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The client is the primary source of data. Family members or other support persons, other health professionals, records and reports, laboratory and diagnostic analyses, and relevant literature are called secondary sources. The primary methods used to collect data are observing, interviewing, and examining.
Consistently reassessing patients is a key component to maintaining patient safety and improving patient health outcomes. Not doing so, may pose docHub risks to their health. Though performing assessments are part of a nurses foundational competencies, it is critical that nurses maintain this knowledge and skill.
Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation.
Data collection gathers information needed to make accurate judgments about a patients present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment.
For example, a nurses assessment of a hospitalized patient in pain includes not only the physical causes and manifestations of pain, but the patients responsean inability to get out of bed, refusal to eat, withdrawal from family members, anger directed at hospital staff, fear, or request for more pain mediation.
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Assessment is the first part of the nursing process, and thus forms the basis of the care plan. The essential requirement of accurate assessment is to view patients holistically and thus identify their real needs.
The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible. Nursing assessment guides are generally based on holistic models rather than medical models.
Data validation can help identify errors, thus increasing the accuracy of your results. To mitigate the risk of forming incorrect hypotheses: Only those inferences and hypotheses that are backed by solid data are considered valid. Thus, data validation can help you form logical and reasonable speculations.

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