Coincidence Analysis: A Novel Approach to Modeling Nurses' Workplace Experience.

Objectives: The purpose of this study is to identify combinations of workplace conditions that uniquely differentiate high, medium, and low registered nurse (RN) ratings of appropriateness of patient assignment during daytime intensive care unit (ICU) work shifts.

Methods: A collective case study design and coincidence analysis were employed to identify combinations of workplace conditions that link directly to high, medium, and low RN perception of appropriateness of patient assignment at a mid-shift time point. RN members of the study team hypothesized a set of 55 workplace conditions as potential difference makers through the application of theoretical and empirical knowledge.

Evaluation of Electronic Health Record-Generated Work Intensity Scores and Nurse Perceptions of Workload Appropriateness.

Electronic health record-generated work intensity scores represent state-of-the art functionality for dynamic nursing workload estimation in the hospital setting. In contrast to traditional stand-alone patient classification and acuity tools, electronic health record-based tools eliminate the need for dedicated data entry, and scores are automatically updated as new information is entered into patient records. This paper summarizes the method and results of evaluation of electronic health record-generated work intensity scores on six hospital patient care units in a single academic medical center.

Registered Nurse Strain Detection Using Ambient Data: An Exploratory Study of Underutilized Operational Data Streams in the Hospital Workplace.

Background: Registered nurses (RNs) regularly adapt their work to ever-changing situations but routine adaptation transforms into RN strain when service demand exceeds staff capacity and patients are at risk of missed or delayed care. Dynamic monitoring of RN strain could identify when intervention is needed, but comprehensive views of RN work demands are not readily available. Electronic care delivery tools such as nurse call systems produce ambient data that illuminate workplace activity, but little is known about the ability of these data to predict RN strain.

Subtle cues: Qualitative elicitation of signs of capacity strain in the hospital workplace.

Through everyday care experiences, nurses develop expertise in recognition of capacity strain in hospital workplaces. Through qualitative interview, experienced nurses identify common activity changes and adaptive work strategies that may signal an imbalance between patient demand and service supply at the bedside. Activity change examples include nurse helping behaviors across patient assignments, increased volume of nurse calls from patient rooms, and decreased presence of staff at the nurses' station.