Analyzing the relationship between socioeconomic deprivation and outpatient Medicare Part D fluoroquinolone claim rates in Texas.

Introduction: Only a few studies have assessed the relationship between deprivation and excessive antibiotic use. In Texas, antimicrobial prescription rates are particularly high compared with the rest of the US. This study analyzed the association between local area socioeconomic deprivation and providers' fluoroquinolone claim rates among beneficiaries 65 years and older in Texas. Methods: This ecological study utilized provider- and area-level data from Medicare Part D Prescribers and the Social Deprivation Index (SDI) repositories. Negative binomial regression models were employed to evaluate the relationship between provider- and area-level characteristics (prescriber's gender, specialty, rural-urban community area, beneficiaries' demographics, area-level population, and SDI) and fluoroquinolone claim rates per 1,000 beneficiaries. Results: A total of 11,996 providers were included. SDI (IRR 0.98, 95% CI 0.97-0.99) and male providers (IRR 0.96, 95% CI 0.94-0.99) were inversely associated with claim rates. In contrast, several factors were associated with higher claim rates, including non-metropolitan areas (1.04, 95% CI 1.00-1.09), and practices with a high proportion of male (IRR 1.12, 95% CI 1.10-1.14), Black (IRR 1.05, 95% CI 1.03-1.07), or Medicaid beneficiaries (IRR 1.15, 95% CI 1.12-1.17). Effect modification was observed between SDI and rurality, with higher SDI in non-metropolitan areas associated with higher claim rates, whereas SDI in metropolitan areas was inversely related to claim rates. Conclusion: Lower fluoroquinolone claim rates were observed among Texas Medicare providers in metropolitan areas with higher SDI. Conversely, higher rates were observed in rural areas with higher SDI. More studies are needed to understand the underlying causes of this variation and develop effective stewardship interventions.

Geological hazards: from early warning systems to public health toolkits.

Extreme geological events, such as earthquakes, are a significant global concern and sometimes their consequences can be devastating. Geographic information plays a critical role in health protection regarding hazards, and there are a range of initiatives using geographic information to communicate risk as well as to support early warning systems operated by geologists. Nevertheless we consider there to remain shortfalls in translating information on extreme geological events into health protection tools, and suggest that social scientists have an important role to play in aiding the development of a new generation of toolkits aimed at public health practitioners. This viewpoint piece reviews the state of the art in this domain and proposes potential contributions different stakeholder groups, including social scientists, could bring to the development of new toolkits.

Using geographical information systems and cartograms as a health service quality improvement tool.

INTRODUCTION: 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.

Mapping mental health service access: achieving equity through quality improvement.

BACKGROUND: 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 to 120 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.

Prevalence of cardiovascular disease risk amongst the population eligible for the NHS Health Check Programme.

BACKGROUND: 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.

Methods and tools for geographical mapping and analysis in primary health care.

AIM: The purpose of this paper is to review methods and tools for mapping, visualising and exploring geographic information to aid in primary health care (PHC) research and development. BACKGROUND: Mapping and spatial analysis of indicators of locality health profiles and healthcare needs assessment are well-established facets of health services research and development. However, while there are a range of different methods and tools used for these purposes, non-specialists responsible for managing the use of such information systems may find knowing where to start and what can be done a relatively steep learning curve. In this review, health and sociodemographic datasets are used to illustrate some key methods, tools and organisational issues, and builds upon two recent reviews in this journal, respectively, focusing on geographic data sources and geographic concepts. Those familiar with mapping and spatial analysis should find this a useful review of current matters. METHOD: A thematic review is presented with illustrative case studies relevant to PHC. It begins with a section on visualising and interpreting geographic information. This is followed by a section critiquing analytical methods. Consideration is given to software and deployment issues in a third section. Content is based on domain knowledge of the authors as a team of geographic information scientists and a public health practitioner working in tandem, with its scope restricted to routine applications of mapping and analysis. Advanced techniques such as spatio-temporal modelling are not considered, neither are methodological technicalities, although guidance on further reading is provided. SUMMARY: Geographical perspectives are now playing a significant role in PHC delivery, and for those engaged in informatics and/or managing population-level care, understanding key geographic information systems methods and terminologies are important as is gaining greater familiarity with institutional aspects of implementation.

Variations in cardiovascular disease under-diagnosis in England: national cross-sectional spatial analysis.

BACKGROUND: 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.

COPD in England: a comparison of expected, model-based prevalence and observed prevalence from general practice data.

BACKGROUND: Primary care data show that 765 000 people in England have a general practice (GP) diagnosis of chronic obstructive pulmonary disease (COPD). We hypothesized that this underestimates actual prevalence, and compared expected prevalence of COPD for English local authority areas with prevalence of diagnosed COPD. METHODS: Cross-sectional comparison of GP observed and model-based prevalence estimates (using spirometry data without clinical diagnosis) from the Health Survey for England. Local underdiagnosis of COPD was estimated as the ratio of observed to expected cases. We investigated geographical patterns using classical and geographically weighted regression analysis. RESULTS: Both observed and expected prevalence of COPD varied widely between areas. There was evidence of a 'north-south' divide, with both observed and modelled prevalence higher in the north. The ratio of diagnosed to expected prevalence varied from 0.20 to 0.95, with a mean of 0.52. Underdiagnosis was more pronounced in urban areas, and is particularly severe in London. The inclusion of GP numbers in the analysis yielded a stronger regression relationship, suggesting primary care supply affects diagnosis. CONCLUSION: Both observed and modelled COPD prevalence varies considerably across England. Cost-effective case-finding strategies should be evaluated, especially in areas where the ratio of observed to expected cases is low.

Attendance for injury at accident and emergency departments in London: a cross-sectional study.

OBJECTIVE: In order to set the foundation for the possible development of injury surveillance initiatives in north-west London, data on all presentations during 2002 at the nine accident and emergency departments (AEDs) in the relevant strategic health authority were examined. STUDY DESIGN: Descriptive, cross-sectional study. METHODS: A search algorithm was devised to extract records pertaining to injury presentations. The results were validated against a manually checked sample. Descriptive, quantitative analyses were performed. RESULTS: Only four of the nine hospitals in the study area routinely recorded data in a form useful for research on injury. In these four hospitals, presentations with injury accounted for 29.7% of total attendances at the AED, which is markedly lower than the national average. CONCLUSIONS: Certain characteristics of London regarding provision of primary care may explain why attendances for injury are proportionately low. However, the unusual pattern also underlines the importance of improving the quality of AED data in order to support adequate local surveillance of injury as the basis of efforts to prevent such incidents and to plan services to deal with injuries.