Reading List: Fundamental Principles of Biomedical Informatics

The concerns of medical information science thus range from the designing and constructing of information systems (a useful but not especially interesting undertaking in the absence of a relevant theory) to the interesting but frequently unrewarded search for fundamental principles.

Marsden S. Blois, Information and Medicine:
The Nature of Medical Descriptions, 1984

The field of biomedical and health informatics has increasingly expanded its scope to a wider and wider range of application domains. Despite this widening scope, informatics applications have not yet had the transformative impact that information technology has had in other non-health domains.

It is my belief that this is because the field has largely ignored the search for fundamental principles that can serve to guide our applications and how we train informatics students.

This reading list is my attempt to highlight the few publications that have addressed fundamental, or foundational issues. It is not intended as a list of historically important biomedical informatics papers. Being based on my own experience and beliefs and (somewhat foggy) memory, it is also sure to leave out important foundational work.

I will be revising this list over time and would appreciate your feedback as part of this process.

Ledley RS, Lusted LB. Reasoning foundations of medical diagnosis. Science. 1959 Jul 3;130(3366):9-21.

Weed LL. Medical records that guide and teach. N Engl J Med. 1968 Mar 14;278(11):593-600.

Blois MS. Information and medicine: the nature of medical descriptions. University of California Press; 1984 Jan 1.

In my opinion this is the most important book ever written about biomedical informatics, because it is one of the few efforts to provide a solid theoretical foundation for the field. Although the book was published in 1984, most of the issues that Blois raises in the book have not yet been addressed and remain highly relevant today.

You can get a free scanned copy at the link above. If you prefer a physical copy, Amazon sometimes has them available here.

Cimino JJ. Desiderata for controlled medical vocabularies in the twenty-first century. Methods of information in medicine. 1998 Nov;37(4-5):394.

Rector AL. Clinical terminology: why is it so hard? Methods of information in medicine. 1999 Dec 1;38(4/5):239-52.

Musen MA. Medical informatics: searching for underlying components. Methods of information in medicine. 2002 Jan 1;41(1):12-9.

Friedman CP. A “fundamental theorem” of biomedical informatics. Journal of the American Medical Informatics Association. 2009 Mar 1;16(2):169-70.

Bernstam EV, Hersh WR, Johnson SB, Chute CG, Nguyen H, Sim I, Nahm MM, Weiner M, Miller P, DiLaura RP, Overcash MM. Synergies and distinctions between computational disciplines in biomedical research: perspective from the Clinical and Translational Science Award programs. Academic medicine: Journal of the Association of American Medical Colleges. 2009 Jul;84(7):964.

Bernstam EV, Johnson TR. Why Health Information Technology Doesn’t Work. The Bridge. 2009;39(3).

Bernstam EV, Smith JW, Johnson TR. What is biomedical informatics? Journal of biomedical informatics. 2010 Feb 1;43(1):104-10.

Kulikowski CA, Shortliffe EH, Currie LM, Elkin PL, Hunter LE, Johnson TR, Kalet IJ, Lenert LA, Musen MA, Ozbolt JG, Smith JW. AMIA Board white paper: definition of biomedical informatics and specification of core competencies for graduate education in the discipline. Journal of the American Medical Informatics Association. 2012 Nov 1;19(6):931-8.




On the Incredible Lightness of Real Education

Something wonderful happened in my daughter’s 4th grade class during the last week of school this year. The students in her class listened, completely engaged, to a series of presentations on science and engineering. They learned about the birth of stars, Gustav Eiffel and his creations–the Statue of Liberty and the Eiffel Tower–the life cycle of sea turtles, how lungs work, and much more. After each topic the students were eager to comment and ask questions–so much so that the session ran way over the scheduled time. What is more remarkable is that the lessons were given by fellow students, not teachers. The student presenters were also completely engaged in the content and in presenting and answering questions. They were clearly proud of what they had learned and in how they decided to present their topic to their classmates and parents. There was an astonishing variety of presentation types. One student used her own hand-drawn cartoon, another made a public web page about stars, my daughter and her classmate made a narrated video using toys and other props to show the lifecycle of sea turtles. Many of the students augmented their presentations with quiz questions delivered via the internet to each student’s mobile tablet. Several made board games. The sea turtle board game was replete with hazards, such as being eaten by a bird, or caught in a fishing net.

As I watched the class it struck me that this was real education. The skills these students were exhibiting, both as they presented and as they engaged in the presentations, are exactly the kinds of skills that we need in our society today. We need individuals who can study an area, learn the content, and then present the content in engaging and exciting ways. And we need people who can listen and ask insightful questions and give insightful comments.

Imagine what these students could do and WHO they would be if the entire year was spent on these kinds of real educational activities–activities that engaged and excited the entire class… every minute of every school day.

Sadly, much of the year is instead spent on preparing for standardized tests. When students do poorly on an assignment throughout the year they are often denied physical activity–they must stay in the classroom and work through boring worksheets. But these are young children–they need to play and they need physical activity. More importantly this is exactly the time when what we really need teach most of all is the joy of learning.

Summer break is nearly over now (it seems to get shorter every year), but my daughter still talks about that presentation. The standardized tests? We haven’t even seen the results.

What does it take to be an informatician?



Informatics is the science of information. Informaticians identify, define, and solve information problems. Determining whether one drug is better than another drug at treating a certain type of breast cancer is a clinical research question. Developing a method to automatically identify possible drugs for treating breast cancer from the published literature is an information problem.

Another example of an information problem is to automatically create meaningful patient overviews from a patient’s electronic medical record. What information constitutes a good overview? How does “good” depend on the goal of the person looking at the overview? How can you extract meaningful information from the free text in the chart? How can you best present the information so that a person can quickly grasp it?

Suppose you create and test a mobile application to help diabetic patients track meals, exercise, insulin, glucose, and HBA1C, then study whether it improves glucose control. This is not an informatics problem or solution, because it does not identify or solve an information problem. Just because it uses a mobile application (IT) to track data, does not make it an informatics solution–informatics is neither computer science nor IT, though it often uses both as tools. What would be a good informatics problem in this area? One informatics approach is to study the kinds of actions a diabetic patient needs to take and the kinds of information they need to determine which action to take, then create a visualization that allows them to quickly “see” what they need to do.

So what do you need to be an informatician? At a minimum, a set of skills called computational thinking, or CT for short. Google breaks CT into several fundamental skills, including:

  • Decomposition: Breaking down a problem into smaller more manageable parts.
  • Pattern Recognition: Observing patterns, trends, and regularities.
  • Pattern Generalization and Abstraction: Discovering the laws, or principles that cause patterns.
  • Algorithm Design: Creating an ordered set of instructions for solving similar problems or for doing a task.

Although CT, including algorithm design, is not programming or math, at present the best way to learn and demonstrate CT skills is by learning to develop and program algorithms and create computational and mathematical models.

There are a number of ways you can get these skills. For computational thinking I recommend:

The Udacity classes are very good because of the interactive in-video code editor with real-time feedback. You should be able to sign up for free or low cost versions of these classes.

A good place to start for mathematical models are with these:

If you only have time for a couple take Intro to CS and Model Thinking first. But keep learning. These are essential skills for informaticians and as an informatician you will ALWAYS need to learn more–especially technical skills. The more technical skills you have, the more employable you are.

Some people may tell you that many top informaticians never program or develop mathematical models. That’s true, but look at what they do and you will see all of the elements of CT. Learning to program and apply mathematical models is just a path to developing your CT skills.

Too often biomedical informatics programs shy away from teaching or requiring technical skills, because they worry that students from diverse, non-technical backgrounds will not be able to learn the skills. This is nonsense. First, CT skills are absolutely necessary for doing informatics. Second, like any set of skills CT skills can be taught and learned. So if you are looking for an informatics program, be sure to choose one that teaches or requires these skills. If you are in a program that does not, make sure you get them for yourself. You simply cannot be an informatician without them.

To support this post consider using one of my referral links below:

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For information on how I record audio in class and in my office see: Voice Recording Equipment

Recording high quality audio for online courses

Screen Shot 2015-03-13 at 10.10.39 AMA perfect audio recording won’t make bad online content good, but poor audio can destroy good content. I found this out the hard way when I first taught an online course in Fall, 2014. Much of the online content for the course came from video of the classroom lectures that our Instructional Tech team captured, mostly as an aide for the occasional student who could not make it to class. I never planned to use these recordings for the online version of the class, but on review I found the content and presentation style much better than I expected, such that with careful editing I could have reasonably high quality content. However, the sound ranged from OK to unintelligible. I tried to use Audacity, an excellent free, open source sound editor, to correct the problems. It helped… but couldn’t perform miracles. So I turned to recording new content. Certainly, the sound would be better with newly recorded content and audio in my office, right? Wrong! I quickly discovered that background noise present in most office environments–the hiss of AC vents, the click of a trackpad, the shuffling of notes–wreaked havoc with audio quality. And then there were inexplicable periods in which the audio was completely garbled. I ended up spending a considerable amount of time over a 2 month period learning about audio recording equipment and sound processing software. I now have tremendous respect for audio engineers. In an effort to distill what I’ve learned, I’ve created a page on  Voice Recording Equipment that I plan to update as I learn more. Check it out and let me know what you think.

Tips for online education



In Fall 2014 I taught my first online-only course, HI6340: Health Information Visualization and Visual Analytics. After completing the original Stanford MOOCs on AI and Machine Learning and a few UDACITY classes, I knew that I liked the UDACITY style of video with embedded questions, but wasn’t quite sure how to go about designing and producing an online course. I spent Summer and Fall 2014 researching online course design and best practices and preparing (while also teaching) the class. Although I still have a lot to learn about online education, I’ve learned a lot that I will be sharing through this site. Today I’m starting with Pedagogy for Online Courses. I’ll be adding others to this, including pages for interactive content preparation and audio recording.