Documenting patterns of nursing interventions using cluster analysis.
Use of inferential statistics in research applications of the Nursing Intervention Classification has been rare, yet use of these statistical techniques is needed to answer questions related to intervention patterns. Using data from a descriptive study of 3,733 visits documented by 19 adult nurse practitioner students, hierarchical agglomerative cluster analysis was used to determine whether meaningful nursing intervention patterns could be depicted. Eight intervention clusters were derived, replicated, and validated. Clusters of intervention classes differed in the type of nursing and medical diagnosis, amount of time the nurse spent during the visit, cost of visit, and the age of the patient. Clustering supported the utility of standardized nursing diagnosis and intervention typologies to identify actual practice patterns of adult nurse practitioner students. Cluster analysis is a valuable data analysis strategy when analyzing multiple related variables.
O'Connor
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NA
Wayne State University, Detroit, Michigan, USA.
Kershaw
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T
Hameister
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AD
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000553:Ambulatory Care / Q000706:statistics & numerical data; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D016208:Databases, Factual; D004282:Documentation / Q000379:methods*; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data; D006801:Humans; D007587:Job Description; D008297:Male; D008875:Middle Aged; D009722:Nurse Practitioners / Q000458:organization & administration*; D009732:Nursing Care / Q000145:classification* / Q000706:statistics & numerical data*; D009733:Nursing Diagnosis / Q000145:classification* / Q000592:standards / Q000706:statistics & numerical data*; D015403:Nursing Evaluation Research / Q000379:methods*; D009737:Nursing Records; D013997:Time Factors; D018875:Vocabulary, Controlled; D016526:Workload