Impact of Nursing Staff Turnover on Patient Outcomes


Nursing staff turnover is a healthcare nightmare affecting many countries across the globe. The magnitude of this problem varies depending on the skill-mix of those leaving the workforce. As such, the consequences of nursing staff turnover are more pronounced when registered and certified nursing staff leave the job market. For policy implementation, it is critical to evaluate the underlying factors behind the increased rates of nurse turnover, the transmission mechanism, the point of incident and resulting adverse effects. The main aim of this is promote evidence practice by critically analysing existing research on the effects of nurses’ turnover on patient outcome. Therefore, this essay will evaluate the quality of evidence produced by Bae et al. (2010), Halter et al. (2017), Duffield et al. (2011), and North et al. (2013), who have conducted research on the subject of nurses’ turnover and revealed significant evidence on the same various aspects of nurses’ turnover including high cost of healthcare and adverse patient outcomes.


Selection Criteria

The selected studies were obtained through a systematic search and retrieval process. The search process was conducted in four online databases, namely MEDLINE, Google Scholar CINAHL, and EBSCO. Ideally, the researcher selected the online databases due to their abundance with nursing literature material and the convenience that comes with their use. The search process was aided by various key words namely patient outcome, turnover, nursing staff, management, and job satisfaction. Furthermore, the search process was based on established inclusion/exclusion criteria, meant to ensure quality and specificity of retrieved evidence. The following table illustrates the inclusion/exclusion criteria with thir respective rationale:


The search Process

The search process began in CINAHL, where 2050 citations emerged when the keywords were applied to the search engine. When the inclusion/ exclusion criteria was applied to the 2050 articles, none of the articles could fit the criteria, and therefore no journal articles was selected from this database. When the same search terms were used on MEDLINE, 453 journal articles were encountered. On applying the selection criteria to the 453 journal articles, 2 articles met the criteria and were picked for inclusion. When the same search process was conducted on Google Scholar, the researcher identified 677 journal articles, two of which met the inclusion/exclusion criteria and were selected for inclusion. Lastly, when the search process was conducted on EBSCO, 554 journal articles were retrieved, but none f them matched the inclusion/exclusion criteria. Ultimately, the four journal articles were selected from MEDLINE and Google Scholar databases.

Critical appraisal of the Studies

This study relies on the Critical Appraisal Skills Programme (CASP) tool to evaluate and compare the effectiveness of evidence presented in the study by Bae et al. (2010), Halter et al. (2017), Duffield et al. (2011), and North et al. (2013). We critically analyse and compare the strengths and weaknesses of each study to understand the value of their evidence.

Study Focus

Bae et al’s main topic was an evaluation of the impact of nursing turnover on patient outcome. Bae et al’s focus are different from that of Duffield et al (2011) who intended to examine how the nursing environment, staffing and workload affect patient outcome. On the other hand, North et al intended to understand the impact of nurse turnover on the costs, staffing practices and patient outcomes; while Halter et al’s (2010) main focus were the causes and consequences of nursing turnover within the adult care setting. Generally, the studies emphasize the issue of nursing turnover, and how it affects the practise or patient outcome. The studies’ focus is generally important to practice because nurse turnover is a significant issue that determines the availability of nurses to deliver care, and the quality of care the available nurses can deliver (Bae et al. 2010).

Study Background

All the authors have developed a robust argument and background for their respective studies, and why they think they needed to conduct them. First, Bae et al argue that while there has been a long-standing assumption that nurse turnover has a significant impact on the quality of care, there is a paucity of knowledge on the relationship between turnover and quality of care, thus the need to evaluate how each variable relates to the other. Similarly, Duffield et al’s main focus was to develop a strong source of evidence to inform policymaking. They argued that measuring the relationship between nursing workload, staffing, work environment and patient outcomes cannot be based single hospital evidence, thus the need to use a combination of primary and secondary data from a variety of hospitals to establish how the variables relate. On the other hand, North et al argued that considering the eminent shortages in nursing staffs, it is important to evaluate the costs and rates of nursing turnover to develop effective nursing management and to improve quality of the patient outcome. Lastly, Halter et al’s argument for conducting the study is that nurse turnover is a major issue of concern and that considering the widening gap between the nursing supply and demand, there is a need to establish clear evidence on how adult nurse turnover affects the delivery of quality care. Thus, despite the difference in research aim, each study appears to have developed a strong argument and background thesis for their respective studies.

Study Methodology and Approach

Bae et al used secondary data collected qualitatively to achieve their objectives. They relied on a registered nurse and patient data from 268 nursing units within 141 hospitals based on a record to data collected from nurses within six months. The use of qualitative data was appropriate for the research aim because the patient outcome could be measured qualitatively by measuring the number of patient falls, patient satisfaction scores, medication errors and length of patient stay. Contrastingly, Halter et al’s main aim was to establish the determinants of nurses’ turnover using a systematic review of evidence. Their research methodology was appropriate for the research aim because they could gather evidence from other studies on what the determinants and consequences are. According to Bryman & Bell (2015), systematic literature reviews are effective sources for evidence because they synthesize evidence from a variety of evidence from different studies with different research methodologies. As opposed to Halter et al and Bae et al, North et al used a mixture of qualitative and quantitative data from secondary sources to achieve their objectives. Using the secondary data, North et al used descriptive statistics to analyse data and measure the relationship between patient outcomes, costs and staffing relationships. The use of descriptive statistics was a wise choice by North et al because according to Barker (2009), descriptive statistics allows for effective measurement of relationships between variables using measures of central tendencies such as mean, median and mode. Thus, descriptive statistics here could allow for the measurement of the average satisfaction level of patients depending on the cost of treatment they have incurred. Lastly, Duffield et al, whose main aim was to evaluate the effectiveness of the relationship between nursing workload, nursing staffing work environment, relied on secondary qualitative and quantitative data. The use of longitudinal and cross-sectional approaches to research was most appropriate for Duffield et al’s main objectives because they could retrieve relevant quantitative data on nursing staffing, workload, as well as qualitative data on the nurse working environment and patient outcomes. Therefore, from an analysis of the research methodology and approaches used in each of the four studies, it emerges that the research methodologies matched the studies’ respective research aim.

Data Analysis Methods

Given (2008) argues that the validity of research findings does not only rely on the methods of data collection but also data analysis methods used by in the study. For instance, Duffield et al relied on descriptive statistics to analyze the data, and this was appropriate because a majority of the longitudinal data were descriptive. Similarly, North et al applied descriptive statistics to find the mean, and mode of patient satisfaction because the data was generally descriptive. Contrastingly, Halter et al used narrative synthesis as their method of data analysis. According to Houser & Oman (2011), narrative synthesis is an appropriate data analysis method for systematic reviews because the researcher might end up with themes warranting a narrative discussion. Lastly, Bae et al used statistical methods to measure and analyze the relationship between variables (i.e., how nursing turnover impacted on patient outcomes). According to Maxwell (2013), statistical methods such as correlation coefficients are effective tools for evaluating the relationship between variables because they assist in understanding how variables influence each other and the significance of such influence.

Ethical considerations

All the studies made significant ethical considerations. For instance, Bae et al sought institutional approval to collect the secondary data from each of the 141 institutions. Halter et al acknowledged all the authors from which their literature was reviewed, while North et al sought data use permission before conducting a reanalysis of the prospective data they had gathered for the 12 months. Similar data use permission was sought by Duffield et al.

Halter et al. (2017) adequately describe the major causes of nurse turnover, which include individual and interpersonal factors, job-related, and organizational determinants. Duffield et al. (2011) share in this philosophy and identify job satisfaction, work-life balance, workload, and burnout and stress as individual determinants contributing to raising nursing staff turnover. In addition to these factors, Halter et al. (2017) list age, marital status, and sleep disturbance as additional individual factors causing a mass exodus of nurses from their jobs. Based on an extensive synthesis of peer-reviewed research studies, Halter et al. (2017) indicate that older nurses tend to stay while younger nurses aged, averagely, 25 years have higher tendency to leave their current jobs. Similarly, RN nurses with less than five years of experience have higher tendencies to leave compared to their counterparts with more years of experience in practice. Regarding gender and marital status, male and unmarried female nurses are more likely to change jobs. A similar case applies to individuals with higher education attainment. These conclusions were reached after a comparative analysis of several studies that documented these factors.

Concerning psychological experiences, Halter et al. (2017) and Duffield et al. (2011) confirm that scheduling problems, high workload, and stringent management are the leading causes of burnout, high-stress level, lack of commitment to current job, and low job satisfaction, which drive practitioners to leave the current posting. Conversely, North et al. (2013) identify inappropriate staffing practices, such as understaffing and overreliance on temporary workers as the primary cause of high turnover. The interplay of these factors with interpersonal determinants encompassing managerial staffing practices, style, compensation scheme, staff autonomy, social cohesion, and group support make the problem worse. Nonetheless, the authors believe that these factors can be overcome by reforming work culture emphasizing on flexible work schedules, proper delegation of work, increased staffing to reduce the nurse-patient ratio and introduction work policies that encourage work-life balance.

Job-related and organizational factors also play a role in perpetuating nurse turnover. Here, Halter et al. (2017) and Duffield et al. (2011) underlie demanding work content, ambiguity task variation and role, and unpredictable shift patterns and high workload as the leading cause of nursing staff turnover. Necessarily, these factors inspire negative psychological experiences causing high-stress level, burnouts, and job dissatisfaction, which drive nurse to quit or leave their jobs. At the organization level, the work environment was identified as a critical determinant of intentions to leave. Here, the primary causes of high nurse turnover include poor working conditions, such as lack of protective gear and insufficient supporting staff; inadequate financial incentives, and bureaucratic organizational structure. These factors describe the determinants, drivers, or causes of high nurse turnover witnessed across the world.

Of the four articles, only Halter et al. (2017), North et al. (2013), and Duffield et al. (2011) explore the input element of the input-process-outcome (IPO) framework that connects the cause of high turnover, the transmission mechanism and eventually the consequences. However, Halter et al. (2017) is more detailed and covers more items than Duffield et al. (2011) and North et al. (2013), as illustrated above. Consequently, this is a strong area for the three articles and weaknesses for the remaining study, which focused only on the process-outcome part of the model.

On another front, the effects of the increased rate of nurse turnover on patient outcomes manifest in several ways. Bae et al. (2010) describe the IPO framework as the basis through the effects of the high rate of turnover translates to adverse patient outcomes. Here, they identify workgroup behavior or processes and performance effectiveness as the mechanism of transmission of turnover consequences. The former is comprehensibly discussed by Bae et al. (2010), while the latter is also addressed by Duffield et al. (2011). Workgroup processes concern the capacity of the team member to work as a group. In this regard, Bae et al. (2010) postulate that increased nurse turnover impairs workgroup processes making working coordination among team members dysfunctional. The authors attribute this effect to the disruptive impact of the exit of a section of existing workers and entry of new employees who have different work beliefs and value system. Perpetual entry and exit of employees create a clash of work values, a factor that undermines workgroup cohesion, relational coordination and group learning and performance effectiveness. Hence, nurses cannot communicate and coordinate effectively resulting in inefficiencies, which translate to poor delivery of care. Halter et al. (2017) and North et al. (2013) also indicate that performance inefficiencies may arise in situations where the long-term costs of nurse turnover are large enough such that the firm cannot replace outgoing employees. These are the mechanism through which nurse turnover is translated into adverse patient outcomes.

Concerning the model of turnover consequences, Bae et al. (2010) explicitly introduce and discuss the input-process-outcome (IPO) framework, while the other three articles imply the model and interrogate particular elements that defined it. Duffield et al. (2011) comprehensively examine performance effectiveness as the link between high turnover and negative patient outcomes, while Halter et al. (2017) and North et al. (2013) demonstrate high costs associated with increased turnover as the main bottleneck to realizing effectiveness in hospital performance. As such, compared to the other three articles, Bae et al (2010) was more comprehensively in demonstrating the model of turnover consequences with Halter et al. (2017) barely mentioning the elements of this framework.

Given the determinants of labour turnover and the transmission mechanism, Bae et al. (2010), and Duffield et al. (2011), identify acquired hospital infections, longer length of stay, higher rates of hospitalization and readmission, medication errors, and low patient satisfaction as the main adverse effects of high nurse turnover. Insufficient workforce due to high rates of nurse turnover offsets the nurse-patient ratio implying a majority of the patient remain unattended for long. Equally, labour shortages indicate that nurse educators are unavailable to educate patients about hygiene practices within the hospital environment, exposing them to numerous health hazards. This reason accounts for high rates of hospital-acquired infections in facilities where the rate of nurse turnover is high.

Bae et al. (2010) affirm that a well-coordinated workforce is capable of recognizing and addressing potential patient risks; hence, able to apply intervention measures appropriately. The absence of this critical workgroup process puts patients are at risk of falls and malpractice issues such as medication errors. Here, they attribute a lack of coordination to a lack of understanding among the workforce as a result of a clash of work cultures as employee exit and enter the firm. As such, they acclaim that higher retention rate is desirable in the sense that it allows existing workers to evaluate work processes and learn from past mistakes, which new workers may not aware of. This factor explains why North et al. (2013) attribute use of temporary workforce to increased turnover and adverse patient outcomes. Essentially, well-coordinated workgroups are more efficient and capable of delivering higher quality care. For example, improved coordination and communication between nurses and physicians ensure patients receive necessary care, which hastens their recovery period and subsequently reduces the length of stay in hospitals. Thus, the availability, efficacy, continuity, and consistency on the part of the nurses improve patient outcomes and the reverse cause harm leading to adverse patient outcomes.

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Lastly, regarding the consequences of higher turnover, Bae et al. (2010), Duffield et al. (2011), and North et al. (2013) are articulate in explaining the detailed account of associated adverse patient outcomes. Conversely, Halter et al. (2017) expressed patient outcomes in economic terms; hence, it was weak in illustrating the particular patient outcomes as a result of high nurse turnover. However, collectively, the articles provide a basis for advancing research on my chosen topic.

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Analytically, these articles build up a framework for progressing knowledge on the subject centered on the IPO model. For specificity, Halter et al. (2017), North et al. (2013), and Duffield et al. (2011) illustrate the input element of the model, which provides a basis for exploring the causes of high turnover in the healthcare sector. Conversely, Duffield et al. (2011) and Bae et al. (2010) demonstrate the process element, which explains how rates of turnover are translated to adverse patient outcomes. Overall, in the exception of Halter et al. (2017), the articles identify the primary patient outcomes associated with increased turnover. By combining the elements of the IPO model, it is easier for a researcher to develop and study the subject in-depth, adding to the body of knowledge. Lastly, concerning the implication for practice, the study advocates for the restructuring of the work environment and organizational culture focusing on institutional and interpersonal factors, such as leadership style, scheduling, and definition of roles and responsibilities which will, in turn, moderate the effects of individual elements and subsequently reduce nursing staff turnover. Equally, healthcare administrators must maintain data regarding the rate of turnover and costs for decision making when implementing staffing strategies.

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