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Disablement from the Institutional Use of Aggregate Statistics

This blog is about the lived experience of “becoming a statistic.” In our increasingly data-oriented society, the use of data serves not merely to try to understand but also to control people and determine their placement in the scheme of things. Central to the theme of systemic racism, gender discrimination, and the formation of class strata is the elevation evidentiary artefacts such as statistics in order to structurally define and diminish “individuals.” The purpose is to make lesser the individual that genuinely exists and to broaden the role and relevance of socially-constructed pigeonholes (the labels and metrics) that establish his or her placement. I suggest that one way to combat oppressor-side disablement is through the externalization and metrification of management processes – i.e. to regulate the regulator. In other blogs although I will not do so here, I wrote about the use of codified narrative to empower individual expression, which is meant to help victims regain control over their own portrayal in society.

From Theory to Life Experience

After a period of hospitalization a few months ago, I eventually returned home with a prescription for some medication. Having been in and out of hospitals over the course of my life, I cannot say that I have ever found the experience satisfying or enjoyable. Apart from having to deal with the medical condition itself, I invariably leave the hospital with some kind of negative sentiment about service. In any event, I took my pills as instructed, hopeful for recovery. As the weeks and months passed, it didn’t seem like my condition was improving; in fact, I started developing even more horrific problems. Perhaps out of desperation, I decided to systematically “test” if my hospital medication was contributing to my increasing disability. I stopped taking one pill; after I found no change, I resumed taking it. I stopped taking the other pill. There was noticeable improvement. I continued to deprive myself of the medication for several days. My most disabling health problems disappeared. For legal reasons, I must advise readers never to discontinue taking their medication without first seeking guidance from their medical practitioner. I am really just sharing my story rather than trying to motivate people or start a movement. Once it became clear that my medication might be harming me, I started doing some research.

First I noticed – from a number of online sources – instructions to discontinue the medication if I am allergic to it. It seemed like a reasonable suggestion. Indications of a severe allergic reaction correspond to a number of complaints that I remember sharing. I then noticed that I was given the maximum pill dosage for my medication while I was at the hospital. The online sources suggest that treatment using this medication should normally be given over a period of time with gradually increasing dosages. Apart from helping to increase tolerance, I imagine that such a precaution would make it possible to detect allergic responses before significant damage occurs. Now, I am not attempting to establish that a “mistake” was made. Everybody makes mistakes. Regardless of whether a treatment is right or wrong, I would make the following observation: it takes a certain level of administrative Nazism to ignore and dismiss patient feedback. Taking into account a single dimension of a drug at the exclusion of important issues, including the side effects to the patient, exhibits a type of “insensitivity.” I don’t mean this on an emotional level but rather in terms of data: the symbolic meaning of data is allowed to stray far from the underlying truth, leading to a kind of alienation.

While doing research on the medication, I came across literature indicating treatments are often based on studies using Caucasian subjects. The literature emphasized that generalizations from tests on Caucasians haven’t proven to be as meaningful on black people or Asians. I identify myself as Asian although I agree this group includes a great deal. I have written on this subject before. Decisions premised on statistics can create disabling conditions. Consequences can become entrenched. Apart from this, consider the pointless use of scarce financial resources when the administration of services is highly institutionalized on one hand and on the other alienated from the lived realities of individuals. To make matters worse, even ignoring phenotypic issues, I understand that my particular condition is actually quite rare; so there isn’t a great deal of data pertaining specifically to people like me. In short, I probably deserve a bit of flexibility; and my feedback is really important to consider.

The only way rigidity in the selection of medication might make sense is if the health care system is deliberately experimenting on the population: e.g. certain groups have been ordained to receive particular medications as a matter of control. If some people die or get extremely ill, a researcher can write a paper on the subject for the glory of the Nazis. I guess that seems kind of ridiculous. It’s too bad that something like this actually occurred in real life to some Aboriginal children in relation to the nutritional content of their food.  Not all Nazis identify themselves as such or wear uniforms. Particularly in a multi-cultural setting, it is important to consider the differences in how people respond to medication. Institutions should be cautious about the administration of drugs. Here is my main point: although there might be data and studies available, their applicability to all types of people is debatable. Consequently, institutional responses premised on certain data and studies might actually be harmful, ineffective, or wasteful. My father passed away not that many years ago. I strongly suspect that he was prescribed the same medication that I decided to discontinue. So this situation is not just theoretical or academic for me. It is a deep and festering wound. I feel compelled to write critically on the subject in order to save lives.

Of course, I am not referring to the Nazis in a political sense but more conceptually. Nazis represent a great “conceptual” reference point. When something having externally defined parameters – such as statistics – is used in order to legitimize decisions, I try to pick up the scent of Nazis. I sometimes wonder if people think of me as a Nazi – being precision-oriented as I am, judging people based on criteria, monitoring and reporting their adherence. I believe somebody once compared me to a “microscope”; this of course is not a flattering comparison. In any event, my perceptions are based on a certain familiarity using many sources and experiences. Why would statistics specifically be a concern? In statistics, data is forcibly yanked from its environment and deprived of circumstantial linkages. It is why sales might tank on certain months without explanation. Sales are decapitated from the body of meaning. On the other hand, patients should they wish to express themselves often do so from the “internal” such as their lived experiences, through narrative and phenomenology. Reality is delineated through this quantitative-qualitative interaction – through the tug-of-war between metrification and the internal expression of underlying phenomena. If one’s mission were to control and bring about particular outcomes, sadly it might not be necessary to listen to the individuals involved – patients, clients, and citizens. Organizations routinely produce products that nobody will buy. It takes the skill of an administrative Nazi to operate in a manner insulated from the realities of the market.

I believe that an exceptionally strong business case can be made for the use of methods beyond anything resembling statistics. Data science heralds the beginning of alternatives. Data objects do not necessarily have to exist in a quantitative framework. So the heavy use of computer technologies in data science makes entirely different types of analyses possible. This is not to say that people will necessarily try new approaches. The recent U.S. presidential election demonstrates dynamics similar to my hospital visit. Who were the disablers in the election that systematically dismissed the plight of the U.S. working class? I will leave that question for readers to ponder. I certainly applaud Bernie Sanders for using the correct term “working class.” (By the way, I suspect that he would have made an awesome president. Then again, being Canadian, I couldn’t vote in the U.S. election.) Like the Nazis, certain stakeholders during the election used a lot of contextual assertions about the significance of things – trivial and superficial compared to the storm raging in the background. Colour was significant, hair, gender, age, manner of speech, adherence to norms, income, taxes paid, and of course all sorts of polls. It seems that these concerns were insulated from the realities of voters that made a difference. I believe that the concept of disablement through the alienation or reification of data will become increasingly important due to the complexities emerging in the world. The civil servants of the past will be replaced by sophisticated administrative systems relying heavily on computers. In effect, the Nazis of the future will be machines plugged into the core systems of society.

Back to Dealing with the Institutional Care of Patients

This blog could have gone a few ways. I could have left it at the preceding paragraph. But no, I would like to return to my original scenario. I pinned under a minivan about 10 years ago . . . and perhaps dealing badly with the shock of what seemed like a near-death experience. I didn’t “appear” physically harmed; but I certainly had a number of medical issues that could be reasonably connected to the experience of being pinned under a minivan. So once again, I was off to the hospital! While I was waiting in emergency, I remember listening to an exchange between an older nurse and a young intern. She was giving him information about drugs and different emergency scenarios. She was also testing his ability to respond to questions. Despite my awful situation, I was utterly captivated by the intern’s plight. I thought he would snap. I wondered how the doctors of tomorrow will deal with the rapid accumulation of knowledge. For the sake of safety and lives, health care systems require the services a particular type of individual. I am not going to call this individual a “data scientist”; but rather, this person must be able to facilitate the interaction between medical professionals and institutional databases – to catch errors and minimize mistakes. It is easy to fill the role – harder to gain people of substance. The expert decision-making of doctors – something quite “internal” – has to become external and checkable – making mistakes possible to catch using external processes and systems such as computers.

I have gone through this process of externalization myself. When I first acquired my duties, I relied heavily on memory and personal judgement. If I were ever asked a detailed question of facts, I would need to dig deep into my shadowy grey matter. If I had to justify a decision or interpretation, there would be some speculation. This simplistic approach is great for speed, but it would be difficult to build a complex system from it. As I started externalizing the work processes, I encountered potential data generation points that could be used to regulate those processes. The outcomes therefore include metrics and control over what was originally an internal process. Once externalized, people other than me could regulate the processes and make use of the metrics for different purposes. The basic concept as I would apply it to the medical profession involves the externalization of protocols and the rationale behind their deployment. For example, before any kind of medication is administered to a patient, the doctor can be required to create or adopt a protocol and include the points of rational invocation. If anything goes wrong – or hopefully before something goes wrong – regulators can question the selection of the protocol and the points rationalizing its use. More importantly, based on the points, the facilitator gathering data can question the choice of protocols.

A computer can compile lists of protocols from the points provided by the doctor or intern; and to some extent, it would be possible to dismiss or question a protocol selection. This is a fairly simple approach, but it would be possible to build a sophisticated system from it. For example, “point protocol negation linkages” are possible. If a point exists or is true, the protocol could be presented as valid only if other points are negated. This would then force the physician not just to assert points but negate other points. These protocols would be developed by doctors themselves over the course doing their duties. The facilitator on the other hand can incorporate worthwhile protocols from other hospitals in the same region or perhaps even from other parts of the world if they have a similar approach. The facilitator doesn’t have to be a doctor. This is an experiential approach not necessarily reliant on statistics. If one considers the logistics, the system is not necessarily quantitative. But it certainly makes intense use of data and computers. Within the design parameters of this type of control environment, there can be “specialists.” If certain minority groups are adversely affected by particular treatments and medications, it might not be common knowledge. Even less common would be the location of suitable protocols.

Of course, a doctor that seems to exhibit a tendency to make the same erroneous selection of protocols can, due to the externalization of processes, be “measured.” Predisposition represents a higher risk, I would think. On the subject of risk, I suggest that insurers – in order to minimize liability – should promote or require this added layer of control or regulation. I would like to mention also that I already have software (that I developed myself) that behaves in the manner described here. There are some notable special features. It is possible to find a protocol based not just on points about the patient or patient’s situation but also desired treatment outcomes. It is possible to determine whether a situation doesn’t seem quite right – i.e. if it contains a melange of points indicative of a bad situation – i.e. making use of the “odour of data.” Other people can develop their own software to access the data. But first, it is important to have the basic building blocks in place. What comes afterwards is a lot of effort combined with experiential development – not so much of the software but rather the intellectual capital – the data. Imagine a hospital becoming more intelligent and less risky over time as a result of its interaction with the specialized database environment. Consider the benefits to the patients, staff, and doctors as metrics become available to enable more effective management.