Department of Population Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, 615 N, Wolfe St,, Room E4622, Baltimore, MD 21205, USA.
Health Res Policy Syst. 2014 Jun 16;12:28. doi: 10.1186/1478-4505-12-28.
This paper presents a system dynamics computer simulation model to illustrate unintended consequences of apparently rational allocations to curative and preventive services.
A modeled population is subject to only two diseases. Disease A is a curable disease that can be shortened by curative care. Disease B is an instantly fatal but preventable disease. Curative care workers are financed by public spending and private fees to cure disease A. Non-personal, preventive services are delivered by public health workers supported solely by public spending to prevent disease B. Each type of worker tries to tilt the balance of government spending towards their interests. Their influence on the government is proportional to their accumulated revenue.
The model demonstrates effects on lost disability-adjusted life years and costs over the course of several epidemics of each disease. Policy interventions are tested including: i) an outside donor rationally donates extra money to each type of disease precisely in proportion to the size of epidemics of each disease; ii) lobbying is eliminated; iii) fees for personal health services are eliminated; iv) the government continually rebalances the funding for prevention by ring-fencing it to protect it from lobbying.The model exhibits a "spend more get less" equilibrium in which higher revenue by the curative sector is used to influence government allocations away from prevention towards cure. Spending more on curing disease A leads paradoxically to a higher overall disease burden of unprevented cases of disease B. This paradoxical behavior of the model can be stopped by eliminating lobbying, eliminating fees for curative services, and ring-fencing public health funding.
We have created an artificial system as a laboratory to gain insights about the trade-offs between curative and preventive health allocations, and the effect of indicative policy interventions. The underlying dynamics of this artificial system resemble features of modern health systems where a self-perpetuating industry has grown up around disease-specific curative programs like HIV/AIDS or malaria. The model shows how the growth of curative care services can crowd both fiscal and policy space for the practice of population level prevention work, requiring dramatic interventions to overcome these trends.
本文提出了一个系统动力学计算机模拟模型，以说明对治疗性和预防性服务的看似合理的分配所产生的意外后果。
模型中的人群只患有两种疾病。疾病 A 是一种可治愈的疾病，可以通过治疗性护理来缩短病程。疾病 B 是一种立即致命但可预防的疾病。治疗性护理工作者由公共支出和私人收费来治疗疾病 A 提供资金。非个人的预防性服务由公共卫生工作者提供，仅由公共支出支持，以预防疾病 B。每种类型的工作者都试图将政府支出的天平向自己的利益倾斜。他们对政府的影响与其累积收入成正比。
该模型演示了在几种疾病流行过程中，失去的残疾调整生命年和成本的影响。测试了包括以下政策干预措施：i）外部捐赠者理性地根据每种疾病的流行规模，按比例向每种疾病捐赠额外的资金；ii）消除游说；iii）消除个人卫生服务收费；iv）政府通过将预防资金专款专用来不断重新平衡预防资金的分配，以防止游说的影响。该模型表现出一种“投入更多，得到更少”的均衡状态，治疗部门的更高收入被用于影响政府的分配，使资金从预防转向治疗。增加对疾病 A 的治疗投入，会导致意想不到的更高的疾病 B 未预防病例的整体疾病负担。模型的这种自相矛盾的行为可以通过消除游说、消除治疗服务收费和将公共卫生资金专款专用来停止。
我们创建了一个人工系统作为实验室，以深入了解治疗性和预防性卫生分配之间的权衡以及指示性政策干预的效果。这个人工系统的基本动态类似于现代卫生系统的特点，在现代卫生系统中，围绕特定疾病的治疗性计划（如艾滋病毒/艾滋病或疟疾）已经形成了一个自我维持的行业。该模型展示了治疗性护理服务的增长如何挤占用于人口层面预防工作的实践的财政和政策空间，需要采取重大干预措施来克服这些趋势。
