Sunday, November 1, 2009

Remote Monitoring: Sensitivity and Accuracy ... using wine tasting as a model

This article focuses on measurement accuracy, sensitivity and informativeness.  Sometime later I shall follow will an article that will focus on predictability.  

I discuss measurement accuracy, sensitivity and informativeness in this article in the abstract and use an example, wine tasting. However, in later articles when I drill-down into specific measurements provided by remote monitoring systems.  I shall make reference to concept foundation articles such as this one when I discuss specific measurements and measurement systems.

For remote monitoring to be a valuable tool, the measurements must be informative.  That is, they must provide something of value to the monitoring process - whether that monitoring process is an informed and well trained person such as a physician or software process.  However, there are conditions that must first be met before any measurement can be considered informative.

For any measurement to be informative, it must be accurate.  It must correctly measure whatever it was intended to measure.  For example, if the measurement system is designed to determine the existence of a particular event, then it should register that the event occurred and the number of times that it did occur.  Furthermore, it should reject or not respond when conditions dictate that the event did not occur - that is, it should not report a false positive.  This is something that I covered in detail on my article on Signal Detection.  Measurement extend beyond mere detection and to the measurement tied to a particular scale, e. g., such as the constituents in a milliliter of blood.

A constituent of accuracy is granularity.  That is, how fine is the measurement and is it fine enough to provide meaningful information.  Measurement granularity can often be a significant topic of discussion, particularly when defining similarities and differences.  For example, the world class times in swimming are to the hundredth of second.  There have been instances when the computer that sensed that two swimmers touched the end simultaneously and that the times were identical.  (I can think of a particular race in the last Olympics that involved Michael Phelps and the butterfly.)  At the resolution of the computer touch-timing system (and I believe it's down to a thousandth of a second), the system indicated that both touched simultaneously and that they had identical times.  However, is that really true?  If we take the resolution down to a nanosecond, one-billionth of a second, did they touch simultaneously?  

However, at the other end, if measurements are too granular, do they lose their meaningfulness?  This is particularly true when defining what is similar.  It can be argued that with enough granularity, every measurement will differ from all other measurements on that dimension. How do we assess similarities because assessing similarities (and differences) is vital to diagnosis and treatment.

We often make compromises when in comes to issues of granularity and similarity by categorizing.  And often times, categorization and assessments of similarities can be context-specific.  This is something that we do without thinking.  We often assess and reassess relative distances.  For example,  Los Angeles and San Diego are 121 miles from each other.  (I used Google to find this distance.)  To people living in either city, 121 miles is a long distance.  However, to someone is London, England, these two cities would seem to be nearly in the same metropolitan area.  They appear within the same geographic area from a far distance. 

Sensitivity is a topic often unto itself.  Since I discussed it at some length when I discussed Signal Detection, I shall make this discussion relatively short.  In the previous discussion, I discussed the issue related to a single detector and its ability to sense and reject.  I want to add the dimension of multiple detectors and the capability to sense based on multiple inputs.  In this case I am not discussing multiple trials to test a single detector, but multiple measures on a single trial.  Multiple measurements on different dimensions can provide greater sensitivity when combined even if the accuracy and sensitivity of each individual measurement system is less accurate and sensitive than the single measurement system.  I'll discuss this more in depth in a later article.

Informativeness ... this has to do with whether the output of the measurement process - its accuracy (granularity) and sensitivity - provides one with anything of value.  And determining the value depends on what you need that measurement to do for you.  I think my example provides a reasonable and accessible explanation.

Wine Tasting - Evaluating Wine

Over the years, people interested in wine have settled on a 1-100 scale - although, I do not know of an instance where I have seen anything less than an 80 rating.  (I am not a wine expert by any stretch of the imagination.  I know enough to discuss it, that's all.  If you're interested, here's an explanation, how ever they will want to sell you bottles of wine and some companies may block access, nevertheless, here's the link:   Independent or "other" wine raters use a similar rating system.  Wine stores all over the US often have their own wine rater who "uses" one of these scales.  In theory, you'll note that they're reasonably similar.  In practice, they can be quite different.  Two 90 ratings from different wine raters don't always mean the same thing.

So, what is a buyer to do?  Lets look at wine rating in a mechanistic way.  Each wine rater is a measuring machine who is sensitive to the various constituents of a wine and how those constituents provide an experience.  Each rating machine provides us with a single number and often a brief description of the tasting experience.  But, for most people buying wine, it's the number that's the most important - and can often lead to the greatest disappointment.  When we're disappointed, the measurement has failed us.  It lacks informativeness.

How to remedy disappointment of expectation and often times, over payment?  I think of four ways:
  1. Taste the wine yourself before you buy it.  The wine should satisfy you.  You can determine if it's worth the price.  However, I've met many who are not always satisfied with this option for a variety of reasons, ranging from they do not trust their own tastes or lack of "wine knowledge" to the knowing that they are not in a position to taste the wide variety of wines available to professional wine tasters, and thus are concerned about "missing out."  Remote monitoring provides a similar situation.  A patient being remote monitored is not in the presence of the person doing the monitoring, thus the entire experience of seeing the patient along with the measurement values is missing.  However, remote monitoring provides the capability to provide great deal of information about many patients without the need to see each individual.  The problem is, the person doing the monitoring needs to trust the measurements from remote monitoring.
  2. Find a wine rater who has tastes similar to yours.  This might take some time or you might get lucky and find someone who likes wine the way you like it.  Again, this all boils down to trust.
  3. Ask an expert at the wine store.  The hope is that the person at the store will provide you with more information, ask you about your own tastes and what you're looking for.  Although this is not experiential information, you are provided with more information on more dimensions with the ability to re-sample on the same or different dimensions (i. e., ask a question and receive an answer).  In this sense, you have an interactive measurement system.  (At this juncture, I have added by implication remote programming to mix.  Remote programming involve adjusting, tuning or testing additional remotely monitored dimensions.  In this sense, the process of remote monitoring can be dynamic, inquiry-driven.  This is a topic for later discussion.)
  4. Consolidate the ratings of multiple wine raters.  Often several wine raters have rated the same wine.  This can get fairly complicated.  In most cases not all wine raters have rated the same wine and you'll probably get a different mix of raters for each wine.  This too may involve some level of tuning based on the "hits" and "misses." 
This ends this discussion of measurement.  Measurement is the foundation of remote monitoring.  For remote monitoring what its measuring and the accuracy and sensitivity of that measurement and whether that measurement is informative is key to its value.  We've also seen a place for remote monitoring as a means for getting at interesting measurements; changing measurement from a passive to an active, didactic process.

Next time I discuss a recent development with respect to physiological measuring systems.  Here's a link to an article that I believe many will find interesting. 

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