Rationality in Medical Decision Making Discussion Paper
Rationality in Medical Decision Making Discussion Paper
Introduction
Medical decision-making is how healthcare professionals, including doctors, nurses, and other care providers, choose the best preferable course of action for a patient’s care (Begoli et al., 2019). The patient’s medical history, present symptoms and condition, available tests and treatments, and the potential risks and benefits of each option are all taken into account during this procedure. Often, healthcare professionals have to engage in constant rationality to make the best suitable decision for the optimal health performance of a patient. Making medical decisions is a difficult process that requires combining clinical expertise, scientific knowledge, and individual judgment (Marewski & Gigerenzer, 2022). Medical decision-making can be approached in a variety of ways, such as evidence-based medicine, which makes use of the best available scientific data to inform treatment choices, and shared decision-making, which entails patient and healthcare provider cooperation in selecting the best course of action. Making medical decisions is a crucial part of patient care. Other important factors that are critical in medical decision-making include goals and objectives that are well-defined and clear. It also includes alternative information that is relevant and accurate in the event the suitable decision fails to produce optimal results. It also includes identifying uncertainties and risks as decisions made by medical health professionals are pruned to potential consequences due to different outcomes. Stakeholders are also equally important to be included as critical factors when considering medical decision-making. This paper will critically evaluate the rationality theories relevant to medical decision-making. It would examine the three main classifications of theories of rationality in decision-making. It would also examine the relevant theories and models of rationality decision-making in clinical and medical decision-making.
Literature Review
Examining the numerous academic resources and papers, as well as theories that have been written on rationality decision-making, would be a critical part of a literature study on rationality in decision-making. Burton et al. (2020) systematically examine the rationality decision-making models and theories and their importance in medicine. Rationality in Medical Decision Making Discussion Paper The researchers identify five distinct themes from their systematic studies: divergent rationalities, cognitive compatibility, incentivization, decision autonomy, and expertise expectations. The researchers conclude that rational decision-making in the medical field is critical in treating patients and their overall care, leading to positive health outcomes. Djulbegovic et al. (2018) research study investigate the implications of the underuse and overuse of rational decision-making in medicine. The research paper identifies what healthcare intervention is considered overuse and what is considered underuse in rational decision-making. The researchers give examples to demonstrate how the theoretical framework healthcare professionals choose affects our policies and individual decision-making. The researchers also draw attention to how their analysis of rationality might be used to gauge care quality and relate that measurement to how money is spent on healthcare services.
Chow et al. (2018) examine the evidence-based theory of rationality decision-making. They conclude that there is a hierarchy of evidence to guide clinical decision-making, and studies at lower risk of bias are likely to provide more reliable findings. Evidence alone is insufficient to make clinical decisions—the values of patients and preferences and resource implications must be taken into account. Power et al. (2019) research study analyses the evidence, bias, and analytics of rational decision-making in healthcare environments. They conclude that decision-support builders and healthcare professionals must always consider a broader range of factors, including issues of belief and knowledge, social factors, and technical capabilities, when developing cognitive rationalities, analytical, and decision-support systems in a healthcare environment.
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The various research articles provide an examination of the definition and significance of rationality in the context of decision-making, as well as the numerous theories and approaches to the concept of rationality in decision-making: This would involve exploring the definition and meaning of rationality in the context of decision making, including the various models and approaches to rational decision making. Rational decision-making is what this idea of rationality in decision-making entails. As part of the literature review, the research articles address the problems that behavioral economics and psychology offer to the traditional conceptions of rationality. These fields have demonstrated that healthcare providers can be susceptible to cognitive biases and heuristics that can result in poor decisions. These articles are important in studying rational decision-making in the medical field.
Classification of Theories of Rationality for Decision-making
In rationality for decision-making, there are three major classifications of theories and models. These are bounded rationality theories, behavioral theories of rationality, and classical theories of rationality.
Bounded Theories of Rationality
The bounded rationality theories recognize the limitations of human reasoning and decision-making skills. According to this classification of rationality decision-making, people, especially in professional fields and the general human environment and organizations, have information and cognitive processing limits, and as a result, their actions are bounded by these restrictions rather than being completely rational (Sent, 2018). These theories under this classification were developed due to the limits of classical models, which presupposed that people had infinite access to knowledge and cognitive capacity. Examples of these theories include Satisficing, Heuristics and biases, Anchoring, and Framing effects of theories.
Behavioral Theories of Rationality
These theories acknowledge that various cognitive biases and heuristics influence human decision-making. Rationality in Medical Decision Making Discussion Paper These theories cast doubt on the traditional conception of rationality. Behavioral theories of rationality concentrate on how individuals behave and make decisions in the real world and acknowledge that people become biased frequently (Kotlar & Sieger, 2019). Examples include the prospect theory, the mental accounting model, and the self-servicing theory.
Classical Theories of Rationality
The classical theories of rationality focus on the assumption that people make decisions based on accurate and complete information (Begoli et al., 2019). Some of the theories that fall under this category include the rational choice theory, the expected utility theory, and the maximization of the expected value.
Rationality Theories and Relevancy to Medical Decision-Making
Evidence-based medicine approach to rational decision making
This approach in healthcare for decision-making emphasizes healthcare professionals putting into use the most efficient scientific evidence in clinical practice (Chow et al., 2018). This model aims to ensure that healthcare clients, including patients, receive the most recent and approved care for optimal health outcomes rather than the traditional intuition methods. For example, the use of Artemether-lumefantrine medicine to treat malaria is other than the traditional chloroquine medication.
Expected Utility Theory (EUT) Decision Analysis/Bayesian Rationality
This theory makes the presumption that decisions made by individuals providing care to patients would lead to an expected outcome. Each utility made by an individual participating in decision-making would lead to an expected outcome (Qaz et al., 2018). Individuals usually measure all possible outcomes to determine the expected outcome. For example, physicians may begin with an initial prior opinion about the likelihood of various diseases and then update these views when they learn new information, such as the outcomes of diagnostic testing. Through this method, an expected outcome can be measured.
Argumentative Theory of Reasoning
This theory holds reasoning as the process through which arguments are evaluated and constructed. The arguments that are constructed and evaluated are used to create firm support for claims (Begoli et al., 2019). For example, a physician in a clinical environment engages other healthcare providers to make a more informed decision on surgery or medication administration.
Meta-rationality or the Master Rationality Motive
This model entails using a higher thinking capacity where the individual breaks down tasks and sets goals and values for every task to develop concrete strategies to deal with a situation (Begoli et al., 2019). For example, in a healthcare environment, a clinician with a diagnostic dilemma may develop short-term goals through tasks to reflect on decision-making.
Robust Satisficing
This approach is rationality decision-making that combines the elements of satisficing and optimization. This approach ensures that individuals set goals for a particular course and then find solutions that fit their goals while remaining open to robust changes in a professional environment (Chow et al., 2018). For example, in a clinical environment where clinicians engaged in providing care to a patient with a chronic health condition, the goals would be to manage the symptoms portrayed by a patient while noting the robust changes to a patient’s lifestyle.
Conclusion
In conclusion, this paper has examined the medical decision-making process in clinical and care environments. Rationality decision-making is one of the key ways healthcare practitioners make decisions that impact the health outcomes of patients. This research paper has examined three critical classifications of rationality decision-making: bounded rationality theories, behavioral theories of rationality, and classical theories. Examples of bounded rationality theories include Satisficing, Heuristics and biases, and Anchoring. Examples of theories and models under classical theories include the rational choice theory, the expected utility theory, and the maximization of the expected value. This paper has also explored some of the theories of rationality and their impact on the clinical environment. These theories would be recommended to improve healthcare outcomes in a medical environment.
References
Begoli, E., Bhattacharya, T., & Kusnezov, D. (2019). The need for uncertainty quantification in machine-assisted medical decision-making. Nature Machine Intelligence, 1(1), 20–23. https://www.osti.gov/pages/servlets/purl/1561669
Burton, J. W., Stein, M. K., & Jensen, T. B. (2020). A systematic review of algorithm aversion in augmented decision making. Journal of Behavioral Decision Making, 33(2), 220-239.
Chow, N., Gallo, L., & Busse, J. W. (2018). Evidence-based medicine and precision medicine: complementary approaches to clinical decision-making. Precision Clinical Medicine, 1(2), 60–64. doi: 10.1093/pcmedi/pby009
Djulbegovic, B., Elqayam, S., & Dale, W. (2018). Rational decision making in medicine: implications for overuse and underuse. Journal of evaluation in clinical practice, 24(3), 655-665. https://doi.org/10.1111/jep.12851
Kotlar, J., & Sieger, P. (2019). Bounded rationality and bounded reliability: A study of nonfamily managers’ entrepreneurial behavior in family firms. Entrepreneurship theory and practice, 43(2), 251-273.
Marewski, J. N., & Gigerenzer, G. (2022). Heuristic decision-making in medicine. Dialogues in clinical neuroscience. https://doi.org/10.31887/DCNS.2012.14.1/jmarewski
Power, D. J., Cyphert, D., & Roth, R. M. (2019). Analytics, bias, and evidence: The quest for rational decision making. Journal of Decision Systems, 28(2), 120-137. https://doi.org/10.1080/12460125.2019.1623534
Qazi, A., Dickson, A., Quigley, J., & Gaudenzi, B. (2018). Supply chain risk network management: A Bayesian belief network and expected utility-based approach for managing supply chain risks. International Journal of Production Economics, 196, 24-42.
Sent, E. M. (2018). Rationality and bounded rationality: You can’t have one without the other. The European Journal of the History of Economic Thought, 25(6), 1370-1386. https://doi.org/10.1080/09672567.2018.1523206
