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Bias01:22

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Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
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Cognitive bias results from limitations in thinking and information processing, leading to systematic errors in judgment. Conversely, motivational bias stems from personal desires or emotions, causing distortions in perception to align with self-interest. Motivational bias influences how individuals perceive and attribute causes to events, often shaped by personal needs, goals, and self-esteem preservation. This bias can distort judgment, leading to inaccurate assessments of success, failure,...
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First impressions play a crucial role in social perception, shaping how individuals assess others in professional, academic, and interpersonal contexts. Psychological research highlights the significance of cognitive biases, such as the primacy and recency effects, which influence how people interpret and recall information.The Primacy Effect and Cognitive AnchoringThe primacy effect describes the tendency for initial information to impact judgment disproportionately. When individuals encounter...
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In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
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The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
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Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
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Biases distorting priority setting.

Bjørn Hofmann1

  • 1Institute for the Health Sciences at the Norwegian University of Science and Technology, Gjøvik, Norway; The Centre of Medical Ethics at the University of Oslo, Norway.

Health Policy (Amsterdam, Netherlands)
|December 12, 2019
PubMed
Summary

Health care priority setting systems are well-developed but often fail due to cognitive biases. Identifying these biases is crucial for improving health policy and resource allocation.

Keywords:
BiasImperativeLow-value carePriority settingRationality

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Area of Science:

  • Health Policy
  • Health Economics
  • Decision Science

Background:

  • Healthcare systems face resource limitations despite technological advancements.
  • Existing health policy and priority-setting systems are often ineffective.
  • Low-value care persists while high-value care remains unaffordable.

Purpose of the Study:

  • To investigate the poor outcomes of health care priority setting.
  • To identify rational, structural, and irrational (bias-driven) explanations for these outcomes.
  • To analyze how biases distort priority setting processes and impact resource allocation.

Main Methods:

  • Literature review and analysis of existing health policy and priority-setting frameworks.
  • Identification and categorization of cognitive biases affecting decision-making in healthcare.
  • Examination of bias implications on overuse, underuse, overinvestment, and disinvestment.

Main Results:

  • Rational and structural factors contribute to the gap between theoretical priority-setting efforts and practical outcomes.
  • Numerous cognitive biases significantly distort healthcare priority setting at micro, meso, and macro levels.
  • Biases lead to suboptimal resource allocation, including overuse, underuse, and hindered disinvestment.

Conclusions:

  • Understanding and addressing cognitive biases is essential for improving health policy and priority setting.
  • Systematic identification of biases is the critical first step toward more effective healthcare resource allocation.
  • Mitigating biases can help align healthcare practices with available resources and technological potential.