From Granizada

Dan Shearer

version 0.70

Last edited May 2010

What's It About?

This page presents a method which is self-funding and practical in the short-term to improve results and decrease costs in medical systems. The method involves a novel set of incentives for collecting detailed medical information using modern technology together with a modified ethical and legal approach.

Summary
	We create a system to address these two very difficult health problems: When an individual is sick we want to catch the illness early and treat with maximum intelligence, however, there are many issues connected with early detection Medical science is ignorant in many fields because good empirical evidence about populations either has not been collected or there are ethical and practical barriers to doing so We address this by creating a new legal and ethical framework. Incentives and ethical rules are created so people may choose to sign a contract for regular, broad-spectrum medical testing. The testing organisation has funds to uphold two duties of care to the individual to an extreme degree: make the testing as close to zero-impact as possible using safe, largely non-invasive, mostly telemedicine techniques, and, deny access to all specific information regarding the tests, test results and methodologies to all parties including the individual. There is no other duty of care. The individual's medical care regime is unrelated to the testing. The individual authorises the testing organisation to have full access to normal medical records without reference to the individual. Testing would be both physiological and otherwise (eg interviews), and ideally the last tests would be during clinical autopsy (ie after death.) From the individual's point of view: It's a personal medical time machine they are paid to create. When the individual's normal medical care regime has evidence of a problem, the individual may request access to medical history. The testing organisation may issue a background report reading narrowly on the specific evidence submitted. The individual has the advantage of perfect medical hindsight, but not the harmful disadvantage of too much early knowledge. From the testing organisation's point of view: It's an unprecedented long-term study, of immense value to society and government. It is also of great commercial value to medical and health-related companies conducting their own testing, and the regulatory bodies for such companies. This is where funding comes from to run the tests and pay the individuals. Safeguards would be put in place to ensure that datasets from the studies would be made generally available for analysis by all under a non-restrictive license. Given the timescales proposed there is ample room for a time delay for commercial exploitation, given that companies have short-term requirements from data that does not conflict with the longer-term interests of most other consumers of medical data.

The whole driver of this scheme is to make it easier to get lots of observational data collected under controlled circumstances over a long period of time. That's the basis of medicine, and it is extraordinarily difficult thing to do! Here are three practical problems:

1. Collecting quality empirical data is difficult ethically, legally and practically, which is why it is so expensive. Motivations for all parties vary so much that it is difficult to achieve the best desired outcome.
2. Causality is a problem, when the mere fact of gathering the data affects the subject or the subject's care. This is especially true in the the problem of over-testing. This alone makes getting good-quality data very difficult.
3. It is not ethical to continue medical observations when we have information that will or could help, even if helping the patient(s) changes or prematurely finishes the study (causality again.)

Whenever we hear the word causality there's a good chance time travel can come to the rescue. Lacking magic, we have to use the perception of time travel instead. Computer Science has done this for years, and it is found to a lesser extent implicitly in biology and law. We do this by controlling the manner, direction and timing of information flows.

Background

The background is presented as a series of reasonable, relatively disjoint statements. The scheme in this paper is justified by building on these background statements without exceeding their scope. Full references are needed for this to become a proposal; for the moment please take statements at face value and focus on the general principles - which are plenty enough to think about to start with!

Statements on Medical Testing and Patient Treatment

Everything in this section is supported by credible sources, often including evidence-based medicine.

The following points illustrate, in a negative way, the problem of causality:

• Many medical conditions are evident in test results long before they become a problem
• Early detection and treatment significantly improve medical outcomes
• Evidence of long-term medical conditions are frequently found in clinical autopsies or CAT scans - such as small cancers - that would certainly have triggered alerts and maybe intervention had tests been taken. With the benefit of hindsight we can say testing would have not been in the patient's interests.

There is evidence (not cited) that the ready availability of tests can lead to a skewing of outcomes:

• patients can become overly concerned with tests and the results of tests
• doctors and patients can come to depend on tests, or even just the fact that tests are in train, at the expense of other diagnostic or treatment paths
• patients can be subject to unnecessary medical procedures following testing, either due to their own anxiety or the anxiety of doctors
• doctors' anxiety may related to risk factors for the doctor rather than the patient (worries about promotion, getting sued, etc...) and this can influence testing behaviour
• medical systems can be distorted by the charging regimes for tests to either order too many tests or to order non-optimal tests (doctors making money by signing test forms...)
• patients can forego tests because of the cost, which can impact the patient's perception as well as possibly be a lack in the medical knowledge relating to that patient

The patient's mental state and expectations can have a significant impact on medical outcomes and even causation. Setting aside discredited notions of 'positive thinking', this means:

• Patients have expectations about knowledge that will be gained from tests
• Patients have reactions to the actual knowledge gained, or their perception of the knowledge gained
• Both mental state and expectations can be greatly affected by mere fact medical testing is taking place

Therefore:

The fact of testing has potential side affects unrelated to the nature of the test

The following two statements are self-evident, and somewhat contradictory:

• Many medical conditions can be better treated, or treated with more confidence, if more is known about their history in as much detail as possible: when were the first signs visible (e.g. change in white cell count); did these signs come and go; what was the medical state when symptoms first noticed; etc.
• Regardless of grey areas about when testing should start in the case of queries, doubts or medical symptoms, regular, broad-spectrum testing is contraindicated for healthy individuals with normal risk profiles. Even though this is the only way to have better medical history.

About errors:

• All testing has an error rate.
• Not all testing is equal: a pathology lab differs from a corner surgery, and tissue takes time to transport, etc.
• Tests can have four possible outcomes: positive, negative, inconclusive (no safe conclusion can be drawn), and invalid (e.g. problem with data)
• false negatives and false positives are common, and are often guarded against
• 'inconclusive' and 'invalid' can also be false. These tend to be overlooked in error statistics (presumably because it is more difficult to measure their error rate, but it demonstrably exists.)
• All treatment has an error rate.
• Some of the easiest treatment error rates to detect are very high (eg drug dosages, amputations) and there is evidence to suggest treatment error rates that are not so easy to detect are also high.

Statements on the State of Medicine

These statements are readily supportable:

• Medicine of all kinds and at all levels is beset by complexity. Inherent complexity means our total knowledge is a small proportion of the amount to be known, and the positive feedback/network effects associated with growth of knowledge often mean the complexity becomes greater (eg Epigenetics.) There is also contextual complexity, to do with the impact of government, ethical and financial factors.
• To demonstrate how quickly complexity builds, consider multimorbidity. Even some of the best-understood and most treatable diseases are not at all well-understood in the context of multimorbidity, and beyond the limits of evidence-based medicine. Multimorbidity is increasingly common, and yet we don't have a good understanding of how treatments should cope with it.
• Both the environmental and inherent nature of medicine is changing rapidly. The following is a sample selection of things that are commonly thought to differ between successive human generations in modern society: microflora, genetic diversity, background levels of artificial chemicals (body burden), and hormone patterns. Even with just these factors there is great complexity, and if these factors are all changing by generation, the complexity is vastly increased again.
• Evidence-based medicine is often helpful, but very incomplete.
• Evidence-based medicine is very difficult to put into practice because of human factors in the medical profession worldwide, even at the level of the simplest routine tasks (classic example, intravenous line cleaning checklists.)
• Empirical data relating to large sample sizes is rare, and relating to an individual medical case is exceptionally rare
• Sufficient empirical data, when available and when its collection has not skewed outcomes, and when properly interpreted, will always improve medical outcomes

No wonder then, that longitudinal studies are regarded as critically urgent by government and also medical companies of all kinds. There are very few of them, and they are regarded as expensive, and worst of all they require long-term commitment by political and medical entities that are geared to short-term decision cycles.

Statements Relating to Medical Ignorance

It can be helpful to think about medical ignorance rather than medical knowledge, although they are dealing with the same subject. The ignorance is so much vaster than the knowledge, yet attention is invariably focussed on the tiny amount of knowledge we have. ^[1]

The following statements are readily supportable:

• It is very expensive to reduce our medical ignorance, and frequently the expense factors have to do with personal, social and regulatory issues rather than medical science.
• Medical ignorance is best addressed by considering data about many people gathered over a long period of time. n=big, t=long, hardly controversial!

The following statements seem intuitive, but need to be verified:

• Medical ignorance decreases as the number of valid data collection regimes increases provided sample sets are large and collected over a long period of time
• Assuming sound design, the value of a data collection increases with the time it has been running. In other words, the most valuable studies are always those that have not yet finished.

First Problem Statement

Here is the statement of the first of two problems addressed by this proposal:

When an individual is sick we want to catch the illness early and treat with maximum intelligence, however, there are many issues connected with early detection

Dilemmas:

• ethical dilemma - we must choose between treating while lacking good knowledge, and delaying treatment until we have good knowledge, with very little middle ground. Each choice can lead to bad outcomes, and they are mutually preclusive.
• medical dilemma - acting prematurely on knowledge about the patient can lead to: under or over-treatment; uncertainty (ie we know there is a very high error margin); entirely wrong results (eg false negative by misinterpreting tests, or wrong limb); and false certainty (ie we don't know that there is a very high error margin.)
• financial dilemma - inefficiency is expensive. A healthcare system that over or under-tests is inefficient, as is one which generates extra work due to the fallout from errors and uncertainty or false certainty.

Causality paradox:

A patient presents with a previously unreported problem, and a doctor decides it should be looked at closely. At that instant, the best medical outcome will arise if a long and very detailed, multidimensional history of the patient is already available.

However, such a history cannot exist within the bounds of today's medical framework, because, in order to gather it:

• we would never get to that instant of decision with little prior background. Given partial previous information we would have been forced to consider alternatives long before
• the process of considering alternatives due to increased (but partial) information frequently leads to interventions being made even though more information could mean no intervention would ever be made
• we may never get to a position of good information because ethically once we've started a series of tests we need to intervene once evidence gets to a certain point

That's the problem in a nutshell - how can we ensure appropriate detailed historical records are available to treat a patient after diagnosis, knowing that if we attempt to make these records beforehand the patient will likely be worse off.

We can be pretty sure about the worse off statement, because of the foregoing statements concerning error rates in testing and treatment, combined with the statements on current medical ethics. Over a large number of cases, ethics will require interventions and some interventions will be either faulty or unnecessary. Hence the status quo: regular broad-spectrum testing is contraindicated so these issues never arise. What we don't know can hurt us, and what we do know can too.

Second Problem Statement

This is the second, larger-scale problem addressed by this proposal:

Medical science is ignorant in many fields because good empirical evidence about populations either has not been collected or there are ethical and practical barriers to doing so

Dilemmas:

• ethical dilemma - quality empirical evidence is all about hands-off observation, however, observing a sick patient closely will often yield information that could help the patient.
• medical dilemma - medical action is often required even when the knowledge behind the action is based on incomplete or non-existant empirical data. This is when doctors just make things up. Part of the skill of being a doctor is operating in twin knowledge vacuums, that of an individual's history and that of the science bearing on the individual case.
• financial dilemma - good empirical datasets are very expensive to gather, and take a long time. This is not compatible with the way most medical research companies and governments wish to fund things.

Medical hubris is not considered anywhere in this document, however this is where it would belong.

Solution

Solution Overview

The solution is to construct a time-travelling medical testing and diagnostic service. This is by applying the Snapshot/Replay Time Manipulation Method, and the Global Optimisation Focus Method. As stated above, the effect is that regular, broad-spectrum testing is done but the patient is strictly barred from seeing any results or even knowing what tests were done.

Information Flows
	The key point is the direction of information flow. Everything flows in to the testing centre. This covers: direct testing of the individual; a running record of what (if any) the medical care system is doing with the patient; and aggregating the above information across many patients and drawing conclusions about this individual. A reverse flow of information to the patient other than an after-the-established-fact release of information would be harmful to the individual and to the wider goals. It destroys the entire premise of the Medical Snapshot Service.

Financial motivation: state and commercial interests wish to decrease medical ignorance by large-scale high-quality data collection, but doing so effectively costs far more than can currently be borne and so many other directions are pursued. An alternative re-statement of this: funding for decreasing medical ignorance is often narrowly and inefficiently aimed, and frequently consideration is only given to people alive now, or likely soon to be alive. Ideally a way could be found to efficiently address medical ignorance while also immediately contributing to those adults who pay for this work.

Participant motivation: individuals wish to participate in a form of medical information insurance lottery so that, should they discover they suffer from a medical condition, there is a reasonable chance a full diagnostic history relating to this problem will be available to their medical carers. The individual accepts there is no right granted for any kind of information or meta-information relating to their own medical information.

Individuals are paid to undergo Medical Snapshot tests. These will be administered in a very low-key way, sometimes self-administered and rarely if ever required to attend a testing centre.

Here's how it works:

1. individuals are contracted by a Medical Snapshot Service to undergo medical snapshots during an agreed period of years (or maybe the rest of their life) subject to some special rules. The Medical Snapshot Service never provides any medical services of any sort.
2. life for the subject proceeds as it normally would - if someone normally goes for a medical checkup then that's what they do, if they normally avoid doctors then that's fine too. They use whatever mix of healthcare they choose to.
3. at a point where the individual's doctor knows there is a medical problem, or can demonstrate a high probability of a problem, the individual's doctor may apply to the Medical Snapshot Service for a medical replay report. The doctor must submit the total medical knowledge relating to the individual, highlighting the knowledge which lead to the report request.
4. entirely at the option of the Medical Snapshot Service, a report may be released detailing everything the Centre considers relevant and that the Service wishes to divulge. The Service may choose not to release any information, regardless of what information it has.

Here are the rules relating to the medical snapshots:

• No access to any results is permitted by the individual or any legal or medical system.
• No specific knowledge of the nature of these snapshots is known. Body fluid samples, advanced scanning technologies, perhaps a treadmill or gait analysis, maybe a lifestyle form or a psychological analysis - the Snapshot centre will decide which collection of tests to administer to a subject on each visit.
• Nobody anywhere in the legal or medical system is permitted access to these records except as part of anonymised studies.
• There is no guarantee of service, or non-service, or even that tests are taken at all on any particular visit.

This is the outline of an experimental but immediately practical healthcare solution. Related areas for developing a theoretical model around these ideas include epistemology and logical positivism besides the usual medical, legal and informatics fields. A model is important, but my hope is that there is enough practical merit and financial incentive to start to look at these ideas as they stand.

Clearly, normal medical/ethical/legal rules and risks do not apply to this process, instead, there are some very special protocols.

Special Rules and Assumptions for the Medical Snapshot Service

• The goal of the Snapshot Service is to reduce medical ignorance
• Reducing medical ignorance requires studies which are not currently ethical, for very good reasons. The ethical way to perform these studies is to be entirely outside the current medical system and to avoid all promise, implication or even hint of performance. This adheres to first, do no harm in a weakened sense - harm could be done to individuals through not telling them important information. The idea is that the individual will be no worse off than if no tests had been done at all since this is independent of all medical services, and that much greater good will be done in the long run by the information embargo. Having dealt with the most significant cause of potential harm is expectations associated with testing, there is only the need to minimise risk of physical harm through botched or inappropriate testing. This latter risk is addressed by emphasising high-technology tests with remote reporting as much as possible, risk-averse policies, and avoiding a testing monoculture so that tests can be used to monitor each other for possible impacts.
• There will be no mandatory reporting. So, for example, tuberculosis is infectious and can often be detected long before symptoms are present. The Snapshot Service is under no obligation to communicate a positive TB diagnosis. The Service might decide that the best outcome for decreasing medical ignorance is to monitor the patient until symptoms are noticed via the standard medical system. As a bald statement this is a horrifying prospect (imagine being the lab technician involved!) and for some types of illness may even be against the law in some countries, but an appropriate protocol could probably be developed for anything which is potentially pandemic. Given the observer-only protocol, it is also feasible that all parties could undertake to accept short-term harm and even deaths in exchange for much greater human savings later. This requires rigorous investigation and ethics debate.
• Following diagnosis, the Service may choose to release a full history to the TB patient's doctors, indicating that other people could have been infected for up to six months previously. That will help the disease control centre decide where the perimeter of infected people lies - it could also make people very upset because of the prevention that could have been done, however, that is the premise on which the Service operates.
• There are other very difficult possibilities that arise, for example, when the medical care is clearly making incorrect decisions about a patient, either due to lack of competence or lack of knowledge. However, intervening in any ordinary sense would completely destroy the premise of the snapshot service. Depending on how early an intervention was made, it could even be harmful to the patient if it stimulates overtesting. Therefore, the only option is to remain silent. Again, there could perhaps be some carefully controlled and minimal protocol for suggesting that the medical carers take a second look at a case.
• The Medical Snapshot Service produces data that needs special protection. Since in principle this protection is equally valuable to all government and individuals, it is in the interests of all parties to respect confidentiality. Think of diplomatic bags.
• No Medical Snapshot Service staff may handle data that may include someone they know - or perhaps even a population they know.
• We assume that there is a way to keep the required absolute barrier between the Snapshot Service's data and any interested party. To be proof against governments' curiosity and their tools (eg anti-terror legislation, personal legal threats against Snapshot Service staff or contractors, etc) and any other party that may wish to either access or subvert the data there will need to be some good solutions in place. This comes down to a well-understood security analysis problem, where potentially compromised collection points provide data for central collation which must not be able to be accessed without authorisation. The system needs to be designed so that the worst that can happen is that results are compromised in just one collection centre.
• We assume the existence therefore of technical and legal mechanisms to make this work. Most of this already exists in one form or another, although its application to medicine would probably be a first. The task is one of multi-disciplinary integration and a technological rather than a technical approach.

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Interesting but not Directly Relevant

Time Patrol

There is some commonality between this idea and many science fiction stories that explore time travel where it comes to the direction of information flow. A common fictional device is to introduce some kind of Time Patrol, an enforcement body whose job is to prevent knowledge of the future contaminating the past for fear of altering the future. The idea here is that consistent causality trumps other ethical considerations, and similarly for the idea of a Medical Snapshot Service. If there is any possibility that snapshot information is available to an individual before any knowledge of a problem then the entire idea is destroyed. That is why it has to be strictly an observer-only system, and the individual must never think of it as a medical service.

Possible Principles

I suspect we can go one step further and formulate two principles behind this entire idea:

• Studies that run indefinitely will always be financially more efficient for a medical system.
• The further in the future we aim for when designing a study's intended benefits, the more certain the financial rewards.

These suggest the possibility of either a market or state-sanctioned national investment in long-running studies. Where this happens now it is either spotty, or accidental. If this was widely recognised it would drive some very interesting discussions about resource allocation.

Next-but-One Researchers

I suspect this means we need a new kind of medical doctor/researcher, one whose entire interest is the health of the next-but-one generation. This differs from most researchers, who are financially or otherwise committed to helping people in the foreseeable future. Perhaps the first version of this could be in epigenetics, where presumably there is a need to gather information for studies to be done 25 and 50 years from now.

Failure Definitions

I proposed above that the longer a well-designed experiment runs, the more valuable it is. If so, this implies two things:

• ending a study is a form of failure
• a study is a failure if another researcher cannot easily take over the running. This is because the best outcomes will otherwise condemn researchers to a career in one single study, because they have to be long-running and nobody else can do the work. It is good practice anyway to make sure protocol and procedures are clear and documented, but often overlooked.

Hypotheses

The following hypotheses developed as thought experiments and helped me formulate this idea. They are testable:

• Hypothesis of medical testing 1 - Error rates increase with the number of tests done during a sufficiently short period of time.
• Hypothesis of medical testing 2 - Error rates decrease with the number tests done during a sufficiently long period of time and in the absence of treatment.

Chances are high that both of these hypothesis have been discussed in specialist texts, and I am just not aware of it. The second summarises an ethical dilemma.

Presentation

Footnotes

1. ↑ Perhaps because people tend to be paid and celebrated on the basis of what they know rather than what they don't! A Nobel Prize for mapping medical ignorance might be a good thing.