Introduction
In the medical field, endoscopic submucosal dissection (ESD), as a minimally invasive surgical technique for the treatment of early tumors and precancerous lesions in the gastrointestinal tract, has become the preferred treatment method due to its advantages of less trauma, faster recovery, and fewer complications [1]. However, due to its high technical requirements and complex operation, patients may still experience postoperative complications such as perforation and bleeding. These complications not only pose a threat to the patient’s health, but may also increase the hospitalization time and aggravate the financial burden of patients and their families.
Failure Model and Effect Analysis (FMEA) [2, 3], as an effective prospective risk assessment tool, is particularly important for its application in healthcare processes. FMEA optimizes the healthcare process by systematically identifying potential risk factors, analyzing their causes in depth, and taking preventive measures before problems occur processes to reduce the occurrence of adverse medical events. This approach not only helps to improve the quality of care, but is also an important part of continuous quality improvement.
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While a previous study [4] has focused on preoperative health education, psychological care, and optimization of the surgical care process in ESD, there remains a gap in the literature regarding comprehensive assessment and effective intervention of high-risk aspects within the care process. The objective of this study is to conduct an in-depth analysis of high-risk segments in the ESD care process through FMEA, and to develop and implement targeted improvement measures with the aim of reducing the risk of surgical care for ESD patients, improving the quality of care, and ensuring patient safety.
This study uses FMEA, a prospective risk assessment tool, to propose innovative care improvement strategies for specific high-risk aspects of the ESD care process. By validating the effectiveness of these strategies through empirical studies, this study is expected to provide new perspectives and methods for clinical nursing practice to further improve the quality of care. In addition, this study will also explore the effectiveness of FMEA in ESD nursing care to provide references and lessons for subsequent studies.
Materials and methods
Patient cohort demographics
This study included 82 patients, including 42 male patients (50.6%) and 40 Female patients (48.2%). The age distribution was predominantly middle-aged and elderly (40–70 years old). Educational levels varied, with a substantial representation at the junior high/technical secondary level (36.1%) and a notable proportion holding a bachelor’s degree or above (24.1%). For further details, see Table 1.
Table 1
Demographic characteristics (N = 82)
Variable | Category | Frequency | Percentage (%) |
|---|---|---|---|
Gender | Male | 42 | 50.6 |
Female | 40 | 48.2 | |
Age(years) | 20–39 | 4 | 4.9 |
40–59 | 29 | 35.4 | |
60–70 | 32 | 39.0 | |
> 70 | 16 | 19.5 | |
Educational levels | Illiterate, Primary School | 13 | 15.7 |
Junior High School, Technical Secondary School | 30 | 36.1 | |
High School, College | 18 | 21.7 | |
Bachelor’s Degree and Above | 20 | 24.1 |
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The control group consisted of 40 patients who were hospitalized and underwent ESD between July and September 2023. The observation group consisted of 42 patients who were hospitalized and underwent ESD between October 2023 and June 2024 after implementing FMEA. The demographic profiles of the two patient groups were compared, including age, gender, and surgical sites, and there were no significant differences between the two groups (P > 0.05) (Table 2).
Table 2
Comparison of age, gender, and Lesion Site scores between two groups (M ± SD, points)
Age | Gender | Surgical sites | |
|---|---|---|---|
Control group | 60.70 ± 11.57 | 1.55 ± 0.50 | 3.78 ± 2.34 |
Observation group | 60.19 ± 12.78 | 1.43 ± 0.50 | 4.02 ± 2.34 |
F | 0.036 | 1.197 | 0.232 |
P | 0.851 | 0.277 | 0.632 |
Methods
Formation of a multidisciplinary FMEA team for ESD
Given the complexity of endoscopic submucosal dissection, which involves collaboration across multiple departments, project team members should avoid being composed solely of endoscopic nursing staff and include multidisciplinary and multidepartmental collaboration. This diverse team composition helps to comprehensively analyze and optimize the ESD process. The inclusion criteria for team members were (1) at least 5 years in GI endoscopic medicine; and at least 5 years in GI endoscopic nursing, or at least 3 years in GI endoscopic nursing after obtaining hospital-level or higher specialty nurse qualification; at least 5 years in nursing management; and at least 5 years in ambulatory anesthesia. (2) Familiar with gastrointestinal endoscopy management and the ESD process; strong research skills; bachelor’s degree or above. The final team consists of gastrointestinal endoscopists, nurse leaders of large departments of outpatient focus, nurse leaders of endoscopy units, advanced practice nurses (APN) in endoscopy, endoscopy nurses, and anesthesiologists, totaling 6 people. The team members covered the principles of multidisciplinary, multidepartmental, multilevel, and highly educated formation to ensure the effective promotion and implementation of FMEA.
The head nurse from the major department led the team, overseeing the FMEA process to ensure everything ran smoothly and in an organized way. The head nurse from the endoscopy unit was responsible for tasks and roles to each team member. The APN focused on executing the work projects. This included arranging training sessions for the team on FMEA concepts, analyzing case studies, and initiating discussions. After each training, the APN also assessed the team members to make sure they were adept at using FMEA for case analysis. Collection of ratings session: team members’ ratings will be collected and sealed in opaque envelopes as soon as they are independently completed and folded.The envelopes will be forwarded to the statistician by the APN and no one will be authorized to view the contents of the envelopes during the entire process. The gastrointestinal endoscopist was responsible for assessing the risk of surgical operation, recording the surgical procedure, and evaluating the preoperative preparation and intraoperative nursing cooperation. The anesthesiologist was responsible for the preoperative anesthesia assessment of the patient and perioperative anesthesia management. They also monitored and recorded the the preoperative temperature and humidity regulation of the operating room, ensured the patient was positioned correctly, and coordinated the handover process between the endoscopy nurse and the anesthesia recovery room after the surgery. The endoscopy nurses were responsible for the evaluation and recording of the collection of general patient information, preoperative preparations, intraoperative cooperation and the management of postoperative specimens. This team structure ensures that every aspect of the ESD procedure is carefully managed and that all team members are equipped with the necessary skills and knowledge to perform their roles effectively. (Details of team member: Table 3).
Table 3
Information of FMEA team members for ESD
Entry | General information | Number of people | Proportion |
|---|---|---|---|
Professional title | Senior | 2 | 33.3% |
Intermediate | 3 | 50% | |
Junior | 1 | 16.7% | |
Work Experience | 20 years and above | 3 | 50% |
10–19 years | 2 | 33.3 | |
6–10 years | 1 | 16.7% | |
Education background | Postgraduate degree | 2 | 33.3% |
Bachelor’s degree | 4 | 66.7% |
Differences in the implementation of the FMEA model across different teams or individuals can lead to differences in results. We follow strict standard operating procedures for FMEA model implementation and hold regular calibration meetings to ensure that all assessors have a consistent understanding of the assessment criteria. Regular monitoring and supervision by the unit nurse manager ensures consistency in model application.
Problem analysis and flowchart design
Following the guidelines for perioperative management of ESD and incorporating extensive team training and clinical experience, the team conducted collaborative brainstorming sessions by engaging in interactive communication and discussions to establish a comprehensive nursing flowchart for ESD. This meticulously designed flowchart encompasses 3 main processes: pre-operation, intra-operation, and post-operation, further delineated into 13 sub-processes. (Fig. 1)
Fig. 1
A preliminary design flowchart of ESD care plan. Note ESD: endoscopic submucosal dissection
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Identification and confirmation of potential failure models and analysis of failure causes
Following the perioperative analysis of patients who underwent ESD at our hospital between July and September 2023, we have integrated findings with literature reviews [5, 6] and engaged in discussions and brainstorming sessions. This comprehensive approach has prompted our team to perform a high-risk assessment of the ESD perioperative care process. Our objective is to identify potential failure modes that could compromise the procedure’s quality, prolong its duration, or jeopardize patient safety. To achieve this, we have conducted in-depth intra-team discussions to thoroughly examine the high-risk failure modes identified. By leveraging brainstorming and root cause analysis, we have revealed the potential causes and consequences of each failure mode, ensuring a thorough understanding of the risks involved in the ESD process.
A total of 13 potential failure modes were obtained in this study. Six potential failure modes were identified through the literature review: many air bubbles and mucus in the patient’s stomach; poor intestinal cleansing of the patient; nervousness and fear of the patient, lack of nurse-patient trust; nurses going in and out of the operating room to look for items during the operation; equipment malfunctions; insufficient nursing professional skills leading to errors in specimen collection. Three potential failure modes were identified through the team brainstorming: low temperature in the operating room, low awareness of tripartite verification, and patient falls/bed fall/stress injuries. Four potential failure modes were identified through pre-focused interview research: insufficient fasting time, deviation in patient’s intraoperative position, increased postoperative risks, and the occurrence of complications such as postoperative bleeding and perforation (Table 4).
Table 4
Analysis of failure models in perioperative care for ESD
Sub-process | Potential failure model | Failure cause | Failure consequence |
|---|---|---|---|
Patient gastrointestinal preparation quality assessment. | Accumulation of excessive gas bubbles and mucus in the stomach; Inadequate intestinal hygiene. | Medication administration timing is poorly controlled, Unpleasant medication taste, insufficient water intake, and lack of physical activity. | Impaired visibility of the surgical field. |
Patient dietary preparation. | Insufficient duration of fasting. | Poor patient compliance. | Delayed initiation of surgery. |
Nurse-Patient communication | Patient exhibits heightened anxiety, fear, and lack of confidence in nursing staff. | Ineffective communication due to hectic work schedule of nurses. | Increased administration of anesthesia drugs, resulting in compromised trust between nursing staff and patients. |
Medication and item preparation | Frequent entry and exit of nurses from the operating room during surgical procedures to retrieve medical items. | Commonly used items are improperly stored. Surgery preparation is inadequate or necessary items cannot be located quickly during the procedure. | Slow progress during surgery. |
Equipment, instruments, and accessory preparation. | Equipment malfunctions that fail to meet intraoperative requirements. | Improper procedures performed. Failure to test functionality before surgery or malfunction occurring during the procedure. | Slow progress during surgery. |
Operating room temperature and humidity regulation. | Relatively low temperature within the operating room. | Insufficient preoperative preparation time due to hectic work schedule of nurses. | Intraoperative hypothermia. |
Positioning of the patient. | Inaccurate positioning during surgical procedure. | Changes in patient positioning after anesthesia. | Repositioning during surgery. |
Triple verification. | Diminished consciousness levels. | Tedious and hectic work. | Heightened surgical risks. |
Nursing coordination. | Deficiencies in professional skills proficiency. | Limited theoretical knowledge. Less successful surgical collaboration. | Further delay in the surgical process. |
Specimen collection. | Errors occurring during specimen collection processes. | Failure to strictly adhere to verification protocols. | Specimen loss or misidentification. |
Patient safety. | Patient falls/bed falls/occurrence of pressure injuries. | Safety precautions are incomplete. | Prolonged hospitalization duration. |
Patient hand-off in the post-anesthesia care unit. | Increased postoperative risks. | Ineffective management practices. | Prolonged hospitalization duration. |
Postoperative dietary and activity instructions. | Occurrence of complications such as postoperative bleeding and perforation. | Failure to inform patients about relevant details. | Prolonged hospitalization duration. |
Calculation of Risk Priority Numbers (RPNs) and determination of priority failure model
The evaluation was conducted based on three dimensions: severity (S), frequency of occurrence (O), and likelihood of detection (D) to assess the failure. The RPN was calculated by multiplying these three dimensions, resulting in RPN = S * O * D, with a range between 1 and 1000. A higher RPN value signifies greater severity of consequences should the failure mode occur, thus necessitating the implementation of measures to mitigate its occurrence. If the RPN value for a failure model exceeds 125, it becomes necessary to initiate measures for improvement. In this study, the RPN index was calculated by examining the ESD nursing failure modes in our hospital from July to September 2023, and the RPN values were averaged from the results of six panelists. Failure patterns with RPN ≥ 125 or S ≥ 9 were selected with the cause of failure. The final result was four priority failure models: medication and item preparation; equipment, instruments, and accessory preparation; and nursing coordination and specimen collection.
Formulation of improvement measures
The team investigated potential causes for failure in the prioritized failure models by referring to relevant literature and applying the triangulation method, which integrates focus interviews, brainstorming sessions, and clinical observations. Through multiple discussions and thorough analyses, the underlying root causes were identified. Based on these identified causes, corresponding improvement measures were devised to proactively prevent the occurrence of failure models (Table 5).
Table 5
Formulation of improvement measures based on FMEA
Priority failure model | Improvement measures |
|---|---|
Medication and item preparation. | 1. Standardize the storage location and quantity of commonly utilized materials. 2. Collaborate with the endoscopist to comprehend the surgical strategy, anticipate the required items during the procedure, and ensure their availability. 3. Self-acquaintance of the location of infrequently used items. |
Equipment, instruments, and accessory preparation | 1. Prior to surgery, inspect and adjust the equipment parameters of the endoscopy unit, therapeutic endoscope, high-frequency electric workstation, water pump, CO2 device, and ensure they are in optimal working condition. 2. Ensure that instruments such as electrocautery knives, hemostatic forceps, metal clips, and transparent caps for endoscopes are fully prepared and neatly arranged for convenient accessibility during surgery. 3. Organize foot pedals for high-frequency electric current control, image capture control, and water pump according to surgeon preferences in a systematic manner. 4. Develop contingency plans in case of equipment malfunction during surgery. |
Nursing coordination | 1. Gain comprehensive understanding of each step involved in the surgical procedure, including its nursing considerations and potential challenges. 2. Acquire expertise in proficiently utilizing various instruments and accessories through rigorous practice. 3. Foster collaboration to proactively prevent complications during surgery and effectively manage any emergency. |
Specimen collection | 1. ESD procedures involve relatively large resection of specimens; ensure specimen integrity by utilizing instrument assistance in conjunction with negative pressure extraction. 2. When fixing or labeling specimens, implement a dual verification process involving both nurses and doctors to mitigate the risk of errors. 3. Prior to transporting specimens, nurses should conduct a comprehensive double-verification with transport personnel and obtain signatures as confirmation. |
Statistical analysis
This study used a single-blind method to ensure that the statisticians were not aware of the grouping of the data during the data analysis process. Statisticians completed the data analysis independently and then submitted the results directly to the APN, and they did not share or discuss the results of their analyses with any other person in the process.
The RPN values of the four prioritized failure modes of medication and item preparation, specimen collection, equipment, instrument and accessory preparation, and nursing coordination in the control and observation groups were compared using the statistical method of t-test (independent samples t-test). All statistical analyses were conducted using SPSS 25.0, with a significance level set at P < 0.05.
Results
Flowcharting the ESD care program based on the FMEA model
Using the FMEA model as a guide, our team collaborated to create a new flowchart for the ESD care program. This updated flowchart will be used for training future staff and as a reference for learning. It will also serve as a benchmark to compare against the existing ESD care program helping us to identify areas for improvement (Fig. 2).
Fig. 2
A new flowchart of the ESD care program based on the FMEA model. Note ESD: endoscopic submucosal dissection; FMEA: Failure Model and Effect Analysis; ICU: intensive care unit
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Comparison of RPN between the two groups before and after implementation of the improvement
Following the implementation of improvement measures, the t-values for medication, preparation of items, specimen collection, preparation of equipment, instruments and accessories, nursing cooperation, were all very high, indicating that the mean differences between the two groups were very large. Meanwhile, the p-values were all less than 0.001, indicating that the differences were statistically significant, and the significant statistical differences support the effectiveness of FMEA in improving the quality of care and reducing the risk of surgery (Table 6).
Table 6
Comparison of RPN before and after improvement measures
Failure model | Control group | Observation group | T value | P value |
|---|---|---|---|---|
Medication and item preparation | 295.097 ± 47.906 | 119.428 ± 11.172 | 22.85 | < 0.001 |
Specimen collection | 172.317 ± 24.439 | 96.809 ± 17.957 | 15.75 | < 0.001 |
Equipment, instruments, and accessory preparation | 171.926 ± 39.893 | 82.857 ± 23.546 | 12.27 | < 0.001 |
Nursing coordination | 164.463 ± 26.910 | 89.380 ± 17.891 | 14.82 | < 0.001 |
Discussion
The FMEA is a risk management methodology developed by the National Center for Patient Safety (NCPS) in the United States to improve medical safety. It utilizes a scientific approach to identify, quantify, evaluate, and control risks while maximizing safety benefits with minimal costs. Extensive research has demonstrated its application across various specialties including hospital infection control, pharmaceutical distribution, patient safety in cancer chemotherapy, hemodialysis, and intensive care unit, and radiation therapy risk management [7‐13]. FMEA also finds relevance in nursing and is predominantly utilized in surgical specimen management, implementation of intravenous drug administration technology, home parenteral nutrition, emergency pediatric nursing, and as well as in emergency endoscopic examination. A Study has indicated that utilizing FMEA models can effectively prevent errors in any stage of the specimen management process and reduce peri-operative nurse-related specimen errors [14]. Prior utilization of FMEA models before implementing intravenous drug administration technology can mitigate risks while optimizing workflow efficiency and minimizing medication errors during chemotherapy preparation [15]. Home parenteral nutrition is a vital clinical intervention that significantly improves patient outcomes; however, undetected hazards or vulnerabilities during the transition from hospital to community care may jeopardize patient safety. Utilizing FMEA throughout the nursing process improves awareness regarding the significance and function of nutritional units [16]. FMEA serves as an invaluable tool for identifying potential risks when analyzing the effect of improvement strategies on monitoring complex clinical departmental risk levels while enhancing patient safety in emergency nursing of pediatric patients [17]. In addition, FMEA has been widely used in the field of gastrointestinal endoscopy diagnosis and surgery. For example, in the emergency endoscopy process for patients with bleeding esophagogastric varices, the application of FMEA effectively optimizes process management [18]. In surgical perioperative risk management, FMEA can foresee potential failure links, identify improvement priorities, analyze the causes of failure, and significantly reduce the incidence of perioperative medical adverse events through the implementation of symptomatic measures to ensure the safety of patient surgery [19]. Through these applications, FMEA has become an important tool for improving healthcare quality and patient safety. ESD improves the resection rate of lesions and ensures the complete removal of diseased tissue in the treatment of gastrointestinal diseases, resulting in surgical-level efficacy and improving the quality of life of patients while preserving the structural integrity of the gastrointestinal tract [20, 21]. Although surgery is highly effective in treating certain diseases, it is also important to incorporate effective nursing care to improve clinical outcomes. Patients can experience unforeseen risks during surgery, thus it is essential for nursing staff and doctors to collaborate closely [22].
In the current study, a multidisciplinary team for ESD was established based on the FMEA model. The team conducted brainstorming sessions to determine the nursing flowchart for ESD, which encompasses 3 main processes and 13 sub-processes. Root cause analysis was used to discuss and analyze each sub-process to identify potential failure models, their underlying causes, and associated consequences. The RPN index was calculated for each failure model, and those with a value exceeding 125 were classified as high-risk failure models. By ranking the RPN values in descending order, four priority failure models were identified: medication and item preparation, specimen collection, equipment and instruments, and accessory preparation and nursing coordination. The team investigated the potential causes of these priority failure models to identify the root causes. Corresponding improvement measures were then formulated to prevent the occurrence of such failure models. Following implementation of these improvement measures, a significant decrease in RPN values was observed. This indicated that implementing FMEA in patients with ESD has clinical significance as it effectively mitigates the risk factors associated with nursing care for ESD while reducing surgical risks and enhancing nursing quality to ensure patient safety.
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Although this study provides preliminary evidence regarding the application of FMEA in the care of ESD patients, we realize that as a single-center study with a limited sample size, our findings may be somewhat limited. To improve the generalizability and reliability of the findings, we suggest that future studies should adopt a multicenter design and increase the sample size to further validate the findings of this study. In addition, although FMEA is a powerful risk assessment tool, in the absence of a standardized assessment scale, the professional background and cognitive level of the assessor may affect the judgment of failure modes and thus bias the assessment of RPN. To minimize this bias, we adopted a strict training and assessment procedure for team members in our study and implemented a single-blind methodology in the data analysis stage to ensure rigor in data analysis and objectivity in results. Specifically, statisticians are completely unaware of the specific grouping of the data as they conduct the data analysis and report the results. This blinded design safeguards the analysts’ independence by allowing them to conduct their analysis based solely on the data itself, without being influenced by any potential bias that may be introduced by the grouping information. To further enhance the transparency and credibility of the study, statisticians reported their results directly to APN after independently completing the data analysis and did not share or discuss the results of their analysis with any other person in the process. This strict confidentiality measure and transparent reporting process ensured the impartiality of the data analysis and the reliability of the study results, while maintaining the integrity and scientific validity of the study. We believe that with these measures, future studies will be able to more accurately assess the effectiveness of FMEA in clinical care and provide a more solid evidence base for nursing practice.
Conclusions
The FMEA model can effectively enables early nursing intervention for risks associated with ESD surgery. By proactively identifying and evaluating potential failure models in ESD care and developing corresponding improvement measures for these failures, the model facilitates continuous enhancement of nursing quality. This approach significantly contributes to reducing surgical care risks, improving surgical safety, and ensuring patient safety.
Acknowledgements
We would like to acknowledge the hard and dedicated work of all the staff that implemented the intervention and evaluation components of the study.
Declarations
Ethics approval and consent to participate
This study was conducted with approval from the Ethics Committee of Zhengzhou Central Hospital affiliated to Zhengzhou University. This study was conducted in accordance with the declaration of Helsinki. Written informed consent was obtained from all participants.
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Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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