Jane Marie Kirschling, DNS, RN, FAAN; Charles Colgan, PhD; Bruce Andrews, PhD
Posted: 09/22/2011; Nurs Econ. 2011;29(3):111-117. © 2011 Jannetti Publications, Inc.
Abstract and Introduction
Introduction
The evolving nursing shortage in the United States and globally is a subject of considerable attention from researchers, the health care industry, higher education, and policy makers, both at the federal and state levels. Unlike past shortages, this one involves both the demand and supply parts of the equation. Consequently, multiple strategies must be put into place to offset the projected shortage of over 260,000 registered nurses (RNs) in 2025 (Buerhaus, Auerbach, & Staiger, 2009).Retaining members of the current nursing workforce and increasing the number of new graduates are major strategies being addressed across the health care industry and higher education. In relation to retention, one of the short-term strategies that 34% of the 32 hospitals in the Community Tracking Studies are using is flexible scheduling, which includes a "broader range of shift types and self-scheduling" (May, Bazzoli, & Gerland, 2006, p. w319). Although the national trend is toward 12-hour shifts in acute care, there is evidence that older nurses prefer 8-hour shifts (Hoffman & Scott, 2003; Mion, Hazel, Cap, Fusilero, Podmore, & Szweda, 2006). However, Shullanberger (2000), in an integrative review of the literature, found that 12-hour shifts, in contrast to 8-hour shifts, were less fatiguing.
According to Norman and colleagues (2005), based on their national survey of 1,783 nurses:
Beyond focusing on retaining older RNs, it is important that employers initiate strategies to retain RNs who are approaching their 40s. Data in this survey showed that, as RNs enter their 4th decade, there is a strong tendency to shift employment into non-acute care settings. Strategies should be developed and tested that encourage retention in direct patient-care positions in acute care environments (p. 289).Using a national sample to explore the impact of flexible scheduling on RNs who "intend to leave their current positions in the next 3 years," Ulrich, Buerhaus, Donelan, Norman, and Dittus (2005) found "more flexible scheduling would be very likely (29%) or somewhat likely (24%) to cause them to reconsider leaving" (p. 393).
In this study, responses from 8,038 nurses in Maine are used to elaborate on these previous studies by examining in some detail the relationship between scheduling and propensity to stay or leave the nursing profession as this relationship is mediated by a number of factors. Maine has been fortunate to date in maintaining its RN workforce, but this is not expected to continue. In 2000, there were 1,023 RNs per 100,000 population (national average 780) and the projected vacancy rate was 12% and was expected to grow to 31% in 2020, according to federal forecasts (U.S. Department of Health and Human Services Health Resources and Services Administration Bureau of Health Profes sions, 2001, 2000). Maine's Department of Labor projects the following employment growth in the health care sector between 2002-2012: ambulatory health-care services 32% (net 7,542), nursing and residential care facilities 29% (net 6,427), and hospitals 21% (net 5,405) (Maine Department of Labor, 2004). In addition, they project 3,469 additional jobs for RNs, which reflects 27% growth, and that annually there will be 1,097 openings (Maine Department of Labor, 2005).
Maine's 13 nursing programs produced 610 graduates in 2004-2005, up from a low of 392 in 2001-2002 (Kirschling, 2006a). It is important to note that the Maine State Board of Nursing has historically licensed to another jurisdiction the same number of out-of-state nurses that it licenses to the State of Maine. What this means for Maine is that retention of the existing workforce is an essential part of the solution, as well as increasing capacity in Maine's nursing programs.
A major question, therefore, about the adequacy of the future supply of nurses is how many will stay in the profession. Of course, this is partly a question about considerations common to any job such as when will people retire. For the baby-boom generation (those born between 1946 and 1964), which composed 65% of the nursing profession at the time of the survey reported here, this is a particularly critical question, since 84% of the nursing profession (at the time of the survey) was either in the baby-boom generation or older.
There are other aspects peculiar to the nursing profession that increase the urgency of identifying the factors affecting the decision to remain in the profession as part of the response to nursing shortages. These include the high-stress nature of many nursing duties and the ability to respond to the rapidly changing technological and organizational context of the nursing profession.
The Data Set
The survey reported here was conducted in cooperation with the Maine State Board of Nursing, which agreed to include a two-page survey with all license-renewal applications beginning September 1, 2002 and concluding August 31, 2004 for all nurses in the 2-year license renewal cycle. The resulting data are referred to as the Maine Minimum Data Set. Completing the survey was voluntary and its return served as informed consent. Returned surveys were separated from the renewal application for data entry and participants did not include their name or license number on the completed surveys.The Maine Minimum Data Set was developed by the first author, working with key stakeholders. Agreement was reached on 19 items focused on education, advanced practice, work status, future plans, average work hours, employment setting, employer and residential ZIP codes, position, year born, race/ethnicity, gender, and, if not one, the reason for not being employed as a LPN or RN. A number of the items were drawn from the Colleagues in Caring minimum supply-side data elements (Lacey, Hoover, McKay, O'Grady, & Sechrist, 2005). A total of 15,960 nurses returned usable surveys, of which 1,995 were licensed practical nurses (LPNs) and 13,714 were RNs (Kirschling, 2006b). For this analysis, we focused on the respondents who were RNs and who were currently working in nursing.
For average work hours, respondents were asked to respond to the following four information requests that relate to their primary nursing position:
- Write in the average number of hours you were hired for in a typical week.
- If you are actively seeking to change the number of hours you are hired for, write in the number of hours you would prefer to work in a typical week.
- Write in the average number of actual hours worked in a typical week.
- Write in the average number of hours per week spent providing direct care (if you don't provide direct care, enter 00).
Table 1 provides descriptive information on the 8,038 RN respondents as well as two subsamples: those who were actively seeking to change the number of hours worked (n=1,831) and those not actively seeking to change the number of hours worked (n=6,207).
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Table 1. Descriptive Information: Combined Sample, RNs Actively Seeking to Change Number of Hours Worked, and RNs Not Actively Seeking to Change Number of Hours Worked
 | Combined Sample (8038) | Actively Seeking to Change number of hours Worked (1831). | Not Actively Seeking to change Number of Hours Worked (6,207) |
|---|---|---|---|
| Average Age (in years) | 46.2 | 45.9 | 46.3 |
| Age Categories | |||
| % 21–30 years | 7.1 | 7.5 | 7.0 |
| % 31–40 years | 21.2 | 20.8 | 21.3 |
| % 41–50 years | 35.9 | 37.6 | 35.4 |
| % 51–60 years | 30.0 | 28.8 | 30.3 |
| % 61+ years | 5.9 | 5.2 | 6.1 |
| Gender | |||
| % Female | 92.7 | 91.8 | 93.0 |
| % Male | 7.3 | 8.2 | 7.0 |
| Highest Education Nursing | |||
| % Diploma | 22.5 | 21.0 | 23.0 |
| % Associate degree | 33.1 | 35.7 | 32.3 |
| % Baccalaureate degree | 34.8 | 33.2 | 35.3 |
| % Master's degree | 9.0 | 9.7 | 8.8 |
| % Doctoral degree any field | 0.6 | 0.4 | 0.7 |
| Nursing Employment Setting | |||
| % Hospital | 57.8 | 59.1 | 57.4 |
| % Ambulatory care | 8.6 | 8.9 | 8.5 |
| % Public/Community health | 3.0 | 2.5 | 3.1 |
| % Occupational health | 1.2 | 1.2 | 1.2 |
| % Insurance company | 1.9 | 2.0 | 1.8 |
| % Long-term care | 9.0 | 9.1 | 8.9 |
| % Home health care | 5.5 | 5.7 | 5.4 |
| % Nursing education | 1.4 | 0.9 | 1.6 |
| % School health | 3.4 | 2.6 | 3.7 |
| % Other | 8.4 | 8.0 | 8.4 |
| Role with Primary Employer | |||
| % Staff/Direct care nurse | 60.2 | 59.9 | 60.5 |
| % Quality assurance/Infection control | 1.0 | 0.7 | 1.0 |
| % Discharge planner | 2.3 | 2.1 | 2.4 |
| % Utilization review/Outcome management/Other insurance related role | 2.2 | 2.4 | 2.1 |
| % Staff development | 1.2 | 1.4 | 1.1 |
| % Facility/Nursing department administrator or supervisor | 6.9 | 6.6 | 7.0 |
| % Team leader/Charge nurse, nurse manager, head nurse | 11.1 | 12.0 | 10.7 |
| % Educator (college/university) | 1.2 | 0.7 | 1.4 |
| % Researcher/Consultant | 1.1 | 1.1 | 1.0 |
| % Nurse practitioner, certified nurse midwife, clinical nurse specialist, nurse anesthetists | 8.6 | 9.6 | 8.3 |
| % Other | 4.5 | 4.5 | 4.5 |
| Plan to Be Working in Nursing in 5 Years | |||
| % Yes | 93.4 | 92.9 | 93.5 |
| % No | 6.6 | 7.1 | 6.5 |
| Average Hours for Typical Week | |||
| Hired | 34.1 | 33.5 | 34.2 |
| Worked | 37.2 | 37.9 | 37.0 |
| Worked minus hired = contract gap | 3.1 | 4.3 | 2.8 |
| Preferred (if seeking to change hours) | n/a | 31.1 | n/a |
| Worked minus preferred = schedule gap | n/a | 6.7 | n/a |
| Spent providing direct care | 24.6 | 25.1 | 24.4 |
| Spent providing non-direct care = direct care gap | 12.6 | 12.7 | 12.6 |
Analysis
We hypothesize that, if scheduling and number of hours worked are factors in whether someone is willing to stay in nursing, dissatisfaction with number of hours worked is a precursor to leaving the profession. In the case of a survey of this type, that precursor effect should be manifest by an association with the stated preference for remaining in nursing.Respondents were asked, "If you are actively seeking to change the number of hours you are hired for, write in the number of hours you would prefer to work in a typical week." Answers to this question yield both a dichotomous variable indicating whether a change in hours is being sought and a variable expressing the level of preference. The dichotomous variable "Actively Seeking to Change Hours" can then be analyzed and used to break the data set into two groups based on whether they are (or are not) seeking to change their number of hours worked. These two subsets can then be analyzed for their relationship to their expectations about staying in the nursing profession. (The data analysis excluded LPNs and those for whom responses to any of the relevant variables were missing.)
Analysis of the relationships with nine potential explanatory variables was conducted using multivariate logistic regression. The examined explanatory variables were categorized into two groups. The first comprised six demographic characteristics of the respondent, and the second comprised three gaps defined in terms of numbers of hours worked. The first group consisted of:
- Age (expressed as an integer).
- Years in nursing profession (expressed as an integer).
- Gender
- Education (defined as highest degree/diploma held).
- Employer type, including:
- Hospital
- Ambulatory care
- Home health care
- Insurance company
- Long-term care
- Public/Community health
- School health
- Primary nursing function as reported on the survey:
- Discharge planner, case manager
- Facility/Departmental administrator or supervisor
- Nurse practitioner, nurse mid wife, clinical nurse specialist, nurse anesthetist
- Quality assurance, infection control nurse
- Researcher, consultant
- Staff development nurse
- Team leader/Charge nurse, nurse manager, head nurse
- Utilization review, outcomes management, other insurance-related nursing roles
- Other
Results
As depicted in Table 1, the contact gap for those actively seeking to change the number of hours worked was 4.3 hours, 1.5 hours greater than for those not actively seeking to change the number of hours worked. The schedule gap for those actively seeking to change the number of hours worked was 6.7 hours. The direct care gap was similar between the two groups with those actively seeking to change spending 12.7 hours in non-direct care and those not actively seeking to change spending 12.6 hours in non-direct care.[ CLOSE WINDOW ]
Table 1. Descriptive Information: Combined Sample, RNs Actively Seeking to Change Number of Hours Worked, and RNs Not Actively Seeking to Change Number of Hours Worked
| | Combined Sample (8038) | Actively Seeking to Change number of hours Worked (1831). | Not Actively Seeking to change Number of Hours Worked (6,207) |
|---|---|---|---|
| Average Age (in years) | 46.2 | 45.9 | 46.3 |
| Age Categories | |||
| % 21–30 years | 7.1 | 7.5 | 7.0 |
| % 31–40 years | 21.2 | 20.8 | 21.3 |
| % 41–50 years | 35.9 | 37.6 | 35.4 |
| % 51–60 years | 30.0 | 28.8 | 30.3 |
| % 61+ years | 5.9 | 5.2 | 6.1 |
| Gender | |||
| % Female | 92.7 | 91.8 | 93.0 |
| % Male | 7.3 | 8.2 | 7.0 |
| Highest Education Nursing | |||
| % Diploma | 22.5 | 21.0 | 23.0 |
| % Associate degree | 33.1 | 35.7 | 32.3 |
| % Baccalaureate degree | 34.8 | 33.2 | 35.3 |
| % Master's degree | 9.0 | 9.7 | 8.8 |
| % Doctoral degree any field | 0.6 | 0.4 | 0.7 |
| Nursing Employment Setting | |||
| % Hospital | 57.8 | 59.1 | 57.4 |
| % Ambulatory care | 8.6 | 8.9 | 8.5 |
| % Public/Community health | 3.0 | 2.5 | 3.1 |
| % Occupational health | 1.2 | 1.2 | 1.2 |
| % Insurance company | 1.9 | 2.0 | 1.8 |
| % Long-term care | 9.0 | 9.1 | 8.9 |
| % Home health care | 5.5 | 5.7 | 5.4 |
| % Nursing education | 1.4 | 0.9 | 1.6 |
| % School health | 3.4 | 2.6 | 3.7 |
| % Other | 8.4 | 8.0 | 8.4 |
| Role with Primary Employer | |||
| % Staff/Direct care nurse | 60.2 | 59.9 | 60.5 |
| % Quality assurance/Infection control | 1.0 | 0.7 | 1.0 |
| % Discharge planner | 2.3 | 2.1 | 2.4 |
| % Utilization review/Outcome management/Other insurance related role | 2.2 | 2.4 | 2.1 |
| % Staff development | 1.2 | 1.4 | 1.1 |
| % Facility/Nursing department administrator or supervisor | 6.9 | 6.6 | 7.0 |
| % Team leader/Charge nurse, nurse manager, head nurse | 11.1 | 12.0 | 10.7 |
| % Educator (college/university) | 1.2 | 0.7 | 1.4 |
| % Researcher/Consultant | 1.1 | 1.1 | 1.0 |
| % Nurse practitioner, certified nurse midwife, clinical nurse specialist, nurse anesthetists | 8.6 | 9.6 | 8.3 |
| % Other | 4.5 | 4.5 | 4.5 |
| Plan to Be Working in Nursing in 5 Years | |||
| % Yes | 93.4 | 92.9 | 93.5 |
| % No | 6.6 | 7.1 | 6.5 |
| Average Hours for Typical Week | |||
| Hired | 34.1 | 33.5 | 34.2 |
| Worked | 37.2 | 37.9 | 37.0 |
| Worked minus hired = contract gap | 3.1 | 4.3 | 2.8 |
| Preferred (if seeking to change hours) | n/a | 31.1 | n/a |
| Worked minus preferred = schedule gap | n/a | 6.7 | n/a |
| Spent providing direct care | 24.6 | 25.1 | 24.4 |
| Spent providing non-direct care = direct care gap | 12.6 | 12.7 | 12.6 |
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Table 2. The Age Effect
| Age | Seeking to change hours p = <0.0001 | Not seeking to Change hours p = <0.0001 |
|---|---|---|
| | 1.14 times less likely to stay | 1.16 times less likely to stay |
Table 3 shows the results of the analysis of educational levels and expectations about staying in nursing. In interpreting the results of the two logistic regression models (one for those "seeking to change hours" and one for those "not seeking to change hours"), each value of the independent variable under examination is compared to one reference value chosen by the authors. This "reference group" is shown in the upper left corner of each table. For the RN diploma group, there is a significant relationship between the highest nursing degree and the propensity to leave nursing within the group not seeking to change their hours. Among those seeking to change their hours, there is also a significant relationship among those with RN diplomas and associate degrees and master/doctorate degrees, and the relationship is in the hypothesized direction. That is, as educational levels increase, there is an increased likelihood they will stay in nursing. How ever, this educational effect is much stronger among those seeking to change their hours.
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Table 3. The Education Effect
| Highest Nursing Degree ref: Master's or Doctorate | Seeking to change hours p = 0.0121 | Not Seeking to change hours p = 0.0007 |
|---|---|---|
| RN diploma | 3.32 times less likely to stay | 1.95 times less likely to stay |
| Associate | 2.83 times more likely to stay | Ns |
| Baccalaureate | ns | Ns |
| ns = not significant (p = 0.05) | ||
This analysis suggests that, other than age and educational level, which do have predictable relationships with likelihood of staying in nursing, there is relatively little about the demographic characteristics measured in the survey that is associated with a likelihood of leaving nursing. However, the work schedule circumstances show much stronger relationships.The first element of scheduling to be examined is the "contract gap," the difference between the hours actually being worked and the hours for which one was hired (actual worked minus hired). The second gap examined is the "schedule gap," which is the difference between one's actual worked hours and preferred hours (actual worked minus preferred).
The impacts of each additional hour worked in excess of that for which the respondent was hired are presented in Table 4. For both those seeking and those not seeking changes in hours, work schedules whose magnitudes fell short of the hours promised at hiring did not significantly influence their propensity to leave or stay. However, for both groups, providing more hours than promised at the time of hiring had a favorable effect on an individual's propensity to stay, particularly with those seeking schedule changes. How ever, among those not interested in changing their schedule, more than 10 additional hours above the level they were promised at hiring is not attractive.
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Table 4. The Contract Gap Effect (Hours Worked-Hours Hired)
| Hours worked – Hours Hired ref: 0 | Seeking to change hours p = <0.0001 | Not Seeking to change hours p = 0.0044 |
|---|---|---|
| ≤ -1 | ns | ns |
| [1, 5] | 2.29 times more likely to stay | 1.37 times more likely to stay |
| [6, 10] | 2.83 times more likely to stay | 1.71 times more likely to stay |
| ≥ 11 | 3.05 times more likely to stay | ns |
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Table 5. The Schedule Gap Effect (Hours Worked-Hours Preferred)
| Hours worked – Hours Preferred ref: 0 | Seeking to change hours p = value <0.0001 |
|---|---|
| ≤ -1 | ns |
| [1, 10] | ns |
| [11, 20] | 5.85 times less likely to stay |
| ≥ 21 | 10.99 times less likely to stay |
Suggestions for Nurse Managers, Nurse Educators, and Further Research
Addressing the shortages of nurses requires both increasing the supply of new nurses coming into the profession and finding ways to reduce the outflow of experienced nurses already working. This analysis of RNs in Maine suggests there are definite characteristics of the work schedules that can influence a nurse's inclination to stay or leave the profession. This is not simply a question of "overwork," but of matching work schedules and hours as closely as possible to employee expectations. Seeking to change the hours of work is a statistically significant precursor to considering staying/leaving the nursing profession when there is a gap between the "contracted" hours or the preferred hours to which the nurse wants to change and the hours they are presently working.This suggests management needs to find a way to pay attention when nurses request changes in hours. Clearly, the mere fact of changing schedules will not solve the nursing shortage, but it is one action within management's control.
The importance of an attractive work schedule was the focus of a recent study by Wright and Bretthauer (2010). They reported on a hospital scheduling model for nurses that reduced labor costs while also reducing overtime and undesirable shifts. Implementation of the model requires the initial schedule be a coordinated effort between the unit and float pool managers, that the float pool size be sufficient to meet target staffing levels, and that the float pool nurses need to be cross-trained for a selected number of units.
On an individual basis, it is essential that expectations about work hours, including whether the position requires working weekends, nights, and holidays, be discussed at the time of interview, reaffirmed in writing when an offer is made, and discussed routinely as part of performance evaluations. The nurse leader needs to have a clear understanding of the nurse's expectation to determine whether it is realistic. This conversation needs to be ongoing and the process for requesting a change in the number of hours worked needs to be readily available. Once schedules have been set, it is important to minimize changes and, when needed, to consider offering some type of reward to the affected staff members.
Nurse educators also have a responsibility for orienting the future nursing workforce to the work demands of a career in health care. Given the majority of nurses work in hospitals, nursing students need to understand nursing care is required around the clock. Providing clinical education in the evening and on the weekend provides first-hand experience. Encouraging nursing students to work as certified nursing assistants and to participate in internship programs also exposes them to the demands of scheduling. Finally, nursing students need structured practice with interviewing and should be guided in what types of questions they should be asking as they consider their first position as a registered nurse.
The survey of Maine nurses reached a very broad sample, which is one reason why the levels of statistical significance found in the logistic regression analysis conducted here provide noteworthy findings. But the survey was also limited in what it could inquire about with respect to the work environment. Further re search should investigate other aspects of the work environment, and do so in a way that interactions with key variables like work schedules and expectations can be explored. This will likely expand the number of strategies and actions available to nurse leaders that will increase the likelihood of nurses remaining in the profession at least until retirement.
Sidebar
Executive Summary
- A major question about the adequacy of the future supply of nurses is how many will stay in the profession.
- The relationship between scheduling and propensity to stay or leave the nursing profession was examined in this study.
- This analysis suggests there are definite characteristics of the work schedules that can influence a nurse's inclination to stay or leave the profession.
- This is not simply a question of "overwork," but of matching work schedules and hours as closely as possible to employee expectations.
- This suggests management needs to find a way to pay attention when nurses request changes in hours.
- The mere fact of changing schedules will not solve the nursing shortage, but it is one action within the management control of any organization employing nurses that could have a positive effect on retention.
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References
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Acknowledgments
The authors wish to thank Karen Stefaniak, University of Kentucky College of Nursing, and Robin Kimball, Anil Oztuncer, and Baris Sagiroglu, University Center Graduate Assistants, Maine Center for Business and Economic Research, for their support on this project.
Note
This work was funded through the first author's Robert Wood Johnson Executive Nurse Fellows Program (2000–2003) and through a University Center grant from the Economic Development Administration.
Nurs Econ. 2011;29(3):111-117. © 2011 Jannetti Publications, Inc.
The authors wish to thank Karen Stefaniak, University of Kentucky College of Nursing, and Robin Kimball, Anil Oztuncer, and Baris Sagiroglu, University Center Graduate Assistants, Maine Center for Business and Economic Research, for their support on this project.
Note
This work was funded through the first author's Robert Wood Johnson Executive Nurse Fellows Program (2000–2003) and through a University Center grant from the Economic Development Administration.
Nurs Econ. 2011;29(3):111-117. © 2011 Jannetti Publications, Inc.
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