Developing a Method to Analyze Observational Data for RN Interruptions

Juliana J. Brixey, MSN, MPH, RN¹, Zhihua Tang, PhD¹, David Robinson, MD, MS, FACEP², Todd R. Johnson, PhD¹, Jiajie Zhang, PhD¹, and James P. Turley, PhD, RN¹. (1) School of Health Information Sciences, University of Texas Health Science Center - Houston, Houston, TX, USA, (2) Medical School, The University of Texas Helath Science Center at Houston, Houston, TX, USA

A hybrid method was developed using both a deductive a prior classification framework with the provision of adding new categories discovered inductively in the data. The inductive process utilized line-by-line coding and constant comparison as stated in Grounded Theory. The hybrid method was tested by analyzing data collected during an ethnographic study of RNs working in a Level One Trauma Center. This site was chosen because such a critical environment is intense, life critical, interruption-laden, and stressful. Understanding the effects of interruptions in such an environment is important for improving healthcare quality and patient safety

Study Design: A prospective analysis of observational field notes collected during an ethnographic study.

Data analysis: A preliminary framework for interruptions was developed a prior to data analysis by reviewing definitions of interruptions published in the healthcare literature. Five defining attributes were identified and became attributes for the categories. This framework was augmented from the inductive process during data analysis. The result was a complete data model.

Nine categories of interruptions were identified. Seven categories were identified and named from the perspective of whether the subject received or initiated the interruption. Two categories of interruption were attributed to the organizational design of the department and the lack of physical or human resources. The categories were organized into a three-tiered hierarchy of activity based on Rosch’s model for concepts. Validity and reliability of the categories was tested by coding a medical error external to the study. No new categories of interruptions were identified.

In this study we have used a hybrid method to identify categories of interruptions. The categories have been organized within a hierarchy of activities. Initial findings suggest that the hybrid model of categorization is more complete than either a deductive or inductive method alone.

Learning Objective #1: to identify an interruption and the five defining attributes.
Learning Objective #2: describe the hybrid method developed in this project and how it was used to categorize interruptions.