Using spatial analysis to demonstrate the heterogeneity of the cardiovascular drug-prescribing pattern in Taiwan

Undernutrition among children and its determinants across the parliamentary constituencies of India: a geospatial analysis

In India, undernutrition among children has been extremely critical for the last few decades. Most analyses of undernutrition among Indian children have used the administrative boundaries of a state or a district level as a unit of analysis. This paper departs from such a practice and focuses instead on the political boundaries of a parliamentary constituency (PC) as the unit of analysis. The PC is a critical geopolitical unit where political parties and party candidates make election promises and implement programmes to improve the socio-economic condition of their electorate. A focus on child undernutrition at this level has the potential for greater policy and political traction and could lead to a paradigm shift in the strategy to tackle the problem by creating a demand for political accountability. Different dimensions and new approaches are also required to evaluate the socio-economic status and generate concrete evidence to find solutions to the problem. Given the significance of advanced analytical methods and models embedded into geographic information system (GIS), the current study, for the first time, uses GIS tools and techniques at the PC level, conducting in-depth analysis of undernutrition and its predictors. Hence, this paper examines the spatial heterogeneity in undernutrition across PCs by using geospatial techniques such as univariate and bivariate local indicator of spatial association and spatial regression models. The analysis highlights the high-low burden areas in terms of local hotspots and identifies the potential spatial risk factors of undernutrition across the constituencies. Striking variations in the prevalence of undernutrition across the constituencies were observed. Most of these constituencies that performed poorly both in terms of child nutrition and socio-economic indicators were located in the northern, western, and eastern parts of India. A statistically significant association of biological, socio-economic, and environmental factors such as women's body mass index, anaemia in children, poverty, household sanitation facilities, and institutional births was established. The results highlight the need to bring in a mechanism of political accountability that directly connects elected representatives to maternal and child health outcomes. The spatial variability and pattern of undernutrition indicators and their correlates indicate that priority setting in research may also be greatly influenced by the neighbourhood association.

Use of spatial panel-data models to investigate factors related to incidence of end-stage renal disease: a nationwide longitudinal study in Taiwan

BACKGROUND

The assumptions of conventional spatial models cannot estimate the responses across space and over time. Here we propose new spatial panel data models to investigate the association between the risk factors and incidence of end-stage renal disease (ESRD).

METHODS

A longitudinal (panel data) study was conducted using data from the National Health Insurance Database in Taiwan. We developed an algorithm to identify the patient's residence and estimate the ESRD rate in each township. Corresponding covariates, including patient comorbidities, history of medication use, and socio-environmental factors, were collected. Local Indicators of Spatial Association were used to describe local spatial clustering around an individual location. Moreover, a spatial panel data model was proposed to investigate the association between ESRD incidence and risk factors.

RESULTS

In total, 73,995 patients with ESRD were included in this study. The western region had a higher proportion of high incidence rates than the eastern region. The proportion of high incidence rates in the eastern areas increased over the years. We found that most "social environmental factors," except average income and air pollution (PM 2.5 and PM10), had a significant influence on the incidence rate of ESRD when considering spatial dependences of response and explanatory variables. Receiving non-steroidal anti-inflammatory drugs and aminoglycosides within 90 days prior to ESRD had a significant positive effect on the ESRD incidence rate.

CONCLUSION

Future comprehensive studies on townships located in higher-risk clusters of ESRD will help in designing healthcare policies for suitable action.

Spatial-temporal analysis of cause-specific cardiovascular hospital admission in Beijing, China

BACKGROUND

The main aim of this study was to explore the spatial-temporal patterns of cause-specific CVD admission in Beijing using retrospective SaTScan analysis.

METHODS

A spatial-temporal analysis was conducted at the district level based on the rates of total and cause-specific CVD admissions, including coronary heart disease (CHD), atrial fibrillation (AF), and heart failure (HF) from 2013 to 2017. We used joint point regression, Global Moran's I and Anselin's local Moran's I, together with Kulldorff's scan statistic.

RESULTS

Hospital admission trend decreased during the study period. Admission rates followed a spatially clustered pattern with differences occurring between cause-specific CVDs. Clusters were mainly identified in ecological preservation areas, with a more likely cluster found in Daxing, Fangshan, Xicheng district for total CVD, CHD, AF and HF, respectively.

CONCLUSIONS

Hospital admission of cause-specific CVD showed spatial clustered pattern, especially in ecological preservation areas.

Antibiotic prescribing patterns in general medical practices in England: Does area matter?

Antimicrobial resistance is an important public health concern. As most antibiotics are prescribed in primary care, understanding prescribing patterns in General Medical (GP) practices is vital. The aim of this study was a spatial pattern analysis of antibiotic prescribing rates in GP practices in England and to examine the association of potential clusters with area level socio-economic deprivation. The pattern analysis identified a number of hot and cold spots of antibiotic prescribing, with hot spots predominantly in the North of England. Spatial regression showed that patient catchments of hot spot practices were significantly more deprived than patient catchments of cold spot practices, especially in the domains of income, employment, education and health. This study suggests the presence of area level drivers resulting in clusters of high and low prescribing. Consequently, area level strategies may be needed for antimicrobial stewardship rather than national level strategies.

Exploring spatial patterns of cardiovascular disease in Sweden between 2000 and 2010

AIMS

Cardiovascular disease (CVD) is one of the leading causes of mortality and morbidity worldwide, including in Sweden. The main aim of this study was to explore the temporal trends and spatial patterns of CVD in Sweden using spatial autocorrelation analyses.

METHODS

The CVD admission rates between 2000 and 2010 throughout Sweden were entered as the input disease data for the analytic processes performed for the Swedish capital, Stockholm, and also for the whole of Sweden. Age-adjusted admission rates were calculated using a direct standardisation approach for men and women, and temporal trends analysis were performed on the standardised rates. Global Moran's I was used to explore the structure of patterns and Anselin's local Moran's I, together with Kulldorff's scan statistic were applied to explore the geographical patterns of admission rates.

RESULTS

The rates followed a spatially clustered pattern in Sweden with differences occurring between sexes. Accordingly, hot spots were identified in northern Sweden, with higher intensity identified for men, together with clusters in central Sweden. Cold spots were identified in the adjacency of the three major Swedish cities of Stockholm, Gothenburg and Malmö.

CONCLUSIONS

The findings of this study can serve as a basis for distribution of health-care resources, preventive measures and exploration of aetiological factors.

Mapping mHealth (mobile health) and mobile penetrations in sub-Saharan Africa for strategic regional collaboration in mHealth scale-up: an application of exploratory spatial data analysis

Background

Mobile health (mHealth), a term used for healthcare delivery via mobile devices, has gained attention as an innovative technology for better access to healthcare and support for performance of health workers in the global health context. Despite large expansion of mHealth across sub-Saharan Africa, regional collaboration for scale-up has not made progress since last decade.

Methods

As a groundwork for strategic planning for regional collaboration, the study attempted to identify spatial patterns of mHealth implementation in sub-Saharan Africa using an exploratory spatial data analysis. In order to obtain comprehensive data on the total number of mHelath programs implemented between 2006 and 2016 in each of the 48 sub-Saharan Africa countries, we performed a systematic data collection from various sources, including: the WHO eHealth Database, the World Bank Projects & Operations Database, and the USAID mHealth Database. Additional spatial analysis was performed for mobile cellular subscriptions per 100 people to suggest strategic regional collaboration for improving mobile penetration rates along with the mHealth initiative. Global Moran’s I and Local Indicator of Spatial Association (LISA) were calculated for mHealth programs and mobile subscriptions per 100 population to investigate spatial autocorrelation, which indicates the presence of local clustering and spatial disparities.

Results

From our systematic data collection, the total number of mHealth programs implemented in sub-Saharan Africa between 2006 and 2016 was 487 (same programs implemented in multiple countries were counted separately). Of these, the eastern region with 17 countries and the western region with 16 countries had 287 and 145 mHealth programs, respectively. Despite low levels of global autocorrelation, LISA enabled us to detect meaningful local clusters. Overall, the eastern part of sub-Saharan Africa shows high-high association for mHealth programs. As for mobile subscription rates per 100 population, the northern area shows extensive low-low association.

Conclusions

This study aimed to shed some light on the potential for strategic regional collaboration for scale-up of mHealth and mobile penetration. Firstly, countries in the eastern area with much experience can take the lead role in pursuing regional collaboration for mHealth programs in sub-Saharan Africa. Secondly, collective effort in improving mobile penetration rates for the northern area is recommended.

Electronic supplementary material

The online version of this article (doi:10.1186/s12992-017-0286-9) contains supplementary material, which is available to authorized users.

National survey of thrombolytic therapy for acute ischemic stroke in Taiwan 2003-2010

Data on thrombolytic therapy at the national level is scarce in Asia. Understanding current practice pattern is important for a policy maker in decision making. This cross-sectional study analyzed the utilization pattern of thrombolytic therapy for acute ischemic stroke (AIS) in Taiwan from 2003 through 2010 and identified factors associated with post-therapy intracerebral hemorrhage (ICH) and mortality. From the Taiwan National Health Insurance Research Database, we retrieved inpatient claims for patients with AIS. The frequency of thrombolytic therapy in AIS admissions and its association with the characteristics of patients, physicians, and hospitals were analyzed. Factors predicting ICH and in-hospital mortality were also analyzed using multiple logistic regressions. Of 394,988 patients with AIS, 2385 (.60%) had received thrombolytic therapy. The utilization rate increased from .03% in 2003 to 1.51% in 2010. Thrombolytic therapy was adopted earlier in a belt of high-frequency counties across rural midwestern Taiwan, twice the rate in the Taipei and Kaohsiung cities. The neurology specialty and hospital's service volume were the most dominant factors related to higher utilization, in addition to weekend admission and the patient's age and comorbidities. ICH and in-hospital mortality rates were 3.48% and 7.71%, respectively. Patients given thrombolytic therapy in hospitals with thrombolysis cases more than the 5.5/year had a lower risk of ICH (odds ratio: .53; 95% confidence interval: .31-.88). Compared with most developed countries, there is indeed much unmet need for stroke thrombolysis in Taiwan. Effective mechanism should be implemented to increase the thrombolysis rate safely and improve outcome for patients with AIS.

Using spatial analysis to predict health care use at the local level: a case study of type 2 diabetes medication use and its association with demographic change and socioeconomic status

Local health status and health care use may be negatively influenced by low local socio-economic profile, population decline and population ageing. To support the need for targeted local health care, we explored spatial patterns of type 2 diabetes mellitus (T2DM) drug use at local level and determined its association with local demographic, socio-economic and access to care variables. We assessed spatial variability in these associations. We estimated the five-year prevalence of T2DM drug use (2005-2009) in persons aged 45 years and older at four-digit postal code level using the University of Groningen pharmacy database IADB.nl. Statistics Netherlands supplied data on potential predictor variables. We assessed spatial clustering, correlations and estimated a multiple linear regression model and a geographically weighted regression (GWR) model. Prevalence of T2DM medicine use ranged from 2.0% to 25.4%. The regression model included the extent of population ageing, proportion of social welfare/benefits, proportion of low incomes and proportion of pensioners, all significant positive predictors of local T2DM drug use. The GWR model demonstrated considerable spatial variability in the association between T2DM drug use and above predictors and was more accurate. The findings demonstrate the added value of spatial analysis in predicting health care use at local level.

A systematic review of the application of spatial analysis in pharmacoepidemiologic research

PURPOSE

Although current reviews of the use of spatial analysis in general epidemiologic research illustrate an important and well-established role in exploring and predicting health, its application has not been reviewed in the subspecialty field of pharmacoepidemiology.

METHODS

We systematically reviewed the scientific literature to assess to what extent spatial analysis has been applied in pharmacoepidemiologic research and explored its potential added value.

RESULTS

A systematic search in PubMed and Embase/MEDLINE yielded 823 potentially relevant articles; 45 articles met our criteria for review. The studies were reviewed on study objective, applied spatial methods and units of analysis, and author-reported added value of the geographic approach used. Of the 45 included studies, 34 (76%) reported a geographic research objective. Comparative spatial methods were most often used (n = 25; 56%). Eleven studies used spatial statistics (32%); cluster analysis (n = 5) and aggregate data analysis (n = 4) being most common. Mapping was done in 15 studies (33%). The most common added value reported was to aid the planning of health policies and interventions (n = 24; 53%). A minority of pharmacoepidemiologic studies used a geographic approach and the applied methods were less advanced compared with the broader field of epidemiology.

CONCLUSIONS

Further advancements are needed to incorporate currently available spatial techniques to impact health care planning.

A review of geographic variation and Geographic Information Systems (GIS) applications in prescription drug use research

BACKGROUND

While understanding geography's role in healthcare has been an area of research for over 40 years, the application of geography-based analyses to prescription medication use is limited. The body of literature was reviewed to assess the current state of such studies to demonstrate the scale and scope of projects in order to highlight potential research opportunities.

OBJECTIVE

To review systematically how researchers have applied geography-based analyses to medication use data.

METHODS

Empiric, English language research articles were identified through PubMed and bibliographies. Original research articles were independently reviewed as to the medications or classes studied, data sources, measures of medication exposure, geographic units of analysis, geospatial measures, and statistical approaches.

RESULTS

From 145 publications matching key search terms, forty publications met the inclusion criteria. Cardiovascular and psychotropic classes accounted for the largest proportion of studies. Prescription drug claims were the primary source, and medication exposure was frequently captured as period prevalence. Medication exposure was documented across a variety of geopolitical units such as countries, provinces, regions, states, and postal codes. Most results were descriptive and formal statistical modeling capitalizing on geospatial techniques was rare.

CONCLUSION

Despite the extensive research on small area variation analysis in healthcare, there are a limited number of studies that have examined geographic variation in medication use. Clearly, there is opportunity to collaborate with geographers and GIS professionals to harness the power of GIS technologies and to strengthen future medication studies by applying more robust geospatial statistical methods.

Mapping English GP prescribing data: a tool for monitoring health-service inequalities

OBJECTIVE

The aim of this paper was to show that easily interpretable maps of local and national prescribing data, available from open sources, can be used to demonstrate meaningful variations in prescribing performance.

DESIGN

The prescription dispensing data from the National Health Service (NHS) Information Centre for the medications metformin hydrochloride and methylphenidate were compared with reported incidence data for the conditions, diabetes and attention deficit hyperactivity disorder, respectively. The incidence data were obtained from the open source general practitioner (GP) Quality and Outcomes Framework. These data were mapped using the Ordnance Survey CodePoint Open data and the data tables stored in a PostGIS spatial database. Continuous maps of spending per person in England were then computed by using a smoothing algorithm and areas whose local spending is substantially (at least fourfold) and significantly (p<0.05) higher than the national average are then highlighted on the maps.

SETTING

NHS data with analysis of primary care prescribing.

POPULATION

England, UK.

RESULTS

The spatial mapping demonstrates that several areas in England have substantially and significantly higher spending per person on metformin and methyphenidate. North Kent and the Wirral have substantially and significantly higher spending per child on methyphenidate.

CONCLUSIONS

It is possible, using open source data, to use statistical methods to distinguish chance fluctuations in prescribing from genuine differences in prescribing rates. The results can be interactively mapped at a fine spatial resolution down to individual GP practices in England. This process could be automated and reported in real time. This can inform decision-making and could enable earlier detection of emergent phenomena.

Geographical epidemiology of antibacterials in the preschool age

Abstract

Riassunto

Identification and location of hot and cold spots of treated prevalence of depression in Catalonia (Spain)

Background

Spatial analysis is a relevant set of tools for studying the geographical distribution of diseases, although its methods and techniques for analysis may yield very different results. A new hybrid approach has been applied to the spatial analysis of treated prevalence of depression in Catalonia (Spain) according to the following descriptive hypotheses: 1) spatial clusters of treated prevalence of depression (hot and cold spots) exist and, 2) these clusters are related to the administrative divisions of mental health care (catchment areas) in this region.

Methods

In this ecological study, morbidity data per municipality have been extracted from the regional outpatient mental health database (CMBD-SMA) for the year 2009. The second level of analysis mapped small mental health catchment areas or groups of municipalities covered by a single mental health community centre. Spatial analysis has been performed using a Multi-Objective Evolutionary Algorithm (MOEA) which identified geographical clusters (hot spots and cold spots) of depression through the optimization of its treated prevalence. Catchment areas, where hot and cold spots are located, have been described by four domains: urbanicity, availability, accessibility and adequacy of provision of mental health care.

Results

MOEA has identified 6 hot spots and 4 cold spots of depression in Catalonia. Our results show a clear spatial pattern where one cold spot contributed to define the exact location, shape and borders of three hot spots. Analysing the corresponding domain values for the identified hot and cold spots no common pattern has been detected.

Conclusions

MOEA has effectively identified hot/cold spots of depression in Catalonia. However these hot/cold spots comprised municipalities from different catchment areas and we could not relate them to the administrative distribution of mental care in the region. By combining the analysis of hot/cold spots, a better statistical and operational-based visual representation of the geographical distribution is obtained. This technology may be incorporated into Decision Support Systems to enhance local evidence-informed policy in health system research.

Regional differences in self-reported screening, prevalence and management of cardiovascular risk factors in Switzerland

Background

In Switzerland, health policies are decided at the local level, but little is known regarding their impact on the screening and management of cardiovascular risk factors (CVRFs). We thus aimed at assessing geographical levels of CVRFs in Switzerland.

Methods

Swiss Health Survey for 2007 (N = 17,879). Seven administrative regions were defined: West (Leman), West-Central (Mittelland), Zurich, South (Ticino), North-West, East and Central Switzerland. Obesity, smoking, hypertension, dyslipidemia and diabetes prevalence, treatment and screening within the last 12 months were assessed by interview.

Results

After multivariate adjustment for age, gender, educational level, marital status and Swiss citizenship, no significant differences were found between regions regarding prevalence of obesity or current smoking. Similarly, no differences were found regarding hypertension screening and prevalence. Two thirds of subjects who had been told they had high blood pressure were treated, the lowest treatment rates being found in East Switzerland: odds-ratio and [95% confidence interval] 0.65 [0.50-0.85]. Screening for hypercholesterolemia was more frequently reported in French (Leman) and Italian (Ticino) speaking regions. Four out of ten participants who had been told they had high cholesterol levels were treated and the lowest treatment rates were found in German-speaking regions. Screening for diabetes was higher in Ticino (1.24 [1.09 - 1.42]). Six out of ten participants who had been told they had diabetes were treated, the lowest treatment rates were found for German-speaking regions.

Conclusions

In Switzerland, cardiovascular risk factor screening and management differ between regions and these differences cannot be accounted for by differences in populations' characteristics. Management of most cardiovascular risk factors could be improved.