Introduction
Nowadays, healthcare optimization issues have received major attention in order to offer more proper services at a lower cost. Additionally, it is imperative and attracts many scholars’ attention as a result of the high cost and limitation of resources in the healthcare facilities. Without a doubt, scheduling is a problem due to the high constraints and preferences, such as resources limitation and personnel requirements. Unlike in any other sector, healthcare facilities are working around the clock. Nevertheless, the lack of staffing as well as irregular working shifts results in job satisfaction and might affect patient satisfaction.
Furthermore, increasing populace longevity will result in a rising in demand for health services. However, increasing in demand for care, and the absence or shortage of it may result in patients feeling their lives being threatened, high infection rates, overworking manpower, and overcrowding patients’ flow. A scheduling system could reduce the time spent by a patient waiting, ease the access to health services and affect the quality of healthcare operations. In order to get feasible scheduling for any system, the soft and hard constraints have to be determined. The latter could not be violated whereas the former incorporated as component of the cost function and need to be minimized.
Patient no-shows destabilize the health care system by producing inefficiencies and holding idle the usage of key resources. Healthcare organizations may be able to lessen and absorb the impact of no-shows by identifying all potential causes and implementing effective mitigation strategies. It includes dynamic scheduling techniques with the use of predictive analytics tools via artificial intelligence and machine learning (Marbouh et al., 2020). Striving to make medicine more effective and efficient, such techniques will enable better match supply with predicted demand under such conditions. Therefore, improving, planning, and scheduling processes of hospital resources play an important role in the enhancement of the healthcare facility’s benefit financially and service quality delivered to patients. A better scheduling system is critical since it allows reduction of costs revenue and enhances accessibility to the healthcare system.
Methodology
The methods used in the study are based on the literature review and comparison of multiple researches. There have been several studies made in healthcare scheduling considering the many scopes. One example is the discussion of healthcare scheduling-based data mining. The authors give a comprehensive examination of the literature that reflects an industrial engineering approach to healthcare scheduling with an emphasis on the behavior of the patients’ participation in scheduling. An included hospital scheduling problem has as well been studied. The assessment has been done according to the information from numerous articles linked with integrated hospital scheduling challenges.
Analysis of Financial Performance with Relevant Supportive Detail
Recently, there have been many reviews conducted in healthcare scheduling considering the various scopes. For instance, healthcare scheduling-based data mining is discussed in (Bartek et al., 2019). The authors offer a systematic assessment of the literature that reflects an industrial engineering approach to healthcare scheduling with a focus on the behavior of the patients’ role in scheduling (Bartek et al., 2019). An incorporated hospital scheduling problem has as well been reviewed by Bartek et al. (2019). The appraisal has been done according to the information from different papers associated with integrated hospital scheduling issues.
Patient Admission Scheduling Problem
The Patient Admission Scheduling is referred to assign patients to room in the facilities over a time horizon. It is a combinatorial optimization issue that is gaining attention from several researchers in the healthcare field (Bartek et al., 2019). PASP support decision-makers at different level such as long term, mid-term, and short-term in the healthcare institutes, which determine whether or not the hospital’s resources are ready for accepting patients through satisfactory services. The PASP is a problem of scheduling individuals within specific time slots in the facilities to maximize management competency as well as comfort and safety (Bartek et al., 2019). This is in addition to improving medical care in the facilities. The problem is a complex and combinatorial one (Bartek et al., 2019). Since it can be formulated, its solution enables the scheduling of patients allocated to particular beds in specific relevant departments (Bartek et al., 2019). This fulfills in an optimal manner to the needs of the patients and guarantees all the needed medical restrictions.
Often, the allocation of a patient to abed is executed by a centralized admission office, by contacting the departments a few days before for efficient patient admission. Some facilities regulate the admission of their patients without a central admission staff, leaving the responsibility to the different respective departments (Fairley et al., 2019). As in the second case, absence of the overall knowledge as well as data of the departments may result in not being occupied optimally. There could be shortage of beds available for individuals in some sections but additional spaces in others.
Nurse Rostering Problem
Nurse rostering issue refers to a type of staff scheduling problem. It can be described as a procedure to arrange a time table that satisfies the demand of every individual without conflict. It has adjusted to be specifically complex and a hard optimization problem. Most researchers try to solve this issue using a different optimization theory (Fairley et al., 2019). Nurse rostering involves two steps, including determining the number of staff members to be scheduled and allocating them in the time horizon for the schedule. This is problem is entrenched in the healthcare system, considered as under resource scheduling in healthcare, entailing the scheduling of a personnel or hospital staff, by balancing the preferences and workload.
The nurse scheduling issue entails NP hard optimization issue which is set via allocating group of varying skilled individuals to different types of shifts over a predefined scheduling duration. In order to obtain the feasible scheduling, the hard constraint needs to be accomplished, whereas the soft constraints are permitted, however will be penalized. It is important to maximize nurse scheduling preferences while minimizing the overall cost (Fairley et al., 2019). Nurse satisfaction is an indicator of the health services’ quality in a hospital. It is an emotional reaction and behavioral expression that reflects individual evaluation of their performance, working environment and life. Job satisfaction stresses on affective side of employee as constellation associated with attitude toward work aspects. Thus, job satisfaction focuses on feeling toward a job (Fairley et al., 2019). A nurse that is satisfied with their work will offer benefit for the hospital.
The nurse may provide commitment and loyalty, which are important to the hospital as well. Their performance would improve once they are satisfied with their working setting. On the contrary, their dissatisfaction would negatively impact the hospital (GĂłmez-RĂos et al., 2019). Hospital may lose its resources as a result of high turnover, sick leave, and absence. Ultimately, the facility will experience losses due to poor performance. Nurse rostering problem considers staff scheduling issues (GĂłmez-RĂos et al., 2019). Several researchers give special attention to this and try to optimize it with the intention of achieving a workable roster that has positive scheduling quality (GĂłmez-RĂos et al., 2019). In recent times, there have been proposal of a Bee Colony algorithm used in addressing NRP (GĂłmez-RĂos et al., 2019). Investigators used a multi-objective mathematical programming model and adapted a Multi-Objective Directed Bee Colony Optimization (GĂłmez-RĂos et al., 2019). The algorithm’s performance is assessed using INRC2010 (GĂłmez-RĂos et al., 2019). A collection of multiple cases of different size of data sets are selected.
Moreover, proposal was made about a hybrid harmony search algorithm with hill climbing as a resolution to address the significantly limited nurse rostering issue. The technique uses hill climbing to empower its exploitation in the search space (GĂĽr et al., 2019). Furthermore, the harmony memory consideration in the harmony search algorithm is via replacement by random selection scheme alongside the global best ideology of particle swarm optimization to accelerate the rate of convergence. The results illustrated that the proposed technique obtained five novel outcomes with regard to the quality of the solution and time necessities.
Operating Room Scheduling
Operating room theatre is an important role in the healthcare sector due to its major effect on hospital performance, both financially and in terms of efficiency. This requires a unique combination of staff as well as equipment. Additionally, each surgery needs preparation, before and after the surgery (Gür et al., 2019). Thus, the operating room theatre comprises two parts, including the preoperative and postoperative. Managing or scheduling is largely difficult as a result of its constraints and the stakeholders’ preferences. Furthermore, the limitations in resources and increase in demand for surgery have to result in better approaches to room scheduling, by applying various strategies to manage the operating room theatre.
The operating theatre scheduling comprises two parts, including the operating and recovery rooms. It involves the needed resources for surgical procedures, which include personnel or staff such as surgeons, nurses, anesthetists, among others (GĂĽr et al., 2019). There are facilities consisting of pre-operative holding units, equipment, several ORs, intensive care, and post-anesthesia care units. There are different operating room scheduling definitions (GĂĽr et al., 2019). An example is that it is a sequence of activities to allocate in the operating room. It is the ultimate essential component of the hospital and represents the source of income and expense for hospitals.
The operating room has great importance with other hospital resources and represent about forty percent of the income generated in a healthcare facility. The schedule is a patient flow management tool and aids the flow of other resources such as instrumentation, equipment, and ancillary hospital staffing resources (GĂĽr et al., 2019). The OR scheduling is a central system whereby the OR is managed by operation room leadership team, functioning as an efficient instrument, for the transmission of real-time patients flow and resources information of each department. Therefore, operating scheduling enables the coordination of resources in the hospital to be assigned in the proper manner.
The primary goal for all hospitals is achieving high-quality service deliverance for clients, hence there is an important requirement for the boosting of operating room accomplishment via optimal resources usage. The operating room surgery scheduling is meant for distribution of operation start time and assign the resources for scheduled surgical procedures (GĂĽr et al., 2019). This is done considering the several constraints in order to obtain the surgery flow, specializations and qualifications of the personnel, and existence and accessibility of resources. Operating room theatre could be grouped into various levels based on the type of patients, decision level, or management processes.
Other Healthcare Scheduling and Planning Problem
With regard to healthcare scheduling problems, many issues get less attention from researchers. Physician scheduling is a real-world challenge that emerges in hospitals. It is a type of scheduling where doctors are assigned to duty such as clinics, calls, surgeries, administration, among others over time slots based on planning horizons with various preferences and constraints. Physician scheduling problem consists of cyclic planning which dictates that planning duration must be restructured since doctors may have varying work rosters weekly. Cyclic planning refers to set models for physicians, with or without weekly rotation.
Planning as well as scheduling in physician problem has emerged in a three-decision level. Nevertheless, it is represented by daily scheduling, where the physicians are given different tasks. This has been researched by various individuals, who proposed a mathematical programming models to solve master physician scheduling problem (Marbouh et al., 2020). Additionally, there was a proposal of a mix integer linear programming to solve the problem (Marbouh et al., 2020). An investigation was conducted of the scheduling of physicians in the pediatric intensive care unit (Marbouh et al., 2020). To solve operating room scheduling problems, they integrated physicians and surgery scheduling for the aim of solving operating room scheduling issues by utilizing mix integer linear programming (Marbouh et al., 2020). Moreover, a research presented the problem from the standpoint of United States hospitals (Marbouh et al., 2020). The authors have investigated various types of physician scheduling using various priorities (Marbouh et al., 2020). Apart from that, the problem has been studied by applying a case hospital from the King Khalid University a Hospital in the Kingdom of Saudi Arabia. Home healthcare scheduling is another healthcare complex optimization issue which has grown in different decision levels, such as scheduling shifts or allocating staff.
For instance, different sets of nurses could be assigned to various patients which are situated in diverse places. Thus, multiple constraints, requirements as well as preference must be considered, such as clients’ requirements, nurse working time, and nurse expertise (Schoenfelder et al., 2020). Nevertheless, balancing the knowhow of nurses and clients is a standard function of home healthcare scheduling optimization and the selection of skills considered depends on the client’s needs and the specific regulatory surrounding. The significant solution technique of home healthcare scheduling has been completed using metaheuristic algorithm (Schoenfelder et al., 2020). In recent times, the field of telemedicine has attracted many researchers since it gives a novel platform for patients to access the healthcare services (Schoenfelder et al., 2020). It offers medical care for patients in distant remote areas such as villages that need outreach services.
Conclusion
A better scheduling system is critical since it allows reduction of costs revenue and enhances accessibility to the healthcare system. Healthcare optimization issues have received major attention in order to offer more proper services at a lower cost. Scheduling is a problem due to the high constraints and preferences, such as resources limitation and personnel requirements. Unlike in any other sector, healthcare facilities are working around the clock. Nevertheless, the lack of staffing as well as irregular working shifts results in job satisfaction and might affect patient satisfaction. Nurse satisfaction is an indicator of the health services’ quality in a hospital. It is an emotional reaction and behavioral expression that reflects individual evaluation of their performance, working environment and life. Job satisfaction stresses on affective side of employee as constellation associated with attitude toward work aspects. A nurse that is satisfied with their work will offer benefit for the hospital.
A scheduling system could reduce the time spent by a patient waiting, ease the access to health services and affect the quality of healthcare operations. In order to get feasible scheduling for any system, the soft and hard constraints have to be determined. The latter could not be violated whereas the former incorporated as component of the cost function and need to be minimized. Therefore, improving, planning, and scheduling processes of hospital resources play an important role in the enhancement of the healthcare facility’s benefit financially and service quality delivered to patients. Often, the allocation of a patient to abed is executed by a centralized admission office, by contacting the departments a few days before for efficient patient admission.
Some facilities regulate the admission of their patients without a central admission staff, leaving the responsibility to the different respective departments. As in the second case, absence of the overall knowledge as well as data of the departments may result in not being occupied optimally. There could be shortage of beds available for individuals in some sections but additional spaces in others. Often, this constitutes the patient admission scheduling problems. It is a combinatorial optimization issue that is gaining attention from several researchers in the healthcare field. PASP support decision-makers at different level such as long term, mid-term, and short-term in the healthcare institutes, which determine whether or not the hospital’s resources are ready for accepting patients through satisfactory services.
The PASP is a problem of scheduling individuals within specific time slots in the facilities to maximize management competency as well as comfort and safety. This is in addition to improving medical care in the facilities. The problem is a complex and combinatorial one. Since it can be formulated, its solution enables the scheduling of patients allocated to particular beds in specific relevant departments. This fulfills in an optimal manner to the needs of the patients and guarantees all the needed medical restrictions.
Recommendations
It is worth recommending certain steps for the improvement of hospitals in scheduling. For instance, choosing to focus on patient communication technologies can increase the speed with which the process of scheduling and registering patients is done. Sending a patient a text message to confirm an appointment and to remind them to finish lab work or update personal information. The hospital should try to schedule morning appointments from noon backward and afternoon appointments from noon forward (Schoenfelder et al., 2020). Establishing this as the standard will help maintain maximum productivity and ensure that the bulk of the day is scheduled out. If morning or afternoon slots do not get filled, you can use those blocks of time much more efficiently by holding your staff meetings then. Empty slots throughout the day generally result in unproductive down-time (GĂĽr et al., 2019). Thus, implementing a scheduling system that is based on service delivery to patients such as the one mentioned above would aid to reduce wasted time.
Additionally, patient visits vary in degree of time requirement and level of care needed. It is important to consider these factors before deciding where and when to schedule patients or whether to put them on the schedule. Many patient issues can be resolved with a brief phone call or email (GĂĽr et al., 2019). One can have the staff member who fields incoming calls use their best judgement to evaluate each call to determine whether to schedule the patient or have the nurse address the issue via a phone. This approach ensures patients needing the highest level of care have better access to same-day appointments if necessary and practice profitability is maximized by treating patients with more complicated or significant medical concerns.
Lastly, automation in the medical appointment reminder lowers the rate at which patients fail to attend, increases confirmation messages, and eventually increases the number of visits via improved slot use. When a person chooses an automated software, they need to consider one that has bidirectional functionality. When they are sending messages to patients, they can ensure that they ensure that they send another text. In case they are sending a confirmation electronic mail, they must utilize a two-way email to enable the clients to respond. A great example is the Riverside Medical Clinic, which is the largest physician-owned practice in the state of California (Schoenfelder et al., 2020). After implementation of the WELL’s two-way system, they witnessed a thirty-three percent reduction in failure to honor commitments by patients (Schoenfelder et al., 2020). Additionally, their verified appointment increased from twenty-nine percent to ninety-four percent using WELL leading to above $40,000 in two months (Schoenfelder et al., 2020). This shows that proper scheduling is beneficial and affects hospital revenues.
References
Bartek, M. A., Saxena, R. C., Solomon, S., Fong, C. T., Behara, L. D., Venigandla, R., & Nair, B. G. (2019). Improving operating room efficiency: machine learning approach to predict case-time duration. Journal of the American College of Surgeons, 229(4), 346-354. Web.
Fairley, M., Scheinker, D., & Brandeau, M. L. (2019). Improving the efficiency of the operating room environment with an optimization and machine learning model. Health Care Management Science, 22(4), 756-767. Web.
GĂłmez-RĂos, M. A., Abad-Gurumeta, A., Casans-FrancĂ©s, R., & Calvo-Vecino, J. M. (2019). Keys to optimize the operating room efficiency. Revista Española de AnestesiologĂa y ReanimaciĂłn (English Edition), 66(2), 104-112. Web.
GĂĽr, Ĺž., Eren, T., & AlakaĹź, H. M. (2019). Surgical operation scheduling with goal programming and constraint programming: A case study. Mathematics, 7(3), 251-252. Web.
Marbouh, D., Khaleel, I., Al Shanqiti, K., Al Tamimi, M., Simsekler, M. C. E., Ellahham, S., & Alibazoglu, H. (2020). Evaluating the impact of patient no-shows on service quality. Risk Management and Healthcare Policy, 13, 509-511. Web.
Schoenfelder, J., Bretthauer, K. M., Wright, P. D., & Coe, E. (2020). Nurse scheduling with quick-response methods: Improving hospital performance, nurse workload, and patient experience. European Journal of Operational Research, 283(1), 390-403. Web.