Determining geographic areas and populations with timely access to cardiac catheterization facilities for acute myocardial infarction care in Alberta, Canada

Population Access to Hospital Emergency Departments: The Spatial Analysis in Public Health Research

The emergency medical services support the primary health care system. Hospital emergency departments (HEDs), which provide medical assistance to all patients in a state of emergency are of considerable importance to the system. When studying access to HEDs, attention should be focused on spatial relations resulting from the location of HEDs and the places of residence of the potential patients. The aim of the paper is to explain the level of spatial accessibility of HEDs and its changes as a result of organizational and spatial transformations of HEDs' networks in Poland. The research was conducted within two time series, comparing the changes in the distribution of HEDs in 2011 and 2021. GIS techniques were used to measure the distances between emergency departments and places of residence. It was observed that the transformation of the spatial organization of the hospital emergency department network in 2011-2021 resulted in the overall improvement of the spatial accessibility of these facilities, reducing the distance between them and places of residence.

Disparities in Geographical Access to Hospitals in Portugal

Geographical accessibility to health care services is widely accepted as relevant to improve population health. However, measuring it is very complex, mainly when applied at administrative levels that go beyond the small-area level. This is the case in Portugal, where the municipality is the administrative level that is most appropriate for implementing policies to improve the access to those services. The aim of this paper is to assess whether inequalities in terms of access to a hospital in Portugal have improved over the last 20 years. A population-weighted driving time was applied using the census tract population, the roads network, the reference hospitals’ catchment area and the municipality boundaries. The results show that municipalities are 25 min away from the hospital—3 min less than in 1991—and that there is an association with premature mortality, elderly population and population density. However, disparities between municipalities are still huge. Municipalities with higher rates of older populations, isolated communities or those located closer to the border with Spain face harder challenges and require greater attention from local administration. Since municipalities now have responsibilities for health, it is important they implement interventions at the local level to tackle disparities impacting access to healthcare.

Impact of traffic variability on geographic accessibility to 24/7 emergency healthcare for the urban poor: A GIS study in Dhaka, Bangladesh

Ensuring access to healthcare in emergency health situations is a persistent concern for health system planners. Emergency services, including critical care units for severe burns and coronary events, are amongst those for which travel time is the most crucial, potentially making a difference between life and death. Although it is generally assumed that access to healthcare is not an issue in densely populated urban areas due to short distances, we prove otherwise by applying improved methods of assessing accessibility to emergency services by the urban poor that take traffic variability into account. Combining unique data on emergency health service locations, traffic flow variability and informal settlements boundaries, we generated time-cost based service areas to assess the extent to which emergency health services are reachable by urban slum dwellers when realistic traffic conditions and their variability in time are considered. Variability in traffic congestion is found to have significant impact on the measurement of timely access to, and availability of, healthcare services for slum populations. While under moderate traffic conditions all slums in Dhaka City are within 60-minutes travel time from an emergency service, in congested traffic conditions only 63% of the city's slum population is within 60-minutes reach of most emergency services, and only 32% are within 60-minutes reach of a Burn Unit. Moreover, under congested traffic conditions only 12% of slums in Dhaka City Corporation comply with Bangladesh's policy guidelines that call for access to 1 health service per 50,000 population for most emergency service types, and not a single slum achieved this target for Burn Units. Emergency Obstetric Care (EmOC) and First Aid & Casualty services provide the best coverage, with nearly 100% of the slum population having timely access within 60-minutes in any traffic condition. Ignoring variability in traffic conditions results in a 3-fold overestimation of geographic coverage and masks intra-urban inequities in accessibility to emergency care, by overestimating geographic accessibility in peripheral areas and underestimating the same for central city areas. The evidence provided can help policy makers and urban planners improve health service delivery for the urban poor. We recommend that taking traffic conditions be taken into account in future GIS-based analysis and planning for healthcare service accessibility in urban areas.

A two-stage spatial allocation model for elderly healthcare facilities in large-scale affordable housing communities: a case study in Nanjing City

Background

As the proportion of elderly residents living in large-scale affordable housing communities (LAHCs) increases in China, serious problems have become apparent related to the spatial allocation of elderly healthcare facilities (EHFs), e.g., insufficient provision and inaccessibility. To address these issues, this study developed a location allocation model for EHFs to ensure equitable and efficient access to healthcare services for the elderly in LAHCs.

Methods

Based on discrete location theory, this paper develops a two-stage optimization model for the spatial allocation of EHFs in LAHCs. In the first stage, the candidate locations of EHFs are specified using geographic information system (GIS) techniques. In the second stage, the optimal location and size of each EHF are determined based on the greedy algorithm (GA). Finally, the proposed two-stage optimization model is tested using the Daishan LAHC in Nanjing, Eastern China.

Results

The demand of the elderly for accessibility to EHFs is in line with Nanjing’s planning standards. Deep insights into spatial data are revealed by GIS techniques that enable candidate locations of EHFs to be obtained. In addition, the model helps EHF planners achieve equity and efficiency simultaneously. Two optimal locations for EHFs in the Daishan LAHC are identified, which in turn verifies the validity of the model.

Conclusions

As a strategy for allocating EHFs, this two-stage model improves the equity and efficiency of access to healthcare services for the elderly by optimizing the potential sites for EHFs. It can also be used to assist policymakers in providing adequate healthcare services for the low-income elderly. Furthermore, the model can be extended to the allocation of other public-service facilities in different countries or regions.

Ambulance use, distance and outcomes in patients with suspected cardiovascular disease: a registry-based geographic information system study

BACKGROUND

Despite guideline recommendations, the majority of patients with symptoms suggestive of acute coronary syndrome do not use emergency medical services to reach the emergency department (ED). The aim of this study was to investigate the factors associated with EMS utilisation and subsequent patient outcomes.

METHODS

Using administrative data, all patients who presented to an ED in the metropolitan areas of Edmonton and Calgary in the years of 2007-2013 with main ED diagnosis of acute coronary syndrome, stable angina or chest pain were included. The travel distance was estimated using the geographic information system method to approximate the distance between the ED and patient home. The clinical endpoints were the 7-day and 30-day all-cause events (death, re-hospitalisation and repeat ED visit).

RESULTS

Of 50,881 patients, 30.5% presented by emergency medical services. Patients with older age, female sex, ED diagnosis of acute coronary syndrome, more comorbidities and lower household income were more likely to use emergency medical services to reach the hospital. Longer travel distance was associated with higher emergency medical services use (odds ratio 1.09, 95% confidence interval 1.09-1.10), but it was not a predictor of clinical events. After adjustment for covariates and inverse propensity score weighting, emergency medical services use was associated with a higher risk of 7-day and 30-day clinical events.

CONCLUSION

Several demographic and clinical features were associated with higher emergency medical services use including geographical variation. Although longer travel distance was shown to be linked to higher emergency medical services use, it was not an independent predictor of patient outcome. This has implications for the design of emergency medical services systems, triage and early diagnosis and treatment options.

Does the edge effect impact on the measure of spatial accessibility to healthcare providers?

BACKGROUND

Spatial accessibility indices are increasingly applied when investigating inequalities in health. Although most studies are making mentions of potential errors caused by the edge effect, many acknowledge having neglected to consider this concern by establishing spatial analyses within a finite region, settling for hypothesizing that accessibility to facilities will be under-reported. Our study seeks to assess the effect of edge on the accuracy of defining healthcare provider access by comparing healthcare provider accessibility accounting or not for the edge effect, in a real-world application.

METHODS

This study was carried out in the department of Nord, France. The statistical unit we use is the French census block known as 'IRIS' (Ilot Regroupé pour l'Information Statistique), defined by the National Institute of Statistics and Economic Studies. The geographical accessibility indicator used is the "Index of Spatial Accessibility" (ISA), based on the E2SFCA algorithm. We calculated ISA for the pregnant women population by selecting three types of healthcare providers: general practitioners, gynecologists and midwives. We compared ISA variation when accounting or not edge effect in urban and rural zones. The GIS method was then employed to determine global and local autocorrelation. Lastly, we compared the relationship between socioeconomic distress index and ISA, when accounting or not for the edge effect, to fully evaluate its impact.

RESULTS

The results revealed that on average ISA when offer and demand beyond the boundary were included is slightly below ISA when not accounting for the edge effect, and we found that the IRIS value was more likely to deteriorate than improve. Moreover, edge effect impact can vary widely by health provider type. There is greater variability within the rural IRIS group than within the urban IRIS group. We found a positive correlation between socioeconomic distress variables and composite ISA. Spatial analysis results (such as Moran's spatial autocorrelation index and local indicators of spatial autocorrelation) are not really impacted.

CONCLUSION

Our research has revealed minor accessibility variation when edge effect has been considered in a French context. No general statement can be set up because intensity of impact varies according to healthcare provider type, territorial organization and methodology used to measure the accessibility to healthcare. Additional researches are required in order to distinguish what findings are specific to a territory and others common to different countries. It constitute a promising direction to determine more precisely healthcare shortage areas and then to fight against social health inequalities.

Population access to reperfusion services for ST-segment elevation myocardial infarction in Kerala, India

Background

Population access to timely reperfusion is a decisive factor in determining the success and acceptability of any regional system of ST-segment elevation myocardial infarction (STEMI) care. We sought to determine the proportion of population of the southern Indian state of Kerala having timely access to STEMI reperfusion.

Methods

We identified the STEMI reperfusion facilities available at all acute-care hospitals, in Kerala, by conducting a cross-sectional survey. We mapped the geographical catchment areas of these hospitals using historical travel speeds and appropriate Geospatial Information Systems (GIS) analyses. Subsequently, using block level population data, we estimated the proportion of the population residing within these geographies.

Results

We estimated that 23.33 million people, forming 69.84% of the state population, resided in the green zone (within half-hour travel distance of a percutaneous coronary intervention [PCI]-capable hospital), which covered 47.94% of the geographical area of the state. Outside this green zone, 21.87% of the state population resided within 1 hr travel distance of a thrombolysis-capable hospital. Finally, 8.28% of the state population resided in the red zone, where access to any reperfusion-capable hospital took >1 hr, which covered 22.15% of the geographical area of the state.

Conclusions

A majority of the population of Kerala had timely access to PCI-capable hospitals. GIS-based mapping of Indian states, in terms of access to STEMI reperfusion, may help devise protocols to achieve seamless transfer of patients to reperfusion-capable hospitals. Such regionalization of STEMI care would enhance organizational synergies to achieve better access to reperfusion, especially in remote areas.

Mapping the rapid expansion of India's medical education sector: planning for the future

BACKGROUND

India has witnessed rapid growth in its number of medical schools over the last few decades, particularly in recent years. One dominant feature of this growth has been expansion in the private medical education sector. At this point it is relevant to trace historically and geographically the changing role of public and private sectors in Indian medical education system.

METHODS

The information on medical schools and sociodemographic indicators at provincial, district and sub-district (taluks) level were retrieved from available online databases. A digital map of medical schools was plotted on a geo-referenced map of India. The growth of medical schools in public and private sectors was tracked over last seven decades using line diagrams and thematic maps. The growth of medical schools in context of geographic distribution and access across the poorer and relatively richer provinces as well as the country's districts and taluks was explored using geographic information system. Finally candidate geographic areas, identified for intervention from equity perspective were plotted on the map of India.

RESULTS

The study presents findings of 355 medical schools in India that enrolled 44250 students in 2012. Private sector owned 195 (54.9%) schools and enrolled 24205 (54.7%) students in the same year. The 18 poorly performing provinces (population 620 million, 51.3%) had only 94 (26.5%) medical schools. The presence of the private sector was significantly lower in poorly performing provinces where it owned 38 (40.4%) medical schools as compared to 157 (60.2%) schools in better performing provinces. The distances to medical schools from taluks in poorly performing provinces were longer [median 65.1 kilometres (km)] than from taluks in better performing provinces (median 41.2 km). Taluks farthest from a medical school were, situated in economically poorer districts with poor health indicators, a lower standard of living index and low levels of urbanization.

CONCLUSIONS

The distribution of medical schools in India is skewed in the favour of areas (provinces, districts and taluks) with better indicators of health, urbanization, standards of living and economic prosperity. This particular distribution was most evident in the case of private sector schools set up in recent decades.

A Nationwide Comparison of Driving Distance Versus Straight-Line Distance to Hospitals

Many geographic studies use distance as a simple measure of accessibility, risk, or disparity. Straight-line (Euclidean) distance is most often used because of the ease of its calculation. Actual travel distance over a road network is a superior alternative, although historically an expensive and labor-intensive undertaking. This is no longer true, as travel distance and travel time can be calculated directly from commercial Web sites, without the need to own or purchase specialized geographic information system software or street files. Taking advantage of this feature, we compare straight-line and travel distance and travel time to community hospitals from a representative sample of more than 66,000 locations in the fifty states of the United States, the District of Columbia, and Puerto Rico. The measures are very highly correlated (r2 > 0.9), but important local exceptions can be found near shorelines and other physical barriers. We conclude that for nonemergency travel to hospitals, the added precision offered by the substitution of travel distance, travel time, or both for straight-line distance is largely inconsequential.

A novel technique to optimize facility locations of new nephrology services for remote areas

BACKGROUND AND OBJECTIVES

Travel distance to healthcare facilities affects healthcare access and utilization. Using the example of patients with kidney disease and nephrology services, we investigated the feasibility and utility of using geographic information system (GIS) techniques to identify the ideal location for new clinics to improve care for patients with kidney disease, on the basis of systematically minimizing travel time for remote dwellers.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Using a provincial laboratory database to identify patients with kidney disease and where they lived, we used GIS techniques of buffer and network analysis to determine ideal locations for up to four new nephrology clinics. Service-area polygons for different travel-time intervals were generated and used to determine the best locations for the four new facilities that would minimize the number of patients with kidney disease who were traveling >2 hours.

RESULTS

We studied 31,452 adults with living in Alberta, Canada. Adding the four new facilities would increase the number of patients living <30 minutes from a clinic by 2.2% and reduce the number living >120 minutes away by 72.5%. Different two- and three-clinic scenarios reduced the number of people living >120 minutes away by as much as 65% or as little as 32%, emphasizing the importance of systematic evaluation.

CONCLUSIONS

GIS techniques are an attractive alternative to the current practice of arbitrarily locating new facilities on the basis of perceptions about patient demand. Optimal location of new clinical services to minimize travel time might facilitate better patient care.

Spatial clustering of non-transported cardiac decedents: the results of a point pattern analysis and an inquiry into social environmental correlates

Background

People who die from heart disease at home before any attempt at transport has been made may represent missed opportunities for life-saving medical intervention. In this study, we undertook a point-pattern spatial analysis of heart disease deaths occurring before transport in a large metropolitan area to determine whether there was spatial clustering of non-transported decedents and whether there were significant differences between the clusters of non-transported cardiac decedents and the clusters of transported cardiac decedents in terms of average travel distances to nearest hospital and area socioeconomic characteristics. These analyses were adjusted for individual predictors of transport status.

Methods

We obtained transport status from the place of death variable on the death certificate. We geocoded heart disease decedents to residential street addresses using a rigorous, multistep process with 97% success. Our final study population consisted of 11,485 adults aged 25-74 years who resided in a large metropolitan area in west-central Florida and died from heart disease during 1998-2002. We conducted a kernel density analysis to identify clusters of the residential locations of cardiac decedents where there was a statistically significant excess probability of being either transported or not transported prior to death; we controlled for individual-level covariates using logistic regression-derived probability estimates.

Results

The majority of heart disease decedents were married (53.4%), male (66.4%), white (85.6%), and aged 65-74 years at the time of death (54.7%), and a slight majority were transported prior to death (57.7%). After adjustment for individual predictors, 21 geographic clusters of non-transported heart disease decedents were observed. Contrary to our hypothesis, clusters of non-transported decedents were slightly closer to hospitals than clusters of transported decedents. The social environmental characteristics of clusters varied in the expected direction, with lower socioeconomic and household resources in the clusters of non-transported heart disease deaths.

Conclusions

These results suggest that in this large metropolitan area unfavorable household and neighborhood resources played a larger role than distance to hospital with regard to transport status of cardiac patients; more research is needed in different geographic areas of the United States and in other industrialized nations.

A spatial analysis of variations in health access: linking geography, socio-economic status and access perceptions

Background

This paper analyses the relationship between public perceptions of access to general practitioners (GPs) surgeries and hospitals against health status, car ownership and geographic distance. In so doing it explores the different dimensions associated with facility access and accessibility.

Methods

Data on difficulties experienced in accessing health services, respondent health status and car ownership were collected through an attitudes survey. Road distances to the nearest service were calculated for each respondent using a GIS. Difficulty was related to geographic distance, health status and car ownership using logistic generalized linear models. A Geographically Weighted Regression (GWR) was used to explore the spatial non-stationarity in the results.

Results

Respondent long term illness, reported bad health and non-car ownership were found to be significant predictors of difficulty in accessing GPs and hospitals. Geographic distance was not a significant predictor of difficulty in accessing hospitals but was for GPs. GWR identified the spatial (local) variation in these global relationships indicating locations where the predictive strength of the independent variables was higher or lower than the global trend. The impacts of bad health and non-car ownership on the difficulties experienced in accessing health services varied spatially across the study area, whilst the impacts of geographic distance did not.

Conclusions

Difficulty in accessing different health facilities was found to be significantly related to health status and car ownership, whilst the impact of geographic distance depends on the service in question. GWR showed how these relationships were varied across the study area. This study demonstrates that the notion of access is a multi-dimensional concept, whose composition varies with location, according to the facility being considered and the health and socio-economic status of the individual concerned.

Transfer travel times for primary percutaneous coronary intervention from low-volume and non-percutaneous coronary intervention-capable hospitals to high-volume centers in Florida

STUDY OBJECTIVE

Current guidelines recommend that ST-elevation myocardial infarction (STEMI) patients receive percutaneous coronary intervention less than or equal to 90 minutes from first medical contact, preferably at high-volume percutaneous coronary intervention centers (≥400 percutaneous coronary interventions annually). Because many patients present to low-volume or non-percutaneous coronary intervention-capable STEMI referral hospitals, timely percutaneous coronary intervention treatment requires effective transfer systems, which include interfacility transport times of less than 30 minutes. We investigate the geographic feasibility of achieving timely interfacility transport from STEMI referral hospitals to percutaneous coronary intervention hospitals in Florida.

METHODS

Using 2006 Florida hospital discharge data, we calculated driving times between STEMI referral hospitals and the nearest medium-/high-volume percutaneous coronary intervention centers. We plotted transfer travel time cumulative proportion survival curves for hospitals and patients to assess the feasibility of transfer within 30 minutes to higher-volume facilities. Differences by geographic location (rural versus urban) and patient race/ethnicity were examined.

RESULTS

In 2006, 77% of STEMI referral hospitals had transfer travel times within 30 minutes; 90th percentile for interhospital driving time was 56 minutes. For patients at STEMI referral hospitals, 85.6% were at facilities within a 30-minute drive of a high-/medium-volume percutaneous coronary intervention center; 90th percentile was 31 minutes. We found marked rural/urban disparities, with longer average driving times for patients in rural and small metropolitan counties. Significant racial/ethnic disparities in transfer travel times were not observed, although 90th percentile driving times were highest for blacks.

CONCLUSION

Driving times do not pose a major geographic barrier to transfer of STEMI patients in Florida. A majority of STEMI patients could be transferred from STEMI referral hospitals to high-volume percutaneous coronary intervention centers within 30 minutes.

Access to primary percutaneous coronary intervention for ST-segment elevation myocardial infarction in Canada: a geographic analysis

BACKGROUND

Primary percutaneous coronary intervention (PCI) is preferred over fibrinolysis for the treatment of ST-segment elevation myocardial infarction (STEMI). In the United States, nearly 80% of people aged 18 years and older have access to a PCI facility within 60 minutes. We conducted this study to evaluate the areas in Canada and the proportion of the population aged 40 years and older with access to a PCI facility within 60, 90 and 120 minutes.

METHODS

We used geographic information systems to estimate travel times by ground transport to PCI facilities across Canada. Time to dispatch, time to patient and time at the scene were considered in the overall access times. Using 2006 Canadian census data, we extracted the number of adults aged 40 years and older who lived in areas with access to a PCI facility within 60, 90 and 120 minutes. We also examined the effect on these estimates of the hypothetical addition of new PCI facilities in underserved areas.

RESULTS

Only a small proportion of the country's geographic area was within 60 minutes of a PCI facility. Despite this, 63.9% of Canadians aged 40 and older had such access. This proportion varied widely across provinces, from a low of 15.8% in New Brunswick to a high of 72.6% in Ontario. The hypothetical addition of a single facility to each of 4 selected provinces could increase the proportion by 3.2% to 4.3%, depending on the province. About 470 000 adults would gain access in such a scenario of new facilities.

INTERPRETATION

We found that nearly two-thirds of Canada's population aged 40 years and older had timely access to PCI facilities. The proportion varied widely across the country. Such information can inform the development of regionalized STEMI care models.

Using genetic algorithms to optimise current and future health planning--the example of ambulance locations

Background

Ambulance response time is a crucial factor in patient survival. The number of emergency cases (EMS cases) requiring an ambulance is increasing due to changes in population demographics. This is decreasing ambulance response times to the emergency scene. This paper predicts EMS cases for 5-year intervals from 2020, to 2050 by correlating current EMS cases with demographic factors at the level of the census area and predicted population changes. It then applies a modified grouping genetic algorithm to compare current and future optimal locations and numbers of ambulances. Sets of potential locations were evaluated in terms of the (current and predicted) EMS case distances to those locations.

Results

Future EMS demands were predicted to increase by 2030 using the model (R² = 0.71). The optimal locations of ambulances based on future EMS cases were compared with current locations and with optimal locations modelled on current EMS case data. Optimising the location of ambulance stations locations reduced the average response times by 57 seconds. Current and predicted future EMS demand at modelled locations were calculated and compared.

Conclusions

The reallocation of ambulances to optimal locations improved response times and could contribute to higher survival rates from life-threatening medical events. Modelling EMS case 'demand' over census areas allows the data to be correlated to population characteristics and optimal 'supply' locations to be identified. Comparing current and future optimal scenarios allows more nuanced planning decisions to be made. This is a generic methodology that could be used to provide evidence in support of public health planning and decision making.