Healing With Algorithms: AI's Impact on Epidemiology and Infection Control

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Media in the US presents AI as both beneficial and risky. Positive coverage shows AI's potential through virtual assistants like Siri, while cautionary tales warn of misuse like misinformation and deepfakes. How does all this work in health care?

Health care innovative technologies   (Adobe Stock 146461139 by wladimir1804)

Health care innovative technologies

(Adobe Stock 146461139 by wladimir1804)

When people hear about artificial intelligence (AI), The Matrix, Terminator, and Ex Machina are popular movies that come to mind. Flashbacks of scenes where a human-like robot attempts to destroy humanity in films like Terminator tend to be what the general population believes AI can and will do. While these movies are entertaining, imagining these screenplays as a potential future reality can easily create a sense of doom and inflate fears of the unknowns of how society will implement AI.

Here, we will uncover ways that AI is currently being used by the general population and in health care. We will also list 3 practical applications we have discovered that will benefit from the ethical use of AI to help promote patient safety and improve infection prevention and epidemiology productivity. Before we dive deeper, what is AI?

Common Knowledge of the Population

Many people are fascinated by AI's capabilities, recognizing its potential to improve various aspects of life. From health care to entertainment, AI's ability to analyze data, make predictions, and automate tasks is impressive and beneficial, but there are also concerns.

US citizens, for example, worry about AI's impact on job security, fearing that automation would lead to widespread unemployment. Others express concerns about privacy and data security, particularly regarding the use of personal data by AI systems, as reported by Reuters and the Pew Research Center.1,2 Language models in the US are evolving, and AI is met with a combination of curiosity and skepticism about the possibilities and caution about the potential risks.

In the Media

In the US, the media's presentation of AI and language models has been multifaceted. Significant coverage has highlighted the potential benefits of AI.3-6 For example, AI-powered virtual assistants like Siri, Alexa, and Google Assistant are frequently featured in news articles and commercials, demonstrating their ability to understand and respond to natural language commands.

However, alongside these positive portrayals, some presentations highlight the challenges and risks associated with AI and language models. The media has reported on the misuse of AI, including the spread of misinformation, deepfake videos, and other forms of digital manipulation, which can have potentially negative political, financial, and social impacts. These narratives stress the importance of ethical considerations and regulations in developing and implementing AI technologies.

AI in Daily Work

As discussed above, AI is a broad field encompassing many types of implementations, with language models often serving as the general population's first encounter with AI. These models, such as chatbots or virtual assistants, are integrated into everyday technologies like smartphones and smart speakers, typically in the form of users asking questions. When users interact with these devices by asking questions or giving commands, they engage with AI-powered language models. This interaction introduces users to machines understanding and responding to human language. This initial encounter often sparks curiosity and interest in learning more about AI and its broader applications beyond language processing.

These language models allow machines to provide information and perform tasks based on learned behaviors and information humans provide. These results are provided in a way (typically by voice) that humans can then understand. While the implications of this concept can prove to be vast, let us focus on how AI is currently used in health care and how we can positively utilize it as a tool in infection prevention and epidemiology.

Current AI Applications in Infection Prevention and Epidemiology

Current literature shows that the current focus of AI use in health care from an infection prevention lens includes:

  1. Support of surveillance activities to help monitor trends in large datasets and identify potential infectious disease outbreaks promptly7,8;
  2. Enhanced diagnostic procedures with early detection of infectious organisms and early recognition of disease patterns allowing for prompt IPC interventions and outbreak containment activities7,8;
  3. Antimicrobial stewardship activities involving microbiologic data to predict appropriate therapies using machine learning to assess risk and modalities in programs8;
  4. Automatic hand hygiene reminders for health care workers with missed opportunities to help improve performance rates.8

AI as a Productivity Tool in Infection Prevention and Epidemiology

In the daily work of infection preventionists (IPs) and epidemiologists (EPIs), we are tasked with preserving the health and safety of our patients, staff, and communities. Responsibilities vary, including basic, repetitive tasks such as data entry and reporting and more complex work like data analysis, program development, and training. While straightforward tasks may only require a few minutes to complete, tackling more complex ones can result in increased labor, burnout, and the need to reprioritize other essential tasks. This is where the potential of AI can be utilized to simplify this work and help achieve our objectives more effectively. While there is a wide variety of practical ways that IPs and EPIs can use AI, we will only focus on 3 areas of their work: research, data analysis, and education.

Research

Primarily, AI can be used as an advanced search engine. The IP or EPI can type in the information they are researching to gather multiple resources on a specific topic with one prompt on a single AI tool or multiple AI tools for comparison if one prefers. Using one AI tool to gather multiple information sources simultaneously reduces research time and proves to increase productivity. However, it is important to highlight that not all AI applications are created equal, and the user must use due diligence, cross-referencing, and fact-checking to ensure that the sources of information are legitimate before disseminating it to the intended audience.

Data analysis

Reading and filtering through information from large databases can be a cumbersome aspect of the work that IPs and EPIs undertake daily. Countless hours of looking through COVID-19 data since the pandemic have proven quite exhausting and inefficient at times when IPs were needed at the frontline to be a resource for frontline staff and for EPIs who needed to engage promptly and educate the community on disease prevention methods. In several tests we ran, we were able to review and analyze information from an extensive database quickly by using AI, thus reducing our work from countless hours of data review and validation to a few minutes of data review and reduced hours in subsequent data validation. It is crucial to emphasize the importance of validating data when using any AI platform to perform such tasks to ensure the accuracy of the output.

Education

These technologies assist in creating educational materials or directives. The quality of the materials depends on the user's understanding and ability to provide appropriate prompts. They help identify knowledge gaps, prompting users to explore different approaches, pathways, and information sources they may not have considered before. For instance, when researching a policy, these tools can reveal directives or recommendations from previously unknown organizations, and the IP can subsequently use the information obtained to educate others.

Leveraging the power of AI in those 3 areas can increase IPs' and EPIs' productivity. However, they must also consider using it ethically. When submitting written works, the user must ensure that information is de-identified and follows HIPAA regulations and all the rules of ethics. Additionally, they must verify that the information published is not plagiarized when used to create educational materials and reports. These methods will help confirm the output’s validity and ensure accuracy before dissemination.

Where Do We Go From Here?

While entertainment has been depicting AI as an evil tool determined to destroy humanity, professionals should focus on the positive things they can and have been able to accomplish in health care by using it as a productivity tool. Regarding the future of AI, we cannot predict what it will become; however, as health care professionals, we can use it today for the common good to promote patient safety and further the work of infection preventionists and epidemiologists. Additionally, in doing so, the user must take extreme care to ensure that the information obtained from AI is accurate and follows professional and ethical standards.

References

  1. Sher G, Benchlouch A. The privacy paradox with AI. Reuters. October 31, 2023. Accessed February 6, 2024. https://www.reuters.com/legal/legalindustry/privacy-paradox-with-ai-2023-10-31/
  2. Smith A, Anderson J. AI, Robotics, and the Future of Jobs. Pew Research Center. August 6, 2014. Accessed February 6, 2024. https://www.pewresearch.org/internet/2014/08/06/future-of-jobs/
  3. Verel P. The Promise and Peril of Artificial Intelligence. Fordham News. September 30, 2021. Accessed February 6, 2024. Available from: https://news.fordham.edu/politics-and-society/the-promise-and-peril-of-artificial-intelligence/
  4. Mehra A. How AI Is Transforming Healthcare. Forbes. March 16, 2020. Accessed February 6, 2024. https://www.forbes.com/sites/forbestechcouncil/2020/03/16/how-ai-is-transforming-health care/?sh=504cf7774ba0
  5. Schaefer G, Littleton RJ, Koversky G, Rao R. What Generative AI Can Mean for Finance. The Wall Street Journal. September 21, 2023. Accessed February 6, 2024. https://deloitte.wsj.com/riskandcompliance/what-generative-ai-can-mean-for-finance-3032069e
  6. Brynjolfsson E, McAfee A. The Business of Artificial Intelligence. Harvard Business Review. July 18, 2017. Accessed February 6, 2024. https://hbr.org/2017/07/the-business-of-artificial-intelligence
  7. Fitzpatrick F, Doherty A, Lacey G. Using Artificial Intelligence in Infection Prevention. Curr Treat Options Infect Dis. 2020;12:135-144. doi:10.1007/s40506-020-00216-7
  8. De Corte T, Van Hoecke S, De Waele J. Artificial Intelligence in Infection Management in the ICU. Crit Care. 2022;26:79. doi:10.1186/s13054-022-03916-2


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