17 research outputs found
Attendance for injury at accident and emergency departments in London: a cross-sectional study
No full textKonrad Jamrozik, Edgar Samarasundera, Rebekah Miracle, Mitch Blair, Dinesh Sethi, Sonia Saxen and Simon Bowe
Socio-demographic data sources for monitoring locality health profiles and geographical planning of primary health care in the UK
No full textAim: the aim of this article is to provide UK-based primary health care research and development workers with a review of the current range of published, aggregated socio-demographic indicators that can be combined with health and health care datasets, for the purposes of monitoring locality health profiles and planning primary health care. Non-UK readers should nevertheless find the review of some relevance to their own national contexts.Background: there is an increasing range of resources available for such purposes and many of these datasets are equally useful outside of geographic work. The 2001 census introduced important changes to what routine data are available, as will the 2011 census. These changes have been paralleled by developments in the availability of socio-demographic indicators and the increasing popularity of geographic information systems. Health data can now be combined with those from socio-demographic more efficiently to produce what are termed value-added datasets.Methods: we review recent and planned developments in key data sources currently available in the UK and examine they can be used to monitor inequalities in primary health care inequalities and their role in the integration of primary health care needs mapping and forecasting with the spatial planning of areas undergoing regeneration.Conclusions: recent and planned developments in the availability of both socio-demographic datasets in tandem with parallel developments in spatial technologies have provided a flexible, potent geographical methodology for primary health care research and development. The current consultation process for the 2011 census provides those involved with primary health care research and development an opportunity to influence future development
Interactive map communication: pilot study of the visual perceptions and preferences of public health practitioners
No full textOlder people's navigation of urban areas as pedestrians: Measuring quality of the built environment using oral narratives and virtual routes
No full textStudies of navigation and walkability of the outdoor built environment are now common. However, few have taken a ‘virtual’ approach and in this study we examine the qualitative oral narratives of forty-eight older people provided whilst they watched film footage of a journey around an unfamiliar, urban landscape, and compare them with quantitative measures of the built environment. Pre-film cognitive/psychological tests were carried out, and the participants filled out a questionnaire covering
relevant issues such as feelings about home area and navigational behaviour. From the oral narratives we
found that signage as well as the presence of historical and distinctive buildings to be central. There was
little evidence that perception of residential (familiar) neighbourhood impacted upon commentary about the unfamiliar space suggesting the findings are generalisable to the wider senior citizen demographic and transferable to other localities. We propose a prototype index for urban landscape navigation from these findings
Variations in cardiovascular disease under-diagnosis in England: national cross-sectional spatial analysis
No full textBACKGROUND:
There is under-diagnosis of cardiovascular disease (CVD) in the English population, despite financial incentives to encourage general practices to register new cases. We compared the modelled (expected) and diagnosed (observed) prevalence of three cardiovascular conditions- coronary heart disease (CHD), hypertension and stroke- at local level, their geographical variation, and population and healthcare predictors which might influence diagnosis.
METHODS:
Cross-sectional observational study in all English local authorities (351) and general practices (8,372) comparing model-based expected prevalence with diagnosed prevalence on practice disease registers. Spatial analyses were used to identify geographic clusters and variation in regression relationships.
RESULTS:
A total of 9,682,176 patients were on practice CHD, stroke and transient ischaemic attack, and hypertension registers. There was wide spatial variation in observed: expected prevalence ratios for all three diseases, with less than five per cent of expected cases diagnosed in some areas. London and the surrounding area showed statistically significant discrepancies in observed: expected prevalence ratios, with observed prevalence much lower than the epidemiological models predicted. The addition of general practitioner supply as a variable yielded stronger regression results for all three conditions.
CONCLUSIONS:
Despite almost universal access to free primary healthcare, there may be significant and highly variable under-diagnosis of CVD across England, which can be partially explained by persistent inequity in GP supply. Disease management studies should consider the possible impact of under-diagnosis on population health outcomes. Compared to classical regression modelling, spatial analytic techniques can provide additional information on risk factors for under-diagnosis, and can suggest where healthcare resources may be most needed
Prevalence of cardiovascular disease risk amongst the population eligible for the NHS Health Check Programme.
No full textBACKGROUND: The National Health Service (NHS) Health Check Programme aims to identify and manage patients in England aged 40-74 years with a 10-year cardiovascular disease (CVD) risk score over 20%. We aimed to assess the prevalence of high CVD risk in the English population, using the two CVD risk scores and the 20% cut off mandated in national policy, and the prevalence of risk factors within this population. DESIGN: Modelling study using patients registered in general practice in England. METHODS: Using data from the Health Survey for England, we modelled the prevalence of high CVD risk in general practice populations. RESULTS: Of those eligible for an NHS Health Check, 10.5% (2,012,000) had a risk score greater than 20% using the QRISK2 risk score; 22.0% (4,267,000) using Joint British Societies' (JBS2) score. There was a median of 206 (range 0-1693) and 447 (0-3321) patients per practice at high risk respectively, with wide geographic variation. Within the high-risk population, there was a high prevalence of CVD risk factors; in the QRISK2 population, for example 82.6% were physically inactive. To reduce risk in those at high CVD risk, we estimate the total costs of the Programme to be £176 million using QRISK2 or £378 million using JBS2. CONCLUSIONS: A large number of high-risk patients will be identified by the Programme; health service commissioners must ensure the adequate provision and the targeted allocation of risk reduction services for the Programme to be effective. The NHS must consider whether extra costs using JBS2 are warranted. The Programme must be fully monitored to ensure its cost effectiveness and appropriate outcomes such as the numbers at high risk assessed
Using geographical information systems and cartograms as a health service quality improvement tool
No full textIntroduction: Disease prevalence can be spatially analysed to provide support for service implementation and health care planning, these analyses often display geographic variation. A key challenge is to communicate these results to decision makers, with variable levels of Geographic Information Systems (GIS) knowledge, in a way that represents the data and allows for comprehension. The present research describes the combination of established GIS methods and software tools to produce a novel technique of visualising disease admissions and to help prevent misinterpretation of data and less optimal decision making. The aim of this paper is to provide a tool that supports the ability of decision makers and service teams within health care settings to develop services more efficiently and better cater to the population; this tool has the advantage of information on the position of populations, the size of populations and the severity of disease. Methods: A standard choropleth of the study region, London, is used to visualise total emergency admission values for Chronic Obstructive Pulmonary Disease and bronchiectasis using ESRI's ArcGIS software. Population estimates of the Lower Super Output Areas (LSOAs) are then used with the ScapeToad cartogram software tool, with the aim of visualising geography at uniform population density. An interpolation surface, in this case ArcGIS' spline tool, allows the creation of a smooth surface over the LSOA centroids for admission values on both standard and cartogram geographies. The final product of this research is the novel Cartogram Interpolation Surface (CartIS). Results: The method provides a series of outputs culminating in the CartIS, applying an interpolation surface to a uniform population density. The cartogram effectively equalises the population density to remove visual bias from areas with a smaller population, while maintaining contiguous borders. CartIS decreases the number of extreme positive values not present in the underlying data as can be found in interpolation surfaces. Discussion: This methodology provides a technique for combining simple GIS tools to create a novel output, CartIS, in a health service context with the key aim of improving visualisation communication techniques which highlight variation in small scale geographies across large regions. CartIS more faithfully represents the data than interpolation, and visually highlights areas of extreme value more than cartograms, when either is used in isolation. © 2014 The Authors
Mapping mental health service access: achieving equity through quality improvement.
No full textBackground Improving access to psychological therapies (IAPTs) services deliver evidence-based care to people with depression and anxiety. A quality improvement (QI) initiative was undertaken by an IAPT service to improve referrals providing an opportunity to evaluate equitable access. Methods QI methodologies were used by the clinical team to improve referrals to the service. The collection of geo-coded data allowed referrals to be mapped to small geographical areas according to deprivation. Results A total of 6078 patients were referred to the IAPT service during the period of analysis and mapped to120 unique lower super output areas (LSOAs). The average weekly referral rate rose from 17 during the baseline phase to 43 during the QI implementation phase. Spatial analysis demonstrated all 15 of the high deprivation/low referral LSOAs were converted to high deprivation/high or medium referral LSOAs following the QI initiative. Conclusion This work highlights the importance of QI in developing clinical services aligned to the needs of the population through the analysis of routine data matched to health needs. Mapping can be utilized to communicate complex information to inform the planning and organization of clinical service delivery and evaluate the progress and sustainability of QI initiatives.</p
Feasibility study of geospatial mapping of chronic disease risk to inform public health commissioning
No full textThis final article is available for use under the terms of the Creative Commons Attribution Non-Commercial 2.0 Licence; see http://bmjopen.bmj.co
