Location Of Health Facilities Research Articles

Optimizing differentiated treatment models for people living with HIV in urban Zimbabwe: Findings from a mixed methods study.

IntroductionZimbabwe is scaling up HIV differentiated service delivery (DSD) to improve treatment outcomes and health system efficiencies. Shifting stable patients into less-intensive DSD models is a high priority in order to accommodate the large numbers of newly-diagnosed people living with HIV (PLHIV) needing treatment and to provide healthcare workers with the time and space needed to treat people with advanced HIV disease. DSD is also seen as a way to improve service quality and enhance retention in care. National guidelines support five differentiated antiretroviral treatment models (DART) for stable HIV-positive adults, but little is known about patient preferences, a critical element needed to guide DART scale-up and ensure person-centered care. We designed a mixed-methods study to explore treatment preferences of PLHIV in urban Zimbabwe.MethodsThe study was conducted in Harare, and included 35 health care worker (HCW) key informant interviews (KII); 8 focus group discussions (FGD) with 54 PLHIV; a discrete choice experiment (DCE) in which 500 adult DART-eligible PLHIV selected their preferences for health facility (HF) vs. community location, individual vs. group meetings, provider cadre and attitude, clinic operation times, visit frequency, visit duration and cost to patient; and a survey with the 500 DCE participants exploring DART knowledge and preferences.ResultsPatient preferences were consistent in the FGDs, DCE and survey. Participants strongly preferred respectful HCWs, HF-based services, individual DART models, and less costly services. Patients also preferred less frequent visits and shorter wait times. They were indifferent to variations in HCW cadre and distances from home to HF. These preferences were mostly homogenous, with only minor differences between male vs. female and older vs. younger patients. HCWs in the KII correctly characterized facility-based individual models as the one most favored by patients; HCWs also preferred this model, which they felt decongested HFs and reduced their workload.ConclusionsDART-eligible PLHIV in Harare found it relatively easy to access HFs, and preferred attributes associated with facility-based individual models. Prioritizing these for scale-up in urban areas may be the most efficient way to sustain positive patient outcomes and increase health system performance.

SISTEM INFORMASI GEOGRAFIS FASILITAS KESEHATAN BPJS DI KOTA PALANGKA RAYA BERBASIS ANDROID

Today the development of technology has been increasing rapidly as well as the use of android smartphones in the field of information systems. It is familiar among the public because it can help in getting the information in a fast and accurate way particularly in an emergency situation. Human needs for information, one of them is information of health facilities in collaboration with Badan Penyelenggara Jaminan Sosial (BPJS) or Agency of Social Security. The purpose of this study is to produce an Android-based application that can facilitate the public in getting information of health facilities in collaboration with BPJS in Palangkaraya. The method applied in the system development in this study is the Waterfall model which consists of five stages, namely, need analysis, system of design, program code writing, program testing, and program implementation. In addition, in creating process, the program uses Android studio software with java programming language and XAMPP connection database, up to UML (Unifield Modeling Language) to depict the system to be made. From this study, the test result shows that the functionality of the BPJS health facility Geographic Information System (GIS) in Palangkaraya City is going well and is in accordance with its function. This android-based application system can display online maps of BPJS health facility locations as well as detailed information from BPJS health facilities in Palangkaraya

Location-allocation models for healthcare facilities with long-term demand

Healthcare facility location decisions are of great importance due to their impact on direct and social cost of people's well-being in a region. Optimal location decisions considering only current demand may become suboptimal as demand distribution changes. Considering future demand realisations in the decision making process can ensure long-term optimality. We present three mathematical models which follow grid-based location approach, and consider current and future demands in providing optimal location-allocation decisions. The first model considers allocations of present and future patients only to the nearest facilities. The second model allows patients to travel to facilities within allowable distance. The third model allows allocation of patients from one location to multiple facilities. The models are implemented with AMPL and numerical instances are solved with the CPLEX solver. Results show that the models are capable of solving medium size problems and the third model performs better in providing high quality solutions.

SOCIO- DEMOGRAPHIC DATA AND EXTENT OF UTIILIZATION ANTENATAL CARE SERVICES AMONG WOMEN IN COMMUNITIES IN ABI LOCAL GOVERNMENT AREA, CROSS RIVER STATE NIGERIA

Socio–Demographic Data is a sensitive indicator used nationally and internationally to measure and compare the health and development status of the population. Access to care and early neonatal death rate are associated in maternal health around the time of delivery. Therefore, clinical antenatal care service before labor are important tool to identify the gaps/strength in this regards. The study was carried out to examine the extent of antenatalcare service utilization by women in riverine communities of Abi Local Government Area of Cross River State. To achieve the objective of the study three (3) research question were formulated and tested at .05 alpha level of significance. A random sampling of 800 women of reproductive age were selected from seven (7) communities in Abi Local Government Area of Cross River State formed the sample of the study. The data collected were analyzed using mean scores and independent t- test analysis for the research question raised. The result of the findings from research question 1 revealed that healthcare provider’s attitude influences the attitude of antenatal services by women. In research question 2 the findings indicated that location of health facilities affect utilization of antenatal care. Findings from research 3 revealed that maternal religion influence the utilization of Antenatal care services. Findings from hypothesis 4 revealed thatmarital status significantly influence the utilization of antenatal care by women. Above all, the study recommended among others that Government should update it’s official guidelines for antenatal care according to new standard promoted by World Health Organization. Also, improved transport and telecommunication facilities at health centers where such care is provided should be enhanced to strengthen accessibility of antenatal care.

"Parar-daktar Understands My Problems Better"

This paper discusses the issues that arise while designing better wellbeing support for a low-income rural population in Bangladesh. Through a four-month long ethnographic study, we explored how people in 13villages in southwestern Bangladesh accessed healthcare. Over the course of our fieldwork, we asked the participants about the existing healthcare services available to them and how they interacted with different ICT-based wellbeing support systems. Our findings show that insufficient resources, schedules, and the distant location of government-supported healthcare facilities were major challenges for the villagers. We also found that villagers' limited knowledge and mistrust of care-providing infrastructure block them from the benefits of available ICT-based supports and resources. Drawing on our findings from the field, we discuss possible alternative design directions for improving wellbeing support for rural Bangladeshis.

A healthcare facility location problem for a multi-disease, multi-service environment under risk aversion

This paper presents a stochastic optimisation model for locating walk-in clinics for mobile populations in a network. The walk-in clinics ensure a continuum of care for the mobile population across the network by offering a perpetuation of services along the transportation lines, and also establishing referral systems to local healthcare facilities. The continuum of care requirements for different diseases is modelled using coverage definitions that are designed specifically to reflect the adherence protocols for services for different diseases. The risk of not providing the required care under different realisations of health service demand is considered. In this paper, for a multi-disease, multi-service environment, we propose a model to determine the location of roadside walk-in clinics and their assigned services. The objective is to maximise the total expected weighted coverage of the network subject to a Conditional-Value-at-Risk (CVaR) measure. This paper presents developed coverage definitions, the optimisation model and the computational study carried out on a real-life case in Africa.

The influence of hospital location and ‘level of care’ on continuing professional development

Healthcare workers core skills are reinforced and knowledge of latest developments ensured by undertaking systematic continuing professional development. The current study explored the impact of health facility location and level of care provided on the continuing professional development offered to maternity services healthcare workers in Victoria, Australia. An online survey of middle to senior management staff of 71 public and private health services as well as 7 professional bodies was conducted, yielding 114 participants. Analysis was by location (metropolitan or regional/rural) and level of care provided. The findings revealed Australian Health Practitioner Regulation Agency registration is the predominant requirement to provide continuing professional development to staff. Dedicated education departments or educators are significantly underrepresented in Level 1&2 facilities, while Level 5&6 facilities are more likely to provide breastfeeding continuing professional development. Metropolitan locations provided more wide-ranging programmes compared with rural/regional locations. Key enablers are the capacity to share resources, have access to external courses and simulation equipment/centres, and the provision of relevant and timely continuing professional development programmes, indicating that ‘Educational hubs’ with credentialed staff working from better resourced regional facilities could deliver a complete array of CPD programmes to lower level facilities.

Considering short-term and long-term uncertainties in location and capacity planning of public healthcare facilities

This paper addresses a real-world problem faced by the public healthcare sector. The problem consists of both the patients’ and service provider's requirements (i.e., accessibility vs. costs) for locating healthcare facilities, allocating service units to those facilities, and determining the facilities’ capacities. The main contribution of this study is capturing both short-term and long-term uncertainties at the modelling stage. The queuing theory is incorporated to consider stochastic demand and service time as a short-term uncertainty, as well as a service level measurement. The developed nonlinear model is then converted into a linear model after introducing a new set of decision variables and proving the properties of the service level constraints. We also demonstrate a way in which a linearized model can become more efficient by eliminating excessive binary variables when service level constraints are approximated using their properties. Additionally, long-term demographic variations are captured through robust optimization in order to create a robust model. To solve the problem under investigation, an evolutionary solution method is designed, and its performance is investigated under different settings. We apply this solution method to determine the location and capacity of healthcare facilities in one of the provinces of Iran. The results illustrate that the suggested network can significantly improve the performance measures compared to the existing network. Furthermore, the importance of robust solution in maintaining the desired service level is demonstrated through examining three levels of demographic variations.

An open source decision support system for facility location analysis

This paper introduces FLP Spreadsheet Solver, an open source spreadsheet based Decision Support System for Facility Location Problems. Structure of the spreadsheets, interface of the solver, and a Tabu Search algorithm implemented within the solver are described. An integer programming formulation of the underlying facility location problem is provided. Computational tests show that FLP Spreadsheet Solver can solve benchmark p-median and capacitated p-median instances to near optimality. The paper also includes a case study consisting of the application of FLP Spreadsheet Solver to a healthcare facility location problem.

Modelling geographic accessibility to Primary Health Care Facilities: combining open data and geospatial analysis

ABSTRACTEnsuring healthy lives and promoting well-being for all ages is the 3rd Sustainable Development Goal (SDG). Inequality in access to health care remains one of the primary challenges in achieving the goal. With the ever-increasing expansion of urban areas and population growth, there is a need to regularly examine the pattern of accessibility of basic amenities across regions, States and urban areas. This study examined geographic access to Primary Health Care Facilities (PHCF) in Nigeria using the combination of open data and geospatial analysis techniques. Thus, showcasing an approach can be replicated across different regions in Sub-Saharan Africa due to issues of information gap. Data on elevation, location of health care facilities, population and network data were utilised. The result shows that PHCF aggregate at certain locations, e.g. major urban agglomerations, and transit route leading to these places. High concentrations are found in the capital city. The average travel time to the nearest PHCF is about 14 min (Standard Deviation ±13.30 min) while the maximum is about 2 hours. Pockets of low accessibility areas exist across the Akwa Ibom State in the Niger Delta region of Nigeria. There is an indication that most places have good geographic access. Across the 1787 settlements identified in our dataset, 98.3% are with good access (<30 min), 27 settlements are located in the poor access class (31–60 min), while two settlements are within the very poor access class (>60 min). Geographic access is not the main limiting factor to health care access in the region. Therefore, computation of access to health care should take into consideration other dimensions of accessibility, to create a robust measure which will support effective and efficient health care planning and delivery.

Set covering models in optimizing the emergency unit location of health facility in Palembang

Palembang comprises 16 districts, but in this research, the focus area is limited to 8 districts namely Sukarami, Sako, Sematang Borang, Kalidoni, Kemuning, Ilir Timur II, Seberang Ulu II, and Plaju. There are currently only 7 districts that have emergency installations. This research is designed to optimize the number and location of emergency installation in Palembang. Optimization of emergency installation location is required to improve health services in Palembang. This optimization uses covering-based models that include location set covering problem and maximal covering location problem. The solutions are obtained by using branch and bound solver on Lingo 13.0. The results of the computation with the best time of 15 minutes are 6 locations of emergency installations in order to serve the existing 8 districts.

Rates and timeliness of treatment initiation among drug-resistant tuberculosis patients in Nigeria- A retrospective cohort study

BackgroundThere were an estimated 580,000 new cases of multidrug/rifampicin resistant TB (DR-TB) in 2015, and only 20% were initiated on treatment. This study explored health system and patient factors associated with initiation and timeliness of treatment among DR-TB patients in Nigeria, ranked 4th globally for estimated TB cases in 2015.MethodsA retrospective cohort study using 2015 diagnosis and treatment data from the Nigerian TB program electronic records examined “treatment ever received” (yes/no) and “treatment within 30 days” (yes/no). We compared health system and patient characteristics using binomial logistic regression, while controlling for confounders.ResultsOf 996 patients diagnosed nationwide in 2015 (aged 0–87 years, median 34), 47.8% were never treated. Of those treated (n = 520), 51.2% were treated within the 30 days prescribed in the National treatment guideline. Healthcare facility locations were significantly associated with ever receiving treatment and timely treatment. Predictors of timely treatment at the national level also included level of care and patient treatment history. The South-West zone, where DR-TB programs started, showed overall better access to DR-TB healthcare.ConclusionsHealthcare facility geographic locations were significantly associated with treatment initiation and timeliness. Significant regional differences in access to DR-TB care in Nigeria persist, reflecting uneven contexts for national DR-TB treatment rollout.

Health-Care Workers' Perspectives on Preparedness of Health-Care Facilities for Outbreak of Communicable Diseases in Nigeria: A Qualitative Study.

A high probability of another outbreak of communicable disease exists in sub-Saharan African countries, after the Ebola virus disease outbreak of 2014. Thus, health-care facility (HCF) preparedness for a prompt and effective response to disease outbreaks needs to be ascertained. In this study, Nigerian health-care workers' (HCWs) knowledge of preparedness, perception of the level of preparedness existing in these HCFs, militating factors, and possible ways to improve, were evaluated through qualitative data collection, using focus group discussion and in-depth interview. Among the 193 HCWs which participated in the study, the perception of 190 (98.4%) was that their HCFs were insufficiently equipped to respond to disease outbreaks. None of the facilities had an emergency operation unit (EOU). Most HCWs perceived preparedness as observation of universal precautions. Other aspects of preparedness, such as training, routine emergency drills, disease surveillance, waste management, and design and location of HCFs were minimally mentioned. None of the participants had undergone any form of emergency drill training. Among the suggestions of how to improve on preparedness were immunization of staff, improved inter-departmental communication within the HCF, and routine training. The overall poor level of preparedness which exists in the HCFs means that they cannot prevent or contain a communicable disease outbreak. There is a need to improve universal precautions, communication within the HCFs, and routine interpretation of surveillance data by epidemiologists. There is also a need for the establishment of EOU in every HCF, a system that responds to, and manages emergency response to disease outbreaks, which also must be functional during non-outbreak periods.

Optimal routing for automated emergency vehicle response for incident intervention in a traffic network

Congestion constitutes a major problem in modern urban traffic networks if not well managed. Its monstrous effects, on occasions, can paralyze a traffic network eating deep into the productive hours of commuters as well as vehicles and persons on essential services. Particularly affected are incidence-intervention vehicles such as emergency vehicles and fire-fighting vehicles. Whatever the cause of the congestion, its effect is counter-productive and an indication of an inefficient traffic network. This work, as presented in this paper, is concerned about the issue of traffic route management for emergency service (emergency vehicle) for which a delay of few minutes may cause tremendous loss of lives and properties. The route management scheme built for this purpose integrates information obtained from the use of Radio Frequency Signals for Traffic Light Preemption at Intersections in a Proteus Simulator environment and the use Arc GIS as a mode of routing the emergency vehicle from base to the incidence location, then to Health Facilities and from thence back to the emergency vehicle base in an optimal routing time. Traffic information are loaded into the Arc GIS environment which predicts the required tri-legged optimal routing and its duration using Dijkstra’s algorithm. Different scenarios of emergency vehicle, incidence and health facility locations were exploited using the scheme and compared with situations without their implementation. The proposed scheme outperforms the trial and error routing of emergency vehicles and can be embedded into traffic advisory system or as stand-alone emergency vehicle management system. Keywords: GIS, Dijkstra’s algorithm, Facility Location, Emergency-Vehicle, Optimal Routing

Spatial accessibility analysis of healthcare service centers in Gamo Gofa Zone, Ethiopia through Geospatial technique

The population of Ethiopia has been facing a high rate of morbidity and mortality. Most of the people live in rural areas where healthcare service is detrimental and very poor and their accessibility to these services is abysmally low. Spatial healthcare accessibility is determined by the availability and location of healthcare facilities as well as the location of people. It can be measured by distance traveled and traveling time. This study was carried out to analyze the distribution and spatial accessibility of healthcare service centers by using Geospatial technologies in Gamo Gofa zone of SNNP (Southern Nations and Nationalities People) region, Ethiopia. Satellite data, DEM (Digital Elevation Model), road network, population data and healthcare service centers location data was used for further analysis by using AccessMod extension 4.0 to Arc GIS 9.3.1 software. 30- and 60-min traveling time were considered to analyze the accessibility by means of walking and motor vehicle as the mode of transportation. It was found that 12.62%, 36.60%, 29.10% and 59% peoples of the total population were able to access the healthcare service centers by means of 30-min walking, 60-min walking, 30-min walking and motor vehicle and 60-min walking and motor vehicle respectively. Health and disease management is key to social, cultural and economic development of any society so this approach offers considerable benefit.

Research to policy on defining accessibility of public health facilities to ensure universal health coverage.

Background:The mandate to ensure the availability of doctors under Universal Health Coverage has been one of the most difficult issues to address in India. It is believed that the geographic location of health facilities has influenced the availability of doctors in rural areas, which may have resulted in long-standing vacancies. There was a need to classify facilities based on location and access, to propose policies and strategies. The classification was arrived through a consultative process, which led to ambiguity.Aim:The aim of this study is to develop a criteria to identify health facilities based on location considering accessibility indicators.Settings and Design:A cross-sectional operational research was conducted during 2010–2011 to collect data for public-health facilities above subcenters and below district hospitals across India.Materials and Methods:Data was collected for geographic, environmental, housing, and vacancy status of doctors; for which scores were assigned for each health facility.Results:A total of 20,528 (76%) were included for analysis out of 26,876 health facilities. Following application of criteria, 3,011 (11%) facilities were identified as eligible; of these, 1%, 3%, and 7% facilities were identified as inaccessible, most-difficult, and difficult facilities, respectively. The consultative meetings with state governments resulted in agreement on the criteria adopted.Conclusion:The study demonstrated more robust criteria to define access to health care facilities by applying composite scoring methods, which was validated through a consultative process with key stakeholders. The study results were applied to incentivize doctors serving in difficult areas in a move to address human resource gaps in rural areas and ensure universal health coverage.

Layanan Kesehatan Swadaya Masyarakat untuk Lansia

The high number of elderly people in Dagen Hamlets, Pendowoharjo, Bantul requires special highlight, especially regarding the health care. This urgency is due to the fact that elderly people generally have accessibility limitations in addition to the remote location of health facilities. Therefore, health service which is practical and easy-to-reach/access by the elderly people needs to be managed to take place. The society empowerment effort, especially towards elderly people, was conducted step-by-step, involving socializations, trainings, practices, and local health service facility establishment. The success indicator achieved in this empowerment activities is shown by the improvement of people’s awareness, especially the elderly ones, towards the significance of health, health service post visitation intensity, and the development of the non-governmental health service facility.

Under vaccination of children among Maasai nomadic pastoralists in Kenya: is the issue geographic mobility, social demographics or missed opportunities?

BackgroundNomadic lifestyle has been shown to be a significant factor in low immunization coverage. However, other factors which might aggravate vaccination uptake in nomadic pastoralists are poorly understood. Our study aimed at establishing the relative influence of social demographics, missed opportunities, and geographical mobility on severe under vaccination in children aged less than two years living in a nomadic pastoralist community of Kenya.MethodsWe used cross-sectional analytical study design. An interviewer-administered questionnaire was used to obtain quantitative data from 515 mothers with children aged less than two years. Under vaccination was the sum the total number of days a delayed vaccine was given after the recommended age range for each vaccine. Severe under vaccination was defined as those children who remained under-vaccinated for more than six months. Geographical mobility was assessed as household members who had gone to live or herd elsewhere in the previous 12 months, missed opportunity included questions on whether a child visiting a health facility had missed being vaccinated, while social demographic data included household size and mothers social demographics.ResultsThree-quarters of the mothers had no formal education. One-third of the children had been taken to a health facility and missed being vaccinated. Forty percent of the households had moved in the previous 12 months. Prevalence of missed opportunity was 30.1%; 42.2% of children had not received any vaccines by their first birthday, and 24.1% of children were severely under vaccinated.No significant association was found between social demographics and under-vaccination. Variables associated with under-vaccination were; movement of the whole family, (p = .015), missed opportunity, (p = <.001), lack of vaccines, (p = (.002), and location of health facility, (p = <.001). Movement of women and children made a significant contribution (p = 0.006) to severe under-vaccination. Children in households where women and children had moved were nine times more likely to be severely under-vaccinated than in those households where there was no movement.ConclusionGeographic mobility of women and children was a key determinant of severe under vaccination among nomadic pastoralists in Kenya.

The Role of Digital Strategies in Financing Health Care for Universal Health Coverage in Low- and Middle-Income Countries.

Countries finance health care using a combination of 3 main functions: raising resources for health, pooling resources, and purchasing health services. In this paper, we examine how digital health technologies can be used to enhance these health financing functions in low- and middle-income countries and can thus contribute to progress toward universal health coverage. We illustrate our points by presenting some recent innovations in digital technologies for financing health care, identifying their contributions and their limits. Some examples include a mobile-health wallet application used in Kenya that encourages households to put money aside for future health expenses; an online software platform developed by a startup in Tanzania in partnership with a private insurance provider to give individuals and families the opportunity to choose among different health coverage options; and digital maps by a number of startups that bring together data on health facility locations and capacity, including equipment, staff, and types of services offered. We also sketch an agenda for future research and action for digital strategies for health financing. The development and adoption of effective solutions that align well with the universal health coverage agenda will require strong partnerships between stakeholders and enough proactive stewardship by authorities.

Capacity of health facilities for diagnosis and treatment of HIV/AIDS in Ethiopia

BackgroundThere are dearth of literature on the capacity of the health system to diagnose and treat HIV/AIDS in Ethiopia. In this study we evaluated the capacity of health facilities for HIV/AIDS care, its spatial distribution and variations by regions and zones in Ethiopia.MethodsWe analyzed the Service Provision Assessment plus (SPA+) survey data that were collected in 2014 in all regions of Ethiopia. We assessed structural, process and overall capacity of the health system based on the Donabedian quality of care model. We included 5 structural and 8 process indicators and overall capacity score was constructed by taking the average of all indicators. Multiple linear regression was done using STATA 14 to assess the association of the location and types of health facilities with overall capacity score. Maps displaying the average capacity score at Zonal level were produced using ArcGIS Desktop v10.3 (Environmental Systems Research Institute Inc., Redlands CA, USA).ResultsA total of 873 health facilities were included in the analysis. Less than 5% of the private facilities provided antiretroviral therapy (ART); had national ART guideline, baseline CD4 count or viral load and tuberculosis screening mechanisms. Nearly one-third of the health centers (34.9%) provided ART. Public hospitals have better capacity score (77.1%) than health centers (45.9%) and private health facilities (24.8%). The overall capacity score for urban facilities (57.1%) was higher than that of the rural (38.2%) health facilities (β = 15.4, 95% CI: 11.7, 19.2). Health centers (β = − 21.4, 95% CI: -25.4, − 17.4) and private health facilities (β = − 50.9, 95% CI: -54.8, − 47.1) had lower overall capacity score than hospitals. Facilities in Somali (β = − 13.8, 95% CI: -20.6, − 7.0) and SNNPR (β = − 5.0, 95% CI: -9.8, − 0.1) regions had lower overall capacity score than facilities in the Oromia region. Zones located in emerging regions such as Gambella and Benishangul Gumz and in remote areas of Oromia and SNNPR had lower capacity score in terms of process indicators.ConclusionsThere is a significant geographical heterogeneity on the capacity of health facilities for HIV/AIDS care and treatment in Ethiopia. Targeted capacity improvement initiatives are recommended with focus on health centers and private health facilities, and emerging Regions and the rural and remote areas.