Decision Analysis最新文献_第5页

Multipolar Security Cooperation Planning: A Multiobjective, Adversarial-Risk-Analysis Approach 多极安全合作规划:多目标、对抗性风险分析方法

IF 1.9 4区管理学 Q3 Decision Sciences

Decision Analysis

Pub Date : 2022-08-24 DOI: 10.1287/deca.2022.0458

William N. Caballero, Ethan Gharst, David L. Banks, J. Weir

In an increasingly competitive environment, defense organizations are met with more difficult decisions than in years past. This problem is especially apparent in security cooperation, that is, defense diplomacy, conducted by the United States. Both the United States and its competitors offer military assistance to third-party nations who, in turn, select an offer based on their own self-interest. Unfortunately, current security cooperation planning practices adopt an ad hoc approach to such problems. Therefore, we set forth herein a decision-analytic-planning framework by (1) provisioning a generic utility model for security cooperation planning applicable to myriad stakeholders and (2) developing a Bayesian solution that allows the stakeholder to select an action that maximizes their expected utility. This combination of value-focused thinking and adversarial risk analysis improves upon standard U.S. defense practices; it tractably encodes planning assumptions and more comprehensively considers the relevant uncertainties. The efficacy of this planning approach is illustrated on a notional U.S. Air Force case study in which a host nation must choose between security assistance from the United States or a competing nation.

在竞争日益激烈的环境中，国防组织面临着比过去更困难的决策。这个问题在美国进行的安全合作，即国防外交中尤为明显。美国及其竞争对手都向第三方国家提供军事援助，而第三方国家则根据自身利益选择援助方案。不幸的是，目前的安全合作规划实践对这类问题采用了一种特别的方法。因此，我们通过(1)提供适用于无数利益相关者的安全合作规划的通用实用模型，(2)开发一个贝叶斯解决方案，允许利益相关者选择一个使其预期效用最大化的行动，在此提出了一个决策分析-规划框架。这种以价值为中心的思维和对抗性风险分析的结合改进了标准的美国国防实践;它可追溯地编码规划假设，并更全面地考虑相关的不确定性。这种规划方法的有效性在一个假想的美国空军案例研究中得到了说明，在这个案例研究中，东道国必须在来自美国或竞争国家的安全援助之间做出选择。

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引用次数: 0

Optimizing the First Response to Sepsis: An Electronic Health Record-Based Markov Decision Process Model 优化败血症的第一反应:基于电子健康记录的马尔可夫决策过程模型

IF 1.9 4区管理学 Q3 Decision Sciences

Decision Analysis

Pub Date : 2022-07-22 DOI: 10.1287/deca.2022.0455

Erik T. Rosenstrom, Sareh Meshkinfam, J. Ivy, Shadi Hassani Goodarzi, M. Capan, J. Huddleston, S. Romero-Brufau

Sepsis is considered a medical emergency where delays in initial treatment are associated with increased morbidity and mortality, yet there is no gold standard for identifying sepsis onset and thus treatment timing. We leverage electronic health record (EHR) data with clinical expertise to develop a continuous-time Markov decision process (MDP) optimal stopping model that identifies the optimal first intervention action (anti-infective, fluid, or wait). To study the impact of initial treatment of patients at risk for developing sepsis, we define the delayed treatment population who received delayed treatment upon admission or during hospitalization and serves as an approximation of the natural history of sepsis. We apply the optimal first treatment policy to sample patient visits from the nondelayed treatment population. This analysis indicates the average risk of death could be reduced by approximately 2.2%, the average time until treatment could be reduced by 106 minutes, and the average severity of the treatment state could be reduced by 15.5% compared with the treatment they received in the hospital. We study the properties of the optimal policy to define an easily interpretable initial treatment heuristic that considers a patient’s organ dysfunction, location, and septic shock status. This generalizable framework can inform personalized treatment of patients at risk for sepsis.

脓毒症被认为是一种医疗紧急情况，其中初始治疗的延迟与发病率和死亡率的增加有关，但没有确定脓毒症发病和治疗时机的黄金标准。我们利用电子健康记录(EHR)数据和临床专业知识开发了一个连续时间马尔可夫决策过程(MDP)最佳停止模型，该模型确定了最佳的首次干预行动(抗感染、输液或等待)。为了研究初始治疗对有脓毒症发生风险的患者的影响，我们定义了延迟治疗人群，他们在入院或住院期间接受了延迟治疗，并作为脓毒症自然历史的近似。我们将最优的首次治疗策略应用于非延迟治疗人群的样本患者访问。该分析表明，与他们在医院接受的治疗相比，平均死亡风险可降低约2.2%，平均治疗时间可减少106分钟，治疗状态的平均严重程度可降低15.5%。我们研究了最优策略的特性，以定义一个易于解释的初始治疗启发式，该启发式考虑了患者的器官功能障碍，位置和感染性休克状态。这一可推广的框架可以为有败血症风险的患者提供个性化治疗。

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引用次数: 4

Model Complexity and Accuracy: A COVID-19 Case Study 模型复杂性和准确性:COVID-19案例研究

IF 1.9 4区管理学 Q3 Decision Sciences

Decision Analysis

Pub Date : 2022-07-21 DOI: 10.1287/deca.2022.0457

Colin Small, J. Bickel

When creating mathematical models for forecasting and decision making, there is a tendency to include more complexity than necessary, in the belief that higher-fidelity models are more accurate than simpler ones. In this paper, we analyze the performance of models that submitted COVID-19 forecasts to the U.S. Centers for Disease Control and Prevention and evaluate them against a simple two-equation model that is specified using simple linear regression. We find that our simple model was comparable in accuracy to highly publicized models and had among the best-calibrated forecasts. This result may be surprising given the complexity of many COVID-19 models and their support by large forecasting teams. However, our result is consistent with the body of research that suggests that simple models perform very well in a variety of settings.

在为预测和决策创建数学模型时，人们倾向于包含比必要的更复杂的东西，因为人们相信高保真度的模型比简单的模型更准确。在本文中，我们分析了向美国疾病控制和预防中心提交COVID-19预测的模型的性能，并对使用简单线性回归指定的简单双方程模型进行了评估。我们发现，我们的简单模型在准确性上与广为宣传的模型相当，并且具有最佳校准的预测。考虑到许多COVID-19模型的复杂性以及大型预测团队的支持，这一结果可能令人惊讶。然而，我们的结果与研究主体一致，表明简单模型在各种环境中都表现得很好。

引用次数: 3

An Empirical Comparison of Rank-Based Surrogate Weights in Additive Multiattribute Decision Analysis 加性多属性决策分析中基于秩的代理权重的实证比较

IF 1.9 4区管理学 Q3 Decision Sciences

Decision Analysis

Pub Date : 2022-06-17 DOI: 10.1287/deca.2022.0456

R. C. Burk, Richard M. Nehring

Many methods for creating surrogate swing weights based only on the rank order of the attributes are proposed to avoid the cost and effort of eliciting weights in multiattribute decision analysis. We explore empirically how well eight different methods perform based on a large sample of real-world elicited weights. We use the Euclidean distance from the elicited weights to judge the quality of the surrogate weights as well as three other metrics. The sum reciprocal method gives results, on average, statistically closest to the elicited weights for all metrics used. The equal ratio method using a fixed ratio of 0.716 performs just as well on three of the metrics. The rank sum method, the simplest and one of the oldest methods, performs generally next best. The rank order centroid method, which does well in simulation studies, performs relatively poorly in this evaluation using real-world data.

为了避免在多属性决策分析中产生权重的成本和工作量，提出了许多仅基于属性的等级顺序来创建代理摆动权值的方法。我们从经验上探讨了八种不同的方法基于现实世界的大样本得出的权重的表现。我们使用欧几里得距离从引出的权重来判断代理权重的质量以及其他三个指标。平均而言，和倒数法给出的结果在统计上最接近所使用的所有指标的所得权重。使用固定比率0.716的等比率方法在三个指标上的表现也一样好。秩和方法是最简单的方法之一，也是最古老的方法之一，它的性能通常是次优的。秩序质心方法在模拟研究中表现良好，但在使用实际数据进行评估时表现相对较差。

引用次数: 1

Supporting Innovation in Early-Stage Pharmaceutical Development Decisions 支持早期药物开发决策的创新

IF 1.9 4区管理学 Q3 Decision Sciences

Decision Analysis

Pub Date : 2022-04-07 DOI: 10.1287/deca.2022.0452

Florian Methling, Steffen A. Borden, Deepak Veeraraghavan, Insa Sommer, J. Siebert, Rudiger von Nitzsch, Mark Seidler

Pharmaceutical companies have frequent portfolio reviews to monitor development progress and prioritize development assets. The earliest assets are drug candidates whose efficacy is unknown and whose effects on the human body have yet to be fully investigated. These assets are characterized by a high degree of uncertainty in reaching the market and in being used in clinical practice. In addition, not all potential applications are foreseen and can often be very different. In the absence of satisfactory methods for making decisions on resource allocation among early development assets, decision makers focus almost exclusively on assessments of an asset’s probability of technical success. This study proposes a more holistic methodology to support early-stage pharmaceutical development decisions using value-focused thinking and multicriteria decision making. The methodology operates within the decision quality framework and provides a consistent evaluation of various early development assets across a diverse set of disease areas. This combination of concepts and methodologies has been implemented and proven valuable at Bayer Pharmaceuticals, which needed a new, more robust decision-making process for early development. Thus, this study discusses how to enable concrete trade-offs at the level of corporate objectives to align, communicate, and translate corporate strategy into portfolio strategy. In addition, this study presents learnings for decision analysts and decision makers in the pharmaceutical industry on how to develop a set of fundamental objectives, how to create scales to operationalize these objectives, and how to take steps to debias an organizational decision-making process.

制药公司经常进行投资组合审查，以监视开发进度并确定开发资产的优先级。最早的资产是药效未知的候选药物，其对人体的影响尚未得到充分研究。这些资产的特点是在进入市场和在临床实践中使用方面具有高度的不确定性。此外，并不是所有潜在的应用都可以预见，而且可能会有很大的不同。在缺乏对早期开发资产的资源分配做出决策的令人满意的方法的情况下，决策者几乎只关注于评估资产的技术成功概率。本研究提出了一种更全面的方法来支持早期药物开发决策，使用以价值为中心的思维和多标准决策。该方法在决策质量框架内运作，并对不同疾病领域的各种早期开发资产提供一致的评估。这种概念和方法的结合在拜耳制药公司得到了实施，并被证明是有价值的，该公司需要一个新的、更强大的决策过程来进行早期开发。因此，本研究讨论了如何在公司目标水平上实现具体的权衡，以协调、沟通并将公司战略转化为投资组合战略。此外，本研究还为制药行业的决策分析师和决策者提供了关于如何制定一套基本目标、如何创建实现这些目标的尺度以及如何采取措施消除组织决策过程中的偏见的学习。

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引用次数: 1

Balanced Opioid Prescribing via a Clinical Trade-Off: Pain Relief vs. Adverse Effects of Discomfort, Dependence, and Tolerance/Hypersensitivity 通过临床权衡平衡阿片类药物处方:疼痛缓解与不良反应，不适，依赖，耐受性/过敏

IF 1.9 4区管理学 Q3 Decision Sciences

Decision Analysis

Pub Date : 2022-02-03 DOI: 10.1287/deca.2021.0447

Abdullah Gökçınar, M. Çakanyıldırım, Theodore John Price, Meredith C. B. Adams

In the backdrop of the opioid epidemic, opioid prescribing has distinct medical and social challenges. Overprescribing contributes to the ongoing opioid epidemic, whereas underprescribing yields inadequate pain relief. Moreover, opioids have serious adverse effects including tolerance and increased sensitivity to pain, paradoxically inducing more pain. Prescribing trade-offs are recognized but not modeled in the literature. We study the prescribing decisions for chronic, acute, and persistent pain types to minimize the cumulative pain that incorporates opioid adverse effects (discomfort and dependence) and the risk of tolerance or hypersensitivity (THS) developed with opioid use. After finding closed-form solutions for each pain type, we analytically investigate the sensitivity of acute pain prescriptions and examine policies on incorporation of THS, patient handover, and adaptive treatments. Our analyses show that the role of adverse effects in prescribing decisions is as critical as that of the pain level. Interestingly, we find that the optimal prescription duration is not necessarily increasing with the recovery time. We show that not incorporating THS or information curtailment at patient handovers leads to overprescribing that can be mitigated by adaptive treatments. Last, using real-life pain and opioid use data from two sources, we estimate THS parameters and discuss the proximity of our model to clinical practice. This paper has a pain management framework that leads to tractable models. These models can potentially support balanced opioid prescribing after their validation in a clinical setting. Then, they can be helpful to policy makers in assessment of prescription policies and of the controversy around over- and underprescribing.

在阿片类药物流行的背景下，阿片类药物处方具有明显的医疗和社会挑战。处方过量导致阿片类药物持续流行，而处方不足导致疼痛缓解不足。此外，阿片类药物具有严重的副作用，包括耐受性和对疼痛的敏感性增加，矛盾的是引起更多的疼痛。处方权衡是公认的，但没有在文献中建模。我们研究了慢性、急性和持续性疼痛类型的处方决定，以尽量减少阿片类药物不良反应(不适和依赖)的累积疼痛，以及阿片类药物使用引起的耐受或超敏反应(THS)的风险。在找到每种疼痛类型的封闭形式解决方案后，我们分析了急性疼痛处方的敏感性，并检查了结合三手疗法、患者移交和适应性治疗的政策。我们的分析表明，不良反应在处方决策中的作用与疼痛程度一样重要。有趣的是，我们发现最佳处方持续时间并不一定随着恢复时间的增加而增加。我们表明，在病人移交时不纳入三手烟或信息限制会导致处方过量，这可以通过适应性治疗来缓解。最后，利用来自两个来源的真实疼痛和阿片类药物使用数据，我们估计了三手烟参数，并讨论了我们的模型与临床实践的接近性。本文提供了一个疼痛管理框架，可以生成可处理的模型。这些模型在临床验证后可以潜在地支持平衡阿片类药物处方。然后，它们可以帮助政策制定者评估处方政策以及围绕处方过量和不足的争议。

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引用次数: 2

Stay Home or Not? Modeling Individuals’ Decisions During the COVID-19 Pandemic 呆在家里还是不呆?COVID-19大流行期间个人决策建模

IF 1.9 4区管理学 Q3 Decision Sciences

Decision Analysis

Pub Date : 2021-09-07 DOI: 10.1287/deca.2021.0437

Qifeng Wan, Xuan-hua Xu, Kyle Hunt, J. Zhuang

During the COVID-19 pandemic, staying home proved to be an effective way to mitigate the spread of the virus. Stay-at-home orders and guidelines were issued by governments across the globe and were followed by a large portion of the population in the early stages of the outbreak when there was a lack of COVID-specific medical knowledge. The decision of whether to stay home came with many trade-offs, such as risking personal exposure to the virus when leaving home or facing financial and mental health burdens when remaining home. In this research, we study how individuals make strategic decisions to balance these conflicting outcomes. We present a model to study individuals’ decision making based on decision and prospect theory, and we conduct sensitivity analysis to study the fluctuations in optimal strategies when there are changes made to the model’s parameters. A Monte Carlo simulation is implemented to further study the performance of our model, and we compare our simulation results with real data that captures individuals’ stay-at-home decisions. Overall, this research models and analyzes the behaviors of individuals during the COVID-19 pandemic and can help support decision making regarding control measures and policy development when public health emergencies appear in the future.

在2019冠状病毒病大流行期间，待在家里被证明是缓解病毒传播的有效方法。全球各国政府发布了居家令和指导方针，在疫情爆发的早期阶段，由于缺乏针对covid - 19的医学知识，很大一部分人都遵循了这些命令和指导方针。是否留在家里的决定需要做出许多权衡，例如离开家时可能会有个人接触病毒的风险，或者留在家里时面临经济和精神健康负担。在这项研究中，我们研究个人如何做出战略决策来平衡这些冲突的结果。基于决策与前景理论，建立了个体决策模型，并对模型参数变化时最优策略的波动进行了敏感性分析。为了进一步研究模型的性能，我们实施了蒙特卡罗模拟，并将模拟结果与捕获个人在家决策的真实数据进行了比较。总体而言，本研究对COVID-19大流行期间的个人行为进行了建模和分析，可以为未来出现突发公共卫生事件时的控制措施和政策制定决策提供支持。

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引用次数: 5

Optimal Policies for Reducing Unnecessary Follow-up Mammography Exams in Breast Cancer Diagnosis. 减少乳腺癌诊断中不必要的后续乳房x光检查的最佳政策。

IF 1.9 4区管理学 Q3 Decision Sciences

Decision Analysis

Pub Date : 2013-09-01 DOI: 10.1287/deca.2013.0272

Oguzhan Alagoz, Jagpreet Chhatwal, Elizabeth S Burnside

Mammography is the most effective screening tool for early diagnosis of breast cancer. Based on the mammography findings, radiologists need to choose from one of the following three alternatives: 1) take immediate diagnostic actions including prompt biopsy to confirm breast cancer; 2) recommend a follow-up mammogram; 3) recommend routine annual mammography. There are no validated structured guidelines based on a decision-analytical framework to aid radiologists in making such patient management decisions. Surprisingly, only 15-45% of the breast biopsies and less than 1% of short-interval follow-up recommendations are found to be malignant, resulting in unnecessary tests and patient-anxiety. We develop a finite-horizon discrete-time Markov decision process (MDP) model that may help radiologists make patient-management decisions to maximize a patient's total expected quality-adjusted life years. We use clinical data to find the policies recommended by the MDP model and also compare them to decisions made by radiologists at a large mammography practice. We also derive the structural properties of the MDP model, including sufficiency conditions that ensure the existence of a double control-limit type policy.

乳房x光检查是早期诊断乳腺癌最有效的筛查工具。根据乳房x光检查结果，放射科医生需要从以下三种选择中选择一种:1)立即采取诊断措施，包括及时活检以确认乳腺癌;2)建议随访乳房x光检查;3)建议每年例行乳房x光检查。目前还没有基于决策分析框架的有效的结构化指南来帮助放射科医生做出这样的患者管理决策。令人惊讶的是，只有15-45%的乳房活组织检查和不到1%的短间隔随访建议被发现是恶性的，导致不必要的检查和患者焦虑。我们开发了一个有限视界离散时间马尔可夫决策过程(MDP)模型，可以帮助放射科医生做出患者管理决策，以最大限度地提高患者的总预期质量调整生命年。我们使用临床数据找到MDP模型推荐的政策，并将其与放射科医生在大型乳房x光检查实践中做出的决定进行比较。我们还得到了MDP模型的结构性质，包括保证双控制-限制型策略存在的充分条件。

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引用次数: 28

Estimating Second Order Probability Beliefs from Subjective Survival Data. 从主观生存数据估计二阶概率信念。

IF 1.9 4区管理学 Q3 Decision Sciences

Decision Analysis

Pub Date : 2013-06-01 DOI: 10.1287/deca.2013.0266

Péter Hudomiet, Robert J Willis

Based on subjective survival probability questions in the Health and Retirement Study (HRS), we use an econometric model to estimate the determinants of individual-level uncertainty about personal longevity. This model is built around the modal response hypothesis (MRH), a mathematical expression of the idea that survey responses of 0%, 50%, or 100% to probability questions indicate a high level of uncertainty about the relevant probability. We show that subjective survival expectations in 2002 line up very well with realized mortality of the HRS respondents between 2002 and 2010. We show that the MRH model performs better than typically used models in the literature of subjective probabilities. Our model gives more accurate estimates of low probability events and it is able to predict the unusually high fraction of focal 0%, 50%, and 100% answers observed in many data sets on subjective probabilities. We show that subjects place too much weight on parents' age at death when forming expectations about their own longevity, whereas other covariates such as demographics, cognition, personality, subjective health, and health behavior are under weighted. We also find that less educated people, smokers, and women have less certain beliefs, and recent health shocks increase uncertainty about survival, too.

基于健康与退休研究(HRS)中的主观生存概率问题，我们使用计量经济模型来估计个人寿命不确定性的决定因素。该模型是围绕模态响应假设(MRH)建立的，这是一种数学表达，即对概率问题的调查回答为0%、50%或100%，表明相关概率的不确定性很高。我们发现，2002年的主观生存预期与2002年至2010年间HRS受访者的实际死亡率非常吻合。我们表明，MRH模型比主观概率文献中通常使用的模型表现得更好。我们的模型对低概率事件给出了更准确的估计，并且能够预测在主观概率的许多数据集中观察到的异常高比例的焦点0%、50%和100%的答案。我们发现，在形成对自己寿命的预期时，受试者过于看重父母的死亡年龄，而其他协变量，如人口统计学、认知、个性、主观健康和健康行为的权重不足。我们还发现，受教育程度较低的人、吸烟者和女性的信念不那么确定，最近的健康冲击也增加了人们对生存的不确定性。

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引用次数: 35

From the Editor---Decisions over Time (Exploding Offers or Purchase Regret), in Game Settings (Embedded Nash Bargaining or Adversarial Games), and in Influence Diagrams 从编辑器——决策随着时间的推移(爆炸报价或购买后悔)，在游戏设置(嵌入纳什讨价还价或对抗游戏)，并在影响图

IF 1.9 4区管理学 Q3 Decision Sciences

Decision Analysis

Pub Date : 2012-03-01 DOI: 10.1287/DECA.1110.0229

L. R. Keller

Our first two articles address decisions involving the passage of time. First, Steven A. Lippman and John W. Mamer explore the question of whether making “Exploding Offers” is beneficial to an employer seeking to hire or, in a more general framing of the question, to a purchaser of an asset. Next, in “Dynamic Purchase Decisions Under Regret: Price and Availability,” Enrico Diecidue, Nils Rudi, and Wenjie Tang examine situations in which a person can make a forward purchase in period 1 or a spot purchase in period 2. Our next two articles involve game theoretic models. In our third article, Steven A. Lippman and Kevin F. McCardle model joint decision making (motivated by dividing up a fortune) via “Embedded Nash Bargaining: Risk Aversion and Impatience.” The fourth article is “Robust Adversarial Risk Analysis: A Level-k Approach,” by Laura McLay, Casey Rothschild, and Seth Guikema. The final article is on “A Framework for Solving Hybrid Influence Diagrams Containing Deterministic Conditional Distributions,” by Yijing Li and Prakash P. Shenoy.

我们的前两篇文章讨论了涉及时间流逝的决策。首先，Steven a . Lippman和John W. Mamer探讨了这样一个问题，即“爆炸性报价”是否对寻求招聘的雇主有利，或者从更一般的角度来看，对资产的购买者有利。接下来，在“后悔下的动态购买决策:价格和可得性”一文中，Enrico Diecidue, Nils Rudi和Wenjie Tang研究了一个人可以在第一阶段进行远期购买或在第二阶段进行现货购买的情况。我们接下来的两篇文章涉及博弈论模型。在我们的第三篇文章中，Steven a . Lippman和Kevin F. McCardle通过“嵌入式纳什议价:风险厌恶和不耐烦”对共同决策(由分割财富驱动)进行了建模。第四篇文章是Laura McLay、Casey Rothschild和Seth Guikema撰写的“稳健的对抗性风险分析:Level-k方法”。最后一篇文章是关于“解决包含确定性条件分布的混合影响图的框架”，作者是Yijing Li和Prakash P. Shenoy。

引用次数: 3