Health Care Management Science最新文献_第9页

Fair allocation strategies for opioid settlements. 阿片类药物解决方案的公平分配策略。

IF 2 3区医学

Health Care Management Science Pub Date : 2025-09-01 Epub Date: 2025-08-07 DOI: 10.1007/s10729-025-09716-8

Qiushi Chen, Robert Newton, Paul Griffin

{"title":"Fair allocation strategies for opioid settlements.","authors":"Qiushi Chen, Robert Newton, Paul Griffin","doi":"10.1007/s10729-025-09716-8","DOIUrl":"10.1007/s10729-025-09716-8","url":null,"abstract":"Multi-billion-dollar opioid settlement agreements have been reached with pharmaceutical manufacturers and distributors to address their liability in contributing to the opioid epidemic in the United States. These agreements stipulate that within the state, the settlement funds must be directly allocated to local government (e.g., counties) and used for abatement activities to remediate the harm of the opioid epidemic in communities. This naturally leads to an important question of how the funds should be distributed to meet the diverse needs of the counties consistently across all counties to be deemed fair. Although there exist various definitions of fairness in the literature, it remains unclear how to empirically quantify the fairness of settlement allocation based on data, which is crucial for developing evidence-based allocation policies. To fill this gap, we define two allocation fairness measures, deviation and maximum regret, and formulate the fair settlement allocation as convex optimization problems. To further enhance the interpretability of the allocation policies, we restrict the allocation to a weighted sum of the given empirical metrics. We apply our analytical framework in a case study of the settlement allocation in Pennsylvania using real-world empirical metrics. We identify the frontiers of the non-dominated allocation policies between min-deviation and minimax-regret allocations, which dominate all alpha fairness-based and formula-based allocation policies. All allocation policies show lower fairness (with higher deviation or maximum regret) in counties that are rural, low-income, and with lower-ranking health factors. The price of interpretability is more significant in terms of maximum regret compared with deviation.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":" ","pages":"335-356"},"PeriodicalIF":2.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12535511/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144794223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reinforcement learning for healthcare operations management: methodological framework, recent developments, and future research directions. 用于医疗运营管理的强化学习：方法框架、最新发展和未来研究方向。

IF 2.3 3区医学

Health Care Management Science Pub Date : 2025-06-01 Epub Date: 2025-04-09 DOI: 10.1007/s10729-025-09699-6

Qihao Wu, Jiangxue Han, Yimo Yan, Yong-Hong Kuo, Zuo-Jun Max Shen

引用次数: 0

A comparative inpatient care efficiency analysis of safety-net vs. non-safety-net hospitals: an analysis using Massachusetts inpatient claims data from 2015 to 2019. 安全网与非安全网医院住院病人护理效率的比较分析：使用马萨诸塞州2015年至2019年住院病人索赔数据的分析

IF 2.3 3区医学

Health Care Management Science Pub Date : 2025-06-01 Epub Date: 2025-04-25 DOI: 10.1007/s10729-025-09704-y

Jiaye Shen, Dominic Hodgkin, Jennifer Perloff

{"title":"A comparative inpatient care efficiency analysis of safety-net vs. non-safety-net hospitals: an analysis using Massachusetts inpatient claims data from 2015 to 2019.","authors":"Jiaye Shen, Dominic Hodgkin, Jennifer Perloff","doi":"10.1007/s10729-025-09704-y","DOIUrl":"10.1007/s10729-025-09704-y","url":null,"abstract":"This study examines the inpatient service efficiency of safety-net and non-safety-net hospitals using a two-stage approach at both the hospital and physician levels. For the hospital-level analysis, we conducted 430 Data Envelopment Analysis (DEA) models at the first stage to measure efficiency at the Diagnosis-Related Groups (DRG) level. In the second stage, Tobit and logistic regression models were applied to compare safety-net hospitals to non-safety-net hospitals. For the physician-level analysis, we conducted 386 DEA models to measure individual physician efficiency within specific DRGs. In the second stage, we compared the performance of the same physicians working in safety-net versus non-safety-net hospitals. The findings reveal that non-safety-net hospitals demonstrate significantly higher efficiency than safety-net hospitals. However, comparisons of the same physicians across settings show no significant differences in individual efficiency. This suggests that the efficiency gap arises not from the support or motivation provided by hospitals but from differences in the quality of physicians employed. These results underscore the need for policies that help safety-net hospitals attract and retain high-quality physicians to bridge the efficiency gap and better serve vulnerable populations.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":" ","pages":"178-190"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143989333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Streamlining emergency department workflow: reducing length of stay with congestion-triggered standing orders. 简化急诊科的工作流程：减少因拥堵引发的住院时间。

IF 2.3 3区医学

Health Care Management Science Pub Date : 2025-06-01 Epub Date: 2025-04-26 DOI: 10.1007/s10729-025-09705-x

Saied Samiedaluie, Vera Tilson, Armann Ingolfsson

{"title":"Streamlining emergency department workflow: reducing length of stay with congestion-triggered standing orders.","authors":"Saied Samiedaluie, Vera Tilson, Armann Ingolfsson","doi":"10.1007/s10729-025-09705-x","DOIUrl":"10.1007/s10729-025-09705-x","url":null,"abstract":"Standing orders allow triage nurses in emergency departments (EDs) to order tests for target patients prior to a physician evaluation. Standing orders specify the medical conditions for which a triage nurse is permitted to order tests but typically do not specify the operational conditions under which ordering tests is desirable, from either a system or a patient point of view. We examine the operational impacts of standing orders on the ED as a whole, and propose a threshold policy for activating standing orders as a function of ED congestion. To parameterize the threshold policy we develop three simplified models: 1) an infinite-server model to derive an easily-computed feature for predicting whether activating standing orders would be beneficial, 2) a Jackson network model, to demonstrate that standing orders can lead to diverse outcomes for different patient populations, and 3) a Markov decision process model, to quantify the optimality gap for our threshold policy. We confirm the tentative findings from the simplified models in a more realistic setting using a simulation model that is calibrated with real data. We find that the threshold policy, with a threshold that is a simple function of the aforementioned feature, performs well across a wide range of parameter values. We demonstrate potential unintended consequences of the use of standing orders, including overtesting and spillover effects on non-target patients. Medical studies demonstrate that the use of standing orders decreases average ED length of stay (LOS) for target patients. Our research shows the importance of investigating the impact of standing orders on the ED as a whole.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":" ","pages":"143-159"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144004526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ambulance location and relocation under budget constraints: investigating coverage-maximization models and ambulance sharing to improve emergency medical services performance. 预算限制下的救护车位置和重新安置：调查覆盖最大化模型和救护车共享以提高紧急医疗服务绩效。

IF 2.3 3区医学

Health Care Management Science Pub Date : 2025-06-01 Epub Date: 2025-05-21 DOI: 10.1007/s10729-025-09708-8

Youness Frichi, Lina Aboueljinane, Fouad Jawab

{"title":"Ambulance location and relocation under budget constraints: investigating coverage-maximization models and ambulance sharing to improve emergency medical services performance.","authors":"Youness Frichi, Lina Aboueljinane, Fouad Jawab","doi":"10.1007/s10729-025-09708-8","DOIUrl":"10.1007/s10729-025-09708-8","url":null,"abstract":"Ambulance location in Emergency Medical Services (EMS) is a widely studied problem requiring efficient resource allocation within budgetary constraints. The literature has focused on enhancing EMS performance with limited attention given to their economic performance. This study addresses EMS performance with an emphasis on budget constraints by revising three coverage maximization models: the time-dependent Maximum Expected Coverage Location Problem (time-dependent MEXCLP), the multi-period Double Standard Model (mDSM), and the multi-period Queueing Maximal Availability Location Problem (Q-MALP-M2). These models are adapted to incorporate ambulance types, multi-period relocation, and budget constraints related to costs associated with ambulance station openings, ambulance acquisition, transport, and multi-period relocation. The revised models, along with two hybrid models (model 1 and model 2), were evaluated and compared using a discrete-event simulation model based on three key performance indicators: 1) coverage, 2) waiting time, and 3) time to arrive at the hospital. Additionally, the study investigates ambulance sharing as a policy to enhance EMS performance, wherein a single ambulance serves two patients whenever feasible. The study uses data from the Fez-Meknes region in Morocco, collected in 2021. Results indicate that hybrid model 1 outperformed the other models in most scenarios, as it allows for the decentralization of ambulances by investing the allocated budget in constructing new ambulance stations and acquiring new ambulances, contrasting with the other models that allocate almost the entire budget to purchasing new ambulances. Furthermore, the findings reveal that ambulance sharing significantly improves EMS performance, particularly under tightening budgetary restrictions and increasing demand; however, the benefits of ambulance sharing diminish as the allocated budget increases.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":" ","pages":"274-297"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144110311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Visualisation of Data Envelopment Analysis in primary health services. 初级卫生服务中数据包络分析的可视化。

IF 2.3 3区医学

Health Care Management Science Pub Date : 2025-06-01 Epub Date: 2025-05-02 DOI: 10.1007/s10729-025-09702-0

Ane Elixabete Ripoll-Zarraga, José Luis Franco Miguel, Carmen Fullana Belda

{"title":"Visualisation of Data Envelopment Analysis in primary health services.","authors":"Ane Elixabete Ripoll-Zarraga, José Luis Franco Miguel, Carmen Fullana Belda","doi":"10.1007/s10729-025-09702-0","DOIUrl":"10.1007/s10729-025-09702-0","url":null,"abstract":"Benchmark efficiency analysis in public health typically focuses on hospitals rather than primary care providers. Data Envelopment Analysis (DEA) is widely used to assess resource efficiency among decision-making units (DMUs). However, traditional DEA struggles to differentiate between efficient units and is sensitive to the selection of inputs and outputs. Methods like super-efficiency and cross-efficiency address some of these limitations but often exclude outliers and may overlook efficiency related to specialisation. DEA Visualisation integrates DEA with multivariate statistical methods allowing for the identification of inefficiency sources and specialisation patterns without losing discriminatory power or removing extreme cases from the sample. This study analyses 82 public primary health centres in Madrid serving senior citizens in 2018. The findings reveal inefficiencies such as a preference for prescribing specific rather than generic drugs, increasing public health costs. Additionally, two extreme cases (outliers or mavericks) were identified as having high infrastructure costs and disproportionate staffing. Redistributing patients from overcrowded centres could enhance efficiency, while centres focused on preventive care showed greater cost-effectiveness, particularly in reducing prescription costs.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":" ","pages":"207-233"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12137389/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143976627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A compartmental modelling methodology to support strategic decision making for managing the elective hospital waiting list; application in England's NHS. 采用分区建模方法，支持管理择期医院候诊名单的战略决策；英国国民健康保险制度的应用。

IF 2.3 3区医学

Health Care Management Science Pub Date : 2025-06-01 Epub Date: 2025-05-13 DOI: 10.1007/s10729-025-09709-7

Richard M Wood, David J Worthington

{"title":"A compartmental modelling methodology to support strategic decision making for managing the elective hospital waiting list; application in England's NHS.","authors":"Richard M Wood, David J Worthington","doi":"10.1007/s10729-025-09709-7","DOIUrl":"10.1007/s10729-025-09709-7","url":null,"abstract":"Waiting list models can support improved strategic management of elective hospital care through estimating possible performance impacts resulting from different demand and capacity related interventions. Single-compartment models have previously been used to model the referral 'inflow' and treatment 'outflow' onto a waiting list, with some also considering the outflow of patients reneging from the waiting list before treatment. The conceptual simplicity of these models promotes scalability through aligning to various waiting list problems and routine data sources. However, these single-compartment models are only able to model waiting list size, and not waiting times. To address this, we extend the single-compartment model with reneging to consider a multi-compartment model, where each compartment represents the number of individuals awaiting treatment for progressively longer periods of time. This problem is formulated in discrete time and solved through a series of difference equations. Open-source code for implementing the model is made freely available. To illustrate the versatility of the methodology, the model is calibrated using routine data for the total England NHS waiting list as of year-end 2023 and used to project various scenarios over the following two years to year-end 2025. Model validation is performed through backtesting (running the model on past unseen data), with 0.4% and 4.7% MAPE attained on six and twelve month windows respectively.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":" ","pages":"259-273"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144006467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Blood platelet inventory management: Incorporating data-driven demand forecasts. 血小板库存管理：结合数据驱动的需求预测。

IF 2.3 3区医学

Health Care Management Science Pub Date : 2025-06-01 Epub Date: 2025-05-02 DOI: 10.1007/s10729-025-09706-w

Maryam Motamedi, Jessica Dawson, Na Li, Douglas Down

{"title":"Blood platelet inventory management: Incorporating data-driven demand forecasts.","authors":"Maryam Motamedi, Jessica Dawson, Na Li, Douglas Down","doi":"10.1007/s10729-025-09706-w","DOIUrl":"10.1007/s10729-025-09706-w","url":null,"abstract":"Platelet products are vital in the blood transfusion system since they are used for treating serious diseases such as cancer. They are expensive products (C$504 per unit) with a short shelf life of five to seven days. Since platelet demand is uncertain and highly variable, platelet inventory management is a challenging task. In this work, we propose a data-driven inventory management model for platelet products that incorporates demand forecasts in the inventory management process. The proposed model uses forecast-dependent target inventory levels to determine an ordering policy that has a goal of minimizing both the shortage and wastage. The data used in this study is a large clinical dataset of daily platelet transfusions for a centralized blood distribution centre for four hospitals in Hamilton, Ontario, spanning from 2016 to 2018. Experimental results show that our proposed policy performs well in minimizing shortages and wastages and that larger forecast errors can be tolerated as the system scales (for example as a result of demand aggregation and inventory pooling). We also perform sensitivity analysis to provide a more in-depth study of the proposed model. In particular, we suggest that by incorporating demand forecasts in the inventory management model, ordering less frequently than daily is feasible.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":" ","pages":"191-206"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144063504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of subsidy policies on the financial status of trauma centers. 补助政策对创伤中心财务状况的影响。

IF 2.3 3区医学

Health Care Management Science Pub Date : 2025-06-01 Epub Date: 2025-04-23 DOI: 10.1007/s10729-025-09701-1

Lin Lin, Pratik J Parikh

{"title":"Impact of subsidy policies on the financial status of trauma centers.","authors":"Lin Lin, Pratik J Parikh","doi":"10.1007/s10729-025-09701-1","DOIUrl":"10.1007/s10729-025-09701-1","url":null,"abstract":"Trauma centers (TCs) play a crucial role in improving patient safety of severely injured individuals, but require substantial financial resources to operate effectively. TCs in low-insured areas are particularly at risk of being confronted with financial deficits, and a threat of closure, due to the inability to recover costs from uncompensated care. While some states in the US provide financial subsidies to support these centers, the diversity of state subsidy policies and their impacts on TC financial viability are poorly understood. To address this, we introduce a generalized subsidy distribution formula that incorporates key components from various state policies. Based on that, we further propose a TC Financial Evaluation Model that employs Monte Carlo simulation to assess the effects of different subsidy policies along three proposed metrics. Utilizing realistic data from multiple US states and national insurance statistics, we conduct a comprehensive experimental study. Our findings suggest that the financial performance of TCs could be affected by the total subsidy amount, the Uninsured level within the Trauma Service Area (TSA), and the specific subsidy distribution policy employed. This research provides trauma decision-makers a quantitative tool to evaluate, compare, and design subsidy policies tailored to their unique demographic and economic contexts, potentially leading to a more standardized approach to mitigate existing policy disparities across states.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":" ","pages":"160-177"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143977581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Location planning, resource reallocation and patient assignment during a pandemic considering the needs of ordinary patients. 考虑到普通患者的需要，在大流行期间进行地点规划、资源重新分配和患者分配。

IF 2.3 3区医学

Health Care Management Science Pub Date : 2025-06-01 Epub Date: 2025-05-10 DOI: 10.1007/s10729-025-09703-z

Yu Lu, Shaochong Lin, Zuo-Jun Max Shen, Junlong Zhang

{"title":"Location planning, resource reallocation and patient assignment during a pandemic considering the needs of ordinary patients.","authors":"Yu Lu, Shaochong Lin, Zuo-Jun Max Shen, Junlong Zhang","doi":"10.1007/s10729-025-09703-z","DOIUrl":"10.1007/s10729-025-09703-z","url":null,"abstract":"During the initial phase of a pandemic outbreak, the rapid increase in the number of infected patients leads to shortages of medical resources for both pandemic-related and non-pandemic (ordinary) patients. It is crucial to efficiently utilize limited existing resources and strike a balance between controlling the pandemic and sustaining regular healthcare system operations. To tackle this challenge, we introduce and investigate the problem of optimizing the location of designated hospitals, reallocating beds within these hospitals, and assigning different types of patients to these hospitals. Designated hospitals isolate pandemic-related patients from ordinary patients to prevent cross-infection. Moreover, isolation beds can be converted into ordinary beds and vice versa. Considering the stochasticity and evolving nature of the pandemic, we formulate this problem as a multi-stage stochastic programming model, integrating a compartmental model with time-varying random parameters to enable dynamic resource allocation as the pandemic progresses. The model is then solved by a data-driven rolling horizon solution approach. We illustrate the effectiveness of our model using real data from the COVID-19 pandemic. Compared with two other approaches, our model demonstrates superior performance in controlling the spread of the pandemic while addressing the needs of both pandemic-related and ordinary patients. We also conduct a series of experiments to uncover managerial insights for policymakers to better utilize existing resources in response to pandemic outbreaks. Results indicate that admitting as many pandemic-related patients as possible during the initial phases of the outbreak can effectively flatten the pandemic peaks and alleviate strain on the healthcare system.","PeriodicalId":12903,"journal":{"name":"Health Care Management Science","volume":" ","pages":"234-258"},"PeriodicalIF":2.3,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144004525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0