Data validation is an essential part of a comprehensive assessment. 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. 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. For example, Gordon's framework (1994) identifies 11 functional health patterns and organizes patient data into these patterns. Maslow (1943) uses a hierarchy of five sets of human needs. Contrarily, the body systems model is a medical model used to organize collected data according to organ and tissue function in various body systems. Although it helps formulate diagnoses related to physiologic problems, the body systems mostly neglect to identify the patient's problems and strengths in psychosocial and spiritual dimensions of health and well-being.

Information acquired through the five senses is cueing, whereas judgment or interpretation of informational cues is called inference. The steps in data validation include identifying the clues, making inferences about clues, and validating cues and inferences.

Inferences can be validated in several ways:

• Physical examination using the proper equipment, technique, and procedure. The findings must be confirmed by an expert.
• Clarifying statements
• Sharing the inferences with other respected members of the team and seeking consensus
• Checking the findings with research reports, textbooks, or journals
• Comparing cues to the knowledge base of normal function
• Checking the consistency of cues

The nurse may validate data as it is collected or at the end of the data-gathering process. When the data is clear, the nurse analyzes the data and formulates nursing diagnoses—the next step of the nursing process.