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The Iowa Model is used to promote quality of care. It is a guideline for nurses in their decision-making process. The decision making can include clinical and administration practices. These practices affect patient outcomes. The model is based on problem-solving steps that are a part of the scientific process.
The nursing process is a cyclical and ongoing process that can end at any stage if the problem is solved. The nursing process exists for every problem that the individual/family/community has. The nursing process not only focuses on ways to improve physical needs, but also on social and emotional needs as well. [11] Cyclic and dynamic
The GAISE document provides a two-dimensional framework, [11] specifying four components used in statistical problem solving (formulating questions, collecting data, analyzing data, and interpreting results) and three levels of conceptual understanding through which a student should progress (Levels A, B, and C). [12]
Gigerenzer & Gaissmaier (2011) state that sub-sets of strategy include heuristics, regression analysis, and Bayesian inference. [14]A heuristic is a strategy that ignores part of the information, with the goal of making decisions more quickly, frugally, and/or accurately than more complex methods (Gigerenzer and Gaissmaier [2011], p. 454; see also Todd et al. [2012], p. 7).
Although much of nursing ethics can appear similar to medical ethics, there are some factors that differentiate it. Breier-Mackie [5] suggests that nurses' focus on care and nurture, rather than cure of illness, results in a distinctive ethics. Furthermore, nursing ethics emphasizes the ethics of everyday practice rather than moral dilemmas. [2]
The nurse scheduling problem (NSP), also called the nurse rostering problem (NRP), is the operations research problem of finding an optimal way to assign nurses to shifts, typically with a set of hard constraints which all valid solutions must follow, and a set of soft constraints which define the relative quality of valid solutions. [1]
Multiple testing procedures are sometimes used to compensate, but that is often difficult or impossible to do precisely. Post hoc analysis that is conducted and interpreted without adequate consideration of this problem is sometimes called data dredging by critics because the statistical associations that it finds are often spurious. [4]
The iteration of such strategies over the course of solving a problem is the "problem-solving cycle". [ 30 ] Common steps in this cycle include recognizing the problem, defining it, developing a strategy to fix it, organizing knowledge and resources available, monitoring progress, and evaluating the effectiveness of the solution.