Current Medical Diagnosis & Treatment in Psychiatry

Clinical Decision Making in Psychiatry

Conclusion

Even after training, experience, and self-reflection, the clinician’s reasoning is not perfectible. How can it be improved? No contemporary computer can match the skill of the expert clinician in recognizing and weighing cues and inferences, and assembling efficient patterns. However, computers excel at storing information, generating extensive arrays of hypotheses, calculating Bayesian probabilities, avoiding judgment biases, and ensuring that inquiry plans will be systematic. In the future, when base-rate probabilities are better understood, computers will become indispensable to accurate diagnosis and treatment planning. Self-report questionnaires, structured interviews, and search protocols could also enhance the reliability and comprehensiveness of data collection.

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Flaws

Flexible and efficient though diagnostic reasoning may be, it is subject to a number of errors that are a consequence of the fact that the human computer has inherent capacity limitations and is vulnerable to interference by intrinsic and extrinsic factors.

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The Strategy of Clinical Reasoning

Diagnostic Reasoning is a feed-forward, feedback hypothetico-deductive process involving cue recognition, clinical inference, hypothesis testing, inquiry, planning, the search for evidence, the reaching of a diagnostic conclusion, and diagnostic formulation. In order to support the complexity of this process, the diagnostician must do several things (Table 9-3).

Research into Clinical Reasoning

There are three types of research into clinical reasoning: clinical judgment, decision theory, and process tracing. Clinical judgment research attempts to identify the criteria used by clinicians in making decisions. Decision theory explores the flaws and biases that deflect accurate clinical judgment. Process tracing elucidates the progressive steps of naturalistic reasoning. The first two types are statistical and prescriptive, the third is normative.

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Clinical Reasoning & Actuarial Prediction

Diagnosis and treatment are risky ventures. They are fraught with the possibility of error that can have serious consequences. How can error be minimized? On the one hand are the clinicians who, having elicited information that is generally both incomplete and inferential, diagnose patients and use subjective probabilities to predict outcome. On the other hand are the psychological actuaries who regard natural clinical reasoning as so flawed as to be virtually obsolete and who seek to replace it with reliable statistical formulas.

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Purpose of Clinical Reasoning

It is through clinical reasoning that clinicians collect, weigh, and combine the information required to reach diagnosis; decide which treatment is required; monitor treatment effectiveness; and change their plans if treatment does not work. The study of clinical reasoning, therefore, concerns the intellectual processes that underlie diagnosis and the planning and implementation of treatment.

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