A Greedy Double Swap Heuristic for Nurse Scheduling

One of the key challenges of nurse scheduling problem (NSP) is the number of constraints placed on preparing the timetable, both from the regulatory requirements as well as the patients' demand for the appropriate nursing care specialists. In addition, the preferences of the nursing staffs related to their work schedules add another dimension of complexity. Most solutions proposed for solving nurse scheduling involve the use of mathematical programming and generally considers only the hard constraints. However, the psychological needs of the nurses are ignored and this resulted in subsequent interventions by the nursing staffs to remedy any deficiency and often results in last minute changes to the schedule. In this paper, we present a staff preference optimization framework which is solved with a greedy double swap heuristic. The heuristic yields good performance in speed at solving the problem. The heuristic is simple and we will demonstrate its performance by implementing it on open source spreadsheet software

Homecare staff scheduling with three-step algorithm

This paper introduces a three-step algorithm, an efficient framework for solving a homecare staff scheduling problem (HSSP) service schedule, a multi-objective problem requiring a combination of the VRP and the staff scheduling problem. The proposed scheduling technique takes account of the design of optimal daily service routes and the dispatch of caregivers to visit patients under time and capacity constraints. The framework consists of three major stages: Step 1) Route scheduling creates effective routes for homecare caregivers to service patients at different task locations with the shortest path. Step 2) Resource selection seeks to match qualified staff to each route with the minimum cost and preferences under possible time, qualification requirement constraints, and modes of transportation. Step 3) Local improvement enhances the output solution generated by the resource selection by swapping tasks based on the cost function. Our empirical study reveals that the proposed scheduling technique can explore the improved service plan for an adapted case study with the minimum service cost and highest efficiency for arranging service tasks compared to the manual procedure

An Evolutionary Algorithm For The Nurse Scheduling Problem With Circadian Rhythms [RT89.N76 R278 2004 f rb][Microfiche 7574].

This thesis investigates the use of memetic algorithm (MA) for solving the nurse scheduling problem

Evidence-Based Interventions that Promote Resident Wellness from the Council of Emergency Residency Directors

Initiatives for addressing resident wellness are a recent requirement of the Accreditation Council for Graduate Medical Education in response to high rates of resident burnout nationally. We review the literature on wellness and burnout in residency education with a focus on assessment, individual-level interventions, and systemic or organizational interventions

An Exploratory Study of Patient Falls

Debate continues between the contribution of education level and clinical expertise in the nursing practice environment. Research suggests a link between Baccalaureate of Science in Nursing (BSN) nurses and positive patient outcomes such as lower mortality, decreased falls, and fewer medication errors. Purpose: To examine if there a negative correlation between patient falls and the level of nurse education at an urban hospital located in Midwest Illinois during the years 2010-2014? Methods: A retrospective crosssectional cohort analysis was conducted using data from the National Database of Nursing Quality Indicators (NDNQI) from the years 2010-2014. Sample: Inpatients aged ≥ 18 years who experienced a unintentional sudden descent, with or without injury that resulted in the patient striking the floor or object and occurred on inpatient nursing units. Results: The regression model was constructed with annual patient falls as the dependent variable and formal education and a log transformed variable for percentage of certified nurses as the independent variables. The model overall is a good fit, F (2,22) = 9.014, p = .001, adj. R2 = .40. Conclusion: Annual patient falls will decrease by increasing the number of nurses with baccalaureate degrees and/or certifications from a professional nursing board-governing body

An Integrated Framework for Staffing and Shift Scheduling in Hospitals

Over the years, one of the main concerns confronting hospital management is optimising the staffing and scheduling decisions. Consequences of inappropriate staffing can adversely impact on hospital performance, patient experience and staff satisfaction alike. A comprehensive review of literature (more than 1300 journal articles) is presented in a new taxonomy of three dimensions; problem contextualisation, solution approach, evaluation perspective and uncertainty. Utilising Operations Research methods, solutions can provide a positive contribution in underpinning staffing and scheduling decisions. However, there are still opportunities to integrate decision levels; incorporate practitioners view in solution architectures; consider staff behaviour impact, and offer comprehensive applied frameworks. Practitioners’ perspectives have been collated using an extensive exploratory study in Irish hospitals. A preliminary questionnaire has indicated the need of effective staffing and scheduling decisions before semi-structured interviews have taken place with twenty-five managers (fourteen Directors and eleven head nurses) across eleven major acute Irish hospitals (about 50% of healthcare service deliverers). Thematic analysis has produced five key themes; demand for care, staffing and scheduling issues, organisational aspects, management concern, and technology-enabled. In addition to other factors that can contribute to the problem such as coordination, environment complexity, understaffing, variability and lack of decision support. A multi-method approach including data analytics, modelling and simulation, machine learning, and optimisation has been employed in order to deliver adequate staffing and shift scheduling framework. A comprehensive portfolio of critical factors regarding patients, staff and hospitals are included in the decision. The framework was piloted in the Emergency Department of one of the leading and busiest university hospitals in Dublin (Tallaght Hospital). Solutions resulted from the framework (i.e. new shifts, staff workload balance, increased demands) have showed significant improvement in all key performance measures (e.g. patient waiting time, staff utilisation). Management team of the hospital endorsed the solution framework and are currently discussing enablers to implement the recommendation

Modelling home care organisations from an operations management perspective

Home Care (HC) service consists of providing care to patients in their homes. During the last decade, the HC service industry experienced significant growth in many European countries. This growth stems from several factors, such as governmental pressure to reduce healthcare costs, demographic changes related to population ageing, social changes, an increase in the number of patients that suffer from chronic illnesses, and the development of new home-based services and technologies. This study proposes a framework that will enable HC service providers to better understand HC operations and their management. The study identifies the main processes and decisions that relate to the field of HC operations management. Hence, an IDEF0 (Integrated Definition for Function Modelling) activity-based model describes the most relevant clinical, logistical and organisational processes associated with HC operations. A hierarchical framework for operations management decisions is also proposed. This analysis is derived from data that was collected by nine HC service providers, which are located in France and Italy, and focuses on the manner in which operations are run, as well as associated constraints, inputs and outputs. The most challenging research areas in the field of HC operations management are also discussed

DEVELOPING AN OPTIMAL MODEL FOR INFANT HOME VISITATION

The United States, Great Britain, Denmark, Canada and many other countries have accepted home visitation (HV) as a promising strategy for interventions for infants after births and for their mothers. Prior HV studies have focused on theoretical foundations, evaluations of programs, cost/benefit analysis and cost estimation by using hospital/payer/insurance data to prove its effectiveness and high cost. As governments and private organizations continue to fund HVs, it is an opportune time to develop and formulate operations research (OR) models of HV coverage, quality and cost so they might be used in program implementation as done for adult home healthcare (HHC) and home care (HC). This dissertation introduces a new modeling approach and proposes a solution methodology which helps to determine the schedules of follow-up nursing care providers (NCP) to visit discharged patients in order to minimize total follow-up cost at the planning and operational level, and to improve the quality of care. The model improves the quality of treatment of infants and mothers during pregnancy, after birth and discharge from the hospital by maximizing the quality of assignment of the right NCP with the right skill, nurse type and years of experience to the right patient with the specific health need. The modeling approach is based on a mixed-interger programming (MIP) formulation that represents the dynamics of the system comprising aspects such as visit schedules and total program’s cost while satisfying a variety of requirements modeled as constraints. The model is tested and validated with real life data. Computational results for the formulation for real life instances of the problem with the Nurse Family Partnership Program (NFP) obtained using IBM CPLEX optimization Studio version 12.6.1 are presented. The intent is to enhance the administrative and deployment process of HV programs, minimize risks, allow planners to explore the best scenarios under different conditions related to cost, treatment and coverage requirements, and highlight the best course of action when assigning NCPs to clients. Results show significant cost savings and enhanced quality treatment in several cases studied and tested. Finally, the study identifies and presents fertile avenues for future research for this field

Nursing workload balancing: Lean healthcare, analytics and optimization in two Latin American University Hospitals

91 páginasIn most Latin American hospitals, the workload assignment of healthcare workers is a crucial process. These strategies seek to improve the level of patient care and safety while avoiding incurring unnecessary costs by hiring and maintaining excessive staff. The distribution of activities falls to the chief nurses in the hospital, taking as criteria for allocation the number of patients rather than the complexity of care that each individual carries. Specifically for the inpatient area and for nursing professionals, it is complex to determine an adequate distribution of human resources, considering the diagnosis of the patients and the number of tasks that a nursing professional must carry out throughout the day. Therefore, this work proposes the development of a strategy and a load-balancing model based on lean healthcare theory, analytics, and mathematical optimization, so that working hours do not result in the generation of stress and the presence of burnout in nurses. Likewise, mathematical modelling maximizes the use of the nursing staff’s capacity, generating awareness based on the integration of continuous improvement theories so that the clinics can be updated to technological trends. Finally, this project is part of a macro-project for the development of technologies that support hospital nursing processes, carried out by the Universidad de La Sabana Clinic in Colombia and the Universidad de los Andes Clinic in Chile, so the results of this project impact two clinics in Latin America.En la mayoría de los hospitales latinoamericanos, la asignación de carga laboral al personal de la salud es un proceso de vital importancia. Estas estrategias buscan mejorar el nivel de atención al paciente y la seguridad, sin tener que incurrir en gastos innecesarios por la contratación y manutención de un personal excesivo. Esto conlleva a la distribución de las actividades recae en los jefes de las áreas en el hospital, tomando como criterios de asignación la cantidad de pacientes y no la complejidad del cuidado que acarrea cada individuo. Específicamente para el área de hospitalización y para los profesionales de enfermería, resulta complejo determinar una distribución adecuada del recurso humano teniendo en cuenta el diagnóstico de los pacientes y la cantidad de tareas que debe realizar un profesional de enfermería a lo largo de su jornada. Por ello, este trabajo propone el desarrollo de una estrategia y un modelo de balanceo de carga a partir de la teoría lean healthcare, analítica y optimización matemática, de tal forma que las jornadas laborales no resulten en la generación de estrés y la presencia de burnout en los enfermeros. Así mismo, se logra maximizar el aprovechamiento de la capacidad del personal de enfermería, generando bases de concientización sobre la integración de teorías de mejora continua para que las clínicas puedan actualizarse a las tendencias tecnológicas. Por último, este proyecto se enmarcó en un macroproyecto para el desarrollo de tecnologías que soporten los procesos hospitalarios de enfermería, llevado a cabo por la Clínica Universidad de La Sabana en Colombia y la Clínica Universidad de los Andes en Chile, por lo que los resultados de este proyecto impactan dos clínicas en Latinoamérica.Maestría en Diseño y Gestión de ProcesosMagíster en Diseño y Gestión de Proceso