Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, United States.
School of Nursing, University of Pennsylvania, Philadelphia, PA 19104, United States.
Artif Intell Med. 2015 Feb;63(2):61-71. doi: 10.1016/j.artmed.2014.08.006. Epub 2014 Sep 11.
Explore whether agent-based modeling and simulation can help healthcare administrators discover interventions that increase population wellness and quality of care while, simultaneously, decreasing costs. Since important dynamics often lie in the social determinants outside the health facilities that provide services, this study thus models the problem at three levels (individuals, organizations, and society).
The study explores the utility of translating an existing (prize winning) software for modeling complex societal systems and agent's daily life activities (like a Sim City style of software), into a desired decision support system. A case study tests if the 3 levels of system modeling approach is feasible, valid, and useful. The case study involves an urban population with serious mental health and Philadelphia's Medicaid population (n=527,056), in particular.
Section 3 explains the models using data from the case study and thereby establishes feasibility of the approach for modeling a real system. The models were trained and tuned using national epidemiologic datasets and various domain expert inputs. To avoid co-mingling of training and testing data, the simulations were then run and compared (Section 4.1) to an analysis of 250,000 Philadelphia patient hospital admissions for the year 2010 in terms of re-hospitalization rate, number of doctor visits, and days in hospital. Based on the Student t-test, deviations between simulated vs. real world outcomes are not statistically significant. Validity is thus established for the 2008-2010 timeframe. We computed models of various types of interventions that were ineffective as well as 4 categories of interventions (e.g., reduced per-nurse caseload, increased check-ins and stays, etc.) that result in improvement in well-being and cost.
The 3 level approach appears to be useful to help health administrators sort through system complexities to find effective interventions at lower costs.
探索基于代理的建模和模拟是否可以帮助医疗保健管理人员发现既能提高人口健康水平和护理质量，又能同时降低成本的干预措施。由于重要的动态往往存在于提供服务的卫生机构之外的社会决定因素中，因此本研究从三个层面（个人、组织和社会）对问题进行建模。
本研究探讨了将现有的（获奖）用于建模复杂社会系统和代理日常活动（如模拟城市风格的软件）的软件转换为所需决策支持系统的效用。案例研究测试了系统建模方法的三个层面是否可行、有效和有用。该案例研究涉及费城的一个有严重精神健康问题的城市人口和医疗补助计划人口（n=527056）。
第 3 节使用案例研究中的数据解释了模型，从而为使用真实系统建模的方法建立了可行性。使用国家流行病学数据集和各种领域专家的输入对模型进行了训练和调整。为了避免训练数据和测试数据的混合，然后运行模拟并将其与 2010 年对 25 万费城患者住院的分析进行比较（第 4.1 节），比较内容包括再住院率、就诊次数和住院天数。基于学生 t 检验，模拟与实际结果之间的偏差没有统计学意义。因此，在 2008-2010 年期间，验证了有效性。我们计算了各种类型的干预措施的模型，包括无效的干预措施和 4 类干预措施（例如，减少每名护士的病例数、增加检查和住院次数等），这些干预措施可改善幸福感和降低成本。
该三层面方法似乎有助于帮助卫生管理人员梳理系统复杂性，找到更具成本效益的有效干预措施。
