Self-perception and Self-concept: Self-concept and perception of self-worth, self-competency, body image, and mood state Sleep-Rest: Sleep, rest, and daily activitiesĬognitive-Perceptual: Perception and cognition Nutritional-Metabolic: Food and fluid consumption relative to metabolic needĮlimination: Excretory function, including bowel, bladder, and skinĪctivity-Exercise: Exercise and daily activities Health Perception-Health Management: A patient’s perception of their health and well-being and how it is managed The nurse makes a hypothesis that the patient has excess fluid volume present. These cues are clustered into a generalization/pattern of fluid balance, which can be classified under Gordon’s Nutritional-Metabolic Functional Health Pattern. The nurse clusters the following relevant cues: elevated blood pressure, elevated respiratory rate, crackles in the lungs, weight gain, worsening edema, shortness of breath, a medical history of heart failure, and currently prescribed a diuretic medication. Refer to Scenario C of the “Assessment” section of this chapter. Concepts related to many of these patterns will be discussed in chapters later in this book.Įxample. See the box below for an outline of Gordon’s Functional Health Patterns. Assessment frameworks such as Gordon’s Functional Health Patternsassist nurses in clustering information according to evidence-based patterns of human responses. These findings are considered “relevant cues.” Clustering Information/Seeing Patterns/Making HypothesesĪfter analyzing the data and determining relevant cues, the nurse clusters data into patterns.
In Scenario C in the “Assessment” section of this chapter, the nurse analyzes the vital signs data and determines the blood pressure, heart rate, and respiratory rate are elevated, and the oxygen saturation is decreased for this patient. From there, nurses determine what data are “clinically relevant” as they prioritize their nursing care.
Performing Data AnalysisĪfter nurses collect assessment data from a patient, they use their nursing knowledge to analyze that data to determine if it is “expected” or “unexpected” or “normal” or “abnormal” for that patient according to their age, development, and baseline status. The nursing diagnoses are then prioritized and drive the nursing care plan. Steps for analyzing assessment data include performing data analysis, clustering of information, identifying hypotheses for potential nursing diagnosis, performing additional in-depth assessment as needed, and establishing nursing diagnosis statements. Analyzing Assessment DataĪfter collection of assessment data, the registered nurse analyzes the data to form generalizations and create hypotheses for nursing diagnoses. This standard is defined as, “The registered nurse analyzes assessment data to determine actual or potential diagnoses, problems, and issues.” The RN “prioritizes diagnoses, problems, and issues based on mutually established goals to meet the needs of the health care consumer across the health–illness continuum and the care continuum.” Diagnoses, problems, strengths, and issues are documented in a manner that facilitates the development of expected outcomes and a collaborative plan. Diagnosis is the second step of the nursing process (and the second Standard of Practice set by the American Nurses Association).
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