Computational Thinking from a Healthcare Perspective: By Jim Eldridge from the CPATH AdCom group

As I sought out inspiring examples of computational thinking, I looked up quite a few articles on computational thinking and watched Dr. Wing’s YahooLabs presentation on the subject. Most were interesting, but still left me without a crystal clear idea of what CT is or what “inspiring examples” of it would be. Rather than be paralyzed in thought or analysis, I decided to just start jotting down my notes and thoughts and see where that takes me. I also decided to focus on HealthCare since that is my identified area of contribution to the group. So here goes:

Dr. Wing’s article identified examples of computational thinking such as robotic surgery, virtual colonoscopies, and electronic health records. I will comment on these and others I think appropriate, but before doing so I would add that I think the opportunities for using CT in healthcare are tremendous for the following reasons:

It is extremely complex. Ethical issues abound in healthcare, and the number of dollars spent at end of life can be staggering for what, in many cases, are inevitable outcomes. Technology has played a huge role in improvement of outcomes but at a huge price tag. Chronic conditions and risk management issues are enormous. I will never forget a visioning session with my staff regarding how the implementation of the electronic medical record was going to change what we do, and we concluded that though we currently manage masses of complex data, in the future would be managing more masses of more complex data.

There is currently a lot of waste. The estimated impact of poor quality or waste in the healthcare industry is staggering. This comes in many different forms, including errors, unnecessary procedures and care, etc.

We have a problem, Houston. Healthcare costs are creating a real problem for American businesses. It is a problem that definitely needs to be solved.

Okay, here are some overall comments on things that I have witnessed relative to computational thinking in healthcare.

1. We have been doing it for a long time. Over 20 years ago we were looking at how we could use computational thinking (I think it could be described as that) to improve patient outcomes. We did this in a lot of ways, but I think one good example (although very simple) was looking at our databases to ensure that diabetics were hooked up with an ophthalmologist. Diabetics have a much higher propensity for eye disease. We did this by looking at prescriptions for insulin and ensuring that anyone who had been prescribed insulin was also seen by an ophthalmologist.

2. Electronic Medical Record. This component is still very early in its implementation, but there have been several findings from it.

· Medication errors were reduced tremendously. The system provides for checks and balances on medications and automatically checks for anything outside of those parameters and requires override to be administered. This has resulted in a big drop in medication errors.

· Some unintended consequences. Redacting medical record data became much more difficult, requiring a lot of work to set up parameters for what really is the record, what should be printed out to share for a variety of sources, i.e. claim and attorney review.

· Not tremendous cost savings—yet. Perhaps that is the great test of how to utilize the data in a manner that will result in savings.

3. Google is better at predicting the flu season than the CDC (Center for Disease Control). Some comments on this are shared below, but I agree that this really opens up the idea at looking at healthcare data and outcomes in a totally different light, and probably indicates a need for expertise outside of the traditional healthcare arena. Google’s experiment in trending flu outbreaks is absolutely – and I mean absolutely – amazing. I’d bet that any professional epidemiologist would cringe at the idea of using non-clinical data to identify disease trends, but this application boggles my mind. Here’s how it works. Google meters its search queries on flu-related topics, figuring that the more that people search on a flu topic, the more likely the flu is occurring in real life. It does not measure anything clinical – nothing about positive throat cultures, visits to emergency departments, or any other traditional sentinel reporting measures. Just search queries. The demo on Google’s own website shows how, using data from the 2007-2008 flu season, it can identify flu trends two weeks ahead of anyone else, including the CDC. The data for this current season – the first full season with the H1N1 virus – confirm that many people are getting sick with the flu already, months before the traditional height of the flu season.

4. Robotic Surgery—da Vinci machines are an example of advances in Robotic surgery and I believe were invented with the intent of enabling the ability for someone across the globe to complete and do a surgery on someone on the other end. It also circumvents current limitations in the design of the human body. For example, the human wrist cannot perform a 360 degree rotation, while the robot can. This allows for a better range of performance and thus, better outcomes. Cost becomes another large issue here as it is very expensive. But the da Vinci robots eliminate two big issues in surgical care:

· Physical location of the surgeon—the surgeon could be across the globe and complete the surgery with the appropriate equipment.

· Physical limitations of the surgeon—i.e., the 360 degree rotation of the wrist.

And from the neither here nor there category, I always find quotes inspiring. I liked the following and found it while I was searching. It does not apply directly to computational thinking, but you get the idea:
“Digital fluency" should mean designing, creating, and remixing, not just browsing, chatting, and interacting.
Mitchel Resnick

Innovation and Technological Convergence With Our Physical World

I searched high and low for an innovative approach that met the CT requirements of Dr. Peckham's, "...absent the computer...", and Jeannette Wing's, "...way humans, not computers, think, solve problems..." providing a point of reference for our students to become inspired and intrigued in the potential promise of technology, and came across this piece. Enjoy!

CPATH II Proposed Timeline

In preparation for the many months of meaningful work ahead, the Executive Committee has prepared the following proposed (and certainly changeable) timeline for the term of the grant. This will be discussed in detail in subsequent meetings.

In addition to the above calendar, the executive committee is now working with a new proposed group structure. It can be "briefed" as follows:

  • The executive committee (ExecCom for short)is a group of approximately 12 core individuals charged with overall planning, implementation, mentoring and guiding throughout the term of the project. They lead the larger group, establish time lines, and have clearly defined responsibilities (e.g., facilitation, work product development, BLOG management)
  • The task group (TaskCom for short) is made up of additional individuals charged with spearheading development of CT modules and infusion strategies for all segments and disciplines in education. Smaller task groups will be derived from this group with the addition of others, and each will presumably accomplish its task with a slightly different approach.
  • The advisory committee (AdCom for short) is the largest group, and includes potential members from a variety of groups and individuals with an interest in the project. They will provide input to the other groups on the progress of the project through a variety of communication channels. All members of this group will be charged with bringing others to the table, and with spreading the word to colleagues and contacts in the community. This will be the most fluid group, and the one withe the least-defined responsibilities. It will also meet with the least frequency.

Soon, ExeCom will act on codifying this proposed group structure, and will set out schedule for future meetings for each of the three groups.

On CT Framework and Rebranding CISE

The recent e.mail exchange regarding the unmentionable, "E" and other "scary" CISE terms brought to mind the discussion regarding re-branding of these terms. So I've put together a few thoughts along those lines. The key question being,

"How can we get the student's attention, and interest in CT / CISE subject matter?"

FLC could provide for a cross-disciplinary Managed Information CT Education Framework with coursework that is sufficiently broad based, innovative, and flexible enough (as technology and industry evolves) to act as a clearinghouse between student's career objectives / aspirations / desires and the skilled labor requirements of business in the year 2020, while maintaining overall education goals for a variety of student segments..

We could begin with:

I. An Introduction to (Computational) Thinking - a G.E. prerequisite that is broad based, illustrating problem solving, information management, introduction to industry (and government), future career options and skills required by employers, student interest, and skills development.

The CT General Education (G.E.) Disciplinary framework could provide for:

  1. Personalization & Participation: Offer program tracks that engages their interests (CT tracks).
  2. Speak in their language and the language of industry/business (re branding taxonomy from traditional to modern)
  3. Provide a pathway to jobs and career opportunities.
  4. Show students the opportunities to achieve their aspirational goals via their interests.
  5. "Soft" start through functional disciplines of interest to them and re branding of CS terms (more on that below).
  6. Targeted student segmentation - student focus, attention via broad based CT introductory prerequisites. and career exploration embedded in the course.
  7. Speak to their altruism - Innovation -"Change the world" opportunities - technology in alternative energies, health care, media, entertainment, entrepreneurship, industry, government, education, etc.
II. The framework enables a Student Driven CT Management Program where different "tracks" position the students for different functions in the industry. This would allow the student to self select and direct in the industry based on their interests and choose an academic track defined and validated by the skills requirements of industry.

III. A G.E. Innovation in Information Management Pathways Program (for Services and Industry) that delineates disciplinary functional tracks with some core courses and elective (experimental) disciplinary industry offerings.

Ex: Innovation in Health care; Innovation in (place industry here)

Ex: Innovation in Marketing; Innovation in (place business function here)

The program prepares its students to learn to think critically (CT) in the identification and analysis of complex systems and work with/manipulate abstract conceptual frameworks to derive, create and deliver value for the organization (beyond the G.E. beginning CT course) within the context of a discipline of their interest.

IV. Beyond the Introduction to CT (G.E.) coursework, and its application to a particular discipline, we then engage the students in the possibilities of such thinking by enabling the study of CT in Innovation as an interdisciplinary subject.

Introduction to Innovation in [insert discipline here]; or "Introduction to Next Generation Disciplines"; a hook, to bring in the audience and have them learn to apply CT in an interdisciplinary manner while simultaneously exploring the potential possibilities of many career paths as they work with students from different tracks in the program.

V. Re-branding (and re-engineering) of existing coursework to express the CT objectives within core CISE to facilitate access, integration with the CT program framework, and approachability of computer science and engineering subjects.
  • Programming? "Introduction to Application Development (Software Engineering) and Management"- inclusion of Facebook development for example, may be more compelling than just traditional languages.
  • Database? "Introduction to Information Management"
Terms like Word Processing, Spreadsheets, Database sound dated and give the perception of low level skills. We should "speak" to student's aspirations and inspire them to achieve. So we re brand and re engineer such coursework. Example:

"Introduction to Business or Office Productivity Suites" where assignments can include presenting a marketing campaign (or other industry specific function/discipline), developing and populating database to feed spreadsheets with pivot tables for calculations merging the results with targeted marketing campaign documents that are published on the web (marketing just being an example of a higher value functional area of potential interest for students).

What thoughts do all of you have regarding the development of a multi-level framework - CT basics, CT + discipline, and CT + interdisciplinary, and the re-branding of terms that perhaps alienate the students from pursuits of such CISE disciplines?

Teaching the Facebook Generation

A call for CT.

Our goal as college professors is to open students minds to new experiences so they can grow intellectually while they mature through the traditional four-year process. But we are also challenged to give students the immediate skills they will need once they graduate so that they can begin their professional careers and move away from the fry-o-later to the cubicle and beyond.

Over the past decade, there has been a sea change in the marketplace demands for graduates. Whereas broad skills used to be sufficient, now our students must demonstrate a set of concrete skills that not long ago were required only of those in highly technical majors. Nowhere has this change created a greater shift than in fields such as marketing and public relations, which traditionally have been viewed as nontechnical but are now demanding a technological competency that is astounding.

The rest of the article can be found here.

Computational Thinking at work?

Study Less, Remember More

Tom Meloche, Gus Mondalek, Eric Justusson, Rich Roberts, and William Cavnar

Companies regularly shell out big bucks for employees to attend professional training seminars. But research shows employees forget 80% of what they learn within a month of the event. Software developer and serial entrepreneur Tom Meloche, 46, a figure within the who has taught corporate seminars since the late 1980s, is trying to change that. Building on clinical research on human cognition, his Ann Arbor (Mich.) company makes software designed to increase knowledge retention by customizing lessons based on an individual user’s responses. Meloche says students who use the software need to study only three to five minutes three to four days a week in order to recall material over an extended period. His team is also writing algorithms meant to determine the most important information for students to learn in the first place.

So far, five-person Procuit, founded in 2007, has created a test app for Facebook (over 10,000 people have used it), landed one commercial customer for custom work, and launched a home-schooling application, (which charges $20 per user), in August. Meloche says Procuit recently received a $50,000 unsecured loan from a local incubator to develop and market the home-schooling product. He expects just under $100,000 in revenue in 2009 and around $500,000 in 2010.