Designing and piloting a mobile application for fair and objective nurse scheduling: a design-based study

Abstract

Background

Nurse scheduling should prioritize fairness and objectivity, considering not only the nurse-patient ratio but also the skills, experiences, competencies, and preferences of nurses.

Objective

This design-based study was conducted to develop a mobile application that ensures fair, objective, fast and systematic scheduling and to evaluate the satisfaction of nurses with the developed application.

Design

We first created a model that included soft and hard constraints and developed the “Hospital Nurse Scheduling,” which can be downloaded to smartphones with Android and IOS operating systems.

Setting(s)

A pilot study with 12 nurses working in the oncology department of a university hospital was conducted to test the functionality and usability of the mobile application.

Participants

The nurses were asked to install the application on their smartphones, use it for one month, and complete the evaluation form at the end of the month. The application was designed for clinical nurses, charge nurses, and nurse managers; however, the pilot study was conducted only with clinical and charge nurses.

Methods

Data were analyzed using descriptive statistics.

Results

The participants believed that the application was user-friendly, faster than manually prepared work schedules, more objective, fairer in scheduling, and considered nurse preferences. The overall satisfaction with the application was rated at 8 out of 10 points, indicating a high level of contentment.

Conclusions

Mobile applications provide efficient means for preparing work schedules.

Introduction

Nurse staffing generally requires medium-term (monthly) planning and preparation of work schedules, which consider conflicting but related factors and assign personnel to units appropriate for their qualifications [1, 2]. Nurse schedules include shifts and daily work to provide labor requirements for each shift [3]. These schedules should be planned in a fair, neutral, and efficient way to meet the preferences and needs of nurses and should consider their expertise, skills, and experiences [3–6]. Manual scheduling is time-consuming and limited in finding a reasonable solution depending on the complexity of legal regulations and contracts [7, 8]. Besides this, unfair scheduling practices, regardless of whether the scheduling is done manually or electronically, may increase organizational conflict and lead to loss of motivation if they are carried out in such a way as to punish or privilege some of the employee [8].

This study proposes a mobile application to prepare standard and objective nurse scheduling, that can help plan human resources, save time, contribute to the literature, and provide convenient use by individual clinical nurses for managing their personal shift preferences and requests, and by responsible nurses for institutional scheduling processes. The application includes customized screens and functions for clinical nurses, charge nurses, and nurse managers.

Background

Nurse scheduling aims to plan the weekly, monthly or annual leaves, and working days and hours of nurses according to the number and medical conditions of patients, international and national legal regulations, and employment policies of the health institution [3]. Mostly prepared by responsible nurses [9]nurse scheduling is a complex weekly or monthly exercise with multiple and conflicting objectives, such as minimizing total costs, maximizing the satisfaction of nurses’ preferences, and equal distribution of workload [10]. Approaches and models of nurse scheduling range from simple tables or charts [2] to evidence-based personnel scheduling proposed by professional organizations, including computational techniques such as mathematical programming, genetic algorithms [3, 7], or typically implemented through computer software [2, 11]. Mathematical programming refers to mathematical models that are based on algorithms and include specific constraints to provide logical solutions for certain problems [12, 13]. Genetic algorithm is an artificial intelligence optimization algorithm, which repeatedly modifies a population of individual solutions in each step based on natural selection [14]. It produces fast and flexible solutions and creates efficient and fair schedules that meet nurses’ demands [13]. Additionally, mobile health applications in the online market, such as Google Play Store, Apple Store, and Samsung Apps, have been developed to serve specific purposes. Although limited in number, mobile scheduling applications have been developed to formulate problems and provide solutions to the problems with a carefully designed interface [15].

Approaches and models of nurse schedules should be developed for specific units of a health institution following the organizational structure of health institutions and the health systems, conditions, and legal regulations of the country. They should include hard and soft constraints [4, 13, 16]. Schedules that include the frequency and time of shifts and the number of nurses should clearly define all shifts, weekly rotations for each nurse, and the number of nurses required for each shift on each day [7, 10, 13]. Factors, such as hard constraints, regulations, institutional policies, and fairness should be met in any schedule, and no violations must be allowed [13]. Even though national laws governing shift scheduling may vary throughout nations, regulations should always be made explicit when imposing limitations. While determining hard restrictions, weekends, official holidays, and annual leaves should be clearly defined. There should be no more than five consecutive working days, weekly plans should be planned for five working days and 40 h, day shift after a night shift, night shift after an afternoon shift, three consecutive night shifts should be avoided, and there should be at least eight hours of rest before the next shift [7, 13]. Soft constraints should involve nurse preferences and should be minimally violated if necessary [13]. While determining soft constraints, the total number of days, afternoon and night shifts may be changed due to sickness or excuses and at least one experienced nurse should work each shift [7, 13].

The quality of nursing staff and schedules is measured in three dimensions that represent the objectives of the hospital and nurses, including effectiveness in providing nursing care, the effectiveness of the nursing unit, and job satisfaction of the nursing staff [17]. Due to this reason, timetables should satisfy all constraints, consider the needs and preferences of nurses, and ensure equity and fairness [3–6].

Legal regulations on working conditions in Turkey are parallel to the international standards and the social and health policies of different governments. Law No. 657 addresses the rights and responsibilities of Turkish civil servants [18]. Additionally, the Ministry of Health’s Provincial Organization’s Bed and Staff Standards Regulation is used for human resources planning in nursing [19]. According to this regulation, the nurse-patient ratio should be 1:2 in intensive care units and 1:7 in other units [20, 21]. This regulation, updated in 2010, remains in effect as the most current version. The nurse-patient ratios are stated as general standards and are not differentiated by shift types such as day or night. However, standards cannot be established in nurse planning due to the lack of workforce analysis that considers nursing care requirements and differences in service areas (intensive care nurses, surgical nurses, etc.) [22]. Consequently, significant differences in nurse scheduling exist in different health institutions depending on the organizational structure of the institution and the number and quality of health professionals. Therefore, rather than directly using existing nurse scheduling models and software, there is a need to develop evidence-based software that considers the legal regulations and unique conditions of different countries and the opinions of nurses regarding their working conditions.

Methodology

Aims

This study is based on a Ph.D. thesis entitled “Investigation of the current status of the nursing work system and development of software programs to be used for shift scheduling.” This study was conducted to develop a mobile application that enables scheduling to be fair, objective, rapid, and systematic, and to evaluate the satisfaction of nurses with the developed application. The application was developed to be used by clinical nurses, charge nurses, and nurse managers.

Ethical considerations

Ethical approval

was obtained from the Non-invasive Research Ethics Board of the university (06.07.2018/GO16969557-1172) and was extended to 2020 (22.09.2020/16969557-1242). Institutional permission was obtained from the Directorates of Nursing Services and Health Services. Written informed consent was obtained from all the participants.

Study design and implementation

This study used a design-based research approach to test a mobile application developed to solve nurse-scheduling problems. Design-based research is “a methodological approach that aligns with research methods from the fields of engineering or applied physics, where products are designed for specific purposes.” [23]Other scholars suggested that the test and evaluation may be conducted within the same step [24]. This study used a design-based research approach to develop and evaluate a mobile application. The research process included the following three phases:

1. Analysis of practical problems: A descriptive study was conducted to understand the challenges faced in nurse scheduling.

2. Development of solutions: Based on findings and legal regulations, a model was conceptualized and the mobile application was developed accordingly.

3. Evaluation and testing of solutions in practice: The developed application was evaluated by experts and tested through a pilot study in a clinical setting.

Stage 1: analysis of practical problems

We identified the problem by conducting a descriptive study to determine the current problems of nurses regarding nurse scheduling [25]. The preliminary study revealed the need for a mobile application that transforms the timetables manually prepared by responsible nurses into systematic, fair, and objective timetables that can be rapidly prepared. In accordance with the study’s findings, the process of creating a mobile application was started.

Stage 2: development of solutions

In the second stage, a mobile application titled “Hospital Nurse Scheduling” was developed. This stage was implemented in two steps: Conceptualization of the solution and model design; and development of mobile applications.

Conceptualization of the solution and model design

We have analyzed the legal regulations on nurse scheduling in Turkey, received the opinions of nurses, and used the findings of a PhD thesis [26]to identify the factors and soft and hard constraints to be considered. During this stage, soft and hard constraints were identified by considering the findings of the first phase of PhD research [25]suggestions of nurses, and labor regulations. Table 1 lists soft and hard constraints.

Table 1.

Hard and soft constraints for mobile application

Hard Constraints	Soft Constraints
Work schedules will be monthly prepared [26]	Depending on necessity, each nurse will work more than 40 hours a week [18]
There will be at least two nurses in each work shift [26]	Responsible nurses will work a maximum of two-day duty shifts [21]
Each nurse will work for at least 40 hours a week [18]	Day duties of responsible nurses will not be on consecutive weekends [34]
Day shifts will start at 08.00 a.m. and end at 04.00 p.m [18]	Night shifts will not be assigned to nurses, who have been working for 25 years or more and only day shifts will be assigned [33]
Night duties will be 16 hours from 04.00 p.m. to 08.00 a.m [21]	Maximum two-day duties will be assigned to nurses, who have been working for 25 years or more [26]
A 24-hour shift will be from 08.00 a.m. to 08.00 a.m. on Saturdays, Sundays, and legal holidays [21]	Day duties of nurses, who have been working for 25 years or more, will not be on consecutive weekends [34]
Day duties will be from 08.00 a.m. to 04.00 p.m. on Saturday, Sunday, and legal holidays [21]	Except for responsible nurses and specially planned nurses, all nurses on duty will work for at most five consecutive days [34]
Each nurse will work only one shift a day [18, 32]	Except for responsible nurses and specially planned nurses, all nurses on duty will work at most three consecutive night shifts [34]
During weekdays, the responsible nurse will work only day shifts [21] Starting with the 24th gestational week, pregnant nurses will work only day shifts [18]	Overwork will be planned as ± 1 or two duties for four weeks [26] Night shifts and 24-hour shifts will be assigned according to the demands and excuses of the nurses [26]
Nurses on breastfeeding leave will not be assigned to night shifts and will only work day shifts on weekdays [32]	Duties will be fixed shifts in accordance with the demands of the nurses (always night shift etc.) [26]
Nurses on maternity leave will not work night shifts [32, 33]	If possible, nurses that work 24-hour shifts will not be assigned two 24-hour shifts after the day they/them worked [34]
Maximum two-day duties will be assigned to the nurses on maternity leave [21]	The 24-hour shift will be at least 48 hours after the consecutive night shifts [34, 35]
Disabled nurses or nurses with disabled relatives will not work night shifts [32, 33]	No two consecutive weekend duties will be assigned to each nurse [34]
Nurses on annual leave will be excluded from the scheduling [18]	Weekend duties will not be assigned before or after annual leave [26]
Nurses on hospital pass, compassionate leave (paternity leave, marriage, death, sickness), accompaniment leave, and unpaid leave will be excluded from the scheduling [18]	If the annual leave (5, 12 or 19 days) starts on Monday, duties will be assigned to Thursday before the leave [26]
Nurses, who worked a night shift, will be given a one-day leave [21]. Newly appointed nurses will not be assigned to night shifts for the first two weeks [26]	Newly appointed nurses will work with more experienced nurses in daily duties, night shifts and 24-hour shifts for four weeks [26]

Mobile application development

After the model was designed, we defined how soft and hard constraints would work in the software and prepared process diagrams for the formation of lists of nurses, excuses, annual leaves, reports, and automatic shifts. The algorithms and commands for the process diagrams were written by software experts. Software experts prepared the parameters of the working principles of software, user information, database, timetables, and reports to calculate shifts within the context of soft and hard constraints, home screens and interfaces, and data design and coding. To prepare the nurse list, each nurse was assigned a reference number in addition to their name. Using the reference number, excuses, annual leave, and report data were classified according to the planned codes. Following this classification, the priority order of nurses was determined. Coding the priority order performs scoring, which is necessary to reflect the soft and hard constraints in the implementation. The scores of each nurse were automatically ranked using this system. After ranking, a system analysis was performed for each constraint. The system assigns higher priority scores to experienced nurses to ensure that each shift includes at least one experienced staff member, as required by the soft constraints. Owing to codes designed to prevent overlapping constraints, the system automatically identifies the most appropriate person for the shift. In line with the scores that constitute priority order and constraints, multiple analyses were performed to determine the type and length of shifts and priority scores to assign nurses to shifts. For example, as working only on weekdays is defined as a hard constraint for the primary nurse, the priority scores of the primary nurse for day and night shifts will be + 10 and − 10 to form the priority order, respectively (Fig. 1).

Fig. 1.

Examples of hard and soft constraint software codes

The application consisted of three main user interfaces, each corresponding to a different user role: clinical nurses, responsible nurses and administrators providing role-specific functions within the application. All home screens included login screens, profile settings, shift lists, excuse lists, annual leave, report lists, contacts, calendars, printers, and assistance. Home screens also reflected the hierarchy and responsibilities of individuals. For example, the home screen for nurses included interfaces for excuses, requests, and private messages, whereas the home screen for responsible nurses included interfaces for responses to requests from nurses and nurse scheduling generators. Figure 2 illustrates the process chart for screening responsible nurses. Below, we explain these screens.

Fig. 2.

Responsıble nurses screen desıgn

• User login screen: This is the screen where users can log into the system with predefined passwords, e-mail addresses, and information on user positions.

• Settings screen: This screen enables all users to change their e-mail addresses and passwords. It also enables responsible nurses and administrators to identify all nurses, define shift settings, and analyze reporting screens.

• Excuse list screen: This screen starts by marking the start and end dates of the relevant month and asks nurses to report their excuses and requests and mark whether they want a night shift.

• Annual leaves screen: On this screen, nurses request to use annual leaves and mark the start and end of the requested dates. Responsible nurses or administrators use this screen to approve or reject the request.

• Report list screen: Nurses use this screen to define information about their reports, such as pregnancy leave, breastfeeding leave, maternity leave, disabilities, relatives with disabilities, or health reports. They first mark the start and end dates and then mark the relevant report category. Responsible nurses or administrators use this screen to approve or reject reports.

• Contact screen: This screen enables users to communicate with all personnel at each stage of shift planning.

• Nurse scheduling generator button: Responsible nurses use this screen to first approve or reject all excuses, reports, and leave requests, and then generate nurse scheduling as per soft and hard constraints.

• Nurse scheduling approval button: Nurse scheduling generated by responsible nurses is sent to nurses, who then use this screen to approve or reject the generated list.

• Reporting screen: This screen enables the responsible nurse or administrator to filter and report excuses, personnel lists, shift schedules, and shift exchange lists within certain parameters.

• Shift schedule screen: After marking the start and end days, the user can see all shifts assigned to the user.

• Calendar screen: This screen is used to select start and end dates and display the assigned shifts.

• Help screen: This screen includes a detailed user manual, and frequently asked questions and answers.

• Print screen: This screen enables the user to connect to the printer and print the selected data.

The software development was carried out in collaboration with professional software experts. Although no external funding was received, the development costs were personally covered by the researcher. The application was designed based on a full-time working model, and it does not specifically support scheduling for part-time staff. The application was designed to be accessible on both Android and iOS platforms. The mobile application was available only within the region where the study was conducted. Due to ongoing additional development efforts, the application has been temporarily removed from the App Store and Google Play for updates and improvements.

Stage 3: evaluation of mobile application and pilot study

During the third stage, the mobile application system was evaluated by software developers, and the application was implemented in a real-life setting.

System test of mobile application

System tests were performed by software experts during the implementation process. Functionality tests confirmed that the screens operated in compliance with the defined soft and hard constraints and correctly displayed the intended data. Security tests showed that there was no internal or external intervention, the system was protected against viruses, and it did not permit unauthorized transactions. Performance tests demonstrated that each screen loaded within approximately two seconds, nurse scheduling was generated in about five seconds, and reports were created in approximately three seconds.

The pilot study of mobil application

The pilot study of mobil application was conducted in a 19-bed clinic of an oncology hospital at Ankara State University between November 1 and November 30, 2020. Although 18 nurses worked at the clinic, the study was concluded with the participation of 12 nurses; one nurse was assigned to another clinic, two nurses were on leave, and three nurses refused to participate. Nurse shifting was prepared weekly by responsible nurses, who first transferred the manually prepared shift into the digital environment and then printed and distributed it to the nurses.

The clinical nurses, responsible nurses, and nurse administrators (n = 12) received face-to-face training on the use of mobile applications during work hours. Afterwards, they were asked to install the “Hospital Nurse Scheduling” application from the App Store or Google Play on their smartphones. We added nurse administrators to the system, who then identified responsible and clinical nurses. Next, clinical nurses were asked to enter data on excuses, leaves, and reports. Nurses who did not enter their data were verbally informed. Responsible nurses were asked to approve or reject data entered by clinical nurses and generate nurse schedules that were shared by all clinical nurses via the application. Subsequently, the nurses controlled the nurse scheduling and approved or rejected it. Nurse scheduling was completed after the nurses evaluated their decisions. The schedule was fixed on the user’s screen during the relevant month. The responsible nurses were informed daily to maintain active usage of the application, and the questions of the responsible nurses were responded via WhatsApp or phone calls.

The following research questions were employed in the pilot study of mobile application:

1. Did the mobile application reduce the time required for nurse scheduling?

2. Was the mobile application more satisfactory than manually prepared timetables?

We have developed methods to evaluate the functionality of mobile applications. The evaluation focused solely on the satisfaction with the mobile application and did not involve a direct comparison with manually prepared timetables.The form was evaluated by five experts, including software experts and academicians from the fields of fundamentals of nursing, nursing management, and community health nursing, and was revised following expert opinions. The questionnaire was developed based on a review of the literature on mobile application evaluation and nursing management needs. Although existing validated tools were reviewed, they were not fully appropriate for evaluating a nurse scheduling mobile application, leading to the creation of a study-specific instrument. The questionnaire was reviewed and revised based on expert opinions but was not pre-tested with a similar population prior to its use in the pilot study. The final evaluation form comprised nine questions regarding the total number of nurses working in the clinic, their position, length of clinical experience, frequency of application usage, and their opinions about the application. We visited the clinical nurses between 08.00 and 16.00 h and asked them to complete the mobile app evaluation form, which was completed in approximately 15 min. Data were analyzed using SPSS version 26.0 (IBM Inc., Chicago, IL, USA). Descriptive statistics were used to analyze the data.

Findings

The questions determined together with the researchers were used by the software engineer to test the software system. According to the system test results, the nursing chart was created in about five seconds (the time from the time the system was instructed to create a nurse work list until the nursing list was displayed on the screen), data security was ensured, and the main screen and other interfaces worked smoothly (Table 2).

Table 2.

System test criteria used to evaluate the mobile application’s functionality and performance

System Tests	Yes	No
Operation Tests
Are the screens created according to the desired constraints?	+
Can they be matched as desired?	+
Attack Tests
Is there any intervention from inside or outside?		+
Can the system be protected against viruses?	+
Does the system accept unauthorized transactions?		+
Is all kinds of coding of the system protected?	+
Performance Tests
How many seconds does it take for the screens to appear?	2 second
How many seconds does it take to complete automatic seizure creation?	5 second
When a report is requested, how many seconds is the relevant report ready?	3 second

Clinical nurses who used the app (n = 8) had 10 years of professional experience. Daily usage of the application was 5–15 min. All nurses expressed that the application could be easily downloaded and that they could easily access their home screens and other connections. The majority of participants (n = 11) stated that the application was suitable for its primary aim and target audience, contained accurate and reliable information, allowed scheduling in a shorter time than manual scheduling, and followed legal regulations, nurse preferences, and the principle of fairness. Additionally, the nurses stated that the main screen and menu were appropriate (n = 8) and that the mobile application contributed to professional practice (n = 9). Functionality and overall satisfaction with the application were assessed at 8 ± 1.97 and 8 ± 1.82 points, respectively, when asked to rate their level of satisfaction on a scale of 0–10 (Table 3).

Table 3.

Nurses’ opinions on the mobile application for the Preparation of work schedule (n=12)

Characteristics	Number/Aritmetic Mean ()	% / Standard Deviation(s)
Is it simple to download the app on a computer or mobile device?
Yes	12	100
No	0	0
Is the app quick to open?
Yes	10	83,3
No	2	16,7
Is it simple to print the relevant pages of the application or save them in a different extension?
Yes	7	58,3
No	5	41,7
Does the home screen contain information or guidance?
Yes	9	75,0
No	3	25,0
Is it simple to access the home screen and other links?
Yes	12	100
No	0	0
Are the menus and main screen's visual design and textual style appropriate?
Yes	8	66,7
No	4	33,3
Does the application include trustworthy and accurate data?
Yes	11	91,7
No	1	8,3
Is there a user manual included with the application?
Yes	11	91,7
No	1	8,3
Is it generally simple to use the app?
Yes	10	83,3
No	2	16,7
Is the app's use generally complicated by design?
Yes	3	25,0
No	9	75,0
Does the app give an error message during use?
Yes	2	16,7
No	10	83,3
Is it possible to get in touch with the system administrator if an error message appears while using the application?
Yes	7	58,3
No	5	41,7
Is the application suitable for its intended purpose?
Yes	11	91,7
No	1	8,3
Is the application suitable for the target audience?
Yes	11	91,7
No	1	8,3
Are the limitations regarding the working system included in the algorithm of the application in accordance with the legislation (e.g. daily and weekly working hours, shifts, leaves)?
Yes	10	83,3
No	2	16,7
In practice, is it possible to deploy the minimum number of nurses required for each shift, including day, night and weekend shifts?
Yes	10	83,3
No	2	16,7
Is the assignment of tasks to shifts or shifts objective in practice? Yes No	10 2	83,3 16,7
Is the assignment of tasks to shifts or shifts in practice fair and equitable?
Yes	11	91,7
No	1	8,3
In practice, can nurse preferences be taken into account when assigning tasks to shifts or shifts?
Yes	10	83,3
No	2	16,7
Does the app enable the preparation of work lists in a shorter time compared to manually prepared lists?
Yes	11	91,7
No	1	8,3
Does the application have any contribution to professional practice?
Yes	9	75,0
No	3	25,0
Are there any features that need to be added according to the characteristics of the clinic or unit being implemented?
Yes	11	91,7
No	1	8,3
How would you rate the functionality of the app on a scale of 0 to 10?	(x̄)=8	(s) = 1,97
How would you rate your overall satisfaction with the app on a scale of 0 to 10?	(x̄)=8	(s) = 1,82

Discussion

Participants of this study believed that “Hospital Nurse Scheduling” was based on national laws, regulations and contracts, less time-consuming than manual scheduling and generated a standard, objective and fair timetable, which took nurse preferences into account, so that it may reduce internal conflicts within the organization and increase motivation.

Most participants were satisfied with the mobile app because it aimed at the target audience, its visual and text design provided user convenience, its content was objective, and followed legal regulations, it considered personal preferences, was less time-consuming, and contributed to professional practice. Our findings are consistent with those of other studies that have reported that fairness in scheduling, consideration of personal preferences [8, 13], flexibility, and nurses’ control over scheduling are important for increasing job satisfaction [3, 4, 13]. Besides these, the findings are important in terms of eliminating subjective practices in manual scheduling, such as using scheduling to reward or punish nurses [7, 8, 27]. Our findings indicate that mobile applications may reduce human errors [8, 10, 28]. To enhance the adoption and effectiveness of the mobile application, it is essential to provide adequate initial training for users and to ensure continuous technical and operational support during its use.

This study found that mobile applications were functional and satisfactory. Similarly, a qualitative study conducted with 10 nurse managers at a university hospital in İzmir, Turkey, found that using electronic shift schedules was less time-consuming and reduces the workload on responsible nurses, whereas manually preparing the work schedule was difficult and did not consider the demands of nurses [8]. Although various studies have been conducted on nursing work schedules that used models with various algorithms, including interactive computer-assisted scheduling methods and nurse needs-based automated systems, the number of mobile and web-based applications created specifically for nurse scheduling is limited due to high costs [13, 29]. (Nurse scheduling web application, PlanSIG.).

Existing studies that created mobile or web-based programs, such as those developing needs-based scheduling systems and optimization models, primarily focused on system functionality and efficiency, did not analyze nurse satisfaction [29, 30]. Some of the studies, including hospital-based research conducted in Turkey and international multi-center studies, reported that work schedules were manually prepared by responsible nurses [2, 3, 7, 8, 10, 27], often taking up to ten hours to complete due to the complexity of balancing various staffing needs [30]. In our case, the hospital regulations required that the timetable be made for a duration of four weeks. The daily use of the program was between 5 and 30 min, which increased to 30 to 45 min for the responsible nurse. The overall time needed for nurse scheduling was relatively short, given that the work schedules were generated in roughly 5 s. However, drawing firm conclusions from such a limited sample size could be deceptive.

Conclusions and suggestions

This study developed and tested a mobile application for a more objective, easy, and systematic generation of nurse work schedules and found that the functionality of the application was high and had various benefits compared with manual scheduling. Based on these findings, we suggest that the application be developed to include other clinics and units and tested in different clinics and hospitals. Additionally, further methodological studies on productivity analyses should be conducted. Finally, this application, which is unique to the literature, can also be used in other hospitals in Turkey. To more comprehensively evaluate the effectiveness of the application, future studies are recommended to empirically assess its optimization performance and include objective evaluations such as constraint satisfaction analysis, time savings measurement, and schedule quality comparison.

Limitations

The results of our study can only be generalized to our sample. Among other limitations, the sample size in which the developed program was piloted was only 12 and the program was used in only one setting. In addition, the instruments used to collect data were based on self-report. Additionally, although the study primarily focused on the development, usability, and user satisfaction of the mobile application, objective comparative analyses such as constraint satisfaction rates, time savings, and schedule quality assessments were not conducted during the pilot phase. This represents a limitation in evaluating the full optimization performance of the application.

Author contributions

The conception and study design: LD, MA Acquisition of the data: MAAnalysis and interpretation of data: LD, MARevising he article critically for important intellectual content: LDFinal approval of the version to be submitted: LD, MA.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethical approval

For conducting this study, an ethical approval was obtained from the Hacettepe University Ethical Commission (Ankara, Türkiye/GO16969557-1172 and 16969557-1242) -Interventional Clinical Research Ethics Committee. The research form included a consent box stating “I agree to participate in the study”, and those who did not provide consent could not complete the questionnaire. Informed consent to participate was obtained from all of the participants in the study. All procedures in the study were conducted in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Concent for publication

Not applicable.

Competing interests

The authors declare no competing interests.