The reverse salient … refers to the sub-system that has strayed behind the advancing performance frontier of the system due to its lack of sufficient performance. In turn, the reverse salient hampers the progress or prevents the fulfillment of potential development of the collective system. … Because reverse salients limit system development, the further development of the system lies in the correction of the reverse salient, where correction is attained through incremental or radical innovations. [1]
The concept of reverse salients was discussed by Ethan Mollick of the Wharton School in a recent Twitter tweet. He defined a reverse salient as “the technology or process that is holding back development of the whole system … Solving the salient unlocks change.” As an example, Mollick notes that the development of adequate car batteries made electric cars viable.
The term reverse salient, originally a military term, to describe technological changes was introduced by Thomas Hughes in a 1983 book about the early years of electrification where the development of alternating current solved the problem with “low voltage transmission distance” of Thomas Edison’s direct current system. [1]
In her August 16, 2022 newsletter, Annie Duke proposed that considering reverse salients is an example of a mental model called “monkey’s and pedestals”. [2] The basic idea is if you want to train a monkey to recite Shakespeare (or juggle flaming torches) on a pedestal in a town square, you should start the more difficult task: training the monkey. Even though building the pedestal would be much easier and a quicker way to show progress is being made, it won’t accomplish the goal until the monkey is trained. In this case training the monkey is the reverse salient that is holding the whole project back.
Musings
I’ve written a lot in this space about the difficulties introducing routine shared clinical decision making into practice and identified a series of models describing conversation-based solutions to the problem. None have made much of a difference.
Perhaps we have focused too much on the pedestal of just changing the script of a standard clinical consultation and not enough on the monkey of how to enable clinicians and patients to become better decision makers.
The key to improving patient care is focusing on ways to improve the clinical decision-making process.
At the most basic level, the objective of clinical decision making is to make good decisions regarding the care of individual patients. Before we can understand the implications of this statement further, we have to first address the question of what a good decision is.
There are two ways to evaluate a decision. One can judge the quality of a decision based on the outcome – what subsequently happens – or the process – how the decision was made.
There is good evidence that people commonly judge decisions by their outcomes. A decision followed by a favorable outcome is considered good and one followed by a poor outcome is considered bad. [1,2] However, judging the quality of a decision by its outcome is only appropriate when the outcomes that will follow each option are known at the time the decision is made and this information is available to the decision maker(s).
When the potential outcomes are uncertain, good outcomes can follow poor decisions and vice versa. For example, one can arrive safely home after choosing to drive home after drinking too much alcohol and be involved in an accident when riding home in a taxi. However, choosing to drive yourself is still not a good choice since the chances of arriving home safely are much higher if you call for a ride. Annie Duke provides a great, real world example the dangers of judging a decision by its outcome (called resulting in poker) in Chapter 1 of her book “Thinking in Bets”, which is included in the free preview on Amazon.com. (Apologies to non-football fans.)
Judging decision choices by their outcomes is not appropriate when the future outcomes are uncertain. In this situation, whether a decision should be considered “good” or “bad” depends on how well it was made, i.e., the decision-making process. Because the majority of clinical decisions are made when the outcomes are uncertain, the key to improving patient care is focusing on ways to improve the clinical decision-making process.
Musings
If one accepts the premise that the goal of clinical decision making is to make good decisions regarding the care of individual patients, it follows that clinicians should be trained (and expected) to be expert decision makers. I don’t think this is widely recognized as a key element in the training of future clinicians. I think it should be.
It also follows that patients should also have decision making expertise. Ideally, learning how to make good decisions should be part of a basic high school education. Since it isn’t (as far as I know), developing and implementing methods to effectively guide patients through the clinical decision making process should be recognized as a key quality of care target metric.
References
Baron J, Hershey JC. Outcome Bias in Decision Evaluation. Journal of personality and social psychology. 1988;54(4):11–11.
Kausel EE, Ventura S, Rodríguez A. Outcome bias in subjective ratings of performance: Evidence from the (football) field. Journal of Economic Psychology. 2019;75:102132–102132.
How situational awareness can help elucidate the path to shared clinical decision making.
A policeman sees a drunk man searching for something under a streetlight and asks what the drunk has lost. He says he lost his keys and they both look under the streetlight together. After a few minutes the policeman asks if he is sure he lost them here, and the drunk replies, no, and that he lost them in the park. The policeman asks why he is searching here, and the drunk replies, “this is where the light is”. (1)
Methods to promote shared decision making in clinical practice have been based on multiple conceptual frameworks. In a 2011 review, Glyn Elwyn and colleagues reviewed eight frameworks – expected utility theory, the conflict model of decision making, prospect theory, fuzzy-trace theory, differentiation and consolidation theory, the ecological rationality theory, the rational–emotional model of decision avoidance, and the Attend, React, Explain, Adapt model of affective forecasting – and concluded that none of them could effectively serve as the basis for decision support interventions. (2) An important limitation of this review is that the authors only reviewed theories they considered “major theoretical developments” and that had been used to develop decision support interventions for patients.
The results of this study, along with the continuing difficulties implementing shared decision making in practice settings, suggest a need to identify effective conceptual frameworks for shared clinical decision making. Aside from a paper published in 2014 by Elwyn and colleagues that was devoted to developing an entirely new theory (3), it appears that the 2011 review sparked little interest in closing the shared decision making theory-practice gap. (If anyone knows of any substantial developments in this area, please let me know.)
In recent blog posts I’ve discussed a couple of decision making frameworks that could be used to advance the practice of clinical shared decision making: the OODA loop on October 7, 2022 and best practices for successfully implementing decision support interventions in real world settings on October 2, 2022. Today I’d like to introduce another: Situational Awareness.
Situational Awareness is:
“… the perception of the elements in the environment within a volume of time and space, the comprehension of their meaning, and the projection of their status into the near future”. (4)
Situational awareness (also sometimes called Situation Awareness) has been most commonly used to understand and guide decisions in rapidly changing aviation and military environments. However, it is fundamentally a framework for understanding factors that affect decisions to identify ways to improve them. Thus concept applies equally well to many situations and could serve as a useful model for shared clinical decision making.
A basic situational awareness model adapted from Endsley and Jones (4) is shown in figure below.
Street and Politi have defined the ultimate goal of shared decision making as the achievement of a “shared mind” between patient and clinician. (5) In terms of Situational Awareness, a shared mind is equivalent to shared situational awareness. Achievement of shared situational awareness depends on both the factors that impact individual situational awareness and the effectiveness of the clinician/patient interaction. An adapted shared situational awareness model is shown in the following figure:
In this model, both the clinician and the patient develop an awareness of the situation and what could happen after following different courses of action. This awareness is influenced by individual characteristics including each person’s goals and objectives, preconceptions, baseline knowledge and ability to process new information, as well as extrinsic factors including their current level of stress, time pressure, and access to needed information. The nature of the clinician/patient interaction then determines the extent to which their individual situational awarenesses are shared and mutually understood. The resulting shared situational awareness then guides the decision making process which, in turn, results in subsequent actions and outcomes. For example, consider how this model would apply to decisions about colorectal cancer screening. Both the clinician and the patient develop an individual awareness of the risks and benefits associated with colorectal cancer screening and the advantages and disadvantages of the different screening options available. They then seek to merge their individual situational awarenesses into a single shared awareness to decide what is best for this particular patient.
Musings
Looking at shared decision making through the situational-awareness lens makes it clear how complicated the process is. In addition to the decision itself, factors associated with the people involved and the environment they are acting in can all effect the final outcome, in both good and bad ways.
Based on my recent review of the shared decision making literature – described in the recent series of posts – it appears that most proposals for implementing shared decision making in clinical practice focus primarily or exclusively on the clinician/patient interaction. To date, none has been very successful in fostering adoption of shared decision making in practice.
The situational awareness model suggests that the conversational approach is too limited to effectively address the complexity involved. If so, we need to develop new ways of thinking about clinical shared decision making that are appropriate for the level of complexity involved. I propose that situational awareness is one that merits further consideration.
Elwyn G, Stiel M, Durand M-A, Boivin J. The design of patient decision support interventions: addressing the theory-practice gap. J Eval Clin Pract. 2011 Aug;17(4):565–74.
Elwyn G, Lloyd A, May C, van der Weijden T, Stiggelbout A, Edwards A, et al. Collaborative deliberation: A model for patient care. Patient Educ Couns. 2014 Nov;97(2):158–64.
Endsley MR, Jones DG. Designing for Situation Awareness: An Approach to User-Centered Design, Second Edition. 2nd ed. 2012;396.
Politi MC, Street RL. The importance of communication in collaborative decision making: facilitating shared mind and the management of uncertainty. J Eval Clin Pract. 2011;17(4):579–84.
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