32,064 research outputs found

    Taxonomic classification of planning decisions in health care: a review of the state of the art in OR/MS

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    We provide a structured overview of the typical decisions to be made in resource capacity planning and control in health care, and a review of relevant OR/MS articles for each planning decision. The contribution of this paper is twofold. First, to position the planning decisions, a taxonomy is presented. This taxonomy provides health care managers and OR/MS researchers with a method to identify, break down and classify planning and control decisions. Second, following the taxonomy, for six health care services, we provide an exhaustive specification of planning and control decisions in resource capacity planning and control. For each planning and control decision, we structurally review the key OR/MS articles and the OR/MS methods and techniques that are applied in the literature to support decision making

    Assuring Access to Care Under Health Reform: The Key Role of Workforce Policy

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    Examines policy and practical options for addressing the projected shortage of primary care physicians to ensure access to health care under expanded insurance coverage, including reorganizing practices to make productive use of nurses and other staff

    Examining The Influence Of Dependent Demand Arrivals On Patient Scheduling

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    This research examines the influence of batch appointments on patient scheduling systems. Batch appointments are characterized by multiple patients within a family desiring appointments within the same time frame

    Patient-Centered Appointment Scheduling Using Agent-Based Simulation

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    Enhanced access and continuity are key components of patient-centered care. Existing studies show that several interventions such as providing same day appointments, walk-in services, after-hours care, and group appointments, have been used to redesign the healthcare systems for improved access to primary care. However, an intervention focusing on a single component of care delivery (i.e. improving access to acute care) might have a negative impact other components of the system (i.e. reduced continuity of care for chronic patients). Therefore, primary care clinics should consider implementing multiple interventions tailored for their patient population needs. We collected rapid ethnography and observations to better understand clinic workflow and key constraints. We then developed an agent-based simulation model that includes all access modalities (appointments, walk-ins, and after-hours access), incorporate resources and key constraints and determine the best appointment scheduling method that improves access and continuity of care. This paper demonstrates the value of simulation models to test a variety of alternative strategies to improve access to care through scheduling

    Simulation and Modeling for Improving Access to Care for Underserved Populations

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    Indiana University-Purdue University Indianapolis (IUPUI)This research, through partnership with seven Community Health Centers (CHCs) in Indiana, constructed effective outpatient appointment scheduling systems by determining care needs of CHC patients, designing an infrastructure for meaningful use of patient health records and clinic operational data, and developing prediction and simulation models for improving access to care for underserved populations. The aims of this study are 1) redesigning appointment scheduling templates based on patient characteristics, diagnoses, and clinic capacities in underserved populations; 2) utilizing predictive modeling to improve understanding the complexity of appointment adherence in underserved populations; and 3) developing simulation models with complex data to guide operational decision-making in community health centers. This research addresses its aims by applying a multi-method approach from different disciplines, such as statistics, industrial engineering, computer science, health informatics, and social sciences. First, a novel method was developed to use Electronic Health Record (EHR) data for better understanding appointment needs of the target populations based on their characteristics and reasons for seeking health, which helped simplify, improve, and redesign current appointment type and duration models. Second, comprehensive and informative predictive models were developed to better understand appointment non-adherence in community health centers. Logistic Regression, Naïve Bayes Classifier, and Artificial Neural Network found factors contributing to patient no-show. Predictors of appointment non-adherence might be used by outpatient clinics to design interventions reducing overall clinic no-show rates. Third, a simulation model was developed to assess and simulate scheduling systems in CHCs, and necessary steps to extract information for simulation modeling of scheduling systems in CHCs are described. Agent-Based Models were built in AnyLogic to test different scenarios of scheduling methods, and to identify how these scenarios could impact clinic access performance. This research potentially improves well-being of and care quality and timeliness for uninsured, underinsured, and underserved patients, and it helps clinics predict appointment no-shows and ensures scheduling systems are capable of properly meeting the populations’ care needs.2021-12-2

    Aiming for service excellence: Implementing a plan for customer service quality at a blended service desk

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    This article discusses a public service review and redesign that resulted in a blended service desk combining reference and circulation functions, staffed by nonlibrarians. The redesign implements a number of organizational structures that encourage service excellence, as found in the business literature and in examples of nonlibrary organizations that excel in customer service. The article identifies key organizational structures that have been shown to support or hinder good service and discusses the process of implementing these structures in practice and the results of an assessment process designed around determining success

    Applying and integer Linear Programming Model to an appointment scheduling problem

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    Dissertação de Mestrado, Ciências Económicas e Empresariais (Economia e Políticas Públicas), 28 de fevereiro de 2022, Universidade dos Açores.A gestão de consultas ambulatórias pode ser um processo complexo, uma vez que envolve vários stakeholders com diferentes objetivos. Para os utentes poderá ser importante minimizar os tempos de espera. Simultaneamente, para os trabalhadores do setor da saúde, condições de trabalho justas devem ser garantidas. Assim, é cada vez mais necessário ter em conta o equilíbrio de cargas horárias e a otimização dos recursos disponíveis como principais preocupações no agendamento e planeamento de consultas. Nesta dissertação, uma abordagem com dois modelos para a criação de um sistema de agendamento de consultas é proposta. Esta abordagem é feita em programação linear, com dois modelos que têm como objetivo minimizar as diferenças de cargas horárias e melhorar o seu equilíbrio ao longo do planeamento. Os modelos foram estruturados e parametrizados de acordo com dados gerados aleatoriamente. Para isso, o desenvolvimento foi feito em Java, gerando assim os dados referidos. O Modelo I minimiza as diferenças de carga horária entre os quartos disponíveis. O Modelo II, por outro lado, propõe uma nova função objetivo que minimiza a diferença máxima observada, com um processo de decisão minxmax. Os modelos mostram resultados eficientes em tempos de execução razoáveis para instâncias com menos de aproximadamente 10 quartos disponíveis. Os tempos de execução mais altos são observados quando as instâncias ultrapassam este número de quartos disponíveis. Em relação ao equilíbrio da carga horária, observou-se que o número de especialidades disponíveis para atendimento e a procura por dia foram o que mais influenciou a minimização da diferença da carga horária. Os resultados do Modelo II mostram melhor tempo de execução e um maior número de soluções ótimas. Uma vez que as diferenças entre os dois modelos não são consideráveis, o Modelo I poderá representar um melhor conjunto de soluções para os decisores já que minimiza a diferença da carga horária total entre quartos em vez de apenas minimizar o valor máximo da diferença de carga horária entre quaisquer dois quartos.ABSTRACT: Outpatient appointment management can be a complex process since it involves many conflicting stakeholders. As for the patients it might be important to minimize waiting time. Simultaneously, for healthcare workers, fair working conditions must be guaranteed. Thus, it is increasingly necessary to have workload balance and resource optimization as the main concerns in the scheduling and planning of outpatient appointments. In this dissertation, a two-model approach for designing an appointment scheduling is proposed. This approach is formulated as two mathematical Integer Linear Programming models that integrate the objective of minimizing workload difference and improving workload balance. The models were structured and parameterized according to randomly generated data. For this, the work was developed in Java, generating said data. Model I minimizes the workload differences among rooms. Model II, on the other hand, proposes a new objective function that minimizes the maximum workload difference, with a minxmax decision process. The computational models behaves efficiently in reasonable run times for numerical examples with less than approximately 10 rooms available. Higher run times are observed when numerical examples surpass these number of available rooms. Regarding workload balance, it was observed that the number of specialties available for appointments and the demand for each day were the most influential in the minimization of workload difference. Model II results show a shorter model run time and more optimal solutions. As the differences between both Models are not considerable, Model I might propose a better set of solution for decision makers since it minimizes the total workload difference amongst rooms instead of only minimizing the maximum workload difference between any two rooms

    Organizing the U.S. Health Care Delivery System for High Performance

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    Analyzes the fragmentation of the healthcare delivery system and makes policy recommendations -- including payment reform, regulatory changes, and infrastructure -- for creating mechanisms to coordinate care across providers and settings

    Open-Access Scheduling

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    abstract: Declaration of Conflicts: This project has no conflicts of interest to declare. Context: This project was completed at a federally qualified primary healthcare clinic in Phoenix, Arizona that served patients of all age groups, but primarily cared for the Hispanic population providing primary care, preventative services, family planning, two lab technicians, one promoter, two medical assistant supervisors, five front desk staff, one chief administrative officer, one chief financial officer, two medical directoers who were also providers at the clinic. Problem and Analysis Assessment: During my clinical rotations, I saw the burden a missed patient appointment had not only on the patients themselves, but also on the clinic, providers, and the staff. It caused delay in treatment for patients, and it did not allow other patients that wanted to be seen to be seen. It also increased unnecessary costs and wasted provider time. Thereafter, I met with some of the leadership team and one of the medical directors to determine a solution to reduce the number of missed appointments that were occurring. An educational session was kept to discuss the findings of this problem to the providers and the staff and when surveys were handed out to the patients, providers, and staff to assess their satisfaction with the old scheduling system versus the new scheduling system, they were also provided with a cover letter discussing the project. Intervention: In order for improvements in care to occur, a system process change including the way patients are scheduled must occur. In this case, an open-access scheduling system (OAS) was implemented. OAS allows a patient to schedule an appointment on the 'same-day' or the 'next-day' to be seen. One provider at each of the clinics, each day of the week was available for 'same-day' appointments from 1300-1600. The providers were still available for scheduled appointments using the previous scheduling method. Walk-ins were still accepted, and were scheduled based on patient provider preference; however, if an appointment was not available for their preferred provider, they were typically seen with the provider that was the 'same-day' provider for that day. Strategy for change: Since patients were only allowed to schedule appointments one month in advance, only one month was needed to implement this process change. A recommendation for the future would be to clearly identify the patient encounter type, and label it as a same-day appointment, as this would be helpful when gathering and extracting data for this type of patient group specifically. Measurement of Improvement: Over a three-month period, a data collection plan was used to determine the number of Mas over a three-month period before and after implementation of this change. Satisfaction scores were measured using likert scales for patients, provider, and staff, and a dichotomous scale was used to determine the likelihood of emergency room or urgent care use. A comparison was done to measure revenue during the same time frame. During the three months, a clinically significant decrease in MAs was seen (68% of all patients, providers and staff reported feeling either very satisfied or extremely satisfied with the new scheduling system. Additionally, patients also reported that they were less likely to visit an emergency room(88%) or urgent care (90%) since they were able to be seen the same-day or the next-day by a provider. Effects of changes: An incidental finding occurred during this study - where 877 more patients were seen in the three months during the implementation of this project, compared to the three months prior; which likely resulted in a 41% increase in revenue. Additionally this project, allowed patients that wanted to be seen on the same day, to be seen, and it decreased unnecessary costs associated with emergency room or urgent care visits. Some of the limitations involved included the current political environment, appointment slots that were previously 15 minutes in length (in 2016), increased to 20 minutes in length (in 2017), a language barrier was noted for the patient surveys since English was not the first language for many of the patients who completed the survey (although documents were translated), and the surveys used were not reliable instrument given that a reliable instrument in previous studies could not be found. Lessons learnt: In order to have accuracy of the survey results, it is best for the author of the study to hand out and provide scripture for the survey so that complete data is received from the surveyors. Messages for others: Begin by making a small process change where only one provider allows for the open-access scheduling so that the entire office is not affected by it, and if results begin to look promising then it can be expanded. Additionally, correct labeling of patients as 'same-day' is also important so that additional data can be gathered when needed regarding the 'same-day' patients. Patient/Family/Guardian Involvement: Patients who benefited from the new scheduling system (open-access scheduling) were asked to fill out a survey that asked them to disclose some demographic data and asked them to determine their satisfaction with the new vs old scheduling system and their likelihood of visiting an emergency room or urgent care. Ethics Approval: Arizona State University Institutional Review Board (IRB) Received: September 201

    Practice-based Qualitative Research: Participant Experiences of Walk-in Counselling and Traditional Counselling

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    Walk-in single session counselling is becoming a more widely used model for delivering mental health services across Ontario. This paper reports findings from the qualitative phase of a mixed method study, exploring the experiences of those attending walk-in counselling (WIC) model compared to the traditional service delivery model employing a wait list. We used a comparative case study design for the qualitative phase. Findings reveal that participant outcomes of the walk-in counselling model is influenced by accessibility, how a participant makes sense of the service, and the degree to which a participant is motivated and able to engage in counselling. WIC supports the mental health system by reducing wait lists associated with traditional service delivery models, and meeting the needs many people identify for immediate consultation. Other participants still perceive themselves as requiring ongoing counselling over time and involving in-depth exploration. This research supports health systems providing access to both models
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