Why Nurses Are Leaving Veterans Affairs Hospitals?

Abstract

An aging veteran population with a median age of 65, their inferior health status, and the rapidly growing number of women veterans propel veterans affairs (VA) hospitals to provide a wide range of nursing services. However, despite the significant roles of nurses and chronic nurse shortages in VA hospitals, there has been little research on the determinants of nurse turnover in the VA healthcare system. This study analyzed registered nurse turnover rates at a panel of 118 VA hospitals from 2015 through 2017 and found that nurse turnover is significantly influenced by patient mortality, job satisfaction, annual salary level, and preventable hospitalizations. These findings suggest that VA hospitals should maintain proper nurse workloads and implement programs that can improve nurses’ stress level and job satisfaction.

Keywords

nurse veteran health care veterans affairs turnover

Introduction

Nurses play a significant role in providing quality health care to patients such as delivering medical care through nursing processes, coordinating care delivered by physicians and other providers, as well as educating patients and their families (Needleman & Hassmiller, 2009; White & Griffith, 2016). Thus, maintaining adequate nurse staffing levels is a very significant factor in achieving high quality care and preventing adverse outcomes. Previous research has demonstrated the negative consequences of low nurse staffing levels in clinical outcomes and/or hospital management (Aiken, 2002; Eckardt et al., 2014; Needleman et al., 2002; O’Brien-Pallas et al., 2006; Person et al., 2004).

In 2019, the national average nurse turnover rate in the United States was 18.7% (Nursing Solutions Inc., 2020), which generated substantial direct and indirect costs in healthcare organizations. Direct costs of nurse turnover entail hospital advertising and marketing expenses to fill the vacant nurse positions with newly hired nurses (Jones & Gates, 2007). Jones (2008) estimated that per registered nurse (RN) the turnover costs range from US$82,000 to US$88,000, depending on the competency of the newly hired registered nurses (RNs). Nursing Solutions Inc. (2020) estimated that a hospital spends between US$3.7 M and US$6.1 M due to RN turnover and an additional 1% of RN turnover causes US$0.3 M annually per hospital. In addition to the economic costs, high nurse turnover brings about diverse indirect costs such as problems in nurses’ mental health, lower job satisfaction, and higher likelihood of medical errors and adverse events (Lee et al., 2009; O’Brien-Pallas et al., 2006).

The mission of the Veterans Health Administration (VHA), under the Department of Veterans Affairs (VA), is to provide quality health care to veterans in a timely manner. To fulfill the mission, the VHA has the largest integrated healthcare delivery system in the United States, which includes 18 Veterans Integrated Services Networks, 170 VA medical centers, and 1074 outpatient clinics (U.S. Department of Veterans Affairs, 2019a). However, the VHA suffers considerable nurse turnover and resultant nurse shortages. The nurse workforce within the VHA consists of nurse practitioners (NPs), RNs, licensed practical nurses (LPNs), and nursing assistants (NAs). Registered nurses account for 64% of the nurse workforce (Government Accountability Office [GAO], 2015). The average nurse turnover rate within the VHA from FY 2010 through 2014 was 7.6%. The VHA estimated 17,000 vacancies of nurse positions across VA medical centers, 12,100 of which were RN vacancies (GAO, 2015). Compared to nonveterans, veterans are more likely to suffer from physical wounds, post-traumatic stress disorder (PTSD), traumatic brain injury (TBI), and substance use disorder (SUD) (Oh & Berry, 2021). Furthermore, a majority of the veteran population is over the age of 65, which requires more complex health care. Given these distinctive health attributes of the veteran population, nurse shortages caused by high nurse turnover in VA hospitals will likely have significant repercussions on veteran health outcomes. Despite the significant role of nurses in the veteran healthcare system and the chronic shortage of nurses in VA hospitals, there has been little research on the determinants of nurse turnover in the context of the VA healthcare system. To fill the academic gap, this study strives to identify the organizational factors influencing nurse turnover in VA hospitals. We conducted a cross-sectional time series analysis of a panel of 118 VA hospitals from 2015 through 2017. The findings showed that high patient mortality, high workload, low salary level, and high preventable hospitalizations contribute to the high nurse turnover rate in VA hospitals.

Nurse Workforce Within VHA

According to the U.S. Census Bureau (2020), the number of veterans living in the United States in 2018 was about 18 million with a median age of 65. The breakdown by service periods in 2018 was .5 million World War II veterans (median age of 93), 1.3 million Korean War veterans (median age of 86), 6.4 million Vietnam Era veterans (median age of 71), and .3 million Post-9/11 veterans (median age of 37) (U.S. Census Bureau, 2020). The number of women veterans is rapidly growing within the veteran population. The proportion of women veterans increased from 4% in 1980 to 9% in 2018 and is expected to constantly grow to 17% by 2040 (U.S. Census Bureau, 2020).

The frequent exposure to hazardous environments during their service periods gives rise to veterans’ distinctive health issues. Veterans, compared to nonveterans, are more likely to suffer from PTSD, TBI, and SUD (Olenick et al., 2015), which are closely related to a high suicide rate (Jakupcak et al., 2009). Veteran’s overrepresentation in the homeless population in the United States is another problem; veterans account for 9% of the homeless population while sharing 7.3% of the general US population (National Alliance to End Homeless, 2019). Homeless veterans are prone to have severe chronic disease without receiving proper health care (Fargo et al., 2012). In addition, 24.2% (4.3 million) of the veteran population have a service-connected disability, with the largest share of service-connected disability belonging to Post-9/11 veterans (8.1% or 1.5 million) and Gulf War veterans (7.7% or 1.4 million) (U.S. Census Bureau, 2020). Post-9/11 veterans account for the largest percentage of severe disability rating¹ with 70% or higher, suggesting that they are more likely to have a service-connected disability in terms of frequency and severity than any other veterans (U.S. Census Bureau, 2020).

The aging veteran population with a median age of 65, their inferior health status and disability connected to their service, and the rapidly growing number of women veterans require that the VHA provide a wide range of nursing services in order to meet the complex healthcare needs of the veterans. The nursing service spectrum within the VHA includes “patient care, clinical practice, education, research, and administration” (Office of Nursing Services [ONS], 2019). The nurses in the VHA deliver coordinated care across “primary, ambulatory, acute, geriatric, rehabilitation, and extended care settings” (ONS, 2019). In addition, the nurses serve not only in medical, surgical, and psychiatric units but also in organ transplant nursing home and hospice units (ONS, 2019).

The VHA has a direct-hire authority for nurses as well as other medical professionals under Title 38, US Code (Office of Inspector General [OIG], 2019). To provide such a wide range of nursing services, the VHA employs the largest nurse workforce in the United States, consisting of NPs, registered nurses (RNs), licensed practical/vocational nurses (LPNs/LVNs), and nursing assistants (ONS, 2019). Given veterans’ diverse and complex healthcare needs, the nurse skill mix—the composition of each type of nurses (NPs, RNs, LPNs, and NAs) at each unit or hospital—has been very significant in providing quality health care (GAO, 2015). For example, veteran patients in intensive care units (ICUs) need more complex and sophisticated nursing care, and thus, the proportion of RNs in the ICUs is higher than in other units that deliver less complex nursing care (GAO, 2015). In VHA nursing workforces, the RNs also comprise the largest percentage. Of the 100,544 nurses serving within the VA healthcare system, 71,286 were RNs (ONS, 2019). Given the high median age and complex health status of veterans, the high percentage of RNs in the workforce is not surprising.

However, the VHA reported substantial challenges in recruiting and retaining RNs with advanced clinical skill, knowledge, and experience (GAO, 2014). The GAO (2015) demonstrated that although the VHA recruited 51,000 RNs (59% of newly hired nurses) in 2015, there were still 12,100 vacancies for registered nurse positions. The VHA implemented multiple initiatives to improve nurse staffing levels in 2015, which focused on offering additional education and training, and providing financial benefits (GAO, 2015). Despite the Veterans Health Administration’s initiatives, VA medical centers experienced difficulties in recruiting and retaining nurses, including inadequate administrative support, competition with private hospitals, location of medical centers in rural areas, and low employee satisfaction leading to turnovers (GAO, 2015). In 2019, 102 out of 140 VA medical facilities reported a considerable shortage of nurses, and 31 medical centers showed a severe shortage of RNs for inpatient care positions (OIG, 2019). A survey conducted by the OIG showed that the two main reasons for the severe shortage in the nurse workforce are an insufficient number of qualified applicants and a noncompetitive salary for VHA nurses (OIG, 2019).

There has been substantial research on the determinants of nurse turnover (intention) in the private healthcare system (Hayes et al., 2012). The determinants are perception of role conflict and ambiguity (O’Brien-Pallas et al., 2010), perception of empowerment (Hauck et al., 2011; Zurmehly et al., 2009), relationship with managers (Boyle et al., 1999; Magbity et al., 2020; Nei et al., 2015; Taunton et al., 1997), job satisfaction (Beecroft et al., 2008; De Simone et al., 2018; Fasbender et al., 2019; Kim & Lee, 2016; Tourangeau & Cranley, 2006), and stress and burnout (Flinkman et al., 2008; Labrague et al., 2020; Lee & Kim, 2020; Leiter & Maslach, 2009; Meeusen et al., 2011). However, notwithstanding the chronic shortage of nurses, who play significant roles in providing quality care to veterans, there has been little research on the determinants of nurse turnover within the VA healthcare system except for a few reports from the GAO and the VA OIG.

Hypotheses on Nurse Turnover in VA Hospitals

The job demands-resources (JD-R) theory suggests that psychological stress, excessive workload, and work dissatisfaction have significant negative impacts on employees’ attitudes toward their work, commitment to the organization, and performance. The JD-R theory explains that work conditions have two major components: job demands and job resources (Bakker & Demerouti, 2014). Job demands are associated with an employee’s psychological stress and burnout while job resources are related to an employee’s motivation and job engagement (Bakker & Demerouti, 2014). In this chapter, I establish hypotheses on nurse turnover in VA hospitals based on the JD-R theory.

Job Demands, Burnout, and Turnover

Job demands refer to “those physical, social, or organizational aspects of the job that require sustained physical or mental effort and are therefore associated with certain physiological and psychological costs (Demerouti et al., 2001, p. 501).” Examples of job demands include emotionally demanding interactions with clients, conflicts with supervisors and coworkers, and excessive workloads (Bakker & Demerouti, 2014). The JD-R theory assumes that workers under high job demands need to mobilize additional energy and effort to achieve occupational goals and to deter decrease of work performance. Workers can recover from fatigue caused by high job demands by taking sufficient breaks or doing less demanding jobs; otherwise, they are likely to experience burnout (Bakker & Demerouti, 2014).

Nursing is an emotionally and physically demanding job. While providing quality care to patients, nurses experience substantial levels of job stress² derived from caring and interacting with patients, excessive workloads, and conflicts with supervisors and coworkers (Lee & Kim, 2020). Nurses experiencing considerable job stress are more likely to quit their jobs to escape from the stress and resultant burnout (Hayes et al., 2012). One of the significant job stressors is the death of patients under nursing care. It might be unavoidable that nurses working in hospitals are faced with recurrent patient deaths. Numerous studies have demonstrated that nurses who experience patient deaths are more likely to feel substantial emotional distress, grief, fear, and powerlessness (Adwan, 2014; Boerner et al., 2017; Khalaf et al., 2018; Lief et al., 2018; Zheng et al., 2018). Also, a nurse is more likely to feel a greater sense of loss and grief when faced with the death of a patient for whom the nurse provided care over a long period of time (Khalaf et al., 2018). After experiencing a patient death, nurses have to activate additional effort and energy to overcome the inevitable emotional reactions and to provide the same quality of care to other patients as they did before experiencing the patient death. Without enough recovery from the grief, the nurse might experience burnout. Previous research has not probed the direct relationship between patient death and nurse turnover. However, nurses’ grief and emotional responses to patient death have a significant correlation with burnout and job dissatisfaction (Adwan, 2014), which suggests that exposure to patient death can influence nurse turnover decisions.

Veterans have inferior health status due to their exposure to harmful environments during their service and their median age is 65 years, which requires VA nurses to provide complex health care. Despite veterans’ inferior health status and higher median age, the overall in-hospital mortality rate in VA hospitals is 5%, which is lower than the rate in private hospitals (Rosenthal et al., 2003). Compared to private hospitals, the majority of patient deaths in VA hospitals happen after hospitalization. While only 8% of patient deaths occur within 2 days after hospitalizations, 37% of patient deaths occur 22 days after hospitalization (Rosenthal et al., 2003). This suggests that VA nurses likely experience more significant grief after the death of a patient who was nursed over a long period of time. A nurse’s grief that is caused by exposure to recurrent patient deaths can lead to emotional exhaustion, burnout, and resultant turnover.

Hypothesis 1 (H1): High patient mortality increases nurse turnover rate in VA hospitals.

In addition to emotional demands, a high workload can lead to burnout in nurses (Aiken, 2002; Greenglass et al., 2001), which can result in greater nurse turnover intention (Hayes et al., 2012; Leiter & Maslach, 2009). For example, Aiken (2002) demonstrated that an increase of patient-to-nurse ratio resulted in an increase of nurse burnout and job dissatisfaction. Also, Tourangeau et al. (2010) studied 78 Canadian nurses and found that these nurses were more likely to leave their hospitals when there were insufficient levels of nursing staff and inadequate resources to provide quality care. Similarly, Zeytinoglu et al. (2007) examined 1396 Canadian nurses hired in three teaching hospitals and found that excessive workload and low job satisfaction led to higher nurse turnover intention.

There has been little research on whether nurses in VA hospitals work under an excessive workload compared to nurses in private hospitals. However, the VA hospital scandal³ in 2014 suggested that excessive workloads in VA hospitals might cause long wait times for veteran patients. In the aftermath of the scandal, Congress enacted the Veterans Access, Choice, and Accountability Act of 2014—often referred to as the Veterans Choice Act—on August 7, 2014. Under the Act, the VA initiated the Veterans Choice Program (VCP) that allows a veteran to use non-VA hospitals if he/she lives 40 miles or more from a VA healthcare facility or has to wait more than 30 days to receive needed health care⁴ (Panangala, 2018). Under the Veterans Choice Program, eligible veterans were able to choose to receive medical care from community care providers (Veterans Choice Program providers) that obtain VA-required credentials or licenses (Panangala, 2018).

The GAO (2008) reported that RNs working in VA hospitals were most dissatisfied with too many time-consuming, non-nursing tasks and a limited availability of flexible work schedules to maintain balance between nursing work and their personal life. Also, nursing officials at VA hospitals reported that reliance on RN overtime due to an inadequate RN staffing level can adversely affect RN job satisfaction and retention (GAO, 2008). Similarly, Helfrich et al. (2017) investigated the effect of workload on the possibility of burnout among VA primary care team members.⁵ By conducting a cross-sectional regression analysis of 4610 surveyed primary care personnel, they found that a high workload in terms of patient panel capacity in primary care has a significant effect on the odds of burnout (Helfrich et al., 2017), which can lead to turnover decisions (Hayes et al., 2012; Leiter & Maslach, 2009).

Hypothesis 2 (H2): High workload increases nurse turnover rate in VA hospitals.

Job Resources and Turnover

In the JD-R theory, job resources are defined as “those physical, psychological, social, or organizational aspects of the jobs that (a) are functional in achieving work goals, (b) reduce job demands and the associated physiological and psychological costs, or (c) stimulate personal growth, learning, and development (Bakker & Demerouti, 2014, p. 9).” While high job demand is a strong predictor of employee exhaustion and burnout, job resources have a positive impact on employee motivation and work engagement (Bakker & Demerouti, 2014). Adequate job resources also mitigate the negative effects of high job demands on employee burnout (Bakker & Demerouti, 2007; Bakker et al., 2005), suggesting a positive effect of job resources on job satisfaction and lowering turnover intention. For example, Bakker et al. (2003), using the JD-R theory, analyzed 477 employees working in the call center of a Dutch telecom company and found that only job resources had a positive effect on employees’ commitment to the company, which led to lower turnover intention.

Salary is one of the key job resources that can compensate for high job demands and their impact on employee turnover intention. However, inadequate salary level can exacerbate employees’ job dissatisfaction and resultant turnover intention. The effort-reward imbalance (ERI) model explains how unsatisfactory reward can adversely influence an employee’s stress level and health outcomes (Siegrist, 1996). Siegrist (1996) demonstrated that, compared to high effort spent at the workplace, low reward level (in terms of salary, esteem, job security, and promotion) causes a broken reciprocal relationship between effort and reward, which leads to the employee’s emotional distress and adverse health outcomes.

Given the highly demanding nursing jobs at VA hospitals, unsatisfactory salary level may cause significant job dissatisfaction for nurses, which might increase their turnover intentions. Derycke et al., (2010) investigated the impact of the ERI on nurse turnover intention by conducting a multivariate logistic regression analysis of 1531 surveyed Belgian nurses. They found that nurses who perceived a failed reciprocity between reward and effort (i.e., high effort but low reward) are more likely to have high turnover intention. Numerous previous research studies explained the negative effect of low salary level on nurse turnover intention (Lee & Kim, 2008; Lu et al., 2002; McHugh & Ma, 2014; Strachota et al., 2003; Tzeng, 2002; Yin & Yang, 2002). For example, in a meta-analytic study on the determinants of nurse turnover intention in Taiwanese hospitals, Yin and Yang (2002) found that satisfaction with salary level had a negative correlation with nurse turnover intention. Similarly, by conducting a cross-sectional logistic regression analysis, McHugh and Ma (2014) investigated how wage, work environment, and nurse staffing level influence nurse outcomes in terms of job satisfaction, burnout, and turnover intention. The authors discovered that high nurse wage has a positive effect on reducing nurse turnover intention and job dissatisfaction but an insignificant effect on mitigating nurse burnout (McHugh & Ma, 2014). In addition, although there has been little research on the effect of low salary level on nurse turnover in VA hospitals, several VA hospital managers reported that low nurse salary level, compared to other competing private hospitals in the area, poses a significant difficulty in recruiting and retaining competent nurses (GAO, 2015).

Hypothesis 3 (H3): Low nurse salary level increases nurse turnover rate in VA hospitals.

Sample, Measurements, and Method

Sample

In this article, the unit of analysis is a VA hospital in the United States from 2015 through 2017. We collected data from three sources. We used the VA Strategic Analytics for Improvement and Learning (SAIL) database to gather the following data: registered nurse (RN) turnover rate, the acute care 30-day standardized mortality ratio (SMR30), and ambulatory care sensitive condition (ACSC) hospitalizations rate. From the American Hospital Association (AHA) annual survey, we gathered the following data: hospital teaching status, number of beds, hospital annual operating expenditures, number of full-time equivalent (FTE) RNs, and three representative VA hospitals’ outputs (inpatient days, outpatient visits, and number of surgical procedures). Finally, we obtained data on the average annual salary level of RNs at VA hospitals from the VHA through an information request under the Freedom of Information Act (FOIA). We integrated the data into panel data from 2015 through 2017, which consisted of 118 VA hospitals each year.⁶

Measurements and Method

Dependent variable

In this study, we are more interested in the RN turnover rate than other nurse groups in VA hospitals because 70.9% (71,286) of nurses working in the VHA are RNs (ONS, 2019) and most VA hospitals suffer from a shortage of RNs to deliver quality health care (GAO, 2015). Registered nurse turnover rate was measured as a loss of RNs due to voluntary resignations, transfers out of the hospitals and terminations, excluding retirement (U.S. Department of Veterans Affairs, 2019b).

Independent variables

To test the three hypotheses mentioned in the previous section, we adopted three independent variables: the acute care 30-day standardized mortality ratio (SMR30) (H1), nurse workload (H2), and nurse annual salary level (H3). The SMR30 was measured as a ratio of the actual number of patients, who died within 30 days of admission to acute care, to the sum of the expected deaths of all acute care patients at the end of 30 days (U.S. Department of Veterans Affairs, 2019b). This variable will explain the effect of patient death on RN turnover rate. To examine the effect of workload, we used three typical outputs of VA hospitals: inpatient days, outpatient visits, and number of surgical procedures (Harrison & Meyer, 2014; Harrison & Ogniewski, 2005).

Control variables

We controlled for ambulatory sensitive care condition (ACSC) hospitalizations. Ambulatory sensitive care condition hospitalizations can be prevented if the patient receives proper primary care in a timely manner (O’Neil et al., 2010). A high ACSC hospitalization rate means low accessibility as well as the ineffectiveness of primary care in the region (Wen et al., 2019). Veterans living in a region with a high ACSC hospitalization rate are less likely to receive timely primary care and thus more likely to be admitted to a VA hospital due to severe health conditions, which might affect nurse workload and stress. The ACSC hospitalization rate at the hospital level was measured as the ratio of the actual number of the ACSC hospitalization rate to the expected number of the ACSC hospitalizations multiplied by the VA nationwide rate per 1000 patients (U.S. Department of Veterans Affairs, 2019b). We also controlled for other organizational factors such as hospital teaching status, number of beds, operating expenditures, and number of full-time equivalent (FTE) RNs. Hospital teaching status was measured as a binary variable: 1 if a VA hospital has a membership in the Council of Teaching Hospitals and Health Systems,⁷ 0 otherwise. In addition, to control for year effect, we included binary year variables: 1 if year is 2016 and 2017, respectively, 0 otherwise. Table 1 presents descriptive statistics of the variables by years.

Table 1.

Descriptive Statistics of Variables.

Variables	2015 (N = 118) Mean (SD)	2016 (N = 118) Mean (SD)	2017 (N = 118) Mean (SD)
Dependent variable
RNs turnover rate (%)	6.83 (2.55)	6.28 (2.48)	4.78 (1.99)
Independent variables
30-day standardized mortality ratio (SMR30)	.949 (.183)	1.02 (.174)	.941(.221)
Inpatient days (1000)	65.341 (55.49)	65.95 (63.60)	67.42 (69.05)
Outpatient visits (1000)	637.25 (355.54)	648.50 (440.94)	640.76 (530.25)
No. of surgical procedures	4202 (2281)	3668 (2089)	3985 (2968)
RN annual salary (US$10,000)	7.91 (1.00)	8.09 (1.03)	8.29 (1.08)
Control variables
ACSC hospitalizations (per 1000 patients)	25.48 (4.98)	25.86 (4.48)	25.02 (4.11)
COTH membership	.63 (.486)	.64 (.480)	.64 (.480)
No. of beds	267 (229)	261 (222)	258 (219)
Operating expenditure (millions)	182 (133.6)	164 (71.2)	171 (78.4)
No. of full-time equivalent RNs	453 (266)	516 (350)	490 (385)

Statistical analysis

We integrated all variables into the following regression equations: “α” indicates intercept of the regression, and “ $β_{i}$ ” indicates coefficients of the independent or control variables

\begin{array}{l} Registred Nurses (RNs) turnover rate = α + β_{1} SMR 30 + β_{2} Inpatient days \\ + β_{3} Outpatient days + β_{4} Surgeries + β_{5} RN Salary + β_{6} ACSC \\ + β_{7} COTH + β_{8} Beds + β_{9} Operating expenditure + β_{10} number of RNs \\ + β_{11} Year 2016 + β_{12} Year 2017 + u \end{array}

Considering the 3-year panel data from 2015 through 2017, we used a cross-sectional time series regression of Stata version 14. We conducted regression assumption diagnostic tests to examine whether the models satisfy non-perfect collinearity, zero-conditional mean, and homoskedasticity (Wooldridge, 2016). Also, we conducted the Wooldridge test for autocorrelation in the panel data and the Hausman test to determine fixed or random effect (Wooldridge, 2016). The model had heteroscedasticity and a fixed effect without an autocorrelation problem. Thus, we applied a fixed effect and robust error to the model.

Findings

We conducted a cross-sectional time series regression analysis to examine the three hypotheses on nurse turnover in VA hospitals. The regression model was statistically significant based on the F-test. Table 2 presents the result of the regression analysis. All independent variables—the acute care 30-day standardized mortality ratio (SMR30), workload (inpatient days, outpatient visits, and surgical procedures), and RN annual salary—were statistically significant.

Table 2.

Results of Cross-Sectional Time Series Regression Analysis.

Variables	Coefficient	Robust SE
30-day standardized mortality ratio (SMR30)	1.111*	.632
Inpatient days (1000)	.015**	.007
Outpatient visits (1000)	.001*	.0007
No. of surgical procedures	−.0002***	.00006
RN annual salary (US$10,000)	−2.352***	.631
ACSC hospitalizations rate (per 1000 patients)	.090**	.043
COTH membership	−.679	.826
No. of beds	−.011***	.002
Operating expenditure (millions)	.006***	.002
No. of full-time equivalent RNs	−.0003	.001
Year 2016	−.314	.295
Year 2017	−1.176***	.343
Constant	23.250***	5.060
Observations	354
Model significance	F(8, 119) = 14.80***
$R^{2}$	Within = .3594, between = .0036, overall = .0278

*p < .10, **p < .05, ***p < .01.

First, a VA hospital with high SMR30 was more likely to suffer from high RN turnover: 0.1 increase in the SMR30 led to, on average, 0.11% increase in the RN turnover rate at the hospital level. This meant that a nurse who is exposed to recurrent patient deaths is more likely to leave the VA hospital to escape from distress. This result supported Hypothesis 1, positing a negative effect of patient death on nurse turnover. A nurse’s emotional responses to patient death include fear, grief, and burnout (Muliira & Muliira, 2016), which might negatively influence the nurse’s job satisfaction and turnover intention (Adwan, 2014). This result implied that the VHA should create and implement a policy to help nurses overcome their grief and stress caused by patient death and continuously provide quality care to veteran patients.

Second, the effect of nurse workload on nurse turnover in VA hospitals was mixed. While an increase in inpatient days and outpatient visits led to an increase in the nurse turnover rate in VA hospitals, an increase of the number of surgical procedures resulted in a decrease in the nurse turnover rate. This result partially supported Hypothesis 2, assuming a negative effect of high workload on nurse turnover. Numerous previous studies demonstrated a negative effect of high workload on nurse burnout and resultant turnover intention (Aiken, 2002; Greenglass et al., 2001; Hayes et al., 2012; Leiter & Maslach, 2009). In addition, the Government Accountability Office (2008) showed that high RN overtime can increase their turnover intention. Helfrich et al. (2017) demonstrated that patient overcapacity at VA primary care can lead to an increase in the possibility of employee’s burnout. Thus, the result of the negative effect of inpatient days and outpatient visits was consistent with the previous research on the effect of nurse workload on nurse turnover.

The positive effect of the number of surgical procedures on reducing nurse turnover was not congruent with the previous research. This result suggests that surgical procedures may involve more than ordinary workloads or duties. Through participations in surgical procedures, nurses might gain professional surgical knowledge and a feeling of professional growth, which can lead to high job satisfaction. Given that the VHA is the leading medical training institution in the United States (U.S. Department of Veterans Affairs, 2018), nurses in VA hospitals likely gain substantial professional tacit knowledge and professional growth by participating in surgical procedures. Thus, the feeling of exhaustion caused by participation in surgical procedures likely has a positive correlation with job satisfaction (Serafin et al., 2019). Similarly, Jackson (2005) explained that nurses working at surgical wards feel high job satisfaction when they feel fulfillment and participate in team work. The nurses, who gain professional knowledge and a feeling of professional growth and self-fulfillment through participating in surgical procedures, likely have high job satisfaction and low turnover intention.

Third, the result showed that nurse salary level is a strong predictor of RN turnover rate in VA hospitals. An increase of US$10,000 in the nurse annual salary level led to, on average, a decrease of 2.35% in the turnover rate. Thus, Hypothesis 3 is supported by this result. The significant effect of the annual salary level supported VA hospital managers' argument that inadequate nurse salary level, compared to competitive private hospitals in the area, imposes a substantial challenge to recruiting and retaining competent nurses (GAO, 2015). Given the high median age of veteran patients and their inferior health status compared to nonveterans (Oh & Berry, 2021), nursing in VA hospitals is a very physically and emotionally demanding job. Therefore, unsatisfactory salary level might have exacerbated the imbalance of effort and reward (Siegrist, 1996), which likely reduced nurse job satisfaction and led nurses to leave the VA hospitals in search of a better work environment (Derycke et al., 2010).

Finally, another interesting result was the positive association between ACSC hospitalizations and RN turnover rate in VA hospitals. VA hospitals with high ACSC hospitalization rates were prone to have a high RN turnover rate. A high ACSC hospitalization rate indicates low accessibility and low effectiveness of primary care in a region. Thus, veterans living in a region with high ACSC hospitalizations are likely to be admitted to VA hospitals in poor health conditions. In addition, given that low socioeconomic status (SES) has a negative effect on a patient’s access to primary care (Shi & Singh, 2017), high ACSC hospitalization rates suggest that many low SES veterans are living in the region. Veterans with low SES are more likely to rely on VA hospitals to receive needed health care (Nelson et al., 2007). Thus, VA hospitals with high ACSC hospitalizations are more likely to treat a large number of veteran patients with poor health conditions, which in turn increases nurse workload and turnover intention.

Conclusion and Implications

While there have been numerous studies on the determinants of nurse turnover and the repercussions of high nurse turnover in private hospitals (Hayes et al., 2012), previous research paid little attention to nurse turnover issues in VA hospitals. Given veterans’ inferior health status due to frequent exposure to hostile environments and their high median age of 65, veterans have high demands for quality health care. The VHA has the largest integrated healthcare system in the United States to meet veterans’ needs for health care, but many VA hospitals suffer high nurse turnover rates and resultant nurse shortages (GAO, 2015). To alleviate the nurse shortage problem in VA hospitals, this study investigated the determinants of RN turnover in VA hospitals. The authors analyzed a panel of 118 VA hospitals from 2015 to 2017 and discovered that patient mortality, nurse workload, nurse salary level, and ACSC hospitalization rate have a significant effect on the RN turnover rate in VA hospitals. The findings of this study suggest implications for policy makers in the VHA and the VA hospitals.

First, policy makers in the VHA and managers in VA hospitals need to recognize the significant impact of patient deaths on nurses’ job stress and their turnover intention. After recurrent patient deaths, nurses have to activate additional energy and skills to overcome emotional fatigue and grief. Otherwise, they can experience burnout and job dissatisfaction, leading to turnover. Some nurses might overcome the stress by using personal resources such as sharing their emotional responses with peer nurses, but this may not be adequate for other nurses. The leadership in the VHA and the VA hospitals should assess the impact of patient loss on the stress level of nurses and develop intervention programs to help nurses overcome patient loss so that they may provide quality care to other patients.

Second, VA hospitals should assess their current capacity for providing health care and determine a proper nurse workload. Numerous previous research studies demonstrated that high workload has a negative effect on nurse job stress, burnout, and turnover intention (Aiken, 2002; Greenglass et al., 2001; Hayes et al., 2012; Leiter & Maslach, 2009). Given the significant role of nurses in delivering quality health care to veteran patients, high nurse workload and the resultant turnovers are a very important issue to be addressed. In addition, given that VA hospitals with high ACSC hospitalizations are more likely to treat veteran patients with severe health conditions, the VHA should increase nurse staffing levels at VA hospitals to maintain proper workloads per nurse and to provide quality care to the patients.

Third, leadership in the VHA and the Department of Veterans Affairs must understand the motivational and job satisfaction factors influencing nurse workforces and implement programs to improve their job satisfaction. Given the high competition with private hospitals to employ competent nurses (GAO, 2015), the VHA could raise nurse salaries and benefits to the level of private hospitals. In addition, the VHA could implement educational programs to provide nurses with opportunities for professional growth. Also, managers in the VA hospitals might provide more flexible work schedules so that nurses can maintain a balance between their professional and personal lives.

This study has a few limitations, however. Due to the limitation of secondary data, the authors did not consider the effects of personal attributes on nurse turnover. For example, Pitts et al. (2011) demonstrated that federal employees’ tenures, along with job satisfaction, are strong predictors of turnover intention. In addition, this study did not consider the impact of competition between VA hospitals and private hospitals when hiring nurses, although officials in VA hospitals reported that one of the greatest challenges in employing and retaining nurses is the high competition. Thus, we suggest that future research on the determinants of nurse turnover in VA hospitals include these points in their analysis. Notwithstanding these limitations, this study contributes to the current literature on nurse turnover. This research is not only the first to examine determinants of nurse turnover in VA hospitals but also the first to shed light on the effects of new variables that previous research did not consider—patient death and ACSC hospitalizations. We hope this research will be an important cornerstone for future research on VA nurse turnover.

Footnotes

Acknowledgements

We thank anonymous reviewers for the thoughtful and constructive comments.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Dongjin Oh

Notes

Author Biographies

Dongjin Oh is a major in the Republic of Korea Army. He obtained his PhD in public administration and policy from Florida State University in 2020. He is currently teaching at Korea National Defense University as an assistant professor. His research interest includes veteran policy, military welfare policy, public health policy, and human resource management.

Keon-Hyung Lee is Arnold L. and Priscilla Moss Greenfield Endowed Professor of Public Administration and Policy and Director of Askew School of Public Administration and Policy at Florida State University. His fields of specialization are healthcare management and healthcare finance.

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