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Where Should Our Brains Be? Final Chapter: Electrons

This is the final installment in this thread. (Whew!)

In his presentation, Christensen explored the domain of expertise. He used the example of the development of fiber optic cable materials. A few decades ago fiber optic materials science was not well understood and the technology to fashion new molecules into new fiber strands that could carry light signals was held by only the most capital-intensive companies in that domain. Today, the materials molecular science is better and more widely understood with thousands of people involved in the development of new types of fiber optic cabling using desktop-sized equipment. That moved the science in that domain from an intuitive process requiring high levels of expertise and experience with very expensive capital equipment to an intermediate phase based on evidence as to how materials would react to various operations involved in synthesis to a final state of rules that guide both our understanding of the underlying physics and mathematics as well as their application using sophisticated systems that apply those rules in fabrication. Quite a journey that helps explain the accelerating pace of change in technology.

I would add that another force is at play as well. It's the pathway that successful technology takes--successful in the fact of its widespread adoption. All new technologies--whether interesting molecules or new machines--at first don't work well, require significant expertise to use, and cost a lot of money. If they are successful, they become reliable and effective, can be used by non-experts, and get cheaper. If they are digital, they can even become free. Chris Anderson explored that in Free: The Future of a Radical Price: The Economics of Abundance and Why Zero Pricing Is Changing the Face of Business (a book that was offered for free in digital form. Really!).

In my mind the real transition we are making is to use electrons to assist our work rather than molecules. If a process can be based on unique arrangements of electrons then it has lower costs and higher effectiveness than its older molecule-based method. In English: medical records are potentially cheaper and more powerful if they are in electronic systems rather than paper files. Setting aside the transition question (a deft dodge), electronic health records will allow the physician treating you to see your medical history without asking you about it. Every treatment, medication, and reading--potentially back to birth. But there's more.... Being able to process millions of records of people with similar characteristics or medical issues will allow physicians to become much better in their jobs. Rather than drawing on the few thousands of patients that an individual may treat in a career, being able to analyze millions' of patients records across millions of procedures will enhance that provider's expertise since she/he will be using the accumulated experience of an entire profession. It's sort of like going in to the hospital for surgery. Do you want the physician who has done 10 such procedures on patients or one who has done 4000? (Duh!) Imagine drawing on the experience of 4,000,000 such procedures, and you can get the impact of scale.


Where Should Our Brains Be? Continued...

Let's resume from our earlier post about the sociology of data visualization. 

So, are we leaving out the human element in our approach? The response is, "Of course not!" Yet, I should explain where we are in the development of our innovation. To explore that, one more digression is in order.

Monday and Tuesday last week, NC State University hosted the Emerging Issues Forum, an annual gathering of state leaders and experts on important issues of the day. This year's forum was on health care and featured Clayton Christensen. He has written a series of very influential books on innovation, leading off with The Innovator's Dilemma. His talk was an update to his thesis that innovation comes in two varieties--sustaining and disruptive. Sustaining in the sense that an organization is changing its product and service to better serve its current customers and hold or increase market share. Think of Sears during most of the 20th Century as the dominant retailer through its catalogs and retail stores in cities and towns. The other variety is disruptive innovation. That can come is several forms. One is essentially an intruder that offers a better value proposition to an underserved part of the market. Think here of WalMart and its rise in the late 20th Century as it moved into the towns and cities from rural areas, featuring substantially lower prices. Eventually WalMart eclipsed Sears as the dominant retailer in the United States. But that is not the only type of disruptive innovation. There is another variant sort of in the same domain--eBay. That is a reseller, but of people not previously engaged in such commerce at a global scale. eBay took the swap meet and put it online, bringing retailing to the masses and creating a global market where none existed before.

Christensen suggested that health care is ripe for disruptive innovation, particularly since the costs keep rising faster than economic growth. He suggested that there were two ways to look at that. The first is to recognize that systems tend to centralize services overtime. In his narrative, we once had the solution come to us when a physician made a house call. (I still remember Dr. Ball coming to my house when we all had chicken pox.) The advent of diagnostic and treatment technology started forcing the patient go to the physician's office or even the pinnacle of medical infrastructure--the hospital. No wonder healthcare spending rose as the costs of infrastructure (both equipment and expertise) grew in scope. Despite these changes and the centralization of care, he noted the evolving character of technologies emerging that allow for hand held ultrasound diagnostic machines to be used by primary care providers that do well enough for everyday medical issues. Rather than pay for the truck-sized MRI and PET scanners, these devices can do some of that job in the physician's offices. For the equipment manufacturers, that opened a new market that the big scanning companies had overlooked. Therefore, he thought that such developments might foster a countercyclical decentralization of healthcare with the big caveat that all other things remain neutral.

(More to come!)


Where Should Our Brains Be?

A colleague sent me an interesting and thought-provoking message a few days ago. It challenged a characteristic of the paradigm we have been following in developing the system of NCB-Prepared. Our initial approach is to access data across a number of domains (clinical, emergency, food safety, weather, etc.) and look for patterns that may be emerging threats to human health. The emphasis is on the analytics that can find the signal in all the data noise. It is necessarily a data- and technology-heavy approach.

The alternative he suggested involves creating and leveraging social networks of experts to understand phenomena. Although he did not reference it, he seemed to move in the same pathway as James Surowiecki explored in The Wisdom of Crowds. The notion he was proposing was connecting a crowd of experts in an online community to allow them to observe, comment, and learn from each other to address issues of cognition (essentially figure out what's going on) together. The connections across organizational borders would reduce the effects of siloed information and expertise that tend to crop up. Across any effective organization there is an interplay between the formal structures where authority and responsibility reside and the informal network that often facilitates getting the work done. As he put it, developing such an approach "implies a careful consideration of how you would like to sociologically engineer your network."

That statement resonated with me as I recalled a rich conversation I had about visual analytics with a researcher at Purdue University. He made the point that presenting data as visual information only expresses one end of the model. The other involves the psychology and sociology of the person engaging with that visualization to understand it and potentially take action. He advocated taking a holistic approach to the experience of data visualization.

These ideas resonated with me and prompted a line of thought that I'll continue in future posts. Stay tuned. 


Quality, Data and Otherwise

As our enterprise incorporates new data sets to help us detect emerging threats to human health, we encounter a set of issues in accessing an organization's data. One area is usually an unspoken reservation that an organization holds in their encounter with us. Put simply, everyone's data is a mess--missing values, entry errors, "idiosyncratic" spelling, cryptic abbreviations, among other issues.

It's sort of like inviting someone to view your bedroom closet. If it's like mine, there are shoes piled in a corner, a top shelf with hats and boots that are rarely used, sweaters and sweatshirts mixed up on other shelves, a rack of ties of ascending ugliness, and shirts, slacks, and jackets in no particular order. Everything is there and I can find it, but a stranger would need time to figure out where everything is and more time to fit things together into useful outfits. Finally, there are vestigial items. (I have never been willing to get rid of the suit I wore on my wedding day even though it has not fit in decades and is wildly out of fashion. What lapels!)

We have been exploring a massive data set that encompasses our entire state with millions of records and includes both normalized data and free text. An expert team from our SAS partnership has investigated the quality issues across the data and are helping develop categorical extractions from the free text so we can apply our analytics model to the data to look for anomalies. Those anomalies may be evidence of issues of concern to human health, but we apply both analytics and subject matter expertise to make that determination. The result are signals that can guide public officials' actions and understanding of an incident.

The process of developing the methods to automatically identify those signals involves sophisticated mathematics and domain expertise to develop rules to apply to the data. The rules allow the system to infer meaning from the data, but meaning tempered by a number of factors such as the characteristics of the data, the number of data points, connections to similar data that may add meaning to promote an anomaly to a signal. (Sort of like enlisting expert help in choosing the right tie, shirt, and jacket combination to those of us with aesthetic challenges.)

What has impressed me in the process of understanding the data is the variety of experts we have involved. Their focus on the task to develop these rules based on the data available exemplifies a major type of creativity of our project. While based on a variety of sciences, it is an art form and these are masters.


Food, Safety, and Moral Behavior

A colleague of mine sent me a link to an article in Foreign Affairs by Evan Fraser and Andrew Rimas titled, "The Psychology of Food Riots: When Do Price Spikes Lead to Unrest?" In citing the article, he challenged us to try to understand the rapid emergence of such popular movements because their causes are predictable. The article's authors look at not just the physical and economic realities of food security, but the moral dimension as well. The perception of merchants' efforts to take advantage of fluctuations in market price and availability of commodities poses a moral issue from the perspective of those who are going hungry. It's not just the fact of the shortage of food that encourages people to take to the streets, but the perception that they have been morally wronged by these merchants in the domain of food. The authors drew from a variety of historical examples to illustrate their thesis and made a strong case about the moral imperative that we all share.

The question my friend posed concerns the development of our technological system and its use. The point he made is that just understanding the physical properties underlying an alert in our context is not completely sufficient in understanding the fuller meaning of what is going on. Just as a sense of moral outrage provides the catalyst for food riots and civil unrest, we need to be aware of the context of the signals we detect that are outside the frame of our data. Put in a more folksy way, when considering information technology, the most important distance is the space between the screen and the back of the chair. That's the place where we need to focus our thinking and consider how to help bridge that gap. If we can do that, then we will be successful.