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Nurse Scheduling Problem Research Paper


Nurse scheduling refers to the process of assigning working schedules or programmes to nursing practitioners in their places of work.

The process entails giving different working schedules to a certain number of nursing practitioners who possess varied skills and qualifications, while at the same time conforming to important aspects that needs to be addressed such as personal preferences, existing working practices, rules and regulations, and ethical standards (Coomber & Louise, 2007).

This, actually, is part of a larger capacity plan that needs a more effective implementation to ensure that the nursing role is achieved within various units of health care. Obviously, a well-planned nurse scheduling exercise is likely to satisfy the interests of nurses, thus generating a positive impact upon the services extended to patients in health care facilities.

The many problems associated with the scheduling of nursing practitioners can be observed from vast areas of medical and health care application in both public and private sectors. In fact, these problems are of great concern to human well-being, and for that reason, have attracted the attention of numerous researchers from allover the world.

The researchers are eager to develop appropriate systems that can successfully be used to undertake these crucial processes. This paper examines the literature research of nurse scheduling problem along with a general overview of some of the different techniques that have been used to address this complex issue of health care.

Nurse scheduling problem is actually a major issue of concern in the health care department, considering its diverse constraints that are likely to affect the quality of nurse responsibilities in hospitals. Nurse scheduling simply entails the short-term timetabling of nurses in their work.

This timetabling is a very crucial aspect of the health care department, since it ensures that proper and effective nursing care service is provided to patients in health care facilities around the clock (Azaiez & Al Sharif, 2005).

In this regard, the implementation of the entire plan will depend on some key considerations that would include the period of planning, type of shift, soft constraints and hard constraints, work-related constraints, workplace regulations, and categories of knowledge or qualification, among other crucial aspects.

As it would be observed, some of the various techniques that have been used to schedule nurses in their work have failed to offer credible results, thus making nurse scheduling one of the biggest challenges in health care matters.

Numerous studies have shown the scheduling of nursing practitioners to be a common problem when it comes to the assignment of staff personnel in hospitals and other health care facilities. Long-term and short-term staffing of nurses in modern-day health care units comes with many challenges, possibly because of the many variations in staffing needs or requirements.

However, most of these challenges will tend to come as a result of various factors such as imbalances of the nursing responsibilities between different working shifts in a day, and variations in the personal wishes of nursing practitioners and the need to maintain acceptable service levels.

Nurse scheduling is not just about ensuring that health care facilities have sufficient number of nursing practitioners, but also that there are enough nurses who possess the desired skill mix on duty around the clock to take care of the patients (Burke et al., 2004).

Nurse scheduling problem is mainly about nurse shift and holiday assignment, whereby the nursing professionals have wishes or restrictions that must be recognized and respected.

The big problem here, however, is to come up with perfect schedules or programmes that would both fulfill the ultimate goal of health care in a particular setting and respect the diverse constraints of the nursing practitioners within that setting.

In this regard, good nurse scheduling systems must be able to satisfy a number of factors to ensure patient in different health care environments have access to effective and proper health care.

Nursing practitioners face both hard constraints and soft constraints in matters regarding scheduling. One common constraint faced by these professionals in their job is that, they cannot be assigned to all the shifts in a day, without being given a break (Louw, Nieuwoudt & Vuuren, 2007).

Nursing practitioners can also leave for holidays, and in that case, will not be expected to take duty shifts in the course of that time. Another common constraint here is that, it would not be possible for nurses to take night shifts and day shifts consecutively.

In this regard, there is always a need to ensure that all these constraints are taken into consideration when conducting nurse scheduling. In other words, the wishes and preferences of nurses should be maximally satisfied, but not to an extend where they can compromise the quality of health care given to patients.

There are various objectives for proper nurse scheduling in any health care facility, and these would include things such as the required skills and available workforce size (Ernst, Jiang & Krishnamoorthy, 2004). A wide range of solution approaches have been applied in an attempt to solve the broad issues associated with nurse scheduling.

These approaches, however, are grouped into several categories that include automatic approaches, systematic approaches, heuristic or mathematical approaches, and manual ways, which have been in use across the world for a very long time.

The most common techniques drawn from the above approaches that have been used to tackle nurse scheduling problem include GRASP, integral programming, linear programming, heuristic approach, constraint programming and mixed-integer programming.

Manual approaches mostly comprise of the ancient techniques that were used to tackle the issue of nurse scheduling within health care facilities in the past. Unlike the modern techniques that are performed using computer-aided programs and other sophisticated ways, the early techniques mainly relied on manual procedures, such as the use of hand (Refalo, 2004).

However, even though these techniques had proved to be useful in the past, they are faced with many challenges when it comes to modern aspects of health care. In other terms, the early techniques cannot effectively address the diverse complexities of nursing demands and interests presented by the current world where everything appears to have taken a different course, owing to the influential impacts of modernity.

This explains the reason as to why many health care facilities across the world have decided to settle for computerized scheduling systems, which are more effective and reliable compared to the early techniques. As it would be observed, the early techniques are associated with a number of advantages and disadvantages.

One big advantage of these early is that they are cheap, since their application entails manual operation. However, a common limitation with the approaches is that they cannot be reliable for effective scheduling, since they have a lot of errors.

GRASP simply stands for ‘Greedy Randomized Adaptive Search Procedures.’ This multi-start process operates in two main phases. First, there is the construction phase, which establishes a feasible answer to a problem, and whose surroundings are studied until a local minima is identified.

Then there is the local search phase, which uses the procedure of a local search to the constructed outcome or result in hope of modifying it further. According to Bellanti, Carello & Croce (2004), GRASP is arguably one of the most effective heuristic approaches commonly applied to provide better solutions for nurse scheduling problems in the contemporary world.

There are numerous advantages linked to this approach, and some of these will include guaranteed optimality at the end, easy implementation, and better solutions to combinatorial optimization problems. However, one major limitation associated with the technique is that, it is stuck in a local minima, thus lacking robustness on a wide scope of problem instances.

Linear programming is another methodology that has proved to be very effective when it comes to matters of nurse scheduling. This is a mathematical approach applied using computer simulation to establish the best possible solution to nurse scheduling problems.

The concept was first introduced in the course of the Second World War, with the aim of optimizing the allocation of material and resources that were critical to the war success.

This technique is used to establish optimal solutions to issues that can be expressed with the use of linear equations and inequalities (Harmeier, 1991). In fact, researchers have found the method to be very accurate in finding the best solutions for real world problems such as nurse scheduling.

In this case, a linear program would comprise of variables, linear constraints that describe the limit on the values of applied variables, and a linear objective function that shows the impact of each variable to determine the expected results.

This approach offers a number of advantages to the vast areas where it is applied. One of the most evident advantages of the approach is that it provides optimum application of the necessary productive factors. The approach also provides for improved qualities of decisions.

More importantly, the technique applies sensitivity analysis, which enables people to make modifications on the linear problem to obtain the modified outcome. Apart from the benefits highlighted above, this technique also has a number of limitations on its side.

One major problem with the technique is that, it can only be relevant to situations where linear goal functions and limitations apply. Another common drawback of the technique is that, aspects of climate conditions and other doubts are usually not put into consideration, and this is likely to interfere with the outcome credibility.

Integer programming is the other technique that has proved effective in tackling the issue of nurse scheduling problem in hospitals. Typically, this approach will express the optimization of a subject of a linear function to various linear constraints.

In cases where this approach is applied to solve real world problems such as nurse scheduling, a modeling phase upon which the problem is translated into a mathematical concept will be required. One major advantage of this technique in solving combinatorial optimization problems is that, the problems can be resolved to optimal results within a reasonable period of time.

This technique has proved to be sufficiently flexible in addressing nurse rostering demands within health care units, and for that reason, it is widely applied in hospitals across the world to ensure that nurse timetables are tailored to fit their personal interests, without having to compromise the quality of care targeted on patients (Okada, 1992).

Just like other techniques used in research based on combinatorial optimization problems, integer programming is also associated with a number of advantages and disadvantages. One common advantage of the approach is the absence of rounding errors.

This particular aspect plays a significant role in improving the credibility of outcomes in research. More importantly, it makes comparison of figures or numbers simple and more reliable. In terms of the limitations, the technique has a limited value range, which is arguably one of the biggest disadvantages associated with it.

As it has been shown in this research paper, nurse scheduling problem is a crucial and complex practice that calls for a lot of attention from hospital managers and other service facilitators in the health care department.

The wide scope of literature about this particular matter is a real manifestation of the big concern of humans in matters of health, particularly the ones that are affiliated to nursing responsibilities in health care facilities.

It is also evident from this research paper that, even though early techniques of tackling nurse scheduling are no longer effective, there is much hope in the computer-aided approaches and other sophisticated systems that are used in the modern day. However, based on findings from previous literature, there is room for further studies to address the complex issue of nurse scheduling problems.

References

Azaiez, M., & Al Sharif, S. (2005). A 0-1 goal-programming model for nurse scheduling.

Computers & Operations Research, 32(3), 491-507. Web.

Bellanti, G., Carello, F., & Croce, R. (2004). A greedy-based neighborhood search approach to a nurse rostering problem. European Journal of Operational Research, 153(15), 28-40.

Burke, K., De Causmaecker, G., Vanden Berghe, H. & Landeghem, V. (2004). The state of the art of nurse rostering. Journal of Scheduling, 7(15), 441-499.

Coomber, B., & Louise, B. (2007). Impact of job satisfaction components on intent to leave and turnover for hospital-based nurses: a review of the research

literature. International Journal of Nursing Studies, 44(2), 297-314. Web.

Ernst, A., Jiang, H., and Krishnamoorthy, M. (2004). Staff scheduling and rostering: A review of applications, methods and models. European Journal of Operational Research, 153(1), 3-27. Web.

Harmeier, P. E. (1991). Linear Programming for Optimization of Nurse Scheduling. Computers in Nursing, 9(4), 149-151. Web.

Louw, M., Nieuwoudt, J. & Vuuren, V. (2007). Finding good nursing duty schedules: A case study. Journal of Scheduling, 10(7), 387-405. Web.

Okada, M. (1992). An Approach to the Generalized Nurse Scheduling Problem- Generation of a Declarative Program to Represent Institution-Specific Knowledge. Computers and Biomedical Research, 25(5), 417- 434. Web.

Refalo, P. (2004). Impact based strategies for constraint programming. CP2004, 11(7), 557-571. Web.

This Research Paper on Nurse Scheduling Problem was written and submitted by user Dayton Ortiz to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly.

Dayton Ortiz studied at Temple University, USA, with average GPA 3.32 out of 4.0.

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Ortiz, D. (2020, January 8). Nurse Scheduling Problem [Blog post]. Retrieved from https://ivypanda.com/essays/nurse-scheduling-problem/

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Ortiz, Dayton. "Nurse Scheduling Problem." IvyPanda, 8 Jan. 2020, ivypanda.com/essays/nurse-scheduling-problem/.

1. Dayton Ortiz. "Nurse Scheduling Problem." IvyPanda (blog), January 8, 2020. https://ivypanda.com/essays/nurse-scheduling-problem/.


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Ortiz, Dayton. "Nurse Scheduling Problem." IvyPanda (blog), January 8, 2020. https://ivypanda.com/essays/nurse-scheduling-problem/.

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Ortiz, Dayton. 2020. "Nurse Scheduling Problem." IvyPanda (blog), January 8, 2020. https://ivypanda.com/essays/nurse-scheduling-problem/.

References

Ortiz, D. (2020) 'Nurse Scheduling Problem'. IvyPanda, 8 January.

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