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Related Concept Videos

Reason and Intuition01:37

Reason and Intuition

The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the brain can only use...
Nursing Interventions II: Selecting and Classifying the Nursing Interventions01:29

Nursing Interventions II: Selecting and Classifying the Nursing Interventions

Creating and executing a nursing diagnosis helps nurses plan care and guide patient, family, and community interventions. They are developed based on a patient's physical evaluation and support measuring the outcomes. It is not recommended to select random interventions throughout the planning process. Instead, consider the following six essential factors when choosing interventions:
The Availability Heuristic01:08

The Availability Heuristic

A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
Decision Making01:20

Decision Making

Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions01:15

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...

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Related Experiment Videos

Evidence-based decision making: when should we wait for more information?

Kalipso Chalkidou1, Joanne Lord, Alastair Fischer

  • 1Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland, USA. kalipso.chalkidou@nice.org.uk

Health Affairs (Project Hope)
|November 11, 2008
PubMed
Summary
This summary is machine-generated.

Managing health care innovation requires balancing evidence-based access and cost-effectiveness. A framework suggests reimbursement for new technologies "in research" may be wise if delaying implementation offers value by awaiting more data.

Related Experiment Videos

Area of Science:

  • Health economics
  • Health services research
  • Health technology assessment

Background:

  • Managing innovation and access to healthcare interventions presents a significant challenge.
  • Ensuring evidence-based and cost-effective implementation of new health technologies is crucial for payers.
  • Existing decision-making processes often lack integration with research policies.

Purpose of the Study:

  • To discuss the challenges in managing health care innovation and access.
  • To present a decision-making framework for health care payers adopting new technologies.
  • To explore the conditions under which reimbursement for cost-effective technologies in research is appropriate.

Main Methods:

  • Utilized U.S. and U.K. case studies to develop a decision-making framework.
  • Analyzed the trade-offs between immediate implementation and delayed adoption for new health technologies.
  • Examined the concept of "keeping options open" through research-context reimbursement.

Main Results:

  • A decision-making framework for health care payers considering new technology adoption was described.
  • Reimbursement for potentially cost-effective technologies within a research context is deemed appropriate under specific conditions.
  • The value of delaying implementation, by waiting for more data, can offset implementation costs.

Conclusions:

  • There is a critical need for improved integration between health care decision-making and research policies.
  • Decision-making frameworks can aid payers in navigating the complexities of health technology adoption.
  • Balancing innovation, access, and cost-effectiveness requires a strategic approach to reimbursement and research.