Spatial accessibility and social inclusion: The impact of Portugal's last health reform

Health policies seek to promote access to health care and should provide appropriate geographical accessibility to each demographical functional group. The dispersal demand of health‐careservices and the provision for such services atfixed locations contribute to the growth of inequality intheir access. Therefore, the optimal distribution of health facilities over the space/area can lead toaccessibility improvements and to the mitigation of the social exclusion of the groups considered mostvulnerable. Requiring for such, the use of planning practices joined with accessibility measures. However,the capacities of Geographic Information Systems in determining and evaluating spatial accessibility inhealth system planning have not yet been fully exploited. This paper focuses on health‐care services planningbased on accessibility measures grounded on the network analysis. The case study hinges on mainlandPortugal. Different scenarios were developed to measure and compare impact on the population'saccessibility. It distinguishes itself from other studies of accessibility measures by integrating network data ina spatial accessibility measure: the enhanced two‐stepfloating catchment area. The convenient location forhealth‐care facilities can increase the accessibility standards of the population and consequently reducethe economic and social costs incurred. Recently, the Portuguese government implemented a reform thataimed to improve, namely, the access and equity in meeting with the most urgent patients. It envisaged,in terms of equity, the allocation of 89 emergency network points that ensured more than 90% of thepopulation be within 30 min from any one point in the network. Consequently, several emergency serviceswere closed, namely, in rural areas. This reform highlighted the need to improve the quality of the emergencycare, accessibility to each care facility, and equity in their access. Hence, accessibility measures becomean efficient decision‐making tool, despite its absence in effective practice planning. According to anapplication of this type of measure, it was possible to verify which levels of accessibility were decreased,including the most disadvantaged people, with a larger time of dislocation of 12 min between 2001 and 2011

Spatial accessibility assessment of homecare workers to the older population in the city of Zurich

Access to homecare is paramount for the older population wishing not to move to retirement homes. In Zurich, the organization “Spitex Zürich” is the public homecare provider, allowing the older population to experience high-quality life at home through regular visits. A major factor for ensuring self-determined living for the older population consists of a detailed understanding of the spatial accessibility to Spitex locations. Therefore, this paper is concerned with applying four different FCA methods for assessing the spatial accessibility of Spitex homecare workers to people aged 65 + in Zurich through the road and bike networks. The modified-Huff-model-three-step-FCA method is found to be best suited for modeling potential spatial accessibility in Zurich. Spatial accessibility index values show similar geographical distributions regardless of transportation mode. The neighborhoods of Seebach and Hottingen are identified as regions with relatively low spatial accessibility. Our findings contribute to a better understanding of the interpretation and the measurement of spatial accessibility, thereby facilitating autonomous living for the older population residing in Zurich, ultimately increasing the inclusiveness of the city

Accessibility to primary health care in Belgium: an evaluation of policies awarding financial assistance in shortage areas

Background: In many countries, financial assistance is awarded to physicians who settle in an area that is designated as a shortage area to prevent unequal accessibility to primary health care. Today, however, policy makers use fairly simple methods to define health care accessibility, with physician-to-population ratios (PPRs) within predefined administrative boundaries being overwhelmingly favoured. Our purpose is to verify whether these simple methods are accurate enough for adequately designating medical shortage areas and explore how these perform relative to more advanced GIS-based methods. Methods: Using a geographical information system (GIS), we conduct a nation-wide study of accessibility to primary care physicians in Belgium using four different methods: PPR, distance to closest physician, cumulative opportunity, and floating catchment area (FCA) methods. Results: The official method used by policy makers in Belgium (calculating PPR per physician zone) offers only a crude representation of health care accessibility, especially because large contiguous areas (physician zones) are considered. We found substantial differences in the number and spatial distribution of medical shortage areas when applying different methods. Conclusions: The assessment of spatial health care accessibility and concomitant policy initiatives are affected by and dependent on the methodology used. The major disadvantage of PPR methods is its aggregated approach, masking subtle local variations. Some simple GIS methods overcome this issue, but have limitations in terms of conceptualisation of physician interaction and distance decay. Conceptually, the enhanced 2-step floating catchment area (E2SFCA) method, an advanced FCA method, was found to be most appropriate for supporting areal health care policies, since this method is able to calculate accessibility at a small scale (e.g. census tracts), takes interaction between physicians into account, and considers distance decay. While at present in health care research methodological differences and modifiable areal unit problems have remained largely overlooked, this manuscript shows that these aspects have a significant influence on the insights obtained. Hence, it is important for policy makers to ascertain to what extent their policy evaluations hold under different scales of analysis and when different methods are used

Accessibility of Health Facilities to Residents in Ibadan, Nigeria

Provision of health facilities is an essential service that government often try to provide for the well-being of its citizens. However, the spatial distribution of this service tends to determine how accessible it is to the residents. This study examined the accessibility of health facilities to residents in Ibadan, Nigeria. Systematic random sampling technique was used to choose 791 respondents for the study. Cumulative opportunity measure was employed to compute the total number of health facilities in the study area. The findings of the study revealed that majority (69.9%) of the residents patronized hospitals where general and specialized services are rendered. Also, more than 30% travelled 5km or less and others about 70% more than 5km for their medical needs. It took majority of the residents 2 hours and they paid an average of ?356 ($2.23) per trip to health facilities. Furthermore, there was unequal distribution of the available 436 health facilities, with major ones situated in the modern areas of the city while the minor ones were concentrated in the older areas. This study concluded that residents have relatively low accessibility to health facilities. Hence, the need to address the lopsided arrangement of health facilities so as to improve residents’ accessibility to them. Keywords: Accessibility, health facilities, cumulative opportunity measur

Distribution of primary health care facilities in Mtwara District, Tanzania: availability and accessibility of services

Background: Access to health care services is a significant factor to health seeking practices that contributes to a healthy population. Improving health care accessibility is an important health priority in low-income countries. The objective of this study was to determine distribution of health care facilities and identify the high priority areas, which require more services in Mtwara, southern Tanzania.Methods: This study was carried in Mtwara Rural district of southern Tanzania and involved health care facilities. A hand held global positioning system was used to geo-reference the coordinates of all facilities. A questionnaire with both closed and open-ended questions was used to gather information from patients who attended the respective facilities. Interviews with district health officials and facility in-charges were conducted.Results:  There were 38 health in the district. Most of them were located within southern part of the district. The majority of facilities (97%) were government owned. On average each facility was serving 2,400 population. Malaria management, reproductive and child health services, family planning and integrated management of childhood illnesses were offered by all health facilities in the district. Prevention of mother to child transmission of HIV was offered by 34 (89.5%) facilities. Tuberculosis services were offered by only 3 facilities while voluntary counselling and testing of HIV and anti-retroviral treatment services were available in 15 and 10 health facilities, respectively. Only 4 facilities had laboratory and inpatients services. The majority of the staff included Medical Attendants (39%), Nurse Midwives (34%), and Clinical Officers (20%). Assistant Medical Officers and Nursing Officers each accounted for 2% of the total staff. There were no Medical Officers, laboratory technicians or pharmaceutical technicians in the district.  A total of 408 health facility clients (≥18yrs) were interviewed. Factors influencing the choice of a health facility were the availability of special services, medicine and qualified human resources.Conclusion: The majority of facilities in Mtwara are government and there is disparity in the distribution of the facilities. Availability of medicines and qualified human resources were the major factors on the preference for accessing health care services

Modeling Multimodal Access to Primary Care in an Urban Environment

Access to primary health care facilities is a key component of public health, and measuring that access is vital to understanding how to target interventions. Transportation is one dimension of access and measuring distance via multiple modes allows better understanding of how varied populations access health care, particularly those who do not have access to a personal vehicle. This work builds on the 2-Step Floating Catchment Area (2SFCA) method to include travel by car, bus, bicycle, and walking. Travel time data are sourced from OpenStreetMap and transit data incorporates stop and schedule information from the General Transit Feed Specification (GTFS). Open source data analysis tools are used to aid reproducibility in other geographic contexts. Modal weights are assigned to measure the population accessing each facility by each mode. Access values for Milwaukee County in Wisconsin, USA are presented, with clear differences shown among modes accessing primary healthcare. Car access is high and consistent across the county, while biking and walking access are more impacted by distance to destination. Transit access is unequal across the county with some tracts showing no access at all. The highly varied access results by mode emphasize the importance of measuring access and travel by non-car modes, particularly when targeting communities with high rates of no car ownership. Improvement of multimodal access measurement will allow for targeted interventions that account for the availability of modes in each community

Measuring the geographic coverage of methadone maintenance programme in Hong Kong by using geographic information system (GIS)

<p>Abstract</p> <p>Objective</p> <p>While access and utilization form core components in assessing the effectiveness of a health service, the concept of coverage is often neglected. In this study we propose to develop a GIS-based methodological framework for the measurement of district-based geographic coverage to examine the service effectiveness of methadone treatment programme (MTP) in Hong Kong on a regular basis.</p> <p>Methods</p> <p>To overcome the incompatibility of spatial units, population data and data of heroin addiction of the year 2001 are interpolated by population-weighted and area-weighted algorithms. Standard overlay and proximity analytical functions are used to delineate altogether 20 accessible zones around each methadone clinic at a fixed 1.5 km Euclidean distance. Geographic coverage here is defined as the percentage of heroin addicts covered by a methadone clinic within the accessible zone by district.</p> <p>Results</p> <p>A total of 6413 out of 11000 reported heroin addicts are found geographically covered. The average geographic coverage in Hong Kong is 44.6%, with the figure varying from 0% to 96% by district. One district having no clinic results in 0% coverage whereas another without a clinic yields 15.3% coverage from the clinic in adjacent district. Maps illustrating district-based geographic coverage are generated.</p> <p>Conclusion</p> <p>As continuous data collection is required for a monitoring system, the simplified approach facilitates the handling of large volume data and relevant data analysis. It is concluded that the number of methadone clinics is as important as their locations. Geographic coverage could become an important consideration for monitoring harm reduction.</p

Development and Applications of Similarity Measures for Spatial-Temporal Event and Setting Sequences

Similarity or distance measures between data objects are applied frequently in many fields or domains such as geography, environmental science, biology, economics, computer science, linguistics, logic, business analytics, and statistics, among others. One area where similarity measures are particularly important is in the analysis of spatiotemporal event sequences and associated environs or settings. This dissertation focuses on developing a framework of modeling, representation, and new similarity measure construction for sequences of spatiotemporal events and corresponding settings, which can be applied to different event data types and used in different areas of data science. The first core part of this dissertation presents a matrix-based spatiotemporal event sequence representation that unifies punctual and interval-based representation of events. This framework supports different event data types and provides support for data mining and sequence classification and clustering. The similarity measure is based on the modified Jaccard index with temporal order constraints and accommodates different event data types. This approach is demonstrated through simulated data examples and the performance of the similarity measures is evaluated with a k-nearest neighbor algorithm (k-NN) classification test on synthetic datasets. These similarity measures are incorporated into a clustering method and successfully demonstrate the usefulness in a case study analysis of event sequences extracted from space time series of a water quality monitoring system. This dissertation further proposes a new similarity measure for event setting sequences, which involve the space and time in which events occur. While similarity measures for spatiotemporal event sequences have been studied, the settings and setting sequences have not yet been considered. While modeling event setting sequences, spatial and temporal scales are considered to define the bounds of the setting and incorporate dynamic variables along with static variables. Using a matrix-based representation and an extended Jaccard index, new similarity measures are developed to allow for the use of all variable data types. With these similarity measures coupled with other multivariate statistical analysis approaches, results from a case study involving setting sequences and pollution event sequences associated with the same monitoring stations, support the hypothesis that more similar spatial-temporal settings or setting sequences may generate more similar events or event sequences. To test the scalability of STES similarity measure in a larger dataset and an extended application in different fields, this dissertation compares and contrasts the prospective space-time scan statistic with the STES similarity approach for identifying COVID-19 hotspots. The COVID-19 pandemic has highlighted the importance of detecting hotspots or clusters of COVID-19 to provide decision makers at various levels with better information for managing distribution of human and technical resources as the outbreak in the USA continues to grow. The prospective space-time scan statistic has been used to help identify emerging disease clusters yet results from this approach can encounter strategic limitations imposed by the spatial constraints of the scanning window. The STES-based approach adapted for this pandemic context computes the similarity of evolving normalized COVID-19 daily cases by county and clusters these to identify counties with similarly evolving COVID-19 case histories. This dissertation analyzes the spread of COVID-19 within the continental US through four periods beginning from late January 2020 using the COVID-19 datasets maintained by John Hopkins University, Center for Systems Science and Engineering (CSSE). Results of the two approaches can complement with each other and taken together can aid in tracking the progression of the pandemic. Overall, the dissertation highlights the importance of developing similarity measures for analyzing spatiotemporal event sequences and associated settings, which can be applied to different event data types and used for data mining, sequence classification, and clustering