Deployment Program Research Articles

Delta Coverage: The Analytics Journey to Implement a Novel Nurse Deployment Program

This paper introduces the Delta Coverage (DC) analytics program, an innovative solution to address the nursing shortage crisis. The program designs a new flexible nursing role supported by an accompanying analytics model for dynamic nurse staffing. Using advanced data analytics, the DC program dynamically allocates flexible nurses across multiple hospitals in response to geographical and temporal nurse demand variability. The DC analytics suite integrates a nurse-demand forecast using a deep generative model and a stochastic optimization for optimal on-call and deployment decisions. A pilot study demonstrated that the DC program reduced understaffing incidents by 17% compared to traditional travel nurse solutions, with projected annual savings of $2.5 million for the partner hospital and over $1.5 billion nationally. These results highlights the potential of the DC analytics program to transform nurse staffing practices on a broader scale.

Modeling coupled driving behavior during lane change: A multi-agent Transformer reinforcement learning approach

In a lane change (LC) scenario, the lane change vehicle interacts with surrounding vehicles. The interactions not only affect their driving behaviors but also influence the traffic flow. This study aims to model the coupled behavior of the lane changer and the follower in the target lane during LC. Large-scale real-world connected vehicle (CV) data from the Safety Pilot Model Deployment (SPMD) program are used to extract LCs and study vehicle interactions. A multi-agent Transformer-based deep deterministic policy gradient (MA-TDDPG) method is proposed to model the coupled behaviors during LC. The multi-agent framework can handle the multiple agents’ behaviors with interactions, and the Transformer can process the observation-action memory accurately and efficiently. The MA-TDDPG algorithm can learn the sequential decision-making process over continuous action space during LC with the accommodation of the multi-vehicle interaction and the driver’s memory effect. Compared to traditional supervised learning and reinforcement learning methods, it demonstrates superior performance in imitating the longitudinal and lateral actions of the lane changer and the follower. The findings of this study provide insights into the development of microscopic simulations by producing realistic LC behaviors, and assistance/automation LC systems by generating LC motions and responses conforming to human driving habits. The model also creates an interactive simulation environment and lays the foundation for optimizing driving strategies.

Work commitment and job satisfaction among nurses under nurse deployment program in Sulu

This descriptive-correlational study assessed the work commitment and job satisfaction among nurses under the Nurses Deployment Program in Sulu during the Fiscal Year 2023 with 100 samples taken through non-probability sampling method via purposive sampling, and with the use of weighted mean, standard deviation, t-test for independent samples, One-way ANOVA, and Pearson’s r, this study reveals the following findings: 1) Of the 100 nurse-respondents, mostly are female, within the range of 31-40 years old, and mostly with 3 years & below of length of service; 2) On the average, nurses under the Nurses Deployment Program in Sulu are committed to their work; 3) On the average, nurses under the Nurses Deployment Program in Sulu are satisfied with nursing job; 4) Generally, except for length of service, variables gender and age do not significantly mediate on how nurses assess the extent of work commitment; 5) Generally, variables gender, age, and length of service do not significantly mediate on how nurses assess the extent of job satisfaction; 6) Group of nurses who perceived the extent of work commitment as Agree in terms of affective commitment, continuance commitment, and normative are most probably the same group of nurses who perceived the extent of job satisfaction as Satisfied in terms of family and work-life balance, co-workers, and praise and recognition, respectively; and 7) This study seems to support the theory of Geary, et al, 2023 based on the work of Mayer and Allen on Work Commitment Model. This model espouses that organizational commitment can be analyzed from three types of commitment types, which include affective commitment, continuance commitment, and normative commitment.

Determinants of vaccination decisions and lived experiences of Ghanaians with the COVID-19 pandemic; a qualitative study

BackgroundTwo years after the WHO declared a state of emergency as a result of the rapid spread of the COVID-19 virus from Wuhan, China, the rate of new infections experienced intermittent flare-ups globally, with vaccinations still ongoing in countries such as Ghana. One year after the implementation of Ghana’s COVID-19 vaccine deployment program, Ghanaians have had the opportunity to reflect on their vaccination decisions, albeit the initial vaccine hesitancy. ObjectivesThe current paper examined the knowledge and lived experiences of Ghanaians during the COVID-19 pandemic, and the factors influencing their vaccination decisions, one year after COVID-19 vaccinations commenced in Ghana, with special focus on the social and geographical histories which influenced their vaccination decisions. MethodologyA qualitative approach using a case study design was used to conduct in-depth interviews among 25 respondents who were 18 years and above, not pregnant, and willing to participate in the study, between 5th and 23rd September 2022. Data was collected in 5 hotspot areas in Ghana with the highest cumulative case counts. A semi-structured interview guide was used to collect data which was analyzed using a thematic approach. FindingsRespondents demonstrated a good level of knowledge on COVID-19 and related vaccines. Fear, panic, and anxiety were some of the experiences lived by respondents during the pandemic. The factors influencing vaccination decisions included conspiracy theories about COVID-19 and related vaccines, subjective notions about the COVID-19 disease, and subjective notions about the vaccine. The type of community one lived in, taboos, and previous successful vaccination programs in the community were geographic factors that informed respondents’ decision to vaccinate or not. Social circles, religion, opinion leaders, and media-based campaigns were the social factors that influenced respondents’ decision to vaccinate or not.

Strategic logic of unilateral climate intervention

Climate change and unabated greenhouse gas emissions are increasing the possibility that the world will turn to climate intervention to curb ever-increasing global temperatures. This paper uses game theory to elucidate the conditions that might make a state more or less likely to begin unilateral, as opposed to internationally coordinated, climate intervention (UCI). We solve this game for several specific scientific, economic, and climatological conditions that change the likelihood of a government starting its own climate intervention deployment program without the participation of the broader international community. Specifically, we demonstrate that the plausibility of UCI is linked to perceptions of three key elements: (1) the effectiveness of climate intervention strategies, (2) the sensitivity of specific governments to punishment by other states, and (3) satisfaction with climate and weather in the present. We conclude by discussing how this formal game theory model informs the design of future Earth system model simulations of UCI, international agreements related to climate intervention, and the development of solar climate intervention technologies.

Analysis of Dynamics and Control During the Deployment of an Annular Tether Group of Spacecraft

The article considers a method for forming a rotating tether group of small spacecraft in the form of a regular polygon. To create an external torque acting on the entire system as a whole, low-thrust engines are used, and the directions of the reactive forces are unchanged in the coordinate systems associated with the spacecraft. The release of the cables is controlled by measuring their length and speed in accordance with the nominal program, which assumes that the mechanisms of the release of the cables work only for their braking. The nominal program is built according to a simplified model of the system's motion, built using the Lagrange equations. The feasibility of the deployment program is checked using a more complete model of the spatial motion of the system, written in a geocentric fixed coordinate system and taking into account the extensibility of the cables, the one-sidedness of the mechanical links corresponding to them, the operation of the control system, disturbances associated with the initial conditions of motion, etc. A more complete model of motion takes into account the motion of space vehicles relative to their centers of mass as solid bodies of finite dimensions, which leads to perturbations in the directions of action of reactive forces. Numerical examples are given of the deployment of ring tether groups of small spacecraft in the form of polygons with up to seven vertices, inclusive, under the action of disturbances.

A Practical Study of a Nursing Manpower Deployment Program Under Temporary Tasks

<i>Objective</i> We aim to investigate the practical methods and effects of hospital nursing manpower allocation under large temporary tasks and emergency situations of public emergencies. <i>Methods</i> A TFF nursing manpower deployment plan based on the principle of a three-level nursing management system, fixed and dedicated shift scheduling, and the assistance of flexible nurses was constructed. Under the condition of ensuring the normal work of in-hospital treatment, 936 nursing staff was flexibly deployed from the whole hospital to support large temporary tasks outside the hospital and emergency tasks of public emergencies. <i>Results</i> During the period of facing large temporary tasks, our hospital managed human resources from April to August 2022 on the basis of ensuring the quality and safety of in-hospital nursing work, and efficiently completed all emergency medical treatment tasks issued by the superior. The nursing staff was 95% satisfied with the manpower deployment program, and the SRQ questionnaire after reasonable manpower deployment showed that the nursing staff had good mental health status. <i>Conclusion</i> The TFF nursing manpower deployment program, with good operational effect, can smoothly cope with large temporary tasks like COVID-19, optimize nursing manpower organization and management, and complete large temporary rescue tasks in an efficient and orderly manner.

Modeling driver’s evasive behavior during safety–critical lane changes: Two-dimensional time-to-collision and deep reinforcement learning

Lane changes are complex driving behaviors and frequently involve safety–critical situations. This study aims to develop a lane-change-related evasive behavior model, which can facilitate the development of safety-aware traffic simulations and predictive collision avoidance systems. Large-scale connected vehicle data from the Safety Pilot Model Deployment (SPMD) program were used for this study. A new surrogate safety measure, two-dimensional time-to-collision (2D-TTC), was proposed to identify the safety–critical situations during lane changes. The validity of 2D-TTC was confirmed by showing a high correlation between the detected conflict risks and the archived crashes. A deep deterministic policy gradient (DDPG) algorithm, which could learn the sequential decision-making process over continuous action spaces, was used to model the evasive behaviors in the identified safety–critical situations. The results showed the superiority of the proposed model in replicating both the longitudinal and lateral evasive behaviors.

Advanced Transportation Technologies—Innovative Mobility Deployment Program (DOT)

Advanced Transportation Technologies—Innovative Mobility Deployment Program (DOT)

Use of whole blood deployment programs for mass casualty incidents: South Texas experience in regional response and preparedness.

Firearm-related deaths have become the leading cause of death in adolescents and children. Since the Sutherland Springs, TX mass casualty incident (MCI), the Southwest Texas Regional Advisory Council for trauma instituted a prehospital whole blood (WB) program and blood deployment program for MCIs. The program was adopted statewide by the Texas Emergency Medical Task Force, of which Southwest Texas Regional Advisory Council is the lead for Emergency Medical Task Force 8. The recent active shooter MCI in Uvalde, TX was the first time the MCI blood deployment program had been used. To our knowledge, no other similar programs exist in this or any other country. On May 24, 2022, 19 children and 2 adults were killed at an MCI in Uvalde, TX. The MCI WB deployment protocol was initiated, and South Texas Blood and Tissue Center prepared 15 U of low-titer O-positive whole blood and 10 U of leukoreduced O packed cells. The deployed blood arrived at Uvalde Memorial Hospital within 67 minutes. One of the pediatric patients sustained multiple gunshots to the chest and extremities. The child was hypotensive and received 2 U of leukoreduced O packed cells, one at the initial hospital and another during transport. On arrival, the patient required 2 U of low-titer O-positive whole blood and underwent a successful hemorrhage control operation. The remaining blood was returned to South Texas Blood and Tissue Center for distribution. Multiple studies have shown the association of early blood product resuscitation and improved mortality, with WB being the ideal resuscitative product for many. The ongoing efforts in South Texas serve as a model for development of similar programs throughout the country to reduce preventable deaths. This event represents the first ever successful deployment of WB to the site of an MCI related to a school shooting in the modern era. Therapeutic/Care Management; Level V.

Broadband Equity, Access, and Deployment Program (DOC)

Broadband Equity, Access, and Deployment Program (DOC)

Evaluation of Site Suitability for Artificial Reefs Deployment in Southeast Coast of India Using Geographical Information System as a Management Tool

A planned artificial reef (AR) deployment program as part of a fisheries enhancement might be a useful tool for managers to supplement traditional ways to utilize available space and augment local productivity. Several AR deployment initiatives have been carried out globally, but they are rarely subjected to a rigorous site selection process. We created a site selection procedure in this study that includes systematic stages including exclusion mapping, underwater visual transect, benthic composition, seawater quality, and comparative visual mapping. This research focused on restoring the fishing grounds for artisanal fishermen by deploying AR along the southeast coast of India. The results of each stage in the procedure enabled us to choose suitable locations at a target depth with low wave action, no slope, and a good substrate capable of supporting an AR. Analysis of variance (ANOVA-one way) showed significant (p &amp;lt; 0.05) spatial variation for depth, slope, seawater current, salinity, chlorophyll-a, benthic density, and diversity. The geographical information system (GIS) based model output showed space allocation for AR deployment. The GIS methodology for site selection was developed to be easily adaptable to the demands of diverse artificial reef programs. The integrated strategy has proven to be a successful regulatory intervention for AR deployment practices in order to facilitate coastal restoration and management.

Success factors for demonstration projects of small-scale stationary fuel cells in residential buildings

Worldwide small-scale micro-CHPs account for the largest share in the fuel cell market by units of installation (not by installed power output). Notably, the Japanese Ene-Farm program is responsible for over 400.000 micro-CHP fuel cell installations (until the end of June 2021). This is the largest worldwide deployment program and it reflects the long- and outstanding commitment of both the Japanese government and the Japanese industry to form a ‘Hydrogen Society’. In Europe, the situation is entirely different. European projects like PACE financed by the European joint undertaking for hydrogen and fuel cells give a positive impulse for fuel cell based micro-CHP, however it has to be judged as insufficient for a market transformation measure. Presently, only Germany, notably by the KFW433 program, is providing frame conditions for a rollout of fuel cell based micro-CHP systems. This article analyses the success factors for the implementation of Ene-Farm systems in Japan. It compares the different frame conditions of Japan and European countries like Austria and discusses the question whether an Ene-Farm project based on the Japanese success factors could be replicated in Austria. On a bird’s eye, a European perspective will be derived from the analysis.

Exploring the Relationship between Job Satisfaction and Job Retention among Registered Nurses under the Nurse Deployment Program in Southern Philippines

Background: This study explores the relationship between job satisfaction and job retention among registered nurses working under the Nurse Deployment Program (NDP) in Southern Philippines. Methods: The study design employed in the study is Descriptive-correlational to measure the nurses' perceptions of organizational job satisfaction, and the link between job satisfaction and job retention using a survey questionnaire. A total of 139 registered nurses were selected using Random sampling method from the hospitals, rural health units, birthing places, and barangay health stations in municipalities of Lanao del Sur, Philippines. The data was analyzed through Frequency and Percentage Distribution and Spearman Rho Correlation using manual computation and SPSS. Nurse retention was calculated by dividing the average number of registered nurses during a period of 6 months by the job turnover rates on the units. Results: The findings revealed that the respondents were ‘satisfied’ on the overall indicators on the job satisfaction scale. With a Spearman Rho Correlation value of 0.003 and p-value of 0.016, the data suggested that there is a significant correlation between the respondents’ job satisfaction and job retention in the Nurse Deployment Project. Conclusion: This research illuminated the factors that may influence nurse retention, improve nurse job satisfaction, and promote healthy workplaces. It can serve as a standard or foundation for policymakers and implementers in identifying areas for improvement in boosting job satisfaction among nurses

Driving behavior at midblock crosswalks with Rectangular Rapid Flashing Beacons: Hidden Markov model approach using naturalistic data

Pedestrian fatalities have increased in the U.S. with the largest increase being observed on urban arterials and away from intersections. Rectangular Rapid Flashing Beacon (RRFB) has been widely implemented as a safety countermeasure to improve driver awareness and visibility of pedestrians, especially for midblock crosswalks. Studies show that drivers are more likely to yield to pedestrians at crosswalks with an RRFB. These studies are often based on a binary outcome of whether or not drivers yield to pedestrians. Nevertheless, it is also important to consider the drivers’ deceleration behavior as a dynamic process at these crosswalks and the impact of pedestrians being present or not. Understanding this dynamic behavior and the related circumstances can provide information on the design of alerting systems that help drivers make more appropriate decisions at these crosswalks to avoid a vehicle–pedestrian crash. This study examined this research topic using Hidden Markov Models (HMMs) and data from a naturalistic study. More specifically, four HMMs were applied to the naturalistic brake and jerk data from the Safety Pilot Model Deployment (SPMD) program given drivers’ intention to slow down, the RRFB activation status, and the presence of pedestrians. The time-based data sequence was converted to distance-based through a moving window to enhance result comparison and interpretation. Grid-search was used to select the best moving window parameters and the optimal number of hidden states. This study confirmed the high compliance at an activated RRFB when pedestrians were present. Even without pedestrians, one in five traversals showed drivers slowing down to less than 8.94 m/s (20 mph) within 35 m of the crosswalk. Model results further indicate that drivers started braking as far back as 180 m before the crosswalk and stopped braking from 70 m before the crosswalk at an activated RRFB without pedestrians. When there were pedestrians, drivers would start braking 20 to 30 m later but would brake more firmly and for longer. Finally, drivers were not likely to brake or decelerate when RRFB was off and no pedestrians were present.

Factors affecting retention in the Philippine National Rural Physician Deployment Program from 2012 to 2019: a mixed methods study

BackgroundTo address the maldistribution of healthcare providers and the shortage of physicians in geographically isolated and disadvantaged areas of the Philippines, the Philippine National Rural Physician Deployment Program, or more commonly known as the Doctors to the Barrios (DTTB) program was established in 1993. However, as of 2011, only 18% of the DTTBs chose to stay in their assigned municipalities after their two-year deployment, termed retention. This study aims to identify the individual, local, work, national, and international factors affecting the retention of DTTBs in their assigned communities after their two-year deployment.MethodsA descriptive, mixed-methods, explanatory design was used. For the quantitative part, the modified and updated Stayers Questionnaire was given to all current DTTBs present in a Continuing Medical Education session in the Development Academy of the Philippines. Descriptive statistics were then presented. For the qualitative part, individual, semi-structured key informant interviews were conducted in-person or via phone with current and alumni DTTBs from 2012 to 2019. Proceedings of the interviews were transcribed, translated, and analyzed thematically.Results102 current DTTBs participated in the quantitative part of our study, while 10 current and former DTTBs participated in the interviews. Demographic factors and location, personal beliefs, well-being, friends and family dynamics, and perceptions about work were the individual factors identified to affect retention. Social working conditions, career development, and infrastructure, medical equipment, and supplies were among the work factors identified to affect retention. Geography, living conditions, local social needs, and technology were among the local factors identified to affect retention. Compensation, the recently signed Universal Healthcare Law, and Safety and Security were identified as national factors that could affect retention. International factors did not seem to discourage DTTBs from staying in their communities.ConclusionsA host of individual, work-related, local, national, and international factors influence the DTTB’s decision to be retained in different, complex, interconnected, and dynamic ways. We also identified implementation issues in the DTTB program and suggested interventions to encourage retention.

Safety Impact of Connected Vehicles on Driver Behavior in Rural Work Zones under Foggy Weather Conditions

Work zone safety is one of the paramount goals of the safety community. Safety in WZs is a particular concern under foggy conditions as they represent an exogenous factor contributing to high variability in driver behavior. In line with the Connected Vehicle (CV) Pilot Deployment Program on Interstate-80 (I-80) in Wyoming, this study investigates the safety benefits of CV Work Zone Warning (WZW) applications on driver behavior during foggy weather conditions. A work zone (WZ) was simulated using VISSIM in four sequential areas, including the advance warning, transition, activity, and termination area. The effect of drivers’ increased situational awareness under the effect of WZW was calibrated in VISSIM based on the results of a high-fidelity driving simulator experiment. Various Surrogate Measures of Safety (SMoS), including Time-To-Collision (TTC), Time Exposed Time-to-collision (TET), Time-Integrated Time-to-collision (TIT), and Modified Deceleration Rate to Avoid Crash (MDRAC), were employed to quantify the safety performance of CVs under varying CV Market Penetration Rates (MPRs). According to the results of TTC and MDRAC, it was found that an increase in CV-MPR enhances the safety performance of the WZ area. Findings showed that, under foggy weather conditions, the advance warning area had the highest TIT and TET values. Furthermore, it was revealed that an increase in MPR of up to 60% on I-80 would reduce mean speeds and the standard deviation of speed at each of the WZ areas, leading to more speed harmonization and minimizing the crash risk in WZs.

Co-writing the Lives of Registered Nurses Employed under the Nurse Deployment Program of the Department of Health

Community Health Nursing is one of the major areas in the nursing profession, yet it is not given many highlights in some circumstances. This condition puts new emphasis on the need for more research about this field of nursing. Consequently, this research study explored the lived experiences of registered nurses employed under the Nurse Deployment Program of the DOH. Furthermore, it involved seven qualified participants from the Rural Health Unit of Nagcarlan, Laguna. The researcher used descriptive, cross-sectional qualitative research, particularly a phenomenological approach by Husserl.The process includes four steps: bracketing, intuiting, analyzing and describing. The researcher facilitated a face-to-face, semi-structured interview in which the process was audio recorded to garner subjective data accurately. Thus, the researcher prepared a written topic guide, which is a list of open-ended questions to be answered by the participants, also known as procedural questions. The statements of participants were transcribed into text and then categorized into different themes. On the validation of the study, the researcher used triangulation Several themes were identified and fit into two factors: first are the intrinsic factors which include proper time and stress management, and career advancement and personal growth; while the others are the extrinsic factors which include fair workload and compensation, and resolution of issues related to working experiences. Based on the findings, the researcher developed a thematic framework that shows that extrinsic and intrinsic factors contributed to the satisfaction of the participants with their job, and made them stay in their chosen field. Hence, this calls for another research study using a mixed-method that approaches specifically the sequential exploratory design.

Hidden Markov Model of Lane-Changing-Based Car-Following Behavior on Freeways using Naturalistic Driving Data

This paper develops a methodology for simultaneously modeling lane-changing and car-following behavior of automated vehicles on freeways. Naturalistic driving data from the Safety Pilot Model Deployment (SPMD) program are used. First, a framework to process the SPMD data is proposed using various data analytics techniques including data fusion, data mining, and machine learning. Second, pairs of automated host vehicle and their corresponding front vehicle are identified along with their lane-change and car-following relationship data. Using these data, a lane-changing-based car-following (LCCF) model, which explicitly considers lane-change and car-following behavior simultaneously, is developed. The LCCF model is based on Gaussian-mixture-based hidden Markov model theory and is disaggregated into two processes: LCCF association and LCCF dissociation. These categories are based on the result of the lane change. The overall goal is to predict a driver’s lane-change intention using the LCCF model. Results show that the model can predict the lane-change event in the order of 0.6 to 1.3 s before the moment of the vehicle body across the lane boundary. In addition, the execution times of lane-change maneuvers average between 0.55 and 0.86 s. The LCCF model allows the intention time and execution time of driver’s lane-change behavior to be forecast, which will help to develop better advanced driver assistance systems for vehicle controls with respect to lane-change and car-following warning functions.

The role of drivers’ social interactions in their driving behavior: Empirical evidence and implications for car-following and traffic flow

Models for describing the microscopic driving behavior rarely consider the “social effects” on drivers’ driving decisions. However, social effect can be generated due to interactions with surrounding vehicles and affect drivers’ driving behavior, e.g., the interactions result in imitating the behavior of peer drivers. Therefore, social environment and peer influence can impact the drivers’ instantaneous behavior and shift the individuals’ driving state. This study aims to explore empirical evidence for existence of a social effect, i.e., when a fast-moving vehicle passes a subject vehicle, does the driver mimic the behavior of passing vehicle? High-resolution Basic Safety Message data set (N = 151,380,578) from the Safety Pilot Model Deployment program in Ann Arbor, Michigan, is used to explore the issue. The data relates to positions, speeds, and accelerations of 63 host vehicles traveling in connected vehicles with detailed information on surrounding environment at a frequency of 10 Hz. Rigorous random parameter logit models are estimated to capture the heterogeneity among the observations and to explore if the correlates of social effect can vary both positively and negatively. Results show that subject drivers do mimic the behavior of passing vehicles –in 16 percent of passing events (N = 18,099 total passings occurred in freeways), subject vehicle drivers are observed to follow the passing vehicles accelerating. We found that only 1.2 percent of drivers normally sped up (10 km/hr in 10 s) during their trips, when they were not passed by other vehicles. However, if passed by a high speed vehicle the percentage of drivers who sped up is 16.0 percent. The speed change of at least 10 km/hr within 10 s duration is considered as accelerating threshold. Furthermore, the acceleration of subject vehicle is more likely if the speed of subject driver is higher and more surrounding vehicles are present. Interestingly, if the difference with passing vehicle speed is high, the likelihood of subject driver’s acceleration is lower, consistent with expectation that if such differences are too high, the subject driver may be minimally affected. The study provides new evidence that drivers’ social interactions can change traffic flow and implications of the study results are discussed.