Another number trick

As reported at American Prospect blog, the Republicans have found a new way to massage the numbers concerning health care reform: simply choose another source, specifically, themselves. The apparent reason for this choice is the fact that the Congressional Budget Office (CBO) reported that the health care bill (ACA) will produce a surplus, rather than increased debt. Naturally they can’t allow that, because it doesn’t fit into their viewpoint. Thus they have decided to select the answer that they want, even though it isn’t connected to reality.

Meanwhile, the world keeps turning and people get poorer and the environment becomes poisoned and we may all die next year. Well, c’est la vie.


Health Care Reform: Another Look at the Numbers

Discussion of most political matters involves numbers, but the debate over the health care reform bill has presented us with a huge discrepancy in numbers such as “how many people support repealing the bill?” and “how much will the bill cost or save?” as presented by different sides. Some numbers result from polling, others from government agencies, and still others from demographics and other statistics.

How is the average American to know which numbers are more accurate than the others? Which ones can be computed exactly and which ones can never be more than estimates? How are the statistics computed and what potential errors exist? Does everyone need courses in statistics, political polling, and accounting to truly understand?

Naturally, a person who has background in one or more of those areas has an advantage over someone who does not, but the rest of us can improve our interpretations of all these numbers with knowledge of a few basic concepts.

Numbers that result from polls, such as the percentage of the population that wants to repeal health care, can be determined in more ways than one. For example, a person could ask all of his/her friends what they think. Most Americans know that is not a valid way of polling, since the result is biased in favor of the individual’s own beliefs. Similarly, a poll that is restricted to a certain group will be affected by the self-selection of group membership (think about asking the health care repeal question at a rally held by the Tea Party). That is why the phone-in or text-in polls created by news networks do not really mean much. The sample consists only of people who watch a certain news show.

In order to give truly valid results, a poll must be conducted with a randomized sample. For instance, a computer program can be designed to select phone numbers at random from all the phone numbers in Texas, or even in the entire United States. Then pollsters call these numbers and ask the questions of interest. Sometimes even this method can result in misleading results, since respondents must agree to answer the questions, but it is one of the best methods available to those who seriously want to find the truth.

In the course of discussion about the health care bill, numbers regarding the financial effects of the bill were bandied about. Some said the bill would result in extra costs which would then be transferred to taxpayers, while others said the bill would actually save the government money. Most of the time numbers like this are meaningless since there is just no way of predicting them, considering the many factors that are involved. One might as well attempt to predict the value of the S&P six months from now. Any stock trader will tell you it’s impossible. An estimated value can be determined, but there are huge margins of error because we just don’t know what will happen between now and then.

The best prediction that can be made about a new government program is that it will cost more money – possibly just a little more, possibly a lot – because very few programs have been known to actually decrease costs.

When demographics are used only in a descriptive fashion, the information obtained can be very accurate. The Census conducted every decade produces an excellent resource for many scientific studies. In between, smaller studies are carried out with the same purpose of describing the characteristics of a certain population. Although demographics always fall behind reality (during the time in which the data are collected and interpreted, the population has already changed), they represent a valid way of presenting facts about a population as a whole.

Problems may occur, however, when data about smaller groups is extracted from the larger census or from a randomized polling study. At the highest level (the population or the random selections), the study may be sufficiently randomized, but lower levels such as “all blacks” or “all Christians” may not be randomized. It is a good idea to check the source of the numbers, regardless of whether they are demographics, polls, or financial predictions. This is particularly true in the health care debate, which still rages on despite having been signed into law. Legislators and their constituents should take a long look at the numbers associated with health care reform to find out where, when, and how they were obtained. With that information, one can make a determination of which side to support.

Camera Phones for Diagnoses

The uses for camera phones continue to expand, as more users think creatively about ways to take advantage of quick snapshots on the go. A person who accidentally stumbles on a newsworthy event can get extra cash by sending the first pictures to news sources, particularly local television stations. If the camera on the phone has a sufficient number of pixels, the image will be clear enough for even a large plasma screen.

Now a new use for camera phones has turned up: diagnosis of flesh wounds and other skin problems, including  rashes and infections. In a study conducted by Neal Sikka of George Washington University, individuals who come to the ER for skin-related issues are recruited to participate by completing a questionnaire and taking pictures of the problem area with their camera phones. Physicians in the study look at the pictures and the questionnaires to inform a diagnosis, which is then compared with the ER diagnosis for accuracy.

Since May, when the 6-month study began, accuracy has averaged 90% ( This positive outcome suggests that mHealth may continue to expand and become a common service of physicians.

However, there are pitfalls to this new use for technology (as always!). What if your email is not protected by appropriate security measures, such as encryption? Medical data and financial data are the most sensitive kinds of personal information, and emails for diagnoses are likely to contain both.

An obvious way that information could be acquired is by hacking into the system itself. However, that isn’t always necessary with wireless signals. Just as wireless Internet can be stolen, mobile phone connections can also be tapped.

The results of the study are not complete, and if physicians volunteered participation they were self-selected. Thus the reports are only preliminary and may be biased in favor of doctors who are already technology users. There is no way at present to establish a “control” group — another issue with the study methodology.

Finally, liability will certainly be a huge problem for doctors who diagnose using mobile phones pictures, in a similar way that diagnosing a psychiatric illness over the phone would be. The inability to view the wound from different angles, to touch it (with gloves, of course), or check circulation both proximally and distally could prevent diagnosis of a serious problem. Until and unless the extravagantly high awards for malpractice suits are managed with new legal statutes, the expansion of diagnostic possibilities available through technology such as camera phones may languish due to fear on the part of doctors.

Tort reform in Texas (my home state) has been an effective strategy to limit non-medical awards to $250,000 and thereby put a lid on the amount of money a physician can be charged for vague issues such as “pain and suffering.”

Final opinion from WideEyedBohemian: Diagnosis via camera phone may help doctors diagnose some types of illness, particularly for people who live in remote rural areas. However, caution is still needed at this time.