Types of Data Analysis in Healthcare

Descriptive analysis is defined by its interaction with descriptive data as numerical values within a data set that represent research variables. Essentially, the analysis of such data is done through calculations or other mathematical procedures to obtain essential information regarding a topic or field of study (Houser 291). The summarization of these calculations also allows researchers to establish patterns that are founded on statistical evidence.

Inferential analysis or statistical inference can be directly contrasted with descriptive analysis. Inferential analysis attempts to observe properties underlying distribution among the collected data. Properties can be determined and hypothesized, after which they can be tested. As such, unlike descriptive analysis, which only investigates the collected data, inferential analysis can make assumptions about other factors related to the sample based on evidence.

Qualitative analysis is characterized by its process, which abides by a less concrete structure and tends to be significantly more time-consuming. Essentially, the interaction with qualitative information, which is sorted into relevant and appropriate units as an analysis proceeds, is inherently more complex and more prone to reevaluation. Data within qualitative processes can include observations, narratives, and transcripts that researchers aim to structure and obtain meaning from.

Data analysis is inherently important to the nursing field, as the study and application of healthcare are especially prone to changes and improvement. With frequent discoveries and experiments that yield new information, diligent data analysis is the primary tool of observation and evaluation within the field of nursing. Within nurse work settings, data analysis is integral to formulating evidence-based practice and policy creation (Benton et al., 2020). Statistical significance indicates the reliability of collected study data and results. Clinical significance refers to the impact of the data or findings within clinical practice.

References

Benton, D. C., Watkins, M. J., Beasley, C. J., Ferguson, S. L., & Holloway, A. (2020). Evidence-based policy: nursing now and the importance of research synthesis. International Nursing Review, 67(1), 52-60. Web.

Houser, J. (2018). Nursing research: reading, using, and creating evidence (4th ed.). Jones & Bartlett Learning.

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NursingBird. 2024. "Types of Data Analysis in Healthcare." November 26, 2024. https://nursingbird.com/types-of-data-analysis-in-healthcare/.

1. NursingBird. "Types of Data Analysis in Healthcare." November 26, 2024. https://nursingbird.com/types-of-data-analysis-in-healthcare/.


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NursingBird. "Types of Data Analysis in Healthcare." November 26, 2024. https://nursingbird.com/types-of-data-analysis-in-healthcare/.