A Study of the Chars Livelihood Programme in Northern Bangladesh

The temporary islands and embankment areas, or chars, of the Jamuna River in northwest Bangladesh are home to three million people: poor and isolated, these rural communities face multiple livelihood challenges. Opportunities to smoothen irregular household cash-flow are limited and households in the region regularly adopt severe coping strategies -- such as the distress sale of assets and reduced food intake -- to meet consumption and emergency needs. The Chars Livelihood Programme (CLP) aims to ensure that most poor char dwellers in the Jamuna River Basin have access to appropriate financial services through Savings Groups

TB STIGMA – MEASUREMENT GUIDANCE

TB is the most deadly infectious disease in the world, and stigma continues to play a significant role in worsening the epidemic. Stigma and discrimination not only stop people from seeking care but also make it more difficult for those on treatment to continue, both of which make the disease more difficult to treat in the long-term and mean those infected are more likely to transmit the disease to those around them. TB Stigma – Measurement Guidance is a manual to help generate enough information about stigma issues to design and monitor and evaluate efforts to reduce TB stigma. It can help in planning TB stigma baseline measurements and monitoring trends to capture the outcomes of TB stigma reduction efforts. This manual is designed for health workers, professional or management staff, people who advocate for those with TB, and all who need to understand and respond to TB stigma

Ireland’s Fiscal Spending Multipliers

This paper estimates government spending multipliers for Ireland. We add to the existing literature on Ireland-specific fiscal spending multipliers in two key ways. First, we focus on measures of economic activity that remove distortions caused by foreign-owned multinational enterprises, thus allowing us to derive truer estimates of the impact on the domestic economy of changes in fiscal policy. Second, we employ a number of statistical approaches in order to sense-check the multiplier estimates we derive, including standard SVAR approaches, an expectations-augmented VAR (EVAR) approach, and estimates based on a large-scale structural model. Our results show that government investment can have positive and significant initial impacts on Irish output, though these effects tend to disappear and/or become statistically insignificant over the longer term. Other forms of fiscal spending do not have a statistically significant effect

Count every newborn; a measurement improvement roadmap for coverage data.

BACKGROUND: The Every Newborn Action Plan (ENAP), launched in 2014, aims to end preventable newborn deaths and stillbirths, with national targets of ≤12 neonatal deaths per 1000 live births and ≤12 stillbirths per 1000 total births by 2030. This requires ambitious improvement of the data on care at birth and of small and sick newborns, particularly to track coverage, quality and equity. METHODS: In a multistage process, a matrix of 70 indicators were assessed by the Every Newborn steering group. Indicators were graded based on their availability and importance to ENAP, resulting in 10 core and 10 additional indicators. A consultation process was undertaken to assess the status of each ENAP core indicator definition, data availability and measurement feasibility. Coverage indicators for the specific ENAP treatment interventions were assigned task teams and given priority as they were identified as requiring the most technical work. Consultations were held throughout. RESULTS: ENAP published 10 core indicators plus 10 additional indicators. Three core impact indicators (neonatal mortality rate, maternal mortality ratio, stillbirth rate) are well defined, with future efforts needed to focus on improving data quantity and quality. Three core indicators on coverage of care for all mothers and newborns (intrapartum/skilled birth attendance, early postnatal care, essential newborn care) have defined contact points, but gaps exist in measuring content and quality of the interventions. Four core (antenatal corticosteroids, neonatal resuscitation, treatment of serious neonatal infections, kangaroo mother care) and one additional coverage indicator for newborns at risk or with complications (chlorhexidine cord cleansing) lack indicator definitions or data, especially for denominators (population in need). To address these gaps, feasible coverage indicator definitions are presented for validity testing. Measurable process indicators to help monitor health service readiness are also presented. A major measurement gap exists to monitor care of small and sick babies, yet signal functions could be tracked similarly to emergency obstetric care. CONCLUSIONS: The ENAP Measurement Improvement Roadmap (2015-2020) outlines tools to be developed (e.g., improved birth and death registration, audit, and minimum perinatal dataset) and actions to test, validate and institutionalise proposed coverage indicators. The roadmap presents a unique opportunity to strengthen routine health information systems, crosslinking these data with civil registration and vital statistics and population-based surveys. Real measurement change requires intentional transfer of leadership to countries with the greatest disease burden and will be achieved by working with centres of excellence and existing networks

Engaging Stakeholders with Evidence and Uncertainty | CEDIL Methods Working Paper 4

Approaches for engaging stakeholders with policy decisions or research tend to favour either generalisable evidence from research or context-specific evidence, including local data and tacit knowledge. Some international development and humanitarian organisations are leading the way with practice and guidance for combining generalisable and context-specific evidence for local action around the world. Some local non-governmental organisations who base their learning on local evidence alone acknowledge their lack of attention to generalisable evidence as a shortcoming. Listening to both groups has resulted in a publicly available toolkit for bringing together generalisable evidence and local knowledge. CEDIL’s Methods Working Paper 4, ‘Engaging Stakeholders with Evidence and Uncertainty: Developing a Toolkit’, offers a new framework that helps choose appropriate stakeholder engagement methods while conducting research and supporting decision-making. The framework provides the foundation for a toolkit that distinguishes major differences in stakeholder engagement, illustrates pathways for choosing appropriate methods for stakeholder engagement, signposts evidence and practical tools to support stakeholder engagement, and guidance for identifying and understanding stakeholders and their relationships

Development and external validation of the electronic frailty index 2 using routine primary care electronic health record data

Background: The electronic frailty index (eFI) is nationally implemented into UK primary care electronic health record systems to support routine identification of frailty. The original eFI has some limitations such as equal weighting of deficit variables, lack of time constraints on variables known to resolve and definition of frailty category cut-points. We have developed and externally validated the eFI2 prediction model to predict the composite risk of home care package; hospital admission for fall/fracture; care home admission; or mortality within one year, addressing the limitations of the original eFI. // Methods: Linked primary, secondary and social care data from two independent retrospective cohorts of adults aged ≥65 in 2018 was used; the population of Bradford using the Connected Bradford dataset (development cohort, 78 760 patients) and the population of Wales, from the Secure Anonymised Information Linkage databank (external validation cohort, 660 417 patients). Candidate predictors included the original eFI variables, supplemented with variables informed by literature reviews and clinical expertise. The composite outcome was modelled using Cox regression. // Results: In internal validation the model had excellent discrimination (C-index = 0.803, Nagelkerke’s R2 = 0.0971) with good calibration (Calibration slope = 1.00). In external validation, the model had good discrimination (C-index = 0.723, Nagelkerke’s R2 = 0.064), with some evidence of miscalibration (Calibration slope = 1.104). // Conclusions: The eFI2 demonstrates robust prediction for key frailty-related outcomes, improving on the original eFI. Our use of novel methodology to develop and validate the eFI2 will advance the field of frailty-related research internationally, setting a new methodological standard

Why are we misdiagnosing urinary tract infection in older patients? A qualitative inquiry and roadmap for staff behaviour change in the emergency department

Purpose - The aim of this study was to identify the psychological and behavioural factors influencing clinicians managing older people with possible UTI in urgent care settings, and to develop an improvement roadmap. Methods - Michie’s behaviour change wheel and COM-B (Capability, Opportunity, Motivation, Behaviour Change) models were used as the theoretical basis for this study. Semi-structured interviews were undertaken with 21 purposively selected medical and nursing staff in a large urban emergency department in the East Midlands, United Kingdom. Analysis was informed by the framework approach. A participatory design approach was used to develop an improvement roadmap. Results - Key themes emerging from the semi-structured interviews included lack of knowledge on the role of urine dipstick testing, bias towards older people, automatic testing, time and resource constraints, pressures from peers and patients, and fear of the legal consequences of inaction. A thematic networks map indicated complex interactions between psychological and behavioural factors. Among more than 50 different intervention ideas identified by the workshop participants, two interventions were prioritised for implementation: i) controlling the use of dip stick urine tests; ii) providing individualised feedback to staff regarding the outcomes of patients diagnosed and treated for UTI. Conclusions - Psychological and behavioural factors play a significant role in the misdiagnosis of UTI in older people. Systematic approaches incorporating these factors might improve patient outcomes. Future studies should focus on implementation and evaluating their effectiveness and sustainability

Development and external validation of the eFalls tool: a multivariable prediction model for the risk of ED attendance or hospitalisation with a fall or fracture in older adults

Background: Falls are common in older adults and can devastate personal independence through injury such as fracture and fear of future falls. Methods to identify people for falls prevention interventions are currently limited, with high risks of bias in published prediction models. We have developed and externally validated the eFalls prediction model using routinely collected primary care electronic health records (EHR) to predict risk of emergency department attendance/hospitalisation with fall or fracture within 1 year. // Methods: Data comprised two independent, retrospective cohorts of adults aged ≥65 years: the population of Wales, from the Secure Anonymised Information Linkage Databank (model development); the population of Bradford and Airedale, England, from Connected Bradford (external validation). Predictors included electronic frailty index components, supplemented with variables informed by literature reviews and clinical expertise. Fall/fracture risk was modelled using multivariable logistic regression with a Least Absolute Shrinkage and Selection Operator penalty. Predictive performance was assessed through calibration, discrimination and clinical utility. Apparent, internal–external cross-validation and external validation performance were assessed across general practices and in clinically relevant subgroups. // Results: The model’s discrimination performance (c-statistic) was 0.72 (95% confidence interval, CI: 0.68 to 0.76) on internal–external cross-validation and 0.82 (95% CI: 0.80 to 0.83) on external validation. Calibration was variable across practices, with some over-prediction in the validation population (calibration-in-the-large, −0.87; 95% CI: −0.96 to −0.78). Clinical utility on external validation was improved after recalibration. // Conclusion: The eFalls prediction model shows good performance and could support proactive stratification for falls prevention services if appropriately embedded into primary care EHR systems

The Falls In Care Home study: a feasibility randomized controlled trial of the use of a risk assessment and decision support tool to prevent falls in care homes

Objective:To explore the feasibility of implementing and evaluating the Guide to Action Care Home fall prevention intervention.Design:Two-centre, cluster feasibility randomized controlled trial and process evaluation.Setting:Purposive sample of six diverse old age/learning disability, long stay care homes in Nottinghamshire, UK.Subjects:Residents aged over 50?years, who had fallen at least once in the past year, not bed-bound, hoist-dependent or terminally ill.Interventions:Intervention homes (n?=?3) received Guide to Action Care Home fall prevention intervention training and support. Control homes (n?=?3) received usual care.Outcomes:Recruitment, attrition, baseline and six-month outcome completion, contamination and intervention fidelity, compliance, tolerability, acceptance and impact.Results:A total of 81 of 145 (56%) care homes expressed participatory interest. Six of 22 letter respondent homes (27%) participated. The expected resident recruitment target was achieved by 76% (52/68). Ten (19%) residents did not complete follow-up (seven died, three moved). In intervention homes 36/114 (32%) staff attended training. Two of three (75%) care homes received protocol compliant training. Staff valued the training, but advised greater management involvement to improve intervention implementation. Fall risks were assessed, actioned and recorded in care records. Of 115 recorded falls, 533/570 (93%) of details were complete. Six-month resident fall rates were 1.9 and 4.0 per year for intervention and control homes, respectively.Conclusions:The Guide to Action Care Home is implementable under trial conditions. Recruitment and follow-up rates indicate that a definitive trial can be completed. Falls (primary outcome) can be ascertained reliably from care records

Development and external validation of the eFalls tool: a multivariable prediction model for the risk of ED attendance or hospitalisation with a fall or fracture in older adults.

Falls are common in older adults and can devastate personal independence through injury such as fracture and fear of future falls. Methods to identify people for falls prevention interventions are currently limited, with high risks of bias in published prediction models. We have developed and externally validated the eFalls prediction model using routinely collected primary care electronic health records (EHR) to predict risk of emergency department attendance/hospitalisation with fall or fracture within 1 year. Data comprised two independent, retrospective cohorts of adults aged ≥65 years: the population of Wales, from the Secure Anonymised Information Linkage Databank (model development); the population of Bradford and Airedale, England, from Connected Bradford (external validation). Predictors included electronic frailty index components, supplemented with variables informed by literature reviews and clinical expertise. Fall/fracture risk was modelled using multivariable logistic regression with a Least Absolute Shrinkage and Selection Operator penalty. Predictive performance was assessed through calibration, discrimination and clinical utility. Apparent, internal-external cross-validation and external validation performance were assessed across general practices and in clinically relevant subgroups. The model's discrimination performance (c-statistic) was 0.72 (95% confidence interval, CI: 0.68 to 0.76) on internal-external cross-validation and 0.82 (95% CI: 0.80 to 0.83) on external validation. Calibration was variable across practices, with some over-prediction in the validation population (calibration-in-the-large, -0.87; 95% CI: -0.96 to -0.78). Clinical utility on external validation was improved after recalibration. The eFalls prediction model shows good performance and could support proactive stratification for falls prevention services if appropriately embedded into primary care EHR systems. [Abstract copyright: © The Author(s) 2024. Published by Oxford University Press on behalf of the British Geriatrics Society.