2,831) from fit to mild, 1,155 days (lower and upper quartiles: 756 and 1,610) from mild to moderate and 898 days (lower and upper quartiles: 584 and 1,275) from moderate to severe. Conclusions further validation of the eFI showed robust predictive validity and utility for new outcomes.

scholarly journals Assessing Global Frailty Scores: Development of a Global Burden of Disease-Frailty Index (GBD-FI)

2020 ◽  
Vol 17 (16) ◽  
pp. 5695
Author(s):  
Mark O’Donovan ◽  
Duygu Sezgin ◽  
Zubair Kabir ◽  
Aaron Liew ◽  
Rónán O’Caoimh
Keyword(s):  
Burden Of Disease ◽  
Accumulation Rate ◽  
Frailty Index ◽  
External Validation ◽  
Population Level ◽  
Face Validity ◽  
Global Burden Of Disease ◽  
Global Burden ◽  
Deficit Accumulation ◽  
Life Years

Frailty is an independent age-associated predictor of morbidity and mortality. Despite this, many countries lack population estimates with large heterogeneity between studies. No population-based standardised metric for frailty is available. We applied the deficit accumulation model of frailty to create a frailty index (FI) using population-level estimates from the Global Burden of Disease (GBD) 2017 study across 195 countries to create a novel GBD frailty index (GBD-FI). Standard FI criteria were applied to all GBD categories to select GBD-FI items. Content validity was assessed by comparing the GBD-FI with a selection of established FIs. Properties including the rate of deficit accumulation with age were examined to assess construct validity. Linear regression models were created to assess if mean GBD-FI scores predicted one-year incident mortality. From all 554 GBD items, 36 were selected for the GBD-FI. Face validity against established FIs was variable. Characteristic properties of a FI—higher mean score for females and a deficit accumulation rate of approximately 0.03 per year, were observed. GBD-FI items were responsible for 19% of total Disability-Adjusted Life Years for those aged ≥70 years in 2017. Country-specific mean GBD-FI scores ranged from 0.14 (China) to 0.19 (Hungary) and were a better predictor of mortality from non-communicable diseases than age, gender, Healthcare Access and Quality Index or Socio-Demographic Index scores. The GBD-FI is a valid measure of frailty at population-level but further external validation is required.

Application of an electronic Frailty Index in Australian primary care: data quality and feasibility assessment

2018 ◽  
Vol 31 (5) ◽  
pp. 653-660 ◽  
Author(s):  
Rachel C. Ambagtsheer ◽  
Justin Beilby ◽  
Julia Dabravolskaj ◽  
Marjan Abbasi ◽  
Mandy M. Archibald ◽  
...  
Keyword(s):  
Primary Care ◽  
Data Quality ◽  
Frailty Index ◽  
Feasibility Assessment ◽  
Primary Care Data

scholarly journals Lung cancer in symptomatic patients presenting in primary care: a systematic review of risk prediction tools

2017 ◽  
Vol 67 (659) ◽  
pp. e396-e404 ◽  
Author(s):  
Mia Schmidt-Hansen ◽  
Sabine Berendse ◽  
Willie Hamilton ◽  
David R Baldwin
Keyword(s):  
Lung Cancer ◽  
Systematic Review ◽  
Primary Care ◽  
Risk Prediction ◽  
External Validation ◽  
Clinical Decision ◽  
Cochrane Library ◽  
Specialist Care ◽  
Prediction Tools ◽  
Primary Care Data

BackgroundLung cancer is the leading cause of cancer deaths. Around 70% of patients first presenting to specialist care have advanced disease, at which point current treatments have little effect on survival. The issue for primary care is how to recognise patients earlier and investigate appropriately. This requires an assessment of the risk of lung cancer.AimThe aim of this study was to systematically review the existing risk prediction tools for patients presenting in primary care with symptoms that may indicate lung cancerDesign and settingSystematic review of primary care data.MethodMedline, PreMedline, Embase, the Cochrane Library, Web of Science, and ISI Proceedings (1980 to March 2016) were searched. The final list of included studies was agreed between two of the authors, who also appraised and summarised them.ResultsSeven studies with between 1482 and 2 406 127 patients were included. The tools were all based on UK primary care data, but differed in complexity of development, number/type of variables examined/included, and outcome time frame. There were four multivariable tools with internal validation area under the curves between 0.88 and 0.92. The tools all had a number of limitations, and none have been externally validated, or had their clinical and cost impact examined.ConclusionThere is insufficient evidence for the recommendation of any one of the available risk prediction tools. However, some multivariable tools showed promising discrimination. What is needed to guide clinical practice is both external validation of the existing tools and a comparative study, so that the best tools can be incorporated into clinical decision tools used in primary care.

scholarly journals Exploring the Effect of Nice Guidelines on Prescribing for Childhood Atopic Eczema in Primary Care with An Interrupted Time Series

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
LIW Schreuders ◽  
SJ Ersser ◽  
C Thompson
Keyword(s):  
Primary Care ◽  
Atopic Eczema ◽  
Best Practice ◽  
Secondary Analysis ◽  
Clinical Excellence ◽  
Population Level ◽  
Prescribing Practices ◽  
Nice Guideline ◽  
Primary Care Data ◽  
First Time

IntroductionAtopic eczema (AE) is a chronic inflammatory skin condition affecting 20-32% of UK children, typically diagnosed and treated in primary care. National Institute of Health and Clinical Excellence (NICE, 2007) guidelines recommend all children presenting with AE in primary care are prescribed emollient; topical corticosteroids (TCS) are co-prescribed if indicated by severity. The proportion of children receiving recommended treatment and NICE guideline impact on prescribing practices is unknown. This study was the first to access population-level UK-wide primary care dermatology data from SystmOne. Objectives and ApproachWe explored treatment patterns for childhood AE documented in primary care data from SystmOne. Secondary analysis of retrospective, longitudinal primary care data for childhood (<12yo) AE-related consultations from 2002 to 2013. Four treatment scenarios were compared: 1) emollient and TCS co-prescribed (NICE-recommended for moderate-high severity presentation), 2) emollient only (NICE-recommended for mild severity presentation), 3) TCS only (not recommended), or 4) no topical treatment prescribed (not recommended). ARIMA used to examine step and trend-change in prescribing following guideline release. ResultsNICE-recommended treatments were more common following guideline release: emollient+TCS increased 8% (95%CI 7.7,8.7%); emollient alone increased 8% (95%CI 7.8,8.8%); TCS alone decreased 5% (95%CI -4.2,-5.1%); and no treatment decreased 11% (95%CI -11.3,-12.3%). Longitudinal analysis indicated increased NICE-recommended prescribing was due to pre-existing trends not significantly altered by the guideline release. By December 2013, ~334 children per month were still not receiving recommended AE treatment (37% of ~900 first-time consultations/month). Conclusion / ImplicationsAdherence to best practice guidelines for treatment and management of childhood atopic eczema is currently sub-optimal. Significant barriers to optimal use of this data could be achieved by improving design of data input interfaces with secondary use for research in mind. As well as study findings, this presentation will share challenges associated with utilising routinely collected SystmOne data for research purposes for the first time in the UK.

scholarly journals Further Development and Validation of the electronic Frailty Index using the Secure Anonymised Information Linkage Databank

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Joe Hollinghurst ◽  
Ashley Akbari ◽  
Sarah Rodgers ◽  
Andrew Clegg
Keyword(s):  
Primary Care ◽  
Frailty Index ◽  
Time Dependent ◽  
Future Research ◽  
Evidence Based ◽  
Deficit Model ◽  
Time Restrictions ◽  
Primary Care Data ◽  
Cumulative Deficit ◽  
Using Data

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.

scholarly journals HIV infection and COVID-19 death: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform

2020 ◽  
Author(s):  
Krishnan Bhaskaran ◽  
Christopher T Rentsch ◽  
Brian MacKenna ◽  
Anna Schultz ◽  
Amir Mehrkar ◽  
...  
Keyword(s):  
Primary Care ◽  
Hiv Infection ◽  
Cox Regression ◽  
Cohort Analysis ◽  
Geographical Area ◽  
Population Based ◽  
People Living With Hiv ◽  
Primary Care Data ◽  
Living With Hiv ◽  
Age And Sex

Background: It is unclear whether HIV infection is associated with risk of COVID-19 death. We aimed to investigate this in a large-scale population-based study in England. Methods: Working on behalf of NHS England, we used the OpenSAFELY platform to analyse routinely collected electronic primary care data linked to national death registrations. People with a primary care record for HIV infection were compared to people without HIV. COVID-19 death was defined by ICD-10 codes U07.1 or U07.2 anywhere on the death certificate. Cox regression models were used to estimate the association between HIV infection and COVID-19 death, initially adjusted for age and sex, then adding adjustment for index of multiple deprivation and ethnicity, and finally for a broad range of comorbidities. Interaction terms were added to assess effect modification by age, sex, ethnicity, comorbidities and calendar time. Results: 17.3 million adults were included, of whom 27,480 (0.16%) had HIV recorded. People living with HIV were more likely to be male, of black ethnicity, and from a more deprived geographical area than the general population. There were 14,882 COVID-19 deaths during the study period, with 25 among people with HIV. People living with HIV had nearly three-fold higher risk of COVID-19 death than those without HIV after adjusting for age and sex (HR=2.90, 95% CI 1.96-4.30). The association was attenuated but risk remained substantially raised, after adjustment for deprivation and ethnicity (adjusted HR=2.52, 1.70-3.73) and further adjustment for comorbidities (HR=2.30, 1.55-3.41). There was some evidence that the association was larger among people of black ethnicity (HR = 3.80, 2.15-6.74, compared to 1.64, 0.92-2.90 in non-black individuals, p-interaction=0.045) Interpretation: HIV infection was associated with a markedly raised risk of COVID-19 death in a country with high levels of antiretroviral therapy coverage and viral suppression; the association was larger in people of black ethnicity.

scholarly journals Measuring daily functioning in older persons using a frailty index: a cohort study based on routine primary care data

2020 ◽  
Vol 70 (701) ◽  
pp. e866-e873
Author(s):  
Willeke M Ravensbergen ◽  
Jeanet W Blom ◽  
Andrea WM Evers ◽  
Mattijs E Numans ◽  
Margot WM de Waal ◽  
...  
Keyword(s):  
Primary Care ◽  
Cohort Study ◽  
Older Persons ◽  
Frailty Index ◽  
Routine Care ◽  
Community Dwelling ◽  
Daily Functioning ◽  
Primary Care Data ◽  
Observational Cohort ◽  
Data Source

BackgroundElectronic health records (EHRs) are increasingly used for research; however, multicomponent outcome measures such as daily functioning cannot yet be readily extracted.AimTo evaluate whether an electronic frailty index based on routine primary care data can be used as a measure for daily functioning in research with community-dwelling older persons (aged ≥75 years).Design and settingCohort study among participants of the Integrated Systemic Care for Older People (ISCOPE) trial (11 476 eligible; 7285 in observational cohort; 3141 in trial; over-representation of frail people).MethodAt baseline (T0) and after 12 months (T12), daily functioning was measured with the Groningen Activities Restriction Scale (GARS, range 18–72). Electronic frailty index scores (range 0–1) at T0 and T12 were computed from the EHRs. The electronic frailty index (electronic Frailty Index — Utrecht) was tested for responsiveness and compared with the GARS as a gold standard for daily functioning.ResultsIn total, 1390 participants with complete EHR and follow-up data were selected (31.4% male; median age = 81 years, interquartile range = 78–85). The electronic frailty index increased with age, was higher for females, and lower for participants living with a partner. It was responsive after an acute major medical event; however, the correlation between the electronic frailty index and GARS at T0 and over time was limited.ConclusionBecause the electronic frailty index does not reflect daily functioning, further research on new methods to measure daily functioning with routine care data (for example, other proxies) is needed before EHRs can be a useful data source for research with older persons.

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