Are #REB members #maximizers or #satisficers? #ethics

At the Canadian Association of Research Ethics Boards (CAREB) conference held in Toronto on December 6th 2013, the keynote speaker, Dr. Ivor Prtichard, gave a talk on how he speculates research ethics board (REB) members make decisions.

He indicated 6 aspects as to why REB members have very different decision making processes, and focused on two points:

  • REB members exhibit psychological behaviour.
  • REB members are influenced by each other in the group’s decision-making processes.

I will discuss the first point.

With respect to his first comment, it can’t be news – humans are notorious when it comes to exhibiting psychological behaviour. He further explores the topic by asking if REB members’ decisions are derived through Rational Choice Theory. Rational Choice Theory is rooted in economics theory and the gist of it is – I am no expert in economics – that any rational individual when presented with options, will pick an option with the highest favourable outcome for themselves. Next, he argued that REB committee members can be categorized as  Maximizers or Satisficers – I’m going to focus on maximizers.

A maximizer is an individual who takes more time to arrive to a decision – by seeking more information – and considers multiple alternatives prior to making a decision. A maximizer in the cereal aisle is the individual who takes the longest time to pick something. To me that seems pretty normal. Anytime I make a decision that affects my finances, I tend to take a long time before I part with my money! I most definitely classify as a maximizer, because I want the “best bang for my buck’.

Dr. Pritchard stipulates that  if a REB community member is a maximizer, they will advocate – on behalf of research participants – to maximize benefits (i.e. reduce harm). You can find his ppt deck on this page. He used the scenarios from slides 15 and 16 as an exercise. Based on the number you had at your seat, you were given either scenario #1 or #2. Based on your scenario, he asked whether you would pick treatment A or B. I got scenario #2 which says:

“Which treatment is more acceptable? 

  • 600 people are exposed to a virus.
  • With treatment A, 400 people will die.
  • With treatment B, there is a 1/3 chance of no one dying, and 2/3 chance of 600 dying.”

We know that a maximizer is an individual who will pick an option that yields the highest benefit/utility. In the case of REBs, it would be the choice of maximizing benefits to study participants and minimizing risks/harm.

If presented with the above example, which treatment would a maximizer choose? I will make the assumption that the study is developed using sound scientific methodology and will be looking at the efficacy of the treatment. The data we get from the study – regardless of treatment option – is very valuable. When it comes to valuing study data for a maximizer, I will make the assumption this is held constant across both treatment options.

I hypothesize that both treatment options are valuable and to validate that, I will look at where benefits can be maximized within each treatment choice.

Treatment A: we know that 400 people will die and 200 will live. The value in this treatment option:

  • 200 individuals will live

Treatment B: we know that there is a 1/3 chance that no one dies, and 2/3 chance of everyone dying. The value in this treatment option may be that:

  • Everyone might survive

Treatment A Argument: I can argue that treatment A guarantees 200 individuals will live. Therefore, I have minimized the harms by guaranteeing that 1/3 of the participants will live, and view treatment A as having the maximum amount of value.

Treatment B Argument: I can argue that if the outcome is favorable, there is a 1/3 chance that 600 individuals will live. Therefore, I am maximizing the benefit to the participant in the case of a favorable outcome, as such treatment B has the maximum amount of value.

With both treatments possessing value, which would a maximizer choose? Would she choose treatment A and guarantee 200 participants live, or would she choose treatment B for the chance of saving everyone?

Rational Choice Theory operates on the assumption that a “rational” individual is going to always make the choice of maximizing their utility – in a REB context it means minimizing the harm to participants.  I would agree that this may be somewhat true when it comes to consumer choice for material goods, but disagree with its applicability in a REB context. Do you think people can be simplified to rational or irrational?

When both treatment options exhibit value, the decision-maker’s choice is skewed by what they perceive to have the highest value – save 200 vs try to save all 600. It seems that the treatment choice is made based on the member’s preferences, and the common denominator in picking treatment A or B is the member’s tolerance for risk.

Is it a “rational” choice not to conduct the study at all? People can’t be simplified down to rational vs irrational, because people have different values. If you are an individual who values gaining information from the study, its applicability in the future and the way it can help advance science and medicine, the differentiating factor becomes your tolerance to risk.

A risk-averse individual is someone who will pick treatment A, because we can guarantee that 200 individuals will live. The risk-seeking individual will pick treatment B – even though it is riskier – because it has the potential of having the best payout .

A recent book I read, does a phenomenal job of looking at how people make decisions as opposed to why they chose an outcome.

The book You Are What You Choose by Scott De Marchi and James T. Hamilton introduces the TRAITS model and identifies 6 categories for an individual’s decision-making process: Time, Information, meToo, Altruism, Stickiness, and Risk.

The authors argue that a person’s decision-making is directly correlated to where they fall within each category, and the combination of their TRAITS is fundamentally the way each person makes decisions, irrespective of context. Based on our TRAITS, we make decisions in all areas of life that are reflective on where we score within each category. They also point out that there is a clear distinction when it comes to “consuming” ideas or material goods. I think Rational Choice Theory fails to hold true in the REB context, because we are not consuming material goods. It would be interesting to test the TRAITS model within a REB setting – there’s a good dissertation topic.

I  believe TRAITS is a better model of explaining how we make choices. It does speak to  people’s individualities and injects “human” back into decision-making. Having said that, my sample size is just me, so take what I say with a grain of salt and decide for yourself.

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Dear eHealth Ontario, come again now?

Today, eHealth Ontario issued a RFP  titled “Predictive Economic Modelling for EHEALTH Benefits” – Where do I begin?

They further elaborate by stating: “submit proposals for a health economics benefit evaluation model and methodology to be used to predict the quantitative benefits of an EHEALTH Ontario clinical program.” – Who wrote this?

Let’s start. Which clinical program are they talking about? Is it their Diagnostic Imaging, Drug Profile Viewer, Medication Management System, OLIS or Physician eHealth program? They can’t possibly be asking for a model that will cover ALL of the above programs, are they? Let’s discuss.  

I’m glad eHealth Ontario is looking for “quantitative benefits” – which I think is great – to see if the numbers make sense, or not.

So, what type of “economic model” are they looking for? Is it cost benefit, cost effectiveness or cost utility analyses? 

What criteria are they looking to quantify? Monetary, productivity or quality adjusted life years?

Who’s perspective are they using? Clients, Providers, Government?

I’m guessing by “Predictive Economic Modelling for EHEALTH Benefits”, they really mean a Health Economics Evaluation for each of the eHealth projects they have funded to date. I may be wrong, but I do not believe there is a “one size fits all” type of analysis for all their programs.

How I interpret this RFP:

eHealth Ontario is looking to acquire experts to conduct an evaluation analysis – with solid methodology and good data – for informed-decision making, which I think is an absolute must at this stage of the game – OLIS anyone? As a tax paying citizen, I support this endeavour.

My perception is that they don’t quite know what they are asking for – although the intention is there – however, I think more direction and organizational clarity is needed… perhaps pilot one program area. Dear RFP requester, sit down with experts and figure out what what you want to measure and what to look for.

Here is a great free resource for Health Systems Evidence.