Abstract
Background:
It is unknown whether the stress of the COVID-19 pandemic, which had a particular impact on inpatient and long-term care (LTC) nurses, had an effect on nurses’ choice of employment settings.
Objective:
Determine whether the COVID-19 pandemic contributed to changes in nurses’ choice of employment setting.
Methods:
This study used data from the 2018 and 2022 National Sample Survey of Registered Nurses to conduct a difference-in-difference analysis. We constructed a state-level measure of COVID-19 caseload, defined as COVID-19 cases per hospital bed; High versus Low COVID-19 states were defined as those above versus below the median, respectively. Logistic regression models were used to estimate the effect of exposure to High COVID-19 caseload (versus Low) and time (2022 versus 2018) on nurse employment choices across inpatient, LTC, outpatient, versus non-clinical settings.
Results:
From 2018 to 2022, the size of the US nursing workforce grew from 3.27 to 3.57 million nurses; however, RN FTEs increased in outpatient settings and decreased in all other settings. In adjusted analyses, nurses were less likely to work in LTC settings in 2022 than 2018; yet, those exposed to High COVID-19 caseloads were 0.9% (95% CI: 0.3, 1.5) more likely to work in LTC than those exposed to Low COVID-19 caseloads. Differences between High versus Low COVID-19 caseload exposure were not statistically significant for the likelihood of working in inpatient, outpatient, and non-clinical settings.
Conclusions:
Our findings suggest that exposure to High COVID-19 caseload was not associated with changes in nurses’ employment settings.
Keywords: Nurses, health workforce, workplace, COVID-19
Introduction
The COVID-19 pandemic caused unprecedented stress to US nurses, thereby amplifying existing concerns about nurses leaving the workforce and an impending national nurse shortage. Compounding this concern is the expected increase in healthcare demand due to the aging population and the needs associated with the rising prevalence of chronic conditions.1 Previous studies have attributed nurse shortages to workplace challenges,2,3 evolving advanced practice roles (e.g., growth in nurse practitioners that favor outpatient settings),4 and clinician burnout.5,6 While nurses leaving the workforce as a result of the pandemic has been examined,7 considerably less is known about how the pandemic may have potentially contributed to changes across the employment settings where nurses work (e.g., inpatient, outpatient settings etc.). Specifically, the impact of the pandemic on a nurse’s choice of employment setting has not been examined directly.
National workforce analyses indicate that, despite a sharp decline in nurse employment during the early phases of the pandemic,8 the nursing workforce has recovered to pre-pandemic levels.9 However, there is some evidence that most of this post-pandemic growth of the US nursing workforce occurred in non-inpatient settings.9 Although the factors that explain changes in employment setting are complex, the pandemic may have affected how nurses choose an employment setting. For instance, compared to pre-pandemic times, nurses entering the workforce may differ in how they choose an employment setting, and existing nurses may choose to leave inpatient and long-term care (LTC) settings, settings that experienced the greatest strain during the pandemic, in favor of outpatient settings. For nurses, the choice of employment setting has been shown to be related to individual (e.g., gender,10 caregiving,11 age,12,13) and organizational (e.g., stressful work environments,14 insufficient staffing, and workplace abuse12) factors. Yet, the experience of caring for high volumes of acutely ill COVID-19 patients may have influenced this decision.
Understanding whether the pandemic affected how nurses choose an employment setting would advance our knowledge of the impact of a widespread crisis and inform subsequent health workforce policy planning. Therefore, the objective of this study was to determine the degree to which the COVID-19 pandemic affected registered nurses’ (RNs) employment choices across inpatient, LTC, outpatient, and non-clinical settings using a quasi-experimental study design.
Methods
We used data from the 2018 and 2022 National Sample Survey of Registered Nurses (NSSRN) to examine whether the COVID-19 pandemic affected the choice of employment settings (inpatient, LTC, outpatient, and non-clinical) by registered nurses. To do so, we leveraged the variation in COVID-19 spread across US states to estimate the effects of higher stress caused by the pandemic relative to regional healthcare capacity. Specifically, data from the COVID-19 Reported Patient Impact and Hospital Capacity by Facility dataset15 was used to estimate state-level COVID-19 cases per hospital bed. Because this study used publicly available data, it was determined to be exempt from review by the [redacted] Institutional Review Board.
Data Source & Study Population
The NSSRN is the largest, long-standing source of data on the US nursing workforce.16 The final analytical sample consisted of 99,507 RN respondents, of which 50,273 completed the survey in 2018 (April to October 2018) and 49,234 in 2022 (December 2022 to April 2023). The NSSRN response rates were 49% in 2018 and 44% in 2022. Respondents were included in this study if they were employed in either survey. Eighty-seven percent of NSSRN respondents were employed in nursing in 2018, and 84 percent of NSSRN respondents were employed in nursing in 2022. The survey utilizes complex survey design methods based on the probability of selection; therefore, analyses represent national estimates. NSSRN also provides weights to generate state-level nursing workforce estimates.
Identification of Employment Setting (dependent variable)
Self-reported ‘primary’ employment setting categorized as inpatient, LTC, outpatient, and non-clinical was our dependent variable.8,9 The NSSRN asks nurses if they were employed on a reference date, which was December 31 of the year preceding the survey (2017 and 2021). Among nurses employed on the reference date, respondents were then asked to describe their employment setting by choosing from several different types of inpatient, LTC, outpatient, or non-clinical employment settings. Employment settings were recategorized by the NSSRN in 2022, so settings were recoded to ensure consistency between the 2018 and 2022 surveys (Supplemental Table 1).
As secondary endpoints, we also examined reasons for leaving nursing by setting. NSSRN respondents report whether they left the nursing position they held on the corresponding reference date. Of the nurses who reported leaving their position, the NSSRN inquires about the reason(s) for leaving the position, such as burnout, career change, inadequate staffing, and retirement (for a full list of reasons, see Supplemental Table 2). In descriptive analyses, we examined the reasons for leaving positions in inpatient, LTC, outpatient, and non-clinical settings.
State-Level Measure of COVID-19 Caseload (independent variable)
To estimate the regional severity of the COVID-19 pandemic, we constructed a state-level measure of COVID-19 caseload. In August 2020, compliance with COVID-19 data reporting became a requirement for Medicare and Medicaid-funded hospitals.17 We used the COVID-19 Reported Patient Impact and Hospital Capacity by Facility dataset15 from the Department of Health and Human Services to gather information on daily COVID-19 admissions by state. This measure was chosen because of a higher level of reporting consistency across states, as it was connected to reimbursement, than public health COVID-19 reporting, which was more discretionary across the country.17 Daily data were aggregated from October 1, 2020 through September 30, 2021 to generate an annual count of COVID-19 admissions for each state. This time frame was identified as having a large number of COVID-19-related admissions based on data from the Centers for Disease Control and Prevention (CDC) due to the circulation of Alpha and Delta COVID-19 variants in the US.18–20
To account for regional healthcare capacity, we used the total number of hospital beds for the denominator. We gathered information on hospital beds for each state from the COVID-19 Reported Patient Impact and Hospital Capacity by Facility.15 Therefore, our measure of state-level COVID-19 caseload was expressed as the number of COVID-19 cases per hospital bed. We operationally defined High COVID-19 caseload states as those above the median of COVID-19 cases per bed and those below the median as Low COVID-19 caseload states.
Covariates
Previous research suggests that sociodemographic factors and professional characteristics are associated with employment setting. Therefore, we collected sociodemographic characteristics from the NSSRN, including age,7,21 sex,7,10 race/ethnicity7,22 (Non-Hispanic White, Non-Hispanic Black, Hispanic, versus other), marital status (Married, Divorced/Separated/Widowed, or Never Married), presence of dependents11 younger than 18, and household income. Age in years was categorized as < 30, 30 to 39, 40 to 49, 50 to 59, 60 to 64, and ≥ 65. Household income was categorized as less than $50,000, $50,000-$100,000, $100,000-$150,000, and greater than $150,000. We also collected professional characteristics, including the highest level of nursing education7 (Diploma or Associate’s degree, Bachelor’s degree, or Graduate degree), scheduled full-time equivalents (FTE, categorized as less than 0.6, 0.6–1.0, and greater than 1.0), and whether the participant was a travel nurse.23 Because not all nurses work 40 hours per week, we calculated RN FTEs to improve our workforce estimates, overall and by employment setting. We calculated RN FTEs by dividing each nurse’s scheduled weekly hours by 40.
Statistical Analyses
Univariate statistical tests were used to determine whether the RN characteristics varied across employment settings and time; chi-squared tests to compare proportions and two-sample t-tests to compare means. We compared the percentage of RNs working in each employment setting in 2018 versus 2022 overall and by state. To estimate overall changes to the RN workforce, we also calculated RN FTEs in each employment setting and compared 2018 and 2022.
Logistic regression models were used to estimate the association between exposure to High COVID-19 (versus Low) and time (2022 versus 2018) on the likelihood of working in inpatient, LTC, outpatient, and non-clinical employment settings. These models included an interaction between time (2018 versus 2022) and COVID-19 caseload (High versus Low), state fixed effects, and age category, sex, race/ethnicity, marital status, caregiver status, highest nursing education, household income, and travel nursing status. For logistic models, average marginal effects were calculated, enabling interpretation of difference-in-differences estimates as the change in the probability of an RN working in a given employment setting in 2022 (compared to 2018) in states with Low versus High COVID-19 caseload.
Complex survey design methods were used for analyses except for the statistical models due to NSSRN methodologic changes across survey years. The NSSRN used jackknife methods in 2018 and successive differences replication in 2022. Missing data were assumed to be missing completely at random, and all analyses were based on complete case analysis. Critical alpha level was set at 0.05 (two-sided) and all analyses were conducted using Stata Statistical Software, version 18 (College Station, TX).
Sensitivity Analyses
We conducted several sensitivity analyses to test the reliability of our estimates. First, we examined the association between COVID-19 caseload and employment settings by restricting to only those states with the highest (75th percentile or higher) and lowest (25th percentile or lower) COVID-19 caseload. Next, to determine whether using RN FTEs as our endpoint (rather than simple frequencies) affected our findings, we used linear regression to examine the association between state-level COVID-19 caseload and RN FTE in each employment setting. Finally, we tested our decision for the time period of COVID-19 by using a different time frame (i.e., January 1, 2021 to December 31, 2021).
Results
From 2018 to 2022, the estimated size of the US nursing workforce grew from 3.27 to 3.57 million nurses; however, RN FTEs increased in outpatient settings (from 32.7% to 34.9%) and decreased in all other settings (P < 0.001, Figure 1, Supplemental Figure 1).
Figure 1. US Registered Nurse Workforce Full-Time Equivalents, Percentage by Employment Setting in 2018 versus 2022.
All analyses weighted to represent the US registered nurse workforce.
Characteristics of RNs by Employment Setting
In 2022, nurses were younger in inpatient settings compared to all other settings, P < 0.001 (Table 1). In all settings, most nurses identified themselves as White, female, and married (Table 1). However, across inpatient, LTC, and outpatient settings, more nurses were male in 2022 compared to 2018 (P < 0.001, Table 1 and Supplemental Tables 3-7). A higher percentage of nurses reported being travel nurses in 2022 compared to 2018, particularly in inpatient settings (P < 0.001, Table 1 and Supplemental Tables 3-7). As compared to all other settings in 2022, a higher percentage of LTC nurses were Black or Asian, had an associate’s degree or diploma, and had an annual family income of less than $100,000 (Table 1).
TABLE 1.
Characteristics of the National Sample Survey of Registered Nurses in 2022 by Employment Setting
| Employment Setting |
P a | ||||
|---|---|---|---|---|---|
| Inpatient | LTC | Outpatient | Non-Clinical | ||
|
| |||||
| Estimated Total in US (n) | 1,732,844 | 232,813 | 1,204,024 | 299,873 | |
| Sociodemographic Characteristics | |||||
| Mean age in years (SE) | 42.77 (0.14) | 49.51 (0.52) | 48.04 (0.21) | 51.10 (0.39) | < 0.0001 |
| Age category, n (%) | < 0.0001 | ||||
| Less than 30 | 252,626 (14.6) | 13,430 (5.8) | 60,156 (5.0) | 6,138 (2.1) | |
| 30 to 39 | 551,253 (31.8) | 43,485 (18.7) | 293,589 (24.4) | 54,376 (18.1) | |
| 40 to 49 | 406,001 (23.4) | 53,120 (22.8) | 308,976 (25.7) | 75,558 (25.2) | |
| 50 to 59 | 321,971 (18.6) | 69,605 (29.9) | 294,711 (24.5) | 84,684 (28.2) | |
| 60 to 64 | 115,465 (6.7) | 27,405 (11.8) | 123,317 (10.2) | 33,701 (11.2) | |
| 65 and greater | 85,527 (4.9) | 25,768 (11.1) | 123,276 (10.2) | 45,416 (15.2) | |
| Sex, n (%) | < 0.0001 | ||||
| Male | 265,169 (15.3) | 40,157 (17.3) | 119,298 (9.9) | 19,264 (6.4) | |
| Female | 1,467,675 (84.7) | 192,656 (82.8) | 1,084,727 (90.1) | 280,609 (93.6) | |
| Race/Ethnicity, n (%) | < 0.0001 | ||||
| Non-Hispanic White | 1,092,614 (63.1) | 142,050 (61.0) | 819,015 (68.0) | 208,104 (69.4) | |
| Non-Hispanic Black | 202,409 (11.7) | 34,969 (15.0) | 124,986 (10.4) | 37,251 (12.4) | |
| Hispanic | 172,323 (9.9) | 15,218 (6.5) | 112,282 (9.3) | 23,679 (7.9) | |
| Non-Hispanic Asian | 184,922 (10.7) | 30,864 (13.3) | 93,062 (7.7) | 15,892 (5.3) | |
| Other/multiple | 80,576 (4.7) | 9,712 (4.2) | 54,680 (4.5) | 14,946 (5.0) | |
| Marital Status, n (%) | < 0.0001 | ||||
| Married | 1,139,330 (65.8) | 152,155 (65.4) | 910,851 (75.7) | 228,820 (76.3) | |
| Divorced, Separated, or Widowed | 212,246 (12.3) | 44,661 (19.2) | 164,435 (13.7) | 49,301 (16.4) | |
| Never Married | 381,268 (22.0) | 35,996 (15.5) | 128,739 (10.7) | 21,751 (7.3) | |
| Caregiver Status, n (%) | < 0.0001 | ||||
| None | 699,616 (40.4) | 91,647 (39.4) | 449,106 (37.3) | 110,220 (36.8) | |
| Dependents, age <18 | 516,841 (29.8) | 75,377 (32.4) | 387,832 (32.2) | 99,120 (33.1) | |
| Dependents, other | 516,387 (29.8) | 65,788 (28.3) | 367,086 (30.5) | 90,533 (30.2) | |
| Professional Characteristics | |||||
| Highest degree, n (%) | < 0.0001 | ||||
| ADN/Diploma | 402,919 (23.3) | 99,364 (42.8) | 373,813 (31.1) | 83,078 (27.7) | |
| BSN | 1,043,383 (60.2) | 101,974 (43.9) | 529,087 (44.0) | 133,075 (44.4) | |
| Graduate Degree (MSN, DNP, PhD) | 286,442 (16.5) | 31,005 (13.3) | 300,760 (25.0) | 83,710 (27.9) | |
| Annual Family earnings, n (%) | < 0.0001 | ||||
| Less than $50,000 | 56,164 (3.2) | 18,134 (7.8) | 60,838 (5.1) | 13,910 (4.6) | |
| $50,000 to $100,000 | 637,560 (36.8) | 96,012 (41.2) | 394,841 (32.8) | 97,062 (32.4) | |
| $100,000 to $150,000 | 825,241 (47.6) | 95,531 (41.3) | 566,396 (47.0) | 149,233 (49.8) | |
| Greater than $150,000 | 213,880 (12.3) | 23,136 (9.9) | 181,949 (15.1) | 39,668 (13.2) | |
| Scheduled FTE, n (%) | < 0.0001 | ||||
| Less than 0.6 | 54,443 (3.1) | 15,252 (6.6) | 81,019 (6.7) | 25,253 (8.4) | |
| 0.6 to 1.0 | 1,554,870 (89.7) | 196,038 (84.2) | 1,049,651 (87.2) | 262,521 (87.5) | |
| 1.0 and greater | 123,530 (7.1) | 21,522 (9.2) | 73,354 (6.1) | 12,099 (6.6) | |
| Travel nursing, n (%) | < 0.0001 | ||||
| Yes | 152,470 (8.8) | 14,522 (6.2) | 48,118 (4.0) | 12,282 (4.1) | |
| No | 1,580,374 (91.2) | 218,291 (93.8) | 1,155,906 (96.0) | 287,591 (95.9) | |
Abbreviations: LTC, long-term care; US, United States; SE, standard error; ADN, Associate Degree in Nursing; BSN, Bachelor of Science in Nursing; MSN, Master of Science of Nursing; PhD, Doctor of Philosophy; FTE, full-time equivalent.
All estimates weighted to represent national estimates.
T-test used to compare means and chi-squared test used to compare proportions.
Association between COVID-19 Caseload and RN Employment Settings
Across US states, COVID-19 caseload ranged from a low of 0.20 (Maine) to a high of 1.19 (Kentucky) COVID-19 cases per bed (coefficient of variation = 32%). In inpatient settings, High COVID-19 caseload states had an overall higher percentage of nurses compared to Low COVID-19 caseload states in 2018 (Figure 2). This percentage decreased in High COVID-19 caseload states and increased in Low COVID-19 caseload states. The percentage of nurses in LTC settings decreased in 2018 compared to 2022. In outpatient settings, High COVID-19 caseload states had overall lower percentages of nurses in 2018 and similar percentages in 2022, compared to Low COVID-19 caseload states. The percentage of RNs in non-clinical settings was similar in High and Low COVID-19 caseload states in 2018 and 2022 (Figure 2, Supplemental Tables 8 and 9).
Figure 2. State-Level Change in the Percentage of Registered Nurses Working in (A) Inpatient, (B) Long-Term Care, (C) Outpatient, and (D) Non-Clinical Employment Settings in 2018 and 2022.
Y-axis labeled in increments of 5%. Thick lines represent overall percentages for Low and High COVID-19 caseload states. Thin lines represent individual states.
In adjusted analyses, individual RNs exposed to either High or Low COVID-19 caseloads had a lower likelihood of working in LTC settings in 2022 versus 2018 (Supplemental Table 10). However, compared to Low COVID-19 caseload RNs exposed to High COVID-19 caseload exhibited a smaller decline in the percent probability of working in LTC over time, 0.9% (95% CI: 0.3, 1.5; Table 2). While we observed a higher percent probability of working in outpatient settings across time, for outpatient, inpatient, and non-clinical settings, statistically significant differences between Low versus High COVID-19 caseload exposure were not observed. Sensitivity analyses demonstrated consistent associations between time, COVID-19 caseload, and employment setting (Supplemental Tables 11-13).
TABLE 2.
Difference-in-Differences Estimates of the Association Between COVID-19 Caseload and Registered Nurse Employment Setting in 2022 (Compared to 2018).
| Marginal Effect of Time % (95% CI) |
Difference-In-Difference |
|||
|---|---|---|---|---|
| Employment Setting | Low COVID-19 Caseload | High COVID-19 Caseload | Unadjusted (95% CI) | Adjusteda (95% CI) |
|
| ||||
| Inpatient | 0.4 (−0.7 to 1.5) | −0.6 (−2.0 to 0.9) | −1.0 (−2.8 to 0.8) | −1.0 (−2.5 to 0.6) |
| Long-Term Care | −1.5 (−1.9 to −1.1) | −0.7 (−1.2 to −0.1) | 0.8 (0.2 to 1.5) | 0.9 (0.3 to 1.5) |
| Outpatient | 2.6 (1.3 to 4.0) | 2.8 (1.5 to 4.1) | 0.2 (−1.7 to 2.0) | 0.4 (−1.2 to 2.0) |
| Non-Clinical | −1.8 (−2.5 to −1.0) | −1.8 (−2.5 to −1.1) | 0.01 (−1.0 to 1.0) | −0.1 (−1.1 to 0.9) |
Abbreviations: CI, confidence interval. Generalized logistic model. Marginal effect (unadjusted) indicates the predicted change in the probability of an RN working in a given employment setting in 2022, compared to 2018, in states with low and high COVID-19 caseload. Difference-in-difference estimates indicate the difference in the probability of an RN working in a given employment setting in 2022 (compared to 2018) in states with low versus high COVID-19 caseload.
Adjusted for the following sociodemographic and professional characteristics - age, sex, race/ethnicity, marital status, caregiver status, professional characteristics, annual earnings, and travel nursing
Reasons for Leaving Position in 2022 versus 2018
Nearly twice as many RNs left their primary position in 2022 compared to 2018. In 2022, 24% (839,621 of 3,479,615) reported leaving their primary position, while 13% (418,769 of 3,272,872) reported leaving their primary position in 2018. Across all settings in 2018 and 2022, the top reasons for leaving their position were workplace-related, including stressful work environment, burnout, and insufficient staffing (Figure 3, Supplemental Tables 14-16). Post-pandemic, these workplace-related reasons for leaving were significantly higher compared to pre-pandemic, most notably for inpatient and LTC RNs, P < 0.001 for all (Figure 3). Two exceptions were stressful work environment and lack of good management, which went down in non-clinical settings in 2022.
Figure 3. Top Self-Reported Reasons For Leaving Among Registered Nurses Who Left Their Primary Nursing Position in 2018 versus 2022 By Employment Setting.
All analyses weighted to represent the US registered nurse workforce. Responses were not mutually exclusive so percentages do not add up to 100. Includes nurses working in non-clinical settings (i.e., public health or community offices and administrative roles).
Note. ‘Stressful work environment’ can be interpreted as follows: Among RNs who left their primary nursing position in 2018, 37% of inpatient RNs, 43% of LTC RNs, 30% of outpatient RNs, and 20% of non-clinical RNs reported that stressful work environment contributed to their decision to leave. In comparison, among RNs who left their primary nursing position in 2022, 49% of inpatient RNs, 51% of LTC RNs, 35% of outpatient RNs, and 19% of non-clinical RNs reported that a stressful work environment contributed to their decision to leave their position.
a: Chi-squared test used to compare proportion in 2018 versus 2022. All comparisons were statistically significant (P < 0.0001)
Discussion
To our knowledge, this study is the first to use nationally representative data to conduct a quasi-experimental design to estimate the contribution of the COVID-19 pandemic to temporal changes in RN employment setting. Despite growth in the overall nursing workforce from 2018 to 2022, we found a higher percentage of nurses in outpatient settings and a lower percentage in all other settings. This finding is consistent with post-pandemic workforce estimates showing that recovery of the overall workforce occurred primarily in non-inpatient settings (1.6% points higher for inpatient RNs compared to 12.8% points higher for RNs in other settings).9 Although a recent study did not find a significant change in the percentage of RNs employed in hospitals,24 our findings may differ because we used a nationally representative sample. Furthermore, while previous studies examined time trends of the RN workforce around the pandemic,8,9,25 our study leveraged state-level variation in COVID-19 caseload to estimate the exposure to High COVID-19 caseloads. Counterintuitively, in our difference-in-difference analysis, we found that RNs exposed to High COVID-19 caseloads compared to Low COVID-19 caseloads exhibited less of a decline in the likelihood of working in LTC settings. Differences between High versus Low COVID-19 caseload exposure were not statistically significant for the likelihood of working in inpatient, outpatient, and non-clinical settings. In sum, these findings suggest that the COVID-19 pandemic did not have the anticipated effect on RN employment setting.
An unexpected finding was that RNs exposed to High COVID-19 caseloads experienced less of a decline in the likelihood of working in LTC settings than those exposed to Low COVID-19 caseloads. Further study is needed to understand the conditions in these High COVID-19 caseload states that contributed to this unexpected finding. However, possible explanations of this finding may include a rebound effect related to local policies enacted in response to High COVID-19 caseload, a countercyclical workforce response to macroeconomic conditions, or targeted recruitment efforts.39 In descriptive analyses, we found that COVID-19 may have had an influence on nurses leaving the workforce. Approximately 2 percent of nurses who left their primary position in 2022 reported doing so because of underlying health conditions that increased the risk of severe illness for themselves or their family (Supplemental Table 16). Consistent with this finding, nurses who were out of the labor force before the pandemic were likely to be older, have a disability, or have children at home.38 Addressing these concerns and implementing policies to mitigate a nurse’s personal or family health risk related to COVID-19 (or future infectious outbreak) may be helpful in encouraging nurses to return to work. Such policies might include ensuring an adequate supply of personal protective equipment, paid personal and family medical leave, and flexible assignments to employment settings with reduced potential for exposure.
Our study offers some insight into the potential mechanisms driving shifts in nurses’ employment settings. We found that nearly twice as many nurses left their primary nursing position in 2022, compared to 2018, representing higher job turnover and employment changes. Nurses reported workplace-related concerns (e.g., stressful work environment, burnout, and insufficient staffing) more frequently than personal, family, or career reasons in 2018 and, to an even greater extent, in 2022. These findings are consistent with other studies linking workplace issues with intent to leave32 and ending healthcare employment2 among RNs during this period. A recent study by Fraher and colleagues found state-level variation in RN staffing intensity (and LPN staffing intensity) indicating that different care models and staffing policies were utilized during the pandemic.33 US hospital occupancy has grown since the pandemic, suggesting that hospitals are caring for a growing number of patients with fewer registered nurses.34 Annual hospitalizations are projected to increase over the next decade due to the aging population,34 which potentially places patients at risk for poorer health outcomes.3,35,36 These findings should inform future policy at both the federal and state levels, such as maximum patient-to-nurse ratios, as well as organizational strategies for staffing and care delivery models.37
Lastly, differences in the composition of the nursing workforce may explain changes in employment settings across time. We observed that the percentage of males increased in all clinical settings in 2022, compared to 2018. Although the nursing workforce remains predominantly female,26 there has been an increase in male registered nurses over the past four decades.27 This trend has been attributed to changes in educational attainment, labor demand, urbanization, and liberalized gender roles in the US.27 Our findings may reflect the influence of increased demand for nurses during the COVID-19 pandemic on the male nursing workforce. Research on the post-pandemic healthcare workforce indicates female healthcare workers were more likely to leave the field compared to males,10 with childcare stress as a likely contributing factor.11 Professional factors, such as changes in nursing educational opportunities, may represent an important avenue of career change away from inpatient nursing. For instance, there has been considerable growth in nurses pursuing doctorates in nursing practice (and other advanced degrees)28 and such preparation is often associated with employment in outpatient settings.29 Travel nurses experienced higher compensation, schedule flexibility, and job control during the pandemic.23,30,31 Compared to before the pandemic, travel nurses were more likely to work in the inpatient setting, suggesting that nurses are willing to work in the hospital under better working conditions. For example, Hickey and colleagues (2024) found that travel nurses searched for particular work environments when considering future assignments during the COVID-19 pandemic by looking for states with mandated staffing laws or hospitals with Magnet status.30
Limitations
This study has several limitations. First, the NSSRN data are based on self-report and we cannot rule out potential misclassification of employment setting, though it is unlikely nurses would systematically misrepresent this information. Second, our measure of COVID-19 caseload was constructed at the state level. Although an analogous measure could be constructed at the level of the healthcare institution, this was not possible due to NSSRN’s de-identification of respondents. Nevertheless, given that COVID-19 public health policies occurred primarily at the state level, there is some justification for a state-based COVID-19 measure. Third, our measure of COVID-19 caseload compared exposure to what we defined empirically as High versus Low COVID-19 caseload, and therefore lacked a true control of no exposure. This likely biased our estimates towards the null. Finally, as this is an observational study, we cannot entirely rule out the possibility of residual confounding affecting our results. However, the NSSRN does collect a wide range of important covariates that we included in our models and we employed a rigorous quasi-experimental design. Despite these limitations, this study advances what is known about the impact of the COVID-19 pandemic on a nurse’s choice of employment setting which can be used to inform preparation for future public health crises.
Conclusions
This study provides initial evidence that COVID-19 caseload did not contribute to temporal changes in nurses’ choice of employment settings. Further research is needed to better understand the factors contributing to nurses leaving LTC settings, as well as those that support the stability of the overall nursing workforce.37 Our study suggests that other factors, beyond the COVID-19 pandemic, are most likely related to observed trends in employment settings among nurses.7 Workplace issues related to stressful work environment, burnout, and insufficient staffing are important, actionable targets to assure workforce stability and optimize patient outcomes.
Supplementary Material
Funding/Support:
Ahr receives funding from the NINR Predoctoral Fellowship Training Grant (T32 NR016914). The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Footnotes
Conflict of Interest Disclosures: Dr. Davis reported receiving personal fees from Regional Anesthesia & Pain Medicine for statistical consultation outside the submitted work. No other disclosures were reported.
References
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