Using Failure mode and Effects Analysis to reduce patient safety risks related to the dispensing process in the community pharmacy setting

Resilience and Protection of Health Care and Research Laboratory Workers During the SARS-CoV-2 Pandemic: Analysis and Case Study From an Austrian High Security Laboratory

The SARS-CoV-2 pandemic has highlighted the interdependency of healthcare systems and research organizations on manufacturers and suppliers of personnel protective equipment (PPE) and the need for well-trained personnel who can react quickly to changing working conditions. Reports on challenges faced by research laboratory workers (RLWs) are rare in contrast to the lived experience of hospital health care workers. We report on experiences gained by RLWs (e.g., molecular scientists, pathologists, autopsy assistants) who significantly contributed to combating the pandemic under particularly challenging conditions due to increased workload, sickness and interrupted PPE supply chains. RLWs perform a broad spectrum of work with SARS-CoV-2 such as autopsies, establishment of virus cultures and infection models, development and verification of diagnostics, performance of virus inactivation assays to investigate various antiviral agents including vaccines and evaluation of decontamination technologies in high containment biological laboratories (HCBL). Performance of autopsies and laboratory work increased substantially during the pandemic and thus led to highly demanding working conditions with working shifts of more than eight hours working in PPE that stressed individual limits and also the ergonomic and safety limits of PPE. We provide detailed insights into the challenges of the stressful daily laboratory routine since the pandemic began, lessons learned, and suggest solutions for better safety based on a case study of a newly established HCBL (i.e., BSL-3 laboratory) designed for autopsies and research laboratory work. Reduced personal risk, increased resilience, and stress resistance can be achieved by improved PPE components, better training, redundant safety measures, inculcating a culture of safety, and excellent teamwork.

Use of failure mode and effect analysis to reduce patient safety risks in purchasing prescription drugs from online pharmacies in China

Background

Online pharmacies have gradually penetrated the market, but pose risks to patients' health. Failure Mode and Effect Analysis (FMEA) is an effective and reliable method for reducing pharmacy and medication risks. The purpose of this study was to conduct a prospective risk analysis of the process of purchasing prescription drugs from online pharmacies in China to guarantee drug quality and patient safety.

Methods

The FMEA was performed at Sichuan University, China. A multidisciplinary team was assembled comprising a leader, four regulators, four pharmacists, two experts, etc. The process was composed of eight subprocesses: searching for prescription drugs, submitting medication requirements, completing patient information forms, dispensing, delivering, etc. Brainstorming was used to identify and prioritize failure modes, propose corrective actions, and reduce risks. Risk priority numbers were the main criterion and were obtained by multiplying three scores: severity, occurrence and detectability, which were scored by the team The team proposed corrective actions for each selected failure mode.

Results

A total of forty-one potential failure modes were identified, and the causes, effects, and corrective actions of the 30 top failure modes were analyzed. The highest risk value was assigned to “photocopies of paper prescriptions uploaded were reused by patients.” Three failure modes for the S value of 5 were: “drugs are eroded and polluted by moisture or insects in the process of transportation,” “the qualification information of the pharmacies were absent or fake,” and “pharmacists fail to check prescriptions in accordance with Prescription Administrative Regulation.” Of the top failure modes, 36.67% were from Step 5, delivering the drug. After taking corrective measures to control risks, the risks reduced by 69.26%.

Conclusion

The results of this study proves that the FMEA is a valuable tool for identifying and prioritizing the risks inherent in online pharmacies. This study shows that there are many potential risks in the process of purchasing prescription drugs from online pharmacies, especially in the drug delivery stage. Enhanced training and the introduction of smart devices may minimize risks. Online pharmacies and Chinese regulators should consider these findings for risk mitigation and the improvement of regulations pertaining to online pharmacies.

Predicting dispensing errors in community pharmacies: An application of the Systematic Human Error Reduction and Prediction Approach (SHERPA)

Introduction

The objective of this study was to use a prospective error analysis method to examine the process of dispensing medication in community pharmacy settings and identify remedial solutions to avoid potential errors, categorising them as strong, intermediate, or weak based on an established patient safety action hierarchy tool.

Method

Focus group discussions and non-participant observations were undertaken to develop a Hierarchical Task Analysis (HTA), and subsequent focus group discussions applied the Systematic Human Error Reduction and Prediction Approach (SHERPA) focusing on the task of dispensing medication in community pharmacies. Remedial measures identified through the SHERPA analysis were then categorised as strong, intermediate, or weak based on the Veteran Affairs National Centre for Patient Safety action hierarchy. Non-participant observations were conducted at 3 pharmacies, totalling 12 hours, based in England. Additionally, 7 community pharmacists, with experience ranging from 8 to 38 years, participated in a total of 4 focus groups, each lasting between 57 to 85 minutes, with one focus group discussing the HTA and three applying SHERPA. A HTA was produced consisting of 10 sub-tasks, with further levels of sub-tasks within each of them.

Results

Overall, 88 potential errors were identified, with a total of 35 remedial solutions proposed to avoid these errors in practice. Sixteen (46%) of these remedial measures were categorised as weak, 14 (40%) as intermediate and 5 (14%) as strong according to the Veteran Affairs National Centre for Patient Safety action hierarchy. Sub-tasks with the most potential errors were identified, which included ‘producing medication labels’ and ‘final checking of medicines’. The most common type of error determined from the SHERPA analysis related to omitting a check during the dispensing process which accounted for 19 potential errors.

Discussion

This work applies both HTA and SHERPA for the first time to the task of dispensing medication in community pharmacies, detailing the complexity of the task and highlighting potential errors and remedial measures specific to this task. Future research should examine the effectiveness of the proposed remedial solutions to improve patient safety.

Preventing dispensing errors through the utilization of lean six sigma and failure model and effect analysis: A prospective exploratory study in China

AIMS

To utilize lean six sigma (LSS) and failure model and effect analysis (FMEA) to prevent dispensing errors in a Chinese teaching hospital.

METHODS

Medication errors (MEs) reported to the China Core Group of the international network for the rational use of drugs (INRUD) by pharmacists at the hospital were collected. Following LSS methodology, the data analysis was structured according to define, measure, analyse, improve, and control (DMAIC) phases, and typical LSS tools (Pareto diagrams, brainstorming sessions) were used to determine the risk factors leading to dispensing errors. FMEA was applied to generate the risk priority numbers (RPNs) of MEs events, and key medications targeted for error prevention strategies were identified through quantitative analysis of the impacts of failure. Finally, corrective measures to prevent MEs were implemented and monitored for efficacy.

RESULTS

Before the implementation of this programme, a total of 603 cases of dispensing errors were reported from the Year 1 to Year 6, reaching an average rate of incidence of 0.33 cases per 10 000 medication orders delivered, and no difference was found between these years (P = .9424). There was also no difference as location, error type, contributing factors, cause classification were considered. We then determined the real cause behind dispensing errors, and a total of 67 medications were targeted for specific error prevention strategies. One year after intervention, progress had been achieved in the following aspects: the incidence rate of dispensing errors was significantly decreased compared with the previous years (0.19, P = .007). Simultaneously, the incidence rate of dispensing errors occurred in outpatient pharmacy (0.04, P = .0008), with junior pharmacists (0.15, P = .0258), with LASA medications (0.06, P = .0319), as well as with memory-based errors were significantly decreased (0.03, P = .0191).

CONCLUSION

The combination of LSS and the FMEA tool can be an efficient approach for helping reduce MEs in pharmacy dispensing.

Application of failure mode and effects analysis (FMEA) to improve medication safety in the dispensing process - a study at a teaching hospital, Sri Lanka

Background

Failure mode and effects analysis (FMEA) is a prospective, team based, structured process used to identify system failures of high risk processes before they occur. Medication dispensing is a risky process that should be analysed for its inherent risks using FMEA. The objective of this study was to identify possible failure modes, their effects, and causes in the dispensing process of a selected tertiary care hospital using FMEA.

Methods

Two independent teams (Team A and Team B) of pharmacists conducted the FMEA for two months in the Department of Pharmacy of a selected teaching hospital, Colombo, Sri Lanka. Each team had five meetings of two hours each, where the dispensing process and sub processes were mapped, and possible failure modes, their effects, and causes, were identified. A score for potential severity (S), frequency (F) and detectability (D) was assigned for each failure mode. Risk Priority Numbers (RPNs) were calculated (RPN=SxFxD), and identified failure modes were prioritised.

Results

Team A identified 48 failure modes while Team B identified 42. Among all 90 failure modes, 69 were common to both teams. Team A prioritised 36 failure modes, while Team B prioritised 30 failure modes for corrective action using the scores. Both teams identified overcrowded dispensing counters as a cause for 57 failure modes. Redesigning of dispensing tables, dispensing labels, the dispensing and medication re-packing processes, and establishing a patient counseling unit, were the major suggestions for correction.

Conclusion

FMEA was successfully used to identify and prioritise possible failure modes of the dispensing process through the active involvement of pharmacists.

Application of Failure Mode and Effect Analysis (FMEA) to improve medication safety: a systematic review

Medication safety is a phenomenon of interest in most healthcare settings worldwide. Failure Mode and Effect Analysis (FMEA) is a prospective method to identify failures. We systematically reviewed the application of FMEA in improving medication safety in the medication use process. Electronic databases were searched using keywords ((failure mode and effect analysis) AND (pharmacy OR hospital)). Articles that fulfilled prespecified inclusion criteria were selected and were then screened independently by two researchers. Studies fulfilling the inclusion criteria and cited in articles selected for the study were also included. Selected articles were then analysed according to specified objectives. Among 27€706 articles obtained initially, only 29 matched the inclusion criteria. After adding four cited articles, a total of 33 articles were analysed. FMEA was used to analyse both existing systems and new policies before implementing. All participants of FMEA reported that this process was an effective group activity to identify errors in the system, although time-consuming and subjective.

[Prospective risk analysis in a retrocession unit: Focus on drug dispensation process]

OBJECTIVES

Failure mode effect analysis (FMEA) improves safety in the drug life cycle. As the drug dispensation by hospital's pharmacy can be at risk, the FMEA tool has been used to evaluate and enhance the process.

METHODS

After detailing the process, a first FMEA has been run in 2015. Corrective actions were implemented every time criticality indexes (CI) were above 15. One year later, we have evaluated potential impacts of these actions by running a new FMEA.

RESULTS

In 2015, 11 failure modes were prioritized (CI>15) and the total CI for the overall process was 397. Corrective actions were implemented and one year later this amount has decreased by 14% (340) with 6 failure modes still prioritized. Thus, thanks to the FMEA, risks could be identified in year "y", they were taken into account and corrected and then effectively reassessed in year "y+1".

CONCLUSION

This study showed us the interest of performing FMEA analysis in the drug dispensation process by hospital. The renewal of this risk analysis after a year helped us to monitor corrective actions, to evaluate their effectiveness and to improve safety. Finally, FMEA seems to be an effective way to steer the drug dispensation process.