Kudos for the Informatics Professor - 2023 Update

Periodically in this blog, lately once a year, I review all of my professional accomplishments, including honors, talks given, papers published, and more for the past year. Last year was a transitional year for me professionally, as I stepped down from two leadership positions as Chair of the Oregon Health & Science University (OHSU) Department of Medical Informatics & Clinical Epidemiology (DMICE) and from being Director of the OHSU Biomedical Informatics Graduate Program. As seen in this post, however, my productivity did not miss a beat in 2023, and in fact I am enjoying my work as much as ever by being able to focus on teaching, research, and writing.

I was awarded one honor in 2023 which was the Lifetime Achievement Award from the HIMSS Oregon Chapter.

I also gave a large number of invited talks, some in person and others virtual. Links to my slides and references, and for some, videos of the talks, are available on my Web site. The talks given include:

• From the Longwood Medical Area to Oregon: An Informatics Career Journey - Harvard Clinical Informatics Lecture Series (virtual), January 24, 2023
• Introduction to Informatics:  What You Should Know as a Health Services Researcher - VA Health Services Research & Development Advanced Fellowship Program (virtual), March 7, 2023
• Translational Artificial Intelligence (AI): The Need to Translate from Basic Science to Clinical Value - University of Iowa Distinguished Biomedical Scholars Lecture Series, Iowa City, IA, March 9, 2023
• Competencies and Curricula Across the Spectrum of Learners for Biomedical and Health Informatics - University of Texas Southwestern Clinical Informatics Research Colloquium (virtual), May 18, 2023
• Informatics Innovation: Quarter-Century of OHSU Leadership - HIMSS Oregon Chapter Annual Conference 2023, Portland, OR, June 1, 2023
• Biomedical and Health Informatics: An Essential Discipline for 21st Century Medicine - Informatics Colloquium, Department of Pathology, Indiana University School of Medicine (virtual), July 19, 2023
• Biomedical and Health Informatics: An Essential Discipline for 21st Century Medicine - Department of Medicine Meet the Global Expert Webinar, University of Cape Town, South Africa (virtual), August 17, 2023
• Artificial Intelligence: Implications for Health Professions Education - Keynote Talk, Commission on Accreditation for Health Informatics and Information Management (CAHIIM) Summit on Higher Education (virtual), September 28, 2023
• Artificial Intelligence in Medicine: Promise and Peril - Grand Rounds, Department of Pathology and Laboratory Medicine, OHSU (virtual), October 4, 2023
• ChatGPT and Other AI Tools for Medicine and Medical Education - International Association of Medical Science Educators (IAMSE) Fall 2023 Webcast Seminar Series: Brains, Bots, and Beyond: Exploring AI's Impact on Medical Education (virtual), October 5, 2023
• Artificial Intelligence: Implications for Health Professions Education - Educator’s Collaborative, OHSU (virtual), October 18, 2023
• Artificial Intelligence in Medicine: Promise and Peril - 33rd Infectious Diseases Society of Oregon Annual Meeting, Salem, OR, October 26, 2023
• Artificial Intelligence in Medicine: Promise and Peril - Public Health Officers Caucus of Oregon (virtual), November 28, 2023
• Artificial Intelligence: Implications for Informatics Education - OHSU DMICE Conference, Portland, OR, December 14, 2023

I also participated in a number of panels at meetings:

• Current Clinical Evidence and Available Technology - Voice AI Symposium, Bridge2AI-Voice Consortium, Washington, DC, April 19, 2023 (Panelist)
• Program Sustainability - Office of the National Coordinator for Health Information Technology (ONC) Public Health Informatics & Technology (PHIT) Workforce Program (virtual) June 20, 2023 (Panelist)
• Strategies for Effective and Equitable Partnerships - Third Meeting of the Data Science Initiative for Africa Consortium, Kigali, Rwanda, November 8, 2023 (Panelist)
• Building Human and Data Capacity in the NIH Data Science for Africa Initiative - AMIA Annual Symposium 2023, New Orleans, LA, November 13, 2023 (Panelist and Moderator)
• Bridging Training Gaps through Voice: An Ethics-based Approach to Teaching Trustworthy AI - AMIA Annual Symposium 2023, New Orleans, LA, November 14, 2023 (Panelist)
• Generative Applications of Large Language Models for Medical Education and Knowledge Searching: Shall We Count on ChatGPT and Co.? - AMIA Annual Symposium 2023, New Orleans, LA, November 15, 2023 (Panelist)

I appeared on an episode of the Health and Explainable AI Podcast from the University of Pittsburgh HexAI Research Laboratory.

I was awarded one new grant in 2023 but continued to be busy with my four existing grant projects. The new grant was an administrative supplement to an existing grant, the Bridge2AI Voice as a Biomarker project, to develop a summer school for college undergraduates and students in clinical training. My existing grants include a National Library of Medicine (NLM) R01, NLM training grants for informatics predocs and postdocs and for a college summer internship program, another training grant in the Data Science Initiative for Africa, and being part of the Skills and Workforce Development Module of the Voice as a Biomarker project.

I continued my teaching in 2023. As always, a major part of my teaching my introductory course in biomedical and health informatics, which is offered as BMI 510/610 at OHSU, the AMIA-OHSU 10x10 ("ten by ten") course, and as MINF 705A/709B, a medical student elective at OHSU. I also gave my annual lecture to OHSU medical students in their first month of class, Information is Different Now That You're a Doctor, on August 25, 2023.

Translational AI: A Necessity and Opportunity for Biomedical Informatics and Data Science

How much of the hype for artificial intelligence (AI) that will truly impact health, healthcare, and research is an unknown. The potential benefits are unequivocal, from assistant patients pursue actions to improve their health to giving guidance to clinicians in diagnosis and treatment to helping researchers find information and devise new ideas to advance their research.

I have published an invited post in the National Library of Medicine (NLM) Musings from the Mezzanine Blog, the blog of the Director of the NLM. I chose to update some of my past writings posted in this blog with a new discussion of what I call translational AI.

The tl;dr is:

• The actual day-to-day use of clinical AI in healthcare is still modest, according to surveys.
• While there are thousands of machine learning model papers that are published, and many systematic reviews of those model papers, there are a much small number, probably on the order of 100, randomized controlled trials (RCTs) of AI interventions in healthcare.
• Of those RCTs, not all have resulted in positive outcomes and a number of them have risk of bias concerns.

Clearly, as in all of healthcare, we cannot do RCTs on every permutation of model, implementation, setting, etc. of AI. However, we must treat AI the same way as any other tool we use in healthcare: Show us the evidence. Granted, evaluating the use of AI has plenty of differences from evaluating other interventions used in patient care, such as drugs and devices. It is difficult to conure a “placebo” for AI, and hard to perform controlled studies when AI, such as ChatGPT, is all around us.

Nonetheless, we can apply evidence-based medicine (EBM) to help inform its clinical use. The ideal way to do that is through randomized controlled trials (RCTs), or ideally systematic reviews of RCTs. As I note in the post, this is imperative not only for those of us who promote the use of AI and other biomedical and health informatics interventions, but also for students and trainees looking for projects to develop impactful research programs in their careers.

Whither Search? A New Perspective on the Impact of Generative AI on Information Retrieval (IR)

When I was putting the finishing touches on the 4th edition of my textbook on information retrieval (IR, also known as search) in the domain on biomedicine and health in 2020, I wondered whether the major problems in the field of IR were mostly solved. Retrieval systems such as Google for general Web searching and PubMed for the biomedical literature were robust and mature. One literally had the world’s written knowledge at their fingertips for general and biomedical topics from these systems respectively (even if paywalls did not always allow immediate access to the content).

There were certainly some areas of IR where additional work was needed and important, e.g., search over specific types of content such as social media or, in the case of my own research, electronic health record (EHR) data and text. There were also some nascent advances in the application of machine learning, although the gains in experimental results were more incremental than transformative.

But any staidness of IR was upended by the emergence of generally available generative artificial intelligence (AI) chatbots, based on large language models (LLMs), initially with ChatGPT and soon others to follow. Shortly thereafter came generative AI capabilities added to the two major Web search engines, Microsoft Bing and Google. All of a sudden, searching the Web was transformed in ways that most of us did not see coming.

I recently took advantage of the call for papers for a special issue devoted to ChatGPT and LLMs in biomedicine and health of the flagship journal for the field of informatics, JAMIA, to write a perspective piece on why search is still important, even in the era of generative AI. At least for me, while the answer to my question is important in a search, it is also critical to know where the information came from. In addition, as I am commonly synthesizing my own knowledge and views on a topic, I do not just want a single generative AI answer to my question but rather the source articles and documents so I can compare and contrast different views and develop my own answer.

At the close of the paper, I do acknowledge that there may well be areas of IR where generative AI may have major impact going forward. I know that there is a lot of buzz around retrieval-augmented generation (RAG), although for many of the questions on which I search, I am much more interested in generation-augmented retrieval (GAR?). That is, how can generative AI methods improve the way we search to steer us to the kinds of authoritative, originally sourced information we seek to carry out our work?

The day before the article was published, a reporter who came across my preprint wrote a piece on the impact of AI on search, noting some of the issues I raise with regards to accuracy and authority for search in fields like medicine and in academia.

The paper itself has been published in JAMIA as an Advance Article, Hersh W, Search still matters: information retrieval in the era of generative AI, Journal of the American Medical Informatics Association, 2024, ocae014. Unfortunately, the open-access publishing fee for JAMIA is fairly steep ($4125), especially for a short perspective piece like this, but those wanting to read it can access the preprint that I posted.