Operations Research in Nurse Scheduling

THOMAS CHOI, HELEN JAMESON, AND MILO L. BREKKE

Among all the problems that currently plague the nation's health profession, perhaps none is so obvious and detrimental as the much publicized nursing shortage. At a time when hospitalization policies mean only the very sick patients are admitted, the retention of nurses, especially qualified nurses, is paramount. Nurses are the largest work force in any hospital and are basic to the operation—but in recent years their turnover rate has been as high as 50 percent (Prescott and Bowen, 1987). An inability to maintain nursing manpower can radically affect quality of care. Clearly it is imperative that ways be found to increase job satisfaction, and thus retention, for qualified nurses.

What makes nurses resign? Previous studies have shown that discrepancies or disappointments between what nurses expect of their work schedules and what they experience are strong predictors of their intent to resign. This is because work schedules impose far-reaching constraints on the nurses' professional and social lives (Choi et al., 1986, 1989). So from 1983 to 1985, Rochester Methodist Hospital in Minnesota conducted an experiment with nurse scheduling to assess how various schedules might affect the retention of nurses.

The hospital's report of that experiment showed that various schedules did indeed reduce the nurses' job disappointment. But equally interesting is the behind-the-scenes report of the organization that elected to try such an experiment, and how it attempted to reconcile good management with the sometimes-



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People and Technology in the Workplace Operations Research in Nurse Scheduling THOMAS CHOI, HELEN JAMESON, AND MILO L. BREKKE Among all the problems that currently plague the nation's health profession, perhaps none is so obvious and detrimental as the much publicized nursing shortage. At a time when hospitalization policies mean only the very sick patients are admitted, the retention of nurses, especially qualified nurses, is paramount. Nurses are the largest work force in any hospital and are basic to the operation—but in recent years their turnover rate has been as high as 50 percent (Prescott and Bowen, 1987). An inability to maintain nursing manpower can radically affect quality of care. Clearly it is imperative that ways be found to increase job satisfaction, and thus retention, for qualified nurses. What makes nurses resign? Previous studies have shown that discrepancies or disappointments between what nurses expect of their work schedules and what they experience are strong predictors of their intent to resign. This is because work schedules impose far-reaching constraints on the nurses' professional and social lives (Choi et al., 1986, 1989). So from 1983 to 1985, Rochester Methodist Hospital in Minnesota conducted an experiment with nurse scheduling to assess how various schedules might affect the retention of nurses. The hospital's report of that experiment showed that various schedules did indeed reduce the nurses' job disappointment. But equally interesting is the behind-the-scenes report of the organization that elected to try such an experiment, and how it attempted to reconcile good management with the sometimes-

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People and Technology in the Workplace frustrating dictates imposed by "good science," or the experimental method. Both reports together tell an evolving tale of organizational change. ROCHESTER METHODIST HOSPITAL In many ways Rochester Methodist Hospital was an ideal site for such an experiment. Rochester Methodist Hospital, affiliated with the Mayo Clinic, was founded in 1954 as an acute-care facility. Methodist Hospital has always been staffed by only Mayo clinic physicians. The present facility with 791 licensed beds was designed in part for research (Sturdavant, 1960). The hospital was built as a "laboratory in which to study alternative designs of nursing units, hospital systems, and organization" (Trites et al., 1969). The Mayo Medical Center and Methodist Hospital's reputation for quality of care and productivity is well known (Dietrich and Biddle, 1986; Fifield, 1988; Sunshine and Wright, 1987). Methodist is more stable than many hospitals because it does not compete for patients. Mayo Clinic allocates admissions between Methodist and St. Mary's Hospital. During the period of the experiment, patient census declined from 85.3 percent occupancy to 65.5 percent, reflecting a national trend. The nursing department at Methodist Hospital was also recognized for its leadership. The organization of the nonunionized department was traditional, with centralization of major functions such as scheduling, budgeting, and education. However, despite centralization, communication "from the bottom up" was consistently encouraged by top management, and nurses' suggestions were shared through the line managers. Nurse turnover had been gradually reduced from 39.1 percent in 1974 for full-time nurses to 12 percent in 1983 (the beginning of the scheduling experiment), a time when many hospitals nationally were still having greater than 50 percent turnover (Prescott and Brown, 1987). Methodist's nursing success was documented in the 1983 report Magnet Hospitals, in which it was named one of the 41 "magnet hospitals" in the United States that had demonstrated outstanding success in attracting and retaining professional nurses (McClure et al., 1983). According to the study, conducted by the Academy of Nursing of the American Nurses' Association, these 41 hospitals are set apart by three common denominators: Knowledgeable leadership providing for nursing input in policies affecting their practice,

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People and Technology in the Workplace Opportunity to practice professional nursing, and Provision for professional growth. The nursing department staff was also clearly interested in research. Methodist Hospital's philosophy read, "The institution has an obligation to its patients and professional groups to seek new knowledge and skills in the health care field." This hospital mission and nursing department staff's interest in research resulted in a 1978 study to review the feasibility of developing a nursing department program for systematic studies at Methodist Hospital (Egan et al., 1981). Several enabling factors were identified in that study, which suggested Methodist Hospital had the right climate for conducting research and implementing research results. When the 1983 research project on nurse scheduling was approved, Methodist Hospital was governed by its own board of directors, whose backgrounds were primarily in fields of medicine, business, and law. The board was supportive of the nursing department, both having worked together for years, and recognized the department's accomplishments in the delivery of quality care, productivity, and nurse retention. All in all, Rochester Methodist Hospital was a progressive and even idyllic place in which to run an experiment. THE TURNOVER PROBLEM The scheduling problem addressed in the research project was how to maintain a qualified work force. This was not an immediate problem for Methodist Hospital, since its nurse turnover rate in 1983 was only 12 percent. However, there were undeniable signals that suggested a likely recurrence of a nursing shortage; one which would be of much longer duration than the cyclical shortages of the past. Inability to maintain nursing manpower would affect quality of care. Patients coming from around the world to this tertiary care setting expected a competent nursing staff. Methodist's need to schedule and staff 35 nursing units 7 days a week, 24 hours a day, with limited turnover seemed difficult for those outside of nursing to understand. But the fact that companies like Atwork, which developed the scheduling software used by Methodist Hospital,1 spent years in developing these computer programs for nurses attests to the complexity that must be taken into account for quality patient care, concern for employees, and the maintaining of a budget.

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People and Technology in the Workplace Mayo Medical Center had experienced a nursing shortage in the early 1970s that precipitated the unprecedented action of closing hospital beds. This was difficult for the physicians. Studies in Minnesota and nationally predicted another shortage of nurses in the 1980s. These studies were conducted by such groups as the Minnesota Higher Education Coordinating Board and the Special Governor's Task Force on Nursing (1982). The report of the Governor's Task Force on Nursing called for "the health care industry to do a better job of retaining nurses in active practice if Minnesota is to deliver quality, cost-effective health care in the 1980's and beyond." The same task force listed the following trends indicating an upcoming nurse shortage: the increasing demand for nurses to work in hospitals and nursing homes, changes in hospital staffing patterns in response to technological and clinical development, the decreasing population of high school graduates (predicted decrease of 34 percent between 1980 and 1992), and the decrease in number of high school graduates who express an interest in nursing as a career. The human-resource prediction model that was developed at Methodist also indicated a nursing shortage at the hospital unless retention could be maintained or improved upon. The decision to go with the scheduling experiment was greatly influenced by the minutes of the Nurse Research Committee, which consisted of representatives from a cross section of nurses in the hospital. The minutes recalled that this research idea was not new: In 1980, a Nursing Research Advisory Task Force was established with the purpose of identifying research study topics which would provide the most potential benefits to the Nursing Service Department, and to develop a framework for a Nursing Studies Department. The idea of a research project related to retention first appeared in the Research Advisory Task Force Minutes of October 1, 1981, when it was listed as a priority for study selection at Rochester Methodist Hospital. In 1982 the hospital's nursing service department—to which all nurses belong—identified scheduling, continuity of care, and research as areas requiring attention. A number of criteria were also identified that would be applied to any nursing research project: each research project would need to be successful and deemed important by the staff at all levels;

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People and Technology in the Workplace each research project should have some practical results; each research results, when implemented, should be visible; each research visibility should go beyond the institution; each research project should mobilize and set up resources with the hospital, viewed positively by Mayo Clinic; each research project should find its own funding; and each project should contribute to an evolving and cumulative base for a research department. As a result of applying these criteria, the immediate objective of Methodist's research was to develop, install, and evaluate alternatives that would improve the scheduling and staffing of nursing personnel in ways that were acceptable to them and that maintained the continuity and quality of patient care. CHOOSING THE SCHEDULE The scheduling research project consisted of the development, implementation, and evaluation of new schedules, or strategies, that would balance the needs and desires of nurses with cost and quality-of-care issues. No one schedule was favored before the research began. However, there was interest in the expanded use of the scheduling department computer. The Research Steering Committee (consisting of researchers, the hospital administrator, the hospital's human resource director, the director of nursing, and the project coordinator) agreed that a literature review of information on scheduling and staffing be the first step of the research project. The review covered issues of staff morale, community, satisfaction, hospital image, cost, turnover and retention, and quality of care. The review identified 20 schedules or strategies being used in hospitals across the nation. Intense discussions occurred between members of the Research Project Committee (researchers) and the Nursing Executive Committee (nurse managers) regarding those 20 work schedules. In these discussions, the researchers wanted to test new schedules that would have transferability within and outside the organization. Nursing managers agreed, but favored those schedules that would be practical and realistic to implement at Methodist. The scheduling supervisor described the 20 schedules and used a paper-and-pencil method to test them against a set of criteria previously identified as essential (see Appendix A). The results were brought to the Nursing Executive Committee for action, and 12 schedules were selected for further consideration and evaluation.

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People and Technology in the Workplace The general procedure was first to rank-order the scheduling options in terms of the estimated scores for each of the criterion variables. A sum of ranks across all the criteria was then computed for every scheduling option. Finally, a rank-ordering of those sums effectively enabled the Nursing Executive Committee to sequence the scheduling options from the one most likely to have the best effect on nurses and the quality and cost of care (by comparison with existing schedules) to the one that probably would have the weakest or poorest effects (see Table 1). In making its selection of experimental schedules, the Nursing Executive Committee also sought as much variety as possible among high-ranking schedules. The Nursing Executive Committee and the Research Project Committees then selected three schedules to be implemented during the experiment: straight shifts, computerized scheduling (compflex), and select-a-plan. These schedules are described in a later section. THE FIRST SNAG It was at this point that the Nursing Executive Committee ran into difficulty with the research. It became clear that in order to test schedules objectively, units would have to be randomly assigned new schedules. This precluded choice or participative involvement—a fact that concerned all levels of nurse managers and nursing staff. The only incentive given to the staff was that if the experimental schedule met the criteria and was preferred over their previous schedules, staff could remain on the new schedule. Good managers know it is virtually axiomatic that there must be good communication, support, mutual troubleshooting, and problem solving between management and staff. This was in fact the tradition at Methodist, which accounted for the esprit de corps and low turnover in the nursing staff. In sharp contrast, scientific research requires a commitment to an unbiased evaluation of new nurse schedules. Specifically, the experiment must be free of management interference. Otherwise, results of the experiment could be due not only to nurse schedules but also to management behavior. Herein lies the conflict: Good management does not necessarily allow for good science. Testing new technologies in one's own organizational site has the advantage of ensuring that the technology—in this instance, nurse schedules—fits the setting. The disadvantage is that such a test may severely disrupt normal behav-

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People and Technology in the Workplace TABLE 1 Example of Comparison of Scheduling Options Criterion Scheduling Option                 1 2 3 4 5 6 7 8 9   Continuity 10% 27% 19% 19% 25% 0% 18% 0% 20% Estimated rank   4 9 6.5 6.5 8 3.5 5 3.5 7   Flexibility .32 .89 .25 .86 .41 .44 .70 .76 .98 Estimated rank   2 8 1 7 3 4 5 6 9   Quality 76 75.4 77.6 75.5 75.9 70.6 73.9 77.4 75.8 Estimated rank   7 3 9 4 6 1 2 8 5   Sum of ranks for each option 13 20 16.5 17.5 17 8.5 12 17.5 21   Rank order of the sums of ranks 3 8 4 6 5 1 2 7 9  

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People and Technology in the Workplace ior, which may in fact hurt the very group the technology is intended in help. Thus on the surface, good management and good science seemed to share a common concept, but putting the concept into operation was a different matter. Despite misgivings, the Nursing Executive Committee decided to go ahead. At the first of what was to be many ''update'' meetings of all head nurses—first-line managers—random schedule assignments were made. Those head nurses in the selected units (i.e., regular nurse work stations) were given special recognition for their forthcoming participation. This recognition was not particularly well received. Individual reactions among head nurses at the meeting ranged from joy to extreme anger—so much so that the Nursing Executive Committee became apprehensive about the possibility of bias in the experimental outcome. Fortunately, however, true to their professionalism, each head nurse presented the new schedules fairly, with assistance from the scheduling department. The nursing staff reacted with the same range of emotions. Because of these strong reactions, an unplanned facet to the research was added, which was to allow head nurses and staff the opportunity to submit anonymous comments about their schedules. The research coordinator on the experiment assembled the comments and shared them with the Nursing Executive Committee. The key to surviving a possible breakdown in morale at this point was trust in the dedication of the manager and the leadership of the department. These comments continued for the nine months of the intervention phase—that is, trying out new schedules—of the experiment. A review of the comments after the experiment still evoked pain on the part of the managers. These comments described the emotions of experiencing change at the personal, staff, and organizational levels. The head nurses were definite losers in this change. They not only lost control of selecting schedules for their unit but also were placed in the most difficult position of bridging between employees and management. Although this situation improved with time, it contributed to stressful relations. OTHER GLITCHES After the research project started in 1983, four activities took place that significantly affected the hospital employees. These activities were important to the research project in terms of time commitments, potential employee morale problems, and lowering of managers' willingness to take risks.

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People and Technology in the Workplace First, pressure increased for immediate action on nurse scheduling. The hospital management and Board of Governors decided in 1983 to develop and conduct the first hospital-wide employee opinion survey. The results were generally positive and management was viewed favorably. However, the additional comment section contained 23 negative remarks (6 percent of the comments) about nurse scheduling. The implication of conducting an opinion survey was that the employees could expect immediate action in response to their comments; therefore, a scheduling experiment could have been seen by staff nurses as an unnecessary delay. Second, the nursing department picked this time to computerize. Although the department had centralized scheduling in 1968, except for the schedules themselves, the department had kept limited data for managing projections. In the mid-1970s, increased record keeping of nurse statistics, such as turnover, manpower requirements, and costs, was begun; and by 1983 it was determined that some data automation was essential to manage this department of more than 1,000 employees. Therefore, in 1983, the nursing and management services departments began investigating scheduling systems that would produce reports, assist in nursing department record keeping, and automate the present schedules. Before this time, there had been no computer programs that could totally automate scheduling. In May 1984 a contrast was signed with Atwork for the Automated Nurse Scheduling System (ANSOS) computer program. The nursing management team had been consistently informed of the investigation into this system but choose not to involve staff nurses because it did not anticipate that the change would negatively affect the staff. They were wrong. Implementation of change without staff involvement taught an invaluable lesson. Initially, ANSOS could not accommodate the size of the nursing staff. Therefore, it became necessary to use two separate programs, which precluded computer tracking of staff between the two programs. The lack of flexibility and integration resulting from this use of two independent computer programs fragmented the hospital into two separate systems, thereby affecting employee schedule exchanges and employees' ability to float or move to all units. The unexpected consequence of this change, in which the nursing staff viewed the computer as deciding their lives, was especially negative. The nurses became skeptical of the use of computers for scheduling. The third activity that affected the research project was the implementation of the government's program of prospective diagnostic related groupings (DRGs) in October 1984. This program

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People and Technology in the Workplace should have had little effect on the already short length of hospital stays at Methodist. The effect it did have, however, was only to postpone the inevitable nursing shortage. This shortage came about because the decrease in the number of beds occupied (to 65 percent) and the length of inpatient hospital stay (by 0.3 days) caused nursing units to close. The hospital decided not to resort to layoffs. Soon, however, trying to stay on budget with too many nurses was one more problem for management to resolve. Fourth was the prospect of a merger of Mayo Clinic, Rochester Methodist Hospital, and Saint Mary's Hospital. The potential merger was announced in 1985 during the study on scheduling and was completed in 1986. The major change was to form a common governance structure. Nurse managers coping with the three other new activities just described, in addition to their normal activities and scheduling research, questioned whether the scheduling experiment should be continued. For this kind of research (and the implementation of its results) to work in a hospital, management needed to be strongly committed to the activity. As discussed, the requirements of good management and good research came into conflict. NATURE OF THE NURSE SCHEDULING EXPERIMENT As mentioned at the outset of this discussion, disappointment in nurse scheduling indicates the process leading to resignation. Figure 1 shows how disappointments and discrepancies between what nurses expect and experience of their work schedules are strong predictors of nurses' intent to resign (Choi et al., 1989). Intention to resign has also been shown to have a direct and significant effect on turnover (Weisman et al., 1981). Satisfaction affects turnover through intention to resign (Weisman et al., 1981). Therefore, intention to leave is a critical intervening variable between satisfaction and actual turnover. Expressed by means of a parsimonious model, nurse turnover is a consequence of intention to resign, which is precipitated by dissatisfaction and discrepancies. Dissatisfaction itself is also a consequence of discrepancies. Each discrepancy variable is a continuum, the two poles of which are represented by disappointment, which stems from expectation exceeding experience, and contentment, from experience superseding expectation. In the larger context of social theories, Davis (1962) and Durkheim (1951) both indicated that attitudes most likely to trigger action have to do with perceived discrepancy between a person's expectations and experiences, or the lack of

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People and Technology in the Workplace FIGURE 1 Operational model—predicting intention of nurses to leave nursing. Key: Scale 06: Discrepancy concerning work schedules creating a climate for ideal professional nursing. Scale 10: Discrepancy concerning work schedules allowing freedom for personal business. Scale 07: Discrepancy concerning work schedules that are predictable. Scale 26: Discrepancy concerning work schedules allowing social activities outside the hospital. Scale 23: Discrepancy concerning work schedules fostering relationships at and outside of work. Scale 29: General satisfaction. Scale 31: Intent to leave nursing altogether because of scheduling dissatisfaction. *P < .01, * * P < .001, and ***r2 = .3085. integration between ends conceived and means available to achieve them. That is, dissatisfaction resulting from failing expectations—jolts that create disequilibrium—may very well induce change-seeking behavior. Low nurse turnover, especially when the economy is sluggish, may lead to the mistaken conclusion that root causes of nurse turnover—schedule-induced dissatisfaction and disappointment—have vanished. The combination of uncorrected root causes and an improved economy would instigate nurse turnover. But redesigning work schedules may increase satisfaction and contentment, hence retention. RESEARCH METHODS To evaluate how different schedules affect retention, the research project committee and the nursing executive committee designed an experiment calling for three experimental groups and one control group. Each experimental and control group in turn consisted of three randomly selected nursing units. All told, 12 randomly chosen units were involved (random sampling process

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People and Technology in the Workplace 1 (low) to 7 (high) and these scores were added together for a unit score. Unit internal community: An estimate to determine the maximum and minimum number of potential staff an employee would work with on the unit. Schedule management: An estimate of the amount of time for ongoing management of the schedule. (Included time for manual work by personnel/payroll and time necessary to keep the schedule operational). Quality of care: Estimates were made of the scores on six scales that would be used to measure quality of care on nursing units after the schedules were implemented. Quality scales included items on physical care, assessment, non-physical care, evaluation of care, etc. Staff morale: An estimate of the effect of the new schedule on staff morale and satisfaction. Behaviorally anchored scales were developed that allowed for varying levels of nurse behavior ranging from 1 (low morale) to 9 (high morale). Schedule flexibility: An estimate of the ability of staff to change schedules through exchanges, etc. The scale ranged from 0 (meaning no flexibility) to 1 (meaning maximum flexibility). Schedule satisfiers/dissatisfiers: An estimate of the number of satisfiers and dissatisfiers within each schedule. The range was from-5 (meaning many dissatisfiers) to +5 (meaning many satisfiers). An example of a satisfier was straight-day shifts with the weekend off. An example of a dissatisfier was working a day/evening rotating shift and working every Friday evening before a weekend off. Schedule implementation: An estimate of the amount of time needed to implement a schedule on the unit. Included were hiring of new staff to fill positions, developing the base pattern, determining the number of full-time and part-time employees for the schedule, etc.  Compliance with personnel policies and regulatory requirements: An evaluation of compliance/noncompliance of each work schedule with department policies and regulatory requirements.

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People and Technology in the Workplace APPENDIX B Significant Characteristics of Nursing Units that were Used to Identify Empirical Types of Nursing Units by Means of Cluster Analyses Ways that ward secretarial services are provided Percent and FTE budgeted by job category (RN/LPN/NA) Average number of patient admissions Average acuity Percent and FTE actual cost by category (RN/LPN/NA) Actual hours per workload index Average patient census Average number of patients of types 1, 2, 3, and 4 Total number of beds on the unit Percent shifts on days, evenings, nights Average percent patient occupancy Average number of patient dismissals/day Percent full-time and part-time by category (RN/LPN/NA) Unit architectural design Percent rotating shifts Average number shifts floated in by category (RN/LPN/NA) Average number shifts floated out by category (RN/LPN/NA) Average number of patients over 65 Average length of stay of nurse staff Percent straight shifts Average number of tests done at Mayo Clinic Average number of patient transfers/day Percent and number of employees hired into unit Percent and number of employees terminating from unit Percent and number of employees transferred out of unit Percent and number of employees on LOA by job category (RN/LPN/NA) Average number of clinical tests done for patients while hospitalized Frequency and number of student nurses on unit Percent and number of employees transferred into unit Average length of stay of patients Length of stay of Head Nurse Number of patient referrals Number of physician services assigned to unit Mayo Clinic support services

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People and Technology in the Workplace Primary physician services assigned to unit Medicus unit quality assurance scores Average number of patient falls APPENDIX C Questionnaire Scales Reliability Related to Job Satisfaction Scale 1: Experience of a work schedule that allows privacy at work Reliability = .92 Scale 2: Sense of one's own marketability Reliability = .86 Scale 3: Experience of a work schedule that fosters staff team work and friendship on the unit Reliability = .80 Scale 4: Expectation of a work schedule that allows communication with key departments Reliability = .93 Scale 5: Expectation of being able to control one's schedule Reliability = * Scale 6: Discrepancy concerning work schedules creating a climate for ideal professional nursing  Reliability = .91 Scale 7: Discrepancy concerning work schedules that are predictable Reliability = .80 Scale 8: Expectation of a work schedule that allows continuity of care Reliability = .70 Scale 9: Expectation of a work schedule that fosters relationships at and outside of work Reliability = .88 Scale 10: Discrepancy concerning work schedules allowing freedom for personal business Reliability = .87 Scale 11: Expectation of a work schedule that allows privacy at work Reliability = .95 *   Reliability coefficient, using Cronbach's alpha, less than .70; but single factor solution was obtained through factor analysis.

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People and Technology in the Workplace Scale 12: Expectation of a work schedule that creates a climate for ideal professional nursing Reliability = .96 Scale 13: Experience of a work schedule that creates a climate for ideal professional nursing Reliability = .88 Scale 14: Experience of a work schedule that allows communication with key departments Reliability = .92 Scale 15: Discrepancy concerning work schedules allowing communication with key departments Reliability = .91 Scale 16: Expectation of a work schedule that allows freedom for personal business Reliability = .92 Scale 17: Experience of a work schedule that allows freedom for personal business Reliability = .93 Scale 18: Discrepancy concerning work schedules allowing privacy at work Reliability = .90 Scale 19: Expectation of a work schedule that is ideal for what I want Reliability = .80 Scale 20: Expectation of a work schedule that fosters communication and teamwork on the unit Reliability = .90 Scale 21: Discrepancy concerning work schedules fostering communication and teamwork on the unit Reliability = .86 Scale 22: Experience of a work schedule that fosters relation ships outside of work Reliability = .84 Scale 23: Discrepancy concerning work schedules fostering relationships outside of work Reliability = .88 Scale 24: Expectation of a work schedule that does not get in the way of social activities outside of the hospital Reliability = .85 Scale 25: Experience of a work schedule that allows social activities outside the hospital Reliability = .83

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People and Technology in the Workplace Scale 26: Discrepancy concerning work schedules allowing social activities outside the hospital Scale 27: Perceptions that work schedules reflect respect and sensitivity toward work and personal lives of nurses Reliability = .91 Scale 28: Perceptions that hospital provides potential for nurses, professional growth Reliability = .86 Scale 29: General satisfaction Reliability = .85 Scale 30: Satisfaction with being a nurse Reliability = .84 Scale 31: Intent to leave nursing altogether Reliability = .91 Scale 32: Intent to change nursing jobs within or outside hospital Reliability = .89 Scale 33: Intent to leave hospital, but not due to dissatisfaction Reliability = .95 Scale 34: Intent to resign job Reliability = .82 Scale 35: Expectation of being able to change one's own schedule Reliability = * Scale 36: Experience of a work schedule that may influence my leaving the hospital or nursing Reliability = * *   Reliability coefficient, using Cronbach's alpha, less than .70; but single factor solution was obtained through factor analysis. APPENDIX D Scales that Discriminated Significantly between Experimental and Control Groups Scale 1. Experience of a Work Schedule That Allows Privacy at Work (Reliability = .92) I experience this at the hospital: A work schedule that allows me time away from nurses on my unit the head nurse on my unit

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People and Technology in the Workplace patients on my unit supervisors on my unit physicians on my unit unit activities Scale 2. Sense of One's Own Marketability (Reliability = .86) Without relocating, what are the chances that you could obtain another job that uses your skills and abilities? obtain another job that pays as much as your present job? obtain another job that is as easy or easier to commute to as your present job? obtain another job that has similar or better hours than your present job? obtain another job that has similar or better working conditions than your present job? Scale 3. Experience of a Work Schedule That Fosters Staff Teamwork and Friendship on the Unit (Reliability = .80) I experience this at the hospital: staff members on my unit that enjoy working with each other a work schedule that fosters a sense of belonging on my unit a work schedule that promotes loyalty among staff on the unit a clear idea of what to expect from the staff with whom I work a work schedule that fosters my sense of teamwork on the unit a work schedule that helps friendships form on the unit

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People and Technology in the Workplace Scale 4. Expectation of a Work Schedule That Allows Communication with Key Departments (Reliability = .93) I currently expect this from a first-rate hospital: A work schedule that allows me the opportunity to communicate with personnel department health services nursing education nursing administration nursing library community agencies Scale 5. Expectation of Being Able to Control One's Schedule (Reliability = .80) I currently expect this from a first-rate hospital: a work schedule in which I am able to make changes by negotiating with other staff nurses a work schedule that is more likely to be determined by the exchanges I make with my co-workers than by the scheduling department a level of satisfaction, while working on my unit, that is dependent more on day-to-day staffing than on the work schedule assigned to me by the scheduling department opportunity for me to suggest adjustments to my work schedule before it is finalized by the scheduling department a work schedule in which I am able to make changes by negotiating with my head nurse

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People and Technology in the Workplace Scale 6. Discrepancy Concerning Work Schedules That Create a Climate for Ideal Professional Nursing (Reliability = .91) Discrepancy between expectation and experience concerning sufficient staff when I am on duty for me to provide quality of care a work schedule that allows me to obtain information that is necessary to my providing care replacement by a nurse when someone on my unit is absent (due to illness, vacations, etc.) sufficient equipment on any work schedule, including weekends, for me to provide quality care a work schedule that allows for the right balance of independence and supervision when I am providing care a flexible work schedule without jeopardizing cost and quality of care a clear idea of what to expect from staff with whom I work a work schedule that allows me to give the most efficient care to my patients a work schedule that allows me to get adequate rest a work schedule that will not lower the quality of care I can provide a work schedule that allows me time to consult with other health professionals a work schedule that allows me to do dismissal planning for patients good supervision even if my head nurse is not there a work schedule that facilitates the opportunity to communicate directly with other nurses regarding the plan for my patients clinically competent staff nurses on my unit a work schedule that is practical a work schedule that allows me to give nursing care the way I choose

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People and Technology in the Workplace Scale 7. Discrepancy Concerning Work Schedules That are Predictable (Reliability = .80) Discrepancy between expectation and experience concerning a work schedule that is regular is predictable allows me to plan months in advance Scale 8. Expectation of a Work Schedule That Allows Continuity of Care (Reliability = .70) I currently expect this from a first-rate hospital: a work schedule that is flexible enough to allow me to care for the same patients several days in a row, if I am willing to change my personal plans in order to provide such care a work schedule that allows patients to receive care from the same nurse on the same shift for several days in a row a work schedule that allows me consistent contact with the same patients during their hospital stay Scale 9. Expectation of a Work Schedule That Fosters Relationships at and Outside of Work (Reliability = .88) I currently expect this from a first-rate hospital: A work schedule that fosters relationships outside of work that are a positive influence on my personal life and make me happy A work schedule that fosters relationships outside of work that are a positive influence on my work are a positive influence on my personal life make me happy make me want to stay in the hospital

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People and Technology in the Workplace Scale 10. Discrepancy Concerning Work Schedules Allowing Freedom for Personal Business (Reliability = .87) A work schedule that does not get in the way of doing banking going out for snacks, dinners seeing a lawyer, tax accountant shopping for clothes, housewares, hardware getting the house/apartment repaired/refurnished Scale 11. Expectation of a Work Schedule That Allows Privacy at Work (Reliability = .95) I currently expect this from a first-rate hospital: A work schedule that allows me time away from nurses on my unit the head nurse on my unit patients on my unit supervisors on my unit physicians on my unit unit activities

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