Evaluation of Workflow Pattern of The Radiation Therapy Department: a Case Study of a Nigerian Tertiary Hospital

1. Introduction

Workflows date back to manufacturing in the 1920s and to the study of rational organization. Pioneers like Henry Gantt and Frederick Taylor who were early project managers and mechanical engineers extensively studied how work can be done efficiently and graphically, especially within the manufacturing domain(1). An organizational workflow such as that in the radiation oncology department requires a group of people or resources to achieve a predetermined goal(2). Three types of workflows may be built by workflow management systems, and the type used depends on the objective the project is set to accomplish. These workflows comprise, firstly, sequential workflow. This is similar to a flow chart, and follows a progressive and linear sequence, going from one task or process to the next without taking a step backwards. Secondly, state machine workflow is more complex than a sequential workflow and may step back in the sequence if the need arises. These workflows go from one “state” to another “state”.  Thirdly, rules-driven workflow. This is a higher-level sequential workflow where the workflow progresses are determined by “rules”(1,3).

The manual system is without a computer or any other automatic system and requires a human to push it through every step(3). This slows down the operation flow and may be prone to a higher rate of inaccuracy. Additionally, the effect of manual workflow on patient care is often obvious due to the misplacement of manually generated patient results causing patients’ dissatisfaction, and a dent in the hospital’s reputation(4,5). An automated system described in the literature requires a combination of software and hardware programmed to automatically execute tasks without requiring inputs and instructions from a human operator. The system manages the flow of tasks including notifications, and reminders, and enables a real-time process and prompt identification and resolution of problems(1,5).

Many composite, time-consuming, and difficult tasks are executed in the radiation therapy (RT) department daily by health workers that need to manage a diverse range of diagnosis and treatment needs. For some patients with the same condition, different examinations and treatments may be needed and the order in which they are conducted can vary greatly(6). A better workflow pursuing common patient-centered goals would aid the team coordination and facilitate the accomplishment of these goals, ensuring reliable, safe, and standard healthcare delivery; a core precept to mitigating adverse health outcomes(5,7).

In the past, the workflow employed in the radiation oncology department has been determined by its needs. Manual processes were developed to support limited technology and help the flow.  However, manual processes often increase turnaround time and retard report delivery. When the department receives a paper order, the order is usually physically processed in a staging room(9). The patient is designated as “new” or “returning” and their demographic information is entered or updated in the relevant applications. However, the correlation of patient data, images, and reports after the patient’s visit is mostly a manual effort which delays the processing of the patient’s order. At the end of the process, a patient report is delivered to a  physician who must then manually enter the data into patient’s electronic medical record system, taking valuable time and creating a higher probability of entry error(7,8,9).

In modern practice, it is becoming routine to design an efficient workflow that is supported by technology. Workflow improvements are also proving to decrease the cost of operation in medical imaging. This is usually accomplished through an efficient, proactive and profitable design and planning process(12). Reduction in patient waiting time is desirable in any radiation oncology department as it enables more patients to be treated over a given period. Some of these improvements include an electronic medical records (EMRs) system that combines patient’s clinical information and image data onto an easy accessible support that improves the radiologist’s interpretation process and maximizes productivity, automating and merging both billing and coding, facilitating reimbursement and potentially reducing operating costs(10-12).

One key indicator of a well-managed RT department is the time patients spend in the imaging department(14). Understanding the workflow by the staff members may help reduce the flow time for each patient and create room for suggestions that sometimes pinpoint to hurdles that cause delays (15,16).

The aim of this study was to assess staff’s perception on the factors that had a negative influence on the workflow efficiency of the RT department of a governmental tertiary hospital in Nigeria, as well as possible areas of improvement.

2. Materials and methods

This was a prospective cross-sectional survey, applied in the RT department of the University of Nigeria Teaching Hospital (UNTH), Ituku-Ozalla, Enugu, Nigeria. An average of 150 patients/ day were received here in 2021(17). The department is distinct from the Radiology department, has an Elekta Linear Accelerator, and a Computed Tomography (CT) machine. The types of delivered treatments include intensity modulated radiation therapy (IMRT), three-dimensional conformal RT (3D-CRT), and volumetric modulated arc therapy (VMAT).

The study population was represented by all the staff and interns who were actively involved in the daily activities of the radiation oncology department of the hospital during the time of distribution of questionnaires. Staff who were not part of the departmental workflow or could not comprehend written material were excluded. The researchers handed out the questionnaires to the staff who were required to respond appropriately and return upon completion.

Semi-structured questionnaires were used for data collection. Each questionnaire had 20 questions and was divided into four sections (A general and demographic questions; B factors that influence the workflow; C factors affecting the departmental workflow; D staff’s recommendations for improvement). Some of the questions were single choice, other multiple choice, and other were open ended. Qualitative assessment was used through Likert scale (SD=strongly disagree, D=disagree, A=agree and SA=Strongly agree in section C and very slow, slow, fast, and very fast in section D) (Annexa 1)

The necessary sample size was determined using the Yamane Taro formula, and  data was analyzed using Statistical Package for Social Sciences (SPSS) version 23 (IBM Corporation 2023) and descriptive statistics of frequency distribution and percentages were used to present the data.

3. Results

The average number of staff that were involved in daily activities of the department were: radiographers – 41, chief radiographers – 17, interns – 24, clerks (receptionists) – 10, payment area – 6, and darkroom technicians – 8. Hence, the total population investigated comprised 106 staff members. Yamane Taro formula indicated a minimal sample size of 84 for representativity. A total of 84 questionnaires were distributed to the respondents during the period of the study, out of which 70 questionnaires were completed and returned (83.3% response rate).

The most represented categories among respondents were men (n=43; 61.4%), aged between 20 and 30 years (n=50; 71.4%) radiographers (n=51; 72.9%), bachelor of science (n=55; 78.6%), and having less of 5 years of experience (n=41; 58.6%) (Table 1).

Table 1. Demographic and professional characteristics of the participants (n=70)

BSc= Bachelor of Science; HND= Higher National Diploma; OND= Ordinary National Diploma; MBBS= Bachelor of Medicine and Bachelor in Surgery; MSc= Master of Sciences; MD= Medical Doctor.

Fifty respondents (71.4%) stated that the department uses a combination of automated and manual methods of workflow; 19 (27.1%) declared that manual method is solely applied, while the automated method was perceived to be used by only one respondent (1.4%).

The main factors hypothesized that are disrupting the workflow, on which the respondents showed agreement (A or SA) were: equipment breakdown (n=63, 90%), staff shortage (n=58, 82.3%), outdated technology (n=53, 75.7%), and unstable power supply (n=51, 72.8%). The level of patient education and poor communication had a smaller percentage of strong agreement, but had an overall agreement of 62.1% and 65.6%, respectively (Table 2).

Table 2: Factors Affecting Workflow Pattern (n=70)

SD=Strongly Disagree, D=Disagree, A=Agree and SA=Strongly Agree, n=number

The areas that were perceived as needing improvement by most of the participants were: reporting (n=22; 31.4%) and reception/registration point (n=20; 28.6%). Only 6 of the respondents (8.6%) indicated that the payment point requires improvement (Figure 1).

Figure 1. Respondent’s views on areas that need improvement

One quarter (n=17; 24.3%) of the respondents recommended increasing staff number as a measure to improve workflow patterns in the radiation oncology department. Other recommendations included the provision of more diagnostic rooms, improved working conditions, and retraining of staff, corresponding to (n=9; 12.9%), (n=8; 11.4), and (n=5; 7.1) respectively (Figure 2).

Figure 2. Respondents’ recommendations on how to improve the workflow pattern

4. Discussion

The questionnaire identified the perception of the personnel of the factors impacting the workflow in the RT department, which is to the author’s knowledge the first evaluation on this topic in a Nigerian radiation oncology department. Another strength of our study is represented by getting feedback from a significant percentage of departments’ staff and including representatives from the main job categories.

The majority of the staff answering our survey were young radiographers, Bachelor of Science. Almost two thirds of the respondents considered that both Manual and Automated workflow is implemented. The main factors perceived disrupting the workflow were: equipment breakdown, shortage of staff, and inadequate power supply. Reporting and registration stand out as the areas that need improvement, according to more than half of the participants.

Workforce shortage in RT was reported in other countries, too (18-20). However, staff’s perception of insufficient workforce could be seen as unusual, since 40 radiographers are reported to work in a department with only one linear accelerator. According to the ESTRO-HERO survey on the equipment and staffing in European RT facilities, a range between 2 and 6 radiographers per linear accelerator existed in 2014 (21). This conclusion can be seen as the result of a suboptimal workflow, where healthcare works feel overwhelmed, even if there is a relative high number of employees.

A study done Umar et al. recorded patients’ perception regarding their care and, similarly, insufficient personnel, lack of modern machines, and resources were the main factors identified as potentially impacting the workflow(22). Similar findings regarding patients’ perceptions of factors impacting their care were reported by Nwobi et al.(23), and  Onwuzu et al.(24). Our findings align with a similar survey by Amo-Antwi et al.(25) who found inadequate equipment and distance to health facilities as the major factors limiting access to radiotherapy treatment in Ghanaian women with cervical cancer. It also corroborates with a study by Mackenzie et al.(26) that evaluated the barriers and facilitators to radiotherapy treatment in geriatric oncology in Australia.

A qualitative study  on workplace factors facilitating the radiographers’ assessment of referrals for diagnostic imaging, published  by Mork-Knudsen et al.(27) concluded that a lack of protocols make prioritization a difficult task and that a lack of process understanding by management leads to insufficient allocated time for certain tasks. Work overload was the major reason for this delay, and this agrees with the 2018 findings of England’s National Review of Radiology which recorded delays in reporting radiology examinations and backlogs in reporting are made worse by issues with staffing as there are not enough radiologists to meet current demand(28).

As patients are being passed through the various units of the RT department, there is a delay in workflow rate due to the aforementioned factors recorded by this study; a situation that the poor level of education of patients has exacerbated. Consequently, patients are faced with longer waiting times, suffer frustration from a high rate of postponement of imaging procedures, and aggravated health conditions. Therefore, a thorough independent analysis done by the administration is needed in order to establish the immediate priorities that may change the workflow (hiring more personnel, investing in a modern equipment and providing an emergency power supply).

The authors acknowledge that the study has some limitations, inherently related to the subjective perception of the respondents. Some of them asked the investigators supplementary questions when they experienced difficulties in understanding the questionnaire, which may have introduced bias. Unfortunately, no significant improvements were made since 2021 when the study was completed.

5. Conclusion

This study suggests that staff shortage, lack of modern technology and equipment breakdown may be the main factors that need to be assessed in order to improve the workflow of a reference Nigerian RT center.

Abbreviations

3D-CRT – three-dimensional conformal radiation therapy

A – Agree

BS – Bachelor of Science

D – Disagree

EMR – Electronic Medical Records

HND – Higher National Diploma

IMRT – intensity modulated RT

MBBS – Bachelor of Medicine and Bachelor in Surgery

MD – Medical Doctor

MSc – Master of Sciences

n – number

OND – Ordinary National Diploma

RT – radiation therapy

SA – Strongly Agree

SD – Strongly Disagree

UNTH – University of Nigeria Teaching Hospital

VMAT – volumetric modulated arc therapy

Statements

Authors’ Contributions: BIU and HTO conceived and planned the data acquisition. BIU and SCU contributed to the data analysis and result interpretation. BIU took the lead in writing the manuscript. BIU and HTO made the final approval. All authors provided essential feedback that shaped the accuracy and integrity of the research, analysis, and manuscript.

Consent for Publication: As the corresponding author, I confirm that the manuscript has been read and approved for submission by all the named authors.

Conflict of Interests: The authors declare no competing interest.

Funding Sources: None.

Statement of Ethics: Ethical approval was obtained from the ethics committee of the RT department, at the University of Nigeria Teaching Hospital (UNTH), Ituku-Ozalla, Enugu, Nigeria.

Acknowledgement: Our profound gratitude goes to the staff and members of the RT Department of UNTH, Ituku-Ozalla, Enugu, Nigeria for their acceptance and cooperation during our data collection.

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