Decision Making Mindset Essay

One of the pioneer works in checking out medical decision making by Lusted and fellow workers suggested that scientific reasoning was based on logic, likelihood, and value theory [1]. Within their work Ledley and Lusted specified a physician description of medical diagnosis process as follows

First, obtain the circumstance facts from the patient's record, physical assessment, and laboratory checks.

Second, measure the relative need for the different indicators and symptoms

Make a differential prognosis that is list all the diseases that your specific case can relatively resemble.

Exclude one disease after another from the list until it becomes visible that the truth can be built in into a particular disease category, or that it might be on of several possible diseases or its character cannot be defined

Ledley and Lusted[1] [27] R. S. Ledley and L. B. Lusted, Reasoning foundations of medical prognosis, Research 130 (1959) (3366), pp. 9-21. View Record in Scopus | Cited By in Scopus (128)analysed the reasoning foundations of medical diagnoses presented the concepts of mathematic reasoning to medical medical diagnosis, attempted to formalize medical analysis by logical relations to symbolize medical knowledge that is the physician's understanding of human relationships between symptoms and diseases and open up medical technology for ways of decision-making and computer sciences.

Approaches to decision making explored by decision analysts are: Normative theory (how people must decide if indeed they work rationally - that is mathematically appropriate) [2]. Descriptive theory (how are decision actually made? and the prescriptive theory (how can decision theory be used to boost decision?) Within the last 30 years decision theory and its applied form, specifically decision analysis have grown to be a multidisciplinary area relating knowledge from a wide range of areas such as viewpoint, organisational theory, computer science, economics, psychology, specialized medical psychology, clinical practice and medical education sociology, figures, computer science, manufactured intellect [refs many, bell, 2], the respected affiliation of various registered to either the normative or descriptive theory is shown in body 3

Figure 3: The various themes from where knowledge comes into the world of decision making.

Normative model of medical Decision consist of the expected electricity theory (the normative theory of preference under doubt) and multi attribute theory, bayes' theorem offers a normative method of the sequential handling of medical data characterized by subjective likelihood [2]. Descriptive ideas like the info processing approach which was developed further into a hypothetico-deductive strategy consider diagnostic decision making as hypotheses era task. Individual bits of information are evaluated to verify or refute the hypotheses[2]. Normative decision theory and decision analysis-both help to make patient choices accessible for medical decision- making [2, 3], a number of data mining techniques like decision tree, neural systems, support vector machine etc. can be used to put into action decision analysis

Nowadays, decision analysts speak of prescriptive decision support and prescriptive decision research as being the software of normative ideas, mindful of the conclusions of descriptive decision studies, to steer real decision-making[4, 5]

"mathematicians (decision theorists) are interested in proposing rational procedures for decision making Psychologists are enthusiastic about how people do make decisions. One third group, the methodologists, the consultants are concerned with how to improve the quality of decisions in practice? methods (are needed) that include the insights gained from normative theories, but in a means that recognizes the cognitive limitations of decision makers"[4].

So, the effort of prescriptive decision theory is to help decision producers solve real decision problems also to concentrate on one problem at the time. Consequently, area of the goal of this work is to incorporate the normative, descriptive techniques in the area of professional medical reasoning and decision-making.

In order to build up decision support program predicated on knowledge breakthrough and data mining techniques thus it is of great importance to know the similarities as well as the dissimilarities between your three ideas[4]: The prescriptive theory handles the art, research of practical decision making and can be viewed as the engineering part of the normative theory[6]. Furthermore, the prescriptive theory is very much concerned with the recognition of the discrepancies between real (descriptive) and idealised (normative) behaviour in decision making and to help to make better decisions. Evaluating the criteria by which they are evaluated can also illustrate the differences between your three models. [4]

Empirical validity is the criterion used when evaluating descriptive models, i. e. from what degree they match observed choices.

Theoretical adequacy is the criterion for analyzing normative models, i. e. from what degree they provide rational choice; and

Pragmatic value is the criterion used when evaluating prescriptive models, i. e. how well they can offer suitable help a decisionmaker to make better decisions (Bell et al. , 1988).

Clinical reasoning

Quite few principles used to spell it out specialized medical reasoning in healthcare (specialized medical decision making, medical problem fixing diagnostic reasoning) [2, 7], (specialized medical judgment, medical inference) [7]. Clinical reasoning is the process use in solving patient's problem predicated on medical data, knowledge and professional judgment [2] [8].

Different strategies aimed at decision making use in scientific reasoning are Hypothetico-deductive or diagnostic reasoning [2, 9, 10], Decision examination, [2, 3, 9], Design identification [9-11] and Intuition [9]. In hypothetico-deductive reasoning hypothesis is produced predicated on data from the patient, which is then analyzed, and additional hypotheses are made to confirm or refute the hypotheses. Use to resolve unfamiliar problem or a sophisticated demonstration [10]. Decision analysis make patient choices available as input for specialized medical decision- making [2, 3]. Von Neumann and Morgenstern first suggested that ideals and attitudes that drive specific reasoning choice could be understood through numerical formulations [3]. Later, Ledley & Lusted use decision analysis to show how the concepts of mathematical disciplines - symbolic logic and possibility can contribute to our knowledge of the reasoning foundations of medical analysis [1, 3]. Routine recognition is an inductive reasoning, the existing patient's problems are associated with previously-seen professional medical problems and a previously-successful treatment is adopted, utilized by expert and experienced practitioners, is commonly faster and better [10]. Intuition is not named a way to obtain scientific knowledge in specialized medical reasoning [9]. Heuristics and experiential knowledge use to process massive amount information successfully Thompson & Dowding. 2002) are essential but not an adequate basis for medical decision making, have a tendency to introduce series of biases into decisions making. [12].

A unifying platform that considers all different clinical reasoning ideas is that of Buckingham and Adams [13], clinical decision making is interpreted as a classification patterns. They argued that hypotheses become classes, the data for which consists of their descriptive features or features. Linking cues with diagnostic categories, usually thought to be pattern reputation is the same process as linking proof with hypothesis in the sense that it is a kind of classification activity.

Figure2: Adapted from[14].

Part of the purpose of this work to aid professional medical decision making using data mining and knowledge breakthrough, incorporating ideas proposed by and Adams [14] to reflect the connections between normative, descriptive theories of decision making that is the identification of the discrepancies between real (descriptive) and idealised (normative) behavior in decision making to be able to help people make smarter decisions through prescriptive support

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