AIMS AND OBJECTIVES: This study explores the reasons nurses identify missed care and what factors account for this variance in nursing practice. Second, the study seeks to understand if the identified reasons behind missed care interact with one another and form a multidimensional construct. BACKGROUND: This study draws on the results of previous research conducted by Kalisch in developing the MISSCARE research survey tool and now applies it to an Australian context. DESIGN: This study engages a nonexperimental exploratory approach where 16 latent variables are identified and estimated using structural equation modelling to determine the capacity each of these factors has in predicting the reasons for reported missed nursing care. METHODS: Data were obtained from an electronic survey sent to nursing members of the Australian Nursing and Midwifery Federation of South Australia. A self-report, Likert-type instrument was used to capture the strength and direction of consensus derived from a sample of 289 nurses and midwives. RESULTS/ FINDINGS: Eight variables were identified as having direct predictor effects as to why nursing care was being missed, and included shift type, nursing resource allocation, health professional communication, workload intensity, workload predictability, the nurses' satisfaction with their current job and their intention to remain working. Additional indirect effects of other variables explained 34% of the variance of the total scores for why nursing care was reported as being missed. CONCLUSION: Historically, the MISSCARE survey has identified and quantified what types of nursing care is missed. This paper takes this concept further by producing an interactional model identifying the effects different variables have on why nursing care is missed. RELEVANCE TO CLINICAL PRACTICE: These Australian findings not only contribute to other international studies that identify why nursing care is omitted, it provides a framework for why reported episodes of missed care can be predicted and subsequently addressed.
AIMS AND OBJECTIVES: This study explores the reasons nurses identify missed care and what factors account for this variance in nursing practice. Second, the study seeks to understand if the identified reasons behind missed care interact with one another and form a multidimensional construct. BACKGROUND: This study draws on the results of previous research conducted by Kalisch in developing the MISSCARE research survey tool and now applies it to an Australian context. DESIGN: This study engages a nonexperimental exploratory approach where 16 latent variables are identified and estimated using structural equation modelling to determine the capacity each of these factors has in predicting the reasons for reported missed nursing care. METHODS: Data were obtained from an electronic survey sent to nursing members of the Australian Nursing and Midwifery Federation of South Australia. A self-report, Likert-type instrument was used to capture the strength and direction of consensus derived from a sample of 289 nurses and midwives. RESULTS/ FINDINGS: Eight variables were identified as having direct predictor effects as to why nursing care was being missed, and included shift type, nursing resource allocation, health professional communication, workload intensity, workload predictability, the nurses' satisfaction with their current job and their intention to remain working. Additional indirect effects of other variables explained 34% of the variance of the total scores for why nursing care was reported as being missed. CONCLUSION: Historically, the MISSCARE survey has identified and quantified what types of nursing care is missed. This paper takes this concept further by producing an interactional model identifying the effects different variables have on why nursing care is missed. RELEVANCE TO CLINICAL PRACTICE: These Australian findings not only contribute to other international studies that identify why nursing care is omitted, it provides a framework for why reported episodes of missed care can be predicted and subsequently addressed.
Keywords:
Numerical Rating Scale; beliefs; care activities; multivariate; nursing activity; policy; quantitative approaches; registered nurses; research in practice