Health Care Management Science

期刊简介：Health Care Management Science publishes papers dealing with health care delivery, health care management, and health care policy. Papers should have a decision focus and make use of quantitative methods including management science, operations research, analytics, machine learning, and other emerging areas. Articles must clearly articulate the relevance and the realized or potential impact of the work. Applied research will be considered and is of particular interest if there is evidence that it was implemented or informed a decision-making process. Papers describing routine applications of known methods are discouraged.Authors are encouraged to disclose all data and analyses thereof, and to provide computational code when appropriate.Editorial statements for the individual departments are provided below.Health Care AnalyticsDepartmental Editors:Margrét Bjarnadóttir, University of MarylandNan Kong, Purdue UniversityWith the explosion in computing power and available data, we have seen fast changes in the analytics applied in the healthcare space. The Health Care Analytics department welcomes papers applying a broad range of analytical approaches, including those rooted in machine learning, survival analysis, and complex event analysis, that allow healthcare professionals to find opportunities for improvement in health system management, patient engagement, spending, and diagnosis. We especially encourage papers that combine predictive and prescriptive analytics to improve decision making and health care outcomes.The contribution of papers can be across multiple dimensions including new methodology, novel modeling techniques and health care through real-world cohort studies. Papers that are methodologically focused need in addition to show practical relevance. Similarly papers that are application focused should clearly demonstrate improvements over the status quo and available approaches by applying rigorous analytics. Health Care Operations ManagementDepartmental Editors:Nilay Tanik Argon, University of North Carolina at Chapel HillBob Batt, University of WisconsinThe department invites high-quality papers on the design, control, and analysis of operations at healthcare systems. We seek papers on classical operations management issues (such as scheduling, routing, queuing, transportation, patient flow, and quality) as well as non-traditional problems driven by everchanging healthcare practice. Empirical, experimental, and analytical (model based) methodologies are all welcome. Papers may draw theory from across disciplines, and should provide insight into improving operations from the perspective of patients, service providers, organizations (municipal/government/industry), and/or society. Health Care Management Science PracticeDepartmental Editor:Vikram Tiwari, Vanderbilt University Medical CenterThe department seeks research from academicians and practitioners that highlights Management Science based solutions directly relevant to the practice of healthcare. Relevance is judged by the impact on practice, as well as the degree to which researchers engaged with practitioners in understanding the problem context and in developing the solution. Validity, that is, the extent to which the results presented do or would apply in practice is a key evaluation criterion. In addition to meeting the journal’s standards of originality and substantial contribution to knowledge creation, research that can be replicated in other organizations is encouraged. Papers describing unsuccessful applied research projects may be considered if there are generalizable learning points addressing why the project was unsuccessful.Health Care Productivity AnalysisDepartmental Editor:Jonas Schreyögg, University of HamburgThe department invites papers with rigorous methods and significant impact for policy and practice. Papers typically apply theory and techniques to measuring productivity in health care organizations and systems. The journal welcomes state-of-the-art parametric as well as non-parametric techniques such as data envelopment analysis, stochastic frontier analysis or partial frontier analysis. The contribution of papers can be manifold including new methodology, novel combination of existing methods or application of existing methods to new contexts. Empirical papers should produce results generalizable beyond a selected set of health care organizations. All papers should include a section on implications for management or policy to enhance productivity.Public Health Policy and Medical Decision MakingDepartmental Editors:Ebru Bish, University of AlabamaJulie L. Higle, University of Southern CaliforniaThe department invites high quality papers that use data-driven methods to address important problems that arise in public health policy and medical decision-making domains. We welcome submissions that develop and apply mathematical and computational models in support of data-driven and model-based analyses for these problems. The Public Health Policy and Medical Decision-Making Department is particularly interested in papers that: Study high-impact problems involving health policy, treatment planning and design, and clinical applications; Develop original data-driven models, including those that integrate disease modeling with screening and/or treatment guidelines; Use model-based analyses as decision making-tools to identify optimal solutions, insights, recommendations.Articles must clearly articulate the relevance of the work to decision and/or policy makers and the potential impact on patients and/or society. Papers will include articulated contributions within the methodological domain, which may include modeling, analytical, or computational methodologies.Emerging TopicsDepartmental Editor:Alec Morton, University of StrathclydeEmerging Topics will handle papers which use innovative quantitative methods to shed light on frontier issues in healthcare management and policy. Such papers may deal with analytic challenges arising from novel health technologies or new organizational forms. Papers falling under this department may also deal with the analysis of new forms of data which are increasingly captured as health systems become more and more digitized.

【译文】《Health Care Management Science》发表关于医疗保健提供、医疗保健管理和医疗保健政策的论文。论文应具有决策焦点，并使用包括管理科学、运筹学、分析、机器学习和其他新兴领域的定量方法。文章必须清楚地阐述工作的相关性和实现或潜在的影响。应用研究将被考虑，如果有证据表明它被实施或影响了决策过程，则特别感兴趣。不鼓励描述已知方法常规应用的论文。作者应披露所有数据和数据分析，并在适当的情况下提供计算代码。以下为各个部门的编辑声明。医疗保健分析部门：Margrét Bjarnadóttir，马里兰大学；Nan Kong，普渡大学。随着计算能力和可用数据的爆炸性增长，我们在医疗保健领域看到的分析应用发生了快速变化。医疗保健分析部门欢迎应用广泛分析方法的论文，包括基于机器学习、生存分析和复杂事件分析的论文，这些方法可以帮助医疗保健专业人员发现改进卫生系统管理、患者参与、支出和诊断的机会。我们特别鼓励结合预测和规范性分析以提高决策和医疗保健成果的论文。论文的贡献可以跨越多个维度，包括新的方法论、新颖的建模技术和通过现实世界队列研究进行的医疗保健。以方法论为重点的论文需要展示实际的相关性。同样，以应用为重点的论文应通过应用严格的统计分析，清楚地表明与现状和现有方法的改进。