Set Of Facilities Research Articles

Medicare reimbursement for interventional pain procedures: 2000 to 2023

BackgroundAn analysis of the financial trends of Interventional Pain (IP) procedures in the United States is lacking. Understanding these relations is necessary to help optimize future IP care delivery and costs. ObjectiveTo examine Medicare reimbursement trends for IP procedures in both facility and non-facility settings. MethodsUtilizing the Physician Fee Schedule Look-Up Tool from the Centers for Medicare and Medicaid, reimbursement data for 32 of the most performed IP procedures was collected between 2000 and 2023 for both facility and non-facility clinical sites. After adjusting for inflation, annual change, total percent change, and compound annual growth rate (CAGR) were calculated for each procedure. ResultsFollowing inflation adjustments, the average reimbursement rate decreased by an average of 61.31 % for facility procedures over the study period and by 60.40 % for non-facility procedures. The average adjusted reimbursement rate for facility procedures decreased by $6.76 per year with an average CAGR of −4.38 %, while the average adjusted reimbursement rate for non-facility procedures decreased by $18.66 per year with an average CAGR of −4.48 %. A two-tailed t-test was performed between facility and non-facility groups for total percent change (P = 0.803), annual change (P < 0.001), and CAGR (P = 0.746). ConclusionMedicare reimbursement rates in both facility and non-facility settings have decreased from 2000 to 2023, with non-facility procedures experiencing a significantly larger decrease.

Identifying relevant diabetes and hypertension control management guidelines in primary healthcare and community settings in Indonesia: A Delphi survey.

The burden of non-communicable diseases (NCDs) in Indonesia is increasing, as evidenced by the latest Indonesian National Health Research, which shows an increase in diabetes prevalence, from 6.9% in 2013 to 10.9% in 2018, and hypertension, from 25.8% in 2013 to 34.1% in 2018. Hence, effective actions in community and primary health care (PHC) facility settings are necessary to tackle the burden of diabetes and hypertension, especially in low- and middle-income countries. The Indonesian government has issued numerous guidelines regarding NCDs. However, not all these guidelines can be applied to communities or PHCs. This study aimed to identify priority guidelines to support the community and PHC for NCD management using the Delphi survey method. These prioritized guidelines will serve as valuable resources for developing relevant, operational and comprehensive modules for community cadres and PHC staff involved in NCD management. The Delphi survey involved 25 experts and comprised three rounds using a questionnaire: 1) identification and assessment of guidelines, 2) assessment of the importance of guidelines, and 3) nomination of the three main priority guidelines. The results revealed three priority guidelines: NCD management guidelines, technical guidelines for Pos Pembinaan Terpadu (POSBINDU) NCDs, and integrated services for NCDs in PHC facilities. Additionally, priority guidelines were used to develop operational modules for community cadres and PHC staff in NCDs management. In conclusion, utilizing the Delphi method serves as a scientific approach to identify priority guidelines crucial for supporting the community and PHC in managing NCDs, particularly in countries with contexts similar to Indonesia.

Investigation of impact of community environment factors on the residents’ visiting rate to outdoor venues in South China

Understanding the activity patterns of urban residents is crucial for urban community design and urban energy forecasting. Predicting the visitation rates of different types of locations is a important issue because urban residents can only be in one place at a time. Achieving accurate predictions of outdoor public space visitation rates is equivalent to predicting the upper limit of the number of visitors to other buildings. Previous similar studies usually rely on survey methods such as questionnaires and GPS positioning. These methods have some drawbacks, such as small sample sizes and inaccurate data. In this paper, we used mobile signaling to investigate the park visit rates of residents in different communities in Guangzhou. In accordance with Chinese tradition, we define a community as a residential community, which consists of multiple residential units and a set of basic service facilities and management structures that are sufficient to meet the daily needs of residents. We found that the park visit rate of a community is closely related to the characteristics of the community itself. The park visit rate is positively correlated with the average LST (land surface temperature) of the communities, the average distance between the community and the large park, and the building coverage rate, while it is negatively correlated with the vegetation coverage rate, the average surface reflection rate, the convenience of transportation, and the per capita green space area. Given the different travel habits of urban residents on weekdays and weekends, we also used multiple linear regression to establish prediction models for community park visitation rates on weekdays and weekends.

Artificial intelligence in healthcare facilities asset information management: mixed review

Healthcare facilities are pivotal in ensuring continuous access to services, particularly for individuals with complex health conditions. Effective asset information management (AIM) in these facilities through artificial intelligence (AI) can enhance operational efficiency. The exploratory bibliometric and systematic review assesses the status and trends of AI applications in AIM within healthcare facilities. The findings reveal a significant gap between research findings and practical implementation, highlighting the need for further integration and real-world usage of AI-powered solutions in healthcare facilities settings. This study identified notable gaps, including the need for research on utilising AI to enhance asset management in healthcare, including maintenance scheduling and procurement processes. Involving stakeholders, such as healthcare professionals, facility managers, and patients, in effective facility management using AI requires further investigation. Research is needed to evaluate the economic benefits and develop robust ethical guidelines for responsible AI implementation. Notably, previous research has given limited attention to AI for healthcare AIM, with emerging trends focusing more on AI and infrastructure than the ‘asset’ aspect. Implementing AI-powered solutions tailored to the unique needs of healthcare facilities and evaluating cost-effectiveness will lead to improved asset management practices, enhanced decision-making processes, and, ultimately, more efficient and effective healthcare operations.

Home-Time, Mortality, and Readmissions Among Patients Hospitalized With Heart Failure: A Baseline Prior to IMPLEMENT-HF.

Home-time is an emerging, patient-centered outcome that represents the amount of time a patient spends alive and outside of health care facility settings, comprising of hospitals, skilled nursing facilities, and acute rehabilitation centers. Studies evaluating home-time in the context of heart failure are limited, and the impact of quality improvement interventions on home-time has not been studied. Medicare beneficiaries aged 65 years or older who were hospitalized for heart failure in the Get With the Guidelines-Heart Failure registry between 2019 and 2021 were included. Postdischarge home-time, mortality, and readmission rates at 30 days and 1 year were calculated with the goal of establishing baseline metrics before the initiation of IMPLEMENT-HF, a multicenter quality improvement program aimed at improving heart failure management. Overall, 66 019 patients were included across 437 sites. Median 30-day and 1-year home-time were 30 (18-30) and 333 (139-362) days, respectively. Only 22.1% of patients experienced 100% home-time in the year after discharge. Older patients spent significantly less time at home, with a median 1-year home-time of 302 (86-359) compared with 345 (211-365) days in patients over 85 and those between 65 and 74 years old, respectively (P<0.001). Black patients also experienced the least amount of home-time with only 328 (151-360) days at 1-year follow-up. Rates of heart failure readmission and all-cause mortality 1-year post-discharge were high at 29.8% and 37.0%, respectively. In this contemporary multicenter cohort, patients hospitalized with heart failure spent a median of 91.2% of their time in the year after discharge alive and at home, largely driven by high mortality rates. These findings serve as a preimplementation baseline for IMPLEMENT-HF, which will evaluate the impact of targeted heart failure initiatives on home-time and other clinical outcomes.

Integrated evaluation of the functioning quality of robotic agricultural vehicle system

The article proposes to use a method for evaluating the effectiveness (Data Envelope Analysis) of a system of robotic agricultural vehicles, which is based on solving the problem of fractional linear programming when analyzing a set of homogeneous production facilities. This method is used for an integrated assessment of the quality of service of robotic vehicles according to the specified key parameters of functioning. The main parameters of the effectiveness of the system of robotic agricultural vehicles are selected: the coefficient of technical readiness, operational speed, downtime in maintenance and repair, the average daily duration of the car, the average monthly mileage of the vehicle, the remaining life of the car, the unit cost of maintenance and specific cargo displacement. Solving systems of linear equations makes it possible to determine the position of each analyzed object relative to the efficiency boundary in a multidimensional parameter space. The solution of the Bunker-Charnes-Cooper problem has been completed. Sets of target changes in the parameters of robotic cars have been obtained, which transfer objects to the efficiency boundary. The analysis of the parameters is carried out by constructing diagrams of production capabilities in a multidimensional space. For two periods of operation of the robotic vehicle system for an agro-industrial enterprise, the Malmquist index was calculated to assess the dynamics of operational efficiency.

Testing the Psychometric Properties of the Readiness for Hospital Discharge Scale Among Residents in Skilled Nursing Facilities: A Pilot Study.

Background and Purpose: The Readiness for Hospital Discharge Scale (RHDS) was created to determine the patient's readiness for discharge to home from the hospital. The purpose of this study is to determine the scale's internal consistency and predictive validity in a skilled nursing facility (SNF) setting. Methods: Participants (N = 30) over the age of 65 were conveniently selected from 10 different SNFs in the Midwest to complete the RHDS prior to discharge. Results: Cronbach's alpha for internal consistency was 0.917. Participants with higher RHDS scores, those who were male, respondents with less education, and participants with Medicare Advantage insurance were more likely to be rehospitalized within 30 days of discharge to home. Conclusions: The results indicate that the RHDS has a good internal consistency in the SNF setting.

Towards greener city logistics: an application of agile routing algorithms to optimize the distribution of micro-hubs in Barcelona

The COVID-19 pandemic accelerated the shift towards online shopping, reshaping consumer habits and intensifying the impact on urban freight distribution. This disruption exacerbated traffic congestion and parking shortages in cities, underscoring the need for sustainable distribution models. The European Union's common transport policy advocates for innovative UFD approaches that promote intermodal transportation, reduce traffic, and optimize cargo loads. Our study addresses these challenges by proposing an agile routing algorithm for an alternative UFD model in Barcelona. This model suggests strategically located micro-hubs selected from a set of railway facilities, markets, shopping centers, district buildings, pickup points, post offices, and parking lots (1057 points in total). It also promotes intermodality through cargo bikes and electric vans. The study has two main objectives: (i) to identify a network of intermodal micro-hubs for the efficient delivery of parcels in Barcelona and (ii) to develop an agile routing algorithm to optimize their location. The algorithm generates adaptive distribution plans considering micro-hub operating costs and vehicle routing costs, and using heuristic and machine learning methods enhanced by parallelization techniques. It swiftly produces high-quality routing plans based on transportation infrastructure, transportation modes, and delivery locations. The algorithm adapts dynamically and employs multi-objective techniques to establish the Pareto frontier for each plan. Real-world testing in Barcelona, using actual data has shown promising results, providing potential scenarios to reduce CO2 emissions and improve delivery times. As such, this research offers an innovative and sustainable approach to UFD, that will contribute significantly to a greener future for cities.

Integrating SARS-CoV-2 rapid antigen testing in maternal, neonatal and child health, HIV, and TB clinics in Kenya and Cameroon: outcomes from the Catalysing COVID-19 Action Project

IntroductionEarly diagnosis of SARS-CoV-2 infection is key to preventing severe disease and poor outcomes in vulnerable populations, such as pregnant women and people living with HIV or diagnosed with tuberculosis...

The Impact of Mindfulness Apps and Cognitive Behavioral Therapy on Prisoners' Mental Health

Prisoners' mental health and overall wellbeing are given significant consideration throughout the COVID-19 pandemic. The correctional facility's setting separates prisoners from the outside world, and their lack of access to modern medical care will result in depressive symptoms and other mental health issues. Prisons can benefit from the cost-effective and useful usage of CBT and mindfulness apps to enhance the mental health and general well-being of their inmates. This study provides an overview of possible ways to use smartphone apps to lessen mental health problems among prisoners. Applications of mindfulness have shown potential benefits in reducing mental health issues, including anxiety, depression, and stress. This paper reviews existing research on the effectiveness of these interventions and explores the feasibility of implementing such applications in prison settings. Although long-term effects are not yet well-documented, preliminary findings suggest that these apps could serve as a valuable tool for enhancing mental health care in correctional facilities. It is worthwhile to employ these applications as a pilot test to investigate their benefits further. By integrating technology with traditional practices and addressing challenges such as noncompliance and lack of personalization, prison systems can develop more effective and engaging mental health interventions. These efforts can contribute to better mental health outcomes, reduced recidivism, and a more rehabilitative prison environment. Future research should focus on long-term studies and strategies to improve adherence to online psychological treatments.

Supporting Correlative Light and Electron Microscopy (CLEM) Services in a Core Facility Setting

Supporting Correlative Light and Electron Microscopy (CLEM) Services in a Core Facility Setting

Bridging the Gap: Specialized Training Programs for Infection Prevention Specialists Increase Certification Success

Background: The role of the infection preventionist (IP) is complex and encompasses a range of responsibilities requiring extensive knowledge in infection control practices, data analysis, surveillance, performance improvement and collaboration with multidisciplinary teams. Infection prevention certification (CIC) by the certification Board of Infection Control (CBIC) is a standardized marker of knowledge and competencies required for practice in the field. In a 2020 survey of IPs, less than half were certified or planned to become certified. Of those that do take the certification exam, less than three quarters pass on their initial exam attempt. Methods: From 2017 to 2023, fifty-two new IPs were enrolled in a competency-based training program which combined didactic and applied learning on core IP job functions, and a structured mentoring program. The initial didactic phase consisted of evidence-based learning modules with validation of competency through post-training testing and practical demonstration. Education was provided by an advanced practice IP via remote webinars, which included discussion of questions, skills coaching, and review of post-tests. Novice IPs were partnered with at least two preceptors: one advanced practice lead preceptor guided the novice IPs through assigned education modules and oversaw program management and training benchmarks. A second, near-peer preceptor or mentor collaborated with the novice IP in the facility setting. Initial training focused on facility operations, surveillance, rounding and other facility specific activities. Facility mentors were responsible for combining education module topics with practical application of skills. Mentors guided novice IPs through National Healthcare Surveillance network (NHSN) surveillance training and validated surveillance and infection coding until the novice IP had an interrater reliability validation assessing surveillance competency. After the initial training phase, the novice IPs began preparation for certification. This phase included additional training modules aligned with the CBIC certification content outline and practice exams. Results: All 52 novice IPs completed the training program and attempted the CIC examination. The initial pass rate for the certification exam among IPs in the supervised training and mentorship program was 98.1% (n=51). This is 33% higher than the initial pass rate published by CBIC, which was 73.9% (Figure 1). Conclusions: Organizing evidence-based guidelines into topic-specific modules builds a foundation of infection prevention and control knowledge, which is enhanced through remote instruction and direct application of skills under a preceptor’s supervision. This method allows IPs to be introduced to concepts covered in the board certification exam upon hire and support certification with improved outcome

Community-associated Carbapenem-Resistant Organism Case Investigations in New York City, December 2020-May 2023

Epidemiology of carbapenem-resistant organisms (CRO) has focused on transmission in acute care hospital or long-term care facility (LTCF) settings. Few investigations have examined community-associated (CA)-CRO, with no consensus about common exposures. To explore possible exposures, the New York City (NYC) Department of Health and Mental Hygiene investigated suspected CA-CRO cases through routine surveillance among NYC residents with specimens collected during December 2020-May 2023. CA-CRO cases were defined as urine or skin specimens with bacterial cultures exhibiting carbapenem resistance, among individuals aged ≤70 years with no international travel, hospitalization, or LTCF stays within 12 months before specimen collection. Inclusion was determined by reviewing data from health information exchanges, when available electronic medical records, and telephone screening for those not excluded through record review. We identified 426 suspected cases for review, those not meeting the case definition were excluded; 44 individuals were not reached for screening. A preliminary questionnaire was fielded with 12 individuals and then refined to capture additional potential exposures. Analyses were completed with 23 individuals interviewed with the refined questionnaire. Of the 23, 70% were female; 39% were Hispanic, 17% Black, and 17% White; their median age was 60 years (range: 26-70 years). Further, 83% reported an outpatient appointment, 48% reported an outpatient procedure/surgery, and 9% reported having a hospitalized household member, all within 12 months before specimen collection; 26% had a urinary catheter or indwelling device within 2 days of specimen collection. Additionally, 30% reported taking antibiotics within 3 months of specimen collection, 52% denied taking antibiotics, 9% were unsure about antibiotic use, and 9% did not answer the question. Whole genome sequencing (WGS) was performed on 14 available isolates from CA-CRO cases by the NYC Public Health Laboratory or Wadsworth Center (WC), of which only 7 could be compared with isolates previously sequenced at WC (2017-2023). Six isolates were separated by &gt;50 mutation events, suggesting no close genomic relationship. One isolate from 2021 was 11 mutation events from a 2018 isolate from the same individual, consistent with the expected evolutionary rate. While infrequent, CA-CRO cases occur in NYC. Outpatient healthcare, antibiotic use, and urinary catheters or indwelling devices were common self-reported exposures. Analyses were limited by screening non-response. Increased specimen availability for WGS could enhance investigation of CA-CRO exposure patterns. Health information exchange data were often incomplete and future surveillance could benefit from healthcare and public health partnerships and better documentation for more complete electronic medical histories.

Strategic integration of vertiport planning in multimodal transportation for urban air mobility: A case study in Beijing, China

In pursuit of strategic sustainable development goals, this study seeks to analyze the spatial placement of vertiports for urban air mobility, positioning them as integral components within the multimodal transportation system. We propose an iterative weighted k-means clustering method that incorporates the value of travel time of different transportation modes to identify potential vertiport locations. A multi-objective optimization model that maximizes total air taxi ridership and minimizes total facility costs and travel distances to vertiports is developed considering the constraints of the distance from vertiports to existing mobility hubs. A case study is conducted using the data of Beijing city, incorporating the modes of taxis and metro. We found that 19 vertiports can guarantee a robust performance of urban air mobility service. Users of urban air mobility can benefit from substantial travel time savings of 80% (48 min on average). This study contributes to a deeper understanding of the optimal setting of urban air mobility facilities from the perspective of network synchronization, offering useful insights into policy decision-making for sustainable infrastructure planning.

Medicare billing and utilization trends in vascular surgery

ObjectiveWithin the past decade, Medicare Part B reimbursements for various surgical procedures have been declining, whereas health care expenses continue to increase. As a result, hospitals may increase service charges to offset losses in revenue, which may disproportionately affect underinsured patients. Our analysis aimed to characterize Medicare billing and utilization trends across common vascular surgical procedures. MethodsThe 2017 to 2021 Medicare Physician and Other Practitioners by Provider and Service dataset was queried for Current Procedural Terminology (CPT) codes for common vascular surgery procedures. The average charges, reimbursements, charge-to-reimbursement ratios, and service counts were calculated for the most common interventions performed by vascular surgeons. Data was stratified by care setting, facility (inpatient and outpatient hospital) vs non-facility locations. All monetary values were adjusted to the 2021 United States dollars to account for inflation. ResultsFor facility settings, the mean charge billed to Medicare Part B increased from $3708 to $3952 (6.6%) from 2017 to 2021, with the average charge-to-reimbursement ratio increasing from 7.2 to 8.6. There were 17 of the 19 facility procedures that had a decline in reimbursements, decreasing from an average of $558 to $499 (−10.4%). Stab phlebectomy had the largest individual decrease in facility reimbursement (−53.5%), followed by above-knee amputation (−11.3%) and below-knee amputation (−11.0%). Both non-facility charges (−10.8%) and reimbursements (−12.2%) declined over the study period. Procedural utilization remained stable from 2017 to 2019. Tibial and femoral-popliteal atherectomy had increases of 45.9% and 33.7%, respectively, in overall procedural utilization when performed in non-facility settings from 2017 to 2019. ConclusionsOur analysis of vascular surgery procedures billed to Medicare Part B from 2017 to 2021 demonstrates an increase in charges, a decline in reimbursements, and a resultant increase in charge-to-reimbursement ratios for facility care settings. In contrast, non-facility charges have decreased in the face of declining reimbursements. These markups in submitted charges in facility locations may serve as an additional barrier to accessing care for patients who are underinsured.

Prescribing patterns of statins and associated factors among type 2 diabetes mellitus patients in Africa: A systematic review and meta-analysis

BackgroundIn sub-Saharan African nations, there's a documented shortfall in the utilization of statins, despite established clinical guidelines advocating their use for reducing cardiovascular risks and overall mortality among Type 2 diabetes patients aged 40–75 years old. Most clinical guidelines recommend prescribing statins to individuals with type 2 diabetes to reduce the chances of cardiovascular disease. There is currently a lack of extensive research on statin utilization specifically for primary prevention of cardiovascular disease in Africa. Thus, this study aimed to assess the prescription patterns of statins for preventing cardiovascular disease in type 2 diabetes patients. MethodsThe findings of the review were presented following the guidelines outlined in the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA-2020) checklist. We conducted searches on electronic databases including PubMed, EMBASE, Cochrane Library, Science Direct, African Journal Online, and Google Scholar. This systematic review and meta-analysis included articles that met specific inclusion criteria: observational studies such as cross-sectional, cohort, and case-control studies focusing on determinants, risk factors, or correlates associated with statin prescription within Africa. Only published articles up to June 2, 2024, published in English, and conducted in either community or healthcare facility settings were considered. Data import was initially conducted using Microsoft Excel, and statistical analysis was performed using STATA software. Cochran's Q test was employed to assess whether there was a significant variance in prevalence among the studies. Additionally, the I2 statistic was utilized to quantify the extent of heterogeneity. A funnel plot, a visual tool, was utilized to evaluate publication bias. ResultsThe search strategy resulted in 7695 published original articles. The full texts of the 89 papers were assessed for eligibility and quality. Moreover, some articles were rejected due to inaccuracies in the outcome variable. Ultimately, only ten studies focusing on the prevalence of statin prescription were examined. The research suggests that the pooled prevalence of statin prescription among Type 2 diabetic individuals in Africa is found to be 48.82% (95% CI: 35.41–63.24). Age greater than 65 years (AOR = 3.56, 95% CI: 1.70–7.45; I2 = 54.7%), comorbidity (AOR = 1.13, 95% CI: 0.27–4.63, I2 = 96.4%), dyslipidemia (AOR = 3.15, 95% CI: 1.54–6.44, I2 = 61.7%), DM duration greater than ten years (AOR = 1.36, 95% CI: 0.81–2.28, I2 = 77.3%), and government insurance (AOR = 8.85, 95% CI: 2.72–28.76, I2 = 81.5%) were factors associated with statin prescription among type 2 diabetic patients. ConclusionsIn general, the extent of statin prescriptions for individuals with type 2 diabetes who are eligible for statin therapy was below the target outlined by clinical practice guidelines. Being over 65 years old, having comorbidities, experiencing dyslipidemia, having type 2 diabetes for more than ten years, and having government insurance were all identified as independent factors predicting the prescription of statins. This finding is concerning and underscores the urgent need to enhance adherence to clinical practice guidelines for the well-being of this vulnerable population at high risk.

Maternal morbidity and death associated with pregnancy loss before 28 weeks in Nigeria.

To determine the prevalence of maternal morbidity and death from pregnancy loss before 28 weeks in referral-level hospitals in Nigeria. Secondary analysis of a nationwide cross-sectional study. Fifty-four referral-level hospitals. Women admitted for complications arising from pregnancy loss before 28 weeks between 1 September 2019 to 31 August 2020. Frequency and type of pregnancy loss were calculated using the extracted data. Multilevel logistic regression was used to determine sociodemographic and clinical factors associated with early pregnancy loss. Factors contributing to death were also analysed. Prevalence and outcome of pregnancy loss at <28 weeks; sociodemographic and clinical predictors of morbidity after early pregnancy loss; contributory factors to death. Of the 4798 women who had pregnancy loss at <28 weeks of pregnancy, spontaneous abortion accounted for 49.2%, followed by missed abortion (26.9%) and ectopic pregnancy (15%). Seven hundred women (14.6%) had a complication following pregnancy loss and 99 women died (2.1%). Most complications (26%) and deaths (7%) occurred after induced abortion. Haemorrhage was the most frequent complication in all types of pregnancy loss with 11.5% in molar pregnancy and 6.9% following induced abortion. Predictors of complication or death were low maternal education, husband who was not gainfully employed, grand-multipara, pre-existing chronic medical condition and referral from another facility or informal setting. Pregnancy loss before 28 weeks is a significant contributor to high maternal morbidity and mortality in Nigeria. Socio-economic factors and delays in referral to higher levels of care contribute significantly to poor outcomes for women.

Optimization of the emergency obstetric and neonatal care network in Benin through expert-based sub-national prioritizations.

To reduce maternal mortality by 2030, Benin needs to implement strategies for improving access to high quality emergency obstetric and neonatal care (EmONC). This study applies an expert-based approach using sub-national travel specificities to identify and prioritize a network of EmONC maternities that maximizes both population coverage and functionality. We conducted a series of workshops involving international, national, and department experts in maternal health to prioritize a set of EmONC facilities that meet international standards. Geographical accessibility modeling was used together with EmONC availability to inform the process. For women in need of EmONC, experts provided insights into travel characteristics (i.e., modes and speeds of travel) specific to each department, enabling more realistic travel times estimates modelled with the AccessMod software. The prioritization approach resulted in the selection of 109 EmONC maternities from an initial group of 125 designated maternities. The national coverage of the population living within an hour's drive of the nearest EmONC maternity increased slightly from 92.6% to 94.1% after prioritization. This increase in coverage was achieved by selecting maternities with sufficient obstetrical activities to be upgraded to EmONC maternities in the Plateau and Atlantique departments. The prioritization approach enabled Benin to achieve the minimum EmONC availability, while ensuring very good geographical accessibility to the prioritized network. Limited human and financial resources can now be targetted towards a smaller number of EmONC facilities to make them fully functioning in the medium-term. By implementing this strategy, Benin aims to reduce maternal mortality rates and deliver effective, high-quality obstetric and neonatal care, especially during emergencies.

Optimizing routing and scheduling of shared autonomous electric taxis considering capacity constrained parking facilities

This paper focuses on routing and scheduling of autonomous electric vehicles to provide reservation-based shared ride services, while a set of parking facilities with limited capacity are used for vehicle intermittent charging. A mixed-integer linear program model is formulated in the form of a vehicle routing problem with satellite facilities (VRPSF), subject to a series of additional time and capacity-related constraints. The objective of the model is to minimize the total operating costs of the system, including those related to vehicle miles traveled and the deployed vehicle fleet size. The number of vehicles inside each parking facility is tracked so as to ensure that the capacity is never exceeded throughout the service horizon. A customized solution method based on an adaptive large neighborhood search algorithm with an explicit treatment of parking facility choices is developed. A series of numerical experiments, consisting of both hypothetical examples and a real-world case study in Hangzhou, China, have been conducted to evaluate the effectiveness and applicability of the proposed model and algorithm. The results demonstrate that ride-sharing services and parking facilities have the potential to significantly reduce the total vehicle energy consumption and operating costs for a shared autonomous electric taxi (SAET) operator in practical scenarios.

P-facility capacitated location problem with customer-equilibrium decisions: a recreational case study in Mazandaran province

PurposeThis paper aims to propose a bi-level mixed integer linear location-allocation problem. The upper-level objective function is dedicated to minimizing the total distances covered by customers to meet the p-selected facilities and the fixed cost values for establishing these facilities. While in the lower level, a customer preference function evaluates the priority of customers in selecting facilities.Design/methodology/approachThe solution approach to the proposed model uses the Karush–Kuhn–Tucker (KKT) optimality conditions to the lower-level problem where a set of p-selected facilities are introduced as the selection of the upper-level decision maker. The bi-level model reduces to a single-level model with some added binary variables.FindingsSensitivity analysis of the proposed bi-level model concerning variations of such different parameters as customers’ preferences and the number of selected facilities have been provided, using some numerical examples. Also, locating a recreational facility in Mazandaran province, Iran, has been provided to evaluate the reliability of the proposed model and efficiency of the solution approach, as well.Originality/valueTo the best of the authors’ knowledge, this paper is original and its findings are not available elsewhere.