Wichita-Sedgwick County EMS System Department of Emergency Medicine, University of Kansas Department of Preventive Medicine and Public Health University of Kansas, Wichita, KS, USA.
Health Serv Res. 2013 Apr;48(2 Pt 2):735-52. doi: 10.1111/1475-6773.12041. Epub 2013 Feb 10.
Microsimulation was used to assess the financial impact on hospitals of a surge in influenza admissions in advance of the H1N1 pandemic in the fall of 2009. The goal was to estimate net income and losses (nationally, and by hospital type) of a response of filling unused hospital bed capacity proportionately and postponing elective admissions (a "passive" supply response).
Epidemiologic assumptions were combined with assumptions from other literature (e.g., staff absenteeism, profitability by payer class), Census data on age groups by region, and baseline hospital utilization data. Hospital discharge records were available from the Healthcare Cost and Utilization Project Nationwide Inpatient Sample (NIS). Hospital bed capacity and staffing were measured with the American Hospital Association's (AHA) Annual Survey.
Nationwide, in a scenario of relatively severe epidemiologic assumptions, we estimated aggregate net income of $119 million for about 1 million additional influenza-related admissions, and a net loss of $37 million for 52,000 postponed elective admissions.
Aggregate and distributional results did not suggest that a policy of promising additional financial compensation to hospitals in anticipation of the surge in flu cases was necessary. The analysis identified needs for better information of several types to improve simulations of hospital behavior and impacts during demand surges.
在 2009 年秋季 H1N1 大流行之前，使用微观模拟来评估流感入院人数激增对医院的财务影响。目标是估计应对措施（即按比例填补未使用的医院床位容量和推迟择期入院）的净收入和损失（全国范围内以及按医院类型）。
将流行病学假设与其他文献中的假设（例如员工缺勤率、按付款人类型划分的利润率）、按地区划分的年龄组的人口普查数据以及基线医院利用数据相结合。医院出院记录可从医疗保健成本和利用项目全国住院患者样本（NIS）中获得。医院床位容量和人员配备情况通过美国医院协会（AHA）年度调查进行衡量。
在相对严重的流行病学假设情景下，我们估计全国范围内，约有 100 万例额外的流感相关入院病例会带来 1.19 亿美元的总净收入，而 5.2 万例推迟的择期入院病例则会带来 3700 万美元的净损失。
总体和分布结果表明，在流感病例激增之前向医院承诺额外经济补偿的政策并非必要。该分析确定了需要更好的多种类型的信息，以改进需求激增期间医院行为和影响的模拟。
