Browsing School, Graduate by Subject "Workload"
Now showing items 1-3 of 3
Neonatal Nurses' Work in a Single Family Room NICUBackground: In the past twenty years, neonatal intensive care units (NICUs) have undergone changes in layout from open-bay (OPBY) to single family room (SFR). SFR layout may be advantageous to nurses’ work in that it improves the quality of the physical environment, patient care, and parent-nurse interactions. SFR layout may disadvantage nurses’ work in terms of decreased interaction among the NICU patient care team, increased nurse workload, and decreased visibility on the unit. It is unclear exactly how SFR layout is producing these changes. Purpose: This study asked: what is it like for neonatal nurses to work in a SFR NICU? Methods: Interpretive description, a qualitative methodology, guided this study. Interviews and observations were conducted in one SFR NICU over a six-month period. Data were coded broadly, then collapsed into themes as patterns within the data emerged. The Systems Engineering Initiative for Patient Safety model aided interpretation of nurses’ job demands. Emotional work was conceptualized as being preceded by emotional demands and anteceded by stress and burnout. Results: A total of 15 nurses participated. Overall, privacy, visibility, and proximity were integral in shaping nurses’ work. Regarding job demands, four themes emerged: challenges in infant surveillance and informal communication, alarm fatigue, and increased walking distances. Regarding emotional work, four themes emerged: families “living on the unit,” isolation of infants, ability to form trust and bonds, and sheltering. Emotional demands increased when families were living on the unit or when infants were left in isolation but were absent when nurses were able to form trusting relationships with parents and shelter them. Privacy gains on SFR NICUs may serve to balance losses in visibility and proximity for nurses. Conclusions: NICU layout impacts nurses’ job demands and emotional work. Future research should investigate unit layouts that maximize visibility and proximity for nurses while maintaining privacy. Neonatal clinicians transitioning to SFR layout should consider overall visibility and proximity of patients, equipment, and staff members from any point on the unit as a primary avenue for decreasing nurses’ work demands. Neonatal nurses will benefit from tactics that improve their communication skills with families.
Nurse Fatigue Increases the Risk of Sickness AbsenceIntroduction: Sickness absence (SA) is problematic in occupations requiring 24/7 coverage where one person's SA cascades into more work days, longer shift durations and elevated fatigued states for remaining workers. As part of this dissertation, a systematic literature review found strong evidence that fatigue increased the risk of SA in the workforce. Few studies examined this relationship in nurses, despite reported high fatigue and differences in shiftwork characteristics. Fatigue-risk scores generated from bio-mathematical fatigue models are popular in safety-sensitive industries and may be useful for assessing and monitoring fatigue on nursing units and predicting SA. Purpose: The purpose of this study was to explore prospective associations between work-related fatigue, bio-mathematically modeled fatigue-risk and SA in 12-hour shift hospital nurses. Methods: Two studies were conducted that used retrospective cohort design of hospital nurses representing four nursing units from a major pediatric hospital. Baseline data on work-related fatigue were from Fatigue Risk, Alertness Management Effectiveness (FRAME) study (n=40) using the self-reported Occupational Fatigue Exhaustion Recovery Scale. Data on fatigue-risk scores were generated from work-rest schedules of 197 nurses working 41,538 shifts using Fatigue Audit InterDyne (FAID) and Fatigue Risk Index (FRI) software programs. Work-related fatigue and fatigue-risk scores were then linked to SA data that were extracted from the hospital's attendance system. The statistical approach was generalized linear mixed models that account for non-independency of repeated measures. Results: The SA rate in both studies was ~5%. Among FRAME participants, for every 1SD increase in acute fatigue scores, nurses were 1.29 times more likely to be absent from work (OR=1.29, 95%CI=1.02-1.63). In the bio-mathematical model study, when FAID-scores were moderate (scores=41-79, OR=1.38, 95%CI=1.21-1.58) or high (scores=81-150, OR=1.67, 95%CI=1.42-1.95), nurses were more likely to take SA than nurses with lower (<41) scores. Similarly, when FRI-scores were >60, nurses were 1.58 times (95%CI=1.05-2.37) more likely to take SA compared to nurses with lower scores. Conclusion: Work-related acute fatigue and fatigue-risk modeled bio-mathematically significantly predicted nurses' SA. While surveys are instrumental in identifying the nature and severity of fatigue, bio-mathematical fatigue models may be more practical to monitor for day-to-day fatigue changes in the workplace.
Unit-level staffing, workload, and adverse events in Army Acute Care Hospitals: 2003-2006Background: A sequence of reports from the Institute of Medicine revealed quality and patient safety issues in hospitals. The crucial role of nurses was recognized, although much of the research has addressed staffing and, more recently, the work environment. Moreover, most of this research has been at the hospital level where attribution of care processes to adverse events is difficult. The Army, Air Force and Navy's hospitals have faced the same economic and quality challenges. However, military medical institutions also have the increased demands of supporting a nation at war. Purpose: This study examined unit level impact of nursing staffing and workload on medication errors and patient falls in Army hospitals between 2003 and 2006. Methods: A descriptive correlational longitudinal design was used to conduct a secondary analysis of 23 Army inpatient units from the Military Nursing Outcomes Database (MilNOD). Relationships among staffing, workload, and quality of care were examined from 2003 to 2006. A cross sectional design using only 2006 data examined the influence of practice environment on outcomes. Generalized Linear modeling (GZLM) was used to accommodate nested data. Results: Large turbulence was expected in the Army inpatient units from 2003-2006. Although some years were significantly higher, turbulence was far less than expected. Staff complement (measure of percent mix of military, civilian and contractor staff) was a significant predictor of medication errors. Patient census was a significant predictor of falls. The professional nursing Practice Environment Scale (PES) was a partial mediator of medication errors in all types of units. Although tested as both, the practice environment did not significantly mediate or moderate falls. Conclusion: This study supports the growing literature on nurse staffing and the influence on patient outcomes. This study was unique in that data was collected at the unit/shift level, outcomes assessed are considered nurse-sensitive, and statistical techniques accounted for the nested data. Despite these advantages, limitations of the measurement of nursing-related acuity and patient turnover are acknowledged. Well-defined and consistent measures are necessary to enhance interpretability and application across nursing settings.