SEI: Data Mining for Multiple Antibiotic Resistance

目前用于治疗细菌感染的抗菌药或抗生素药库是可用的最重要的公共卫生工具之一，但它并不是取之不尽的资源。抗菌药物的使用越随意，目标病原体就会产生越多的耐药性。一旦病原体对所有可用的药物产生抗药性，治疗感染患者可能变得困难或不可能。该项目是计算机科学家和健康科学家之间的合作，旨在开发数据挖掘工具，以发现医院内(医院获得性)感染何时以及为什么出现抗菌素耐药性。数据挖掘工具是一种计算机程序，用于自动检测非常大的数据库中的重要趋势和模式，由于数据量和复杂性，人类分析师很难发现这些趋势和模式。首先是问题的严重性。在每年住院的3600万美国人中，大约有200万人会感染医院感染，导致9万多人死亡，其中许多人直接与耐药细菌有关。据估计，与院内病原体耐药性相关的经济负担每年从45亿美元到300亿美元不等。不幸的是，由于经常接触抗菌剂，医院是对大多数或所有可用的治疗方法产生抗药性的“超级细菌”的理想滋生地。因此，如果能够在开发工具方面取得任何进展，以帮助卫生科学家了解问题发生的原因和方式，回报可能是巨大的。研究医院感染很重要的第二个原因是，医院是一个受控的、数据丰富的环境，在那里可能相对容易了解有效管理抗菌药物的规则。该项目将开发的数据挖掘工具旨在从医院重症监护病房、微生物实验室和药房搜索数据，以寻找耐药微生物感染的模式。该项目的技术重点是数据的时间性或时效性。该项目将开发的数据挖掘工具可用于检测医院感染模式随时间的变化，以及发现因果关系，这些因果关系可能向卫生科学家建议，抗菌剂的使用模式似乎与未来耐药微生物的发展有关。与外部卫生科学家的接触是该项目的重要组成部分，目的是将该项目的结果传播给更大的社区，以便对抗菌素耐药性问题产生积极影响。该项目开发的用于模式发现的计算机软件将公开供流行病学家使用，该项目将提供软件使用方面的支持和教程。该项目的另一个目标是向未来的科学家和工程师介绍科学研究。该项目资金的很大一部分将用于支持本科生研究人员，他们将在该项目将开发的软件的开发和应用中发挥重要作用。

The current arsenal of antimicrobial or antibiotic drugs for treating bacterial infection is one of the most important public health tools available, but it is not an inexhaustible resource. The more haphazardly antimicrobial drugs are used, the more the targeted pathogens develop resistance. Once a pathogen develops resistance to all of the available drugs, treating an infected patient may become difficult or impossible. This project is a collaboration between computer scientists and health scientists aimed at developing data mining tools for discovering when and why antimicrobial resistance appears in nosocomial (hospital acquired) infections. Data mining tools are computer programs for automatically detecting important trends and patterns in very large databases that would be difficult for a human analyst to spot due to the amount and complexity of the data.Nosocomial resistance is a particularly significant problem for two reasons. The first is the severity of the problem. Approximately 2 million of the 36 million Americans hospitalized each year will acquire a nosocomial infection, resulting in more than 90,000 deaths, many of them directly related to drug-resistant bugs. Estimates of the financial burden associated with resistance among nosocomial pathogens range from 4.5 billion dollars to 30 billion dollars annually. Unfortunately, because of constant exposure to antimicrobials, hospitals are ideal breeding grounds for "super bugs" resistant to most or all of the available treatments. Thus, if any progress can be made towards developing tools that can help health scientists to understand why and how problems occur, the payoff may be enormous. The second reason that studying nosocomial infection is important is that hospitals are a controlled, data rich environment where it may be relatively easy to learn the rules of effective stewardship of antimicrobial drugs.The data mining tools that the project will develop are targeted towards searching data from a hospital intensive care unit, microbiology laboratory, and pharmacy for patterns in drug-resistant microbial infections. The technical emphasis of the project is on the temporal or time-oriented nature of the data. The data mining tools the project will develop can be used to detect changes in the patterns of nosocomial infections over time, as well as to discover cause-effect relationships that might suggest to health scientists what antimicrobial use patterns seem to be linked with the development of drug-resistant microbes in the future.Outreach to external health scientists is a vital part of the project, with the goal of disseminating the project's results to the larger community in order to have a positive impact on the problem of antimicrobial resistance. The computer software for pattern discovery that is developed by the project will be made publicly available for use by epidemiologists, and the project will provide support and tutorials on software usage. Another goal of the project is introducing scientific research to tomorrow's scientists and engineers. A significant fraction of the project's funds will be used to support undergraduate researchers who will play a significant role in the development and application of the software the project will develop.