The Utility of Failure Modes and Effects Analysis of Consultations in a Tertiary, Academic, Medical Center

Examination of the Protein Drug Supply Chain in a Swedish University Hospital: Focus on Handling Risks and Mitigation Measures

Protein drugs, such as monoclonal antibodies, have proved successful in treating cancer and immune system diseases. The structural complexity of these molecules requires careful handling to ensure integrity and stability of the drug. In this study, a failure mode and effects analysis was performed based on a Gemba Walk method in a Swedish University Hospital. The Gemba Walk is focused on pharmacists observing the actual supply process steps from distributor, pharmacy cleanroom to patient administration. Relevant protein drugs are chosen based on sales statistics within the hospital and the corresponding wards were observed. Further is the Double Diamond design method used to identify major risks and deliver mitigation strategies. The study identified potential stress factors such as temperature, shock by impact, shaking, vibration and light exposure. There were also risks associated with porters' and healthcare professionals' lack of awareness and access to information. These risk factors may cause loss of efficacy and quality of the protein drug, potentially leading to patient safety concerns. In this study, a simulation is also performed to list measures that theoretically should be in place to ensure the quality of the protein drug, for example validated and protocol-based compounding in cleanroom, training and validated transports.

Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS)

We performed FMEA on the existing RRS with the help of routine users of the RRS who acted as subject matter experts and evaluated the failures for their criticality using the Risk Priority Number approach based on their experience of the RRS. The FMEA found 35 potential failure modes and 101 failure mode effects across 13 process steps of the RRS. The afferent limb of RRS was found to be more prone to these failures (62, 61.4%) than the efferent limb of the RRS (39, 38.6%). Modification of calling criteria (12, 11.9%) and calculation of New Zealand Early Warning Scores (NZEWS) calculation (11, 10.9%) steps were found to potentially give rise to the highest number of these failures. Causes of these failures include human error and related factors (35, 34.7%), staff workload/staffing levels (30, 29.7%) and limitations due to paper-based charts and organisational factors (n = 30, 29.7%). The demonstrated electronic system was found to potentially eliminate or reduce the likelihood of 71 (70.2%) failures. The failures not eliminated by the electronic RRS require targeted corrective measures including scenario-based training and education, and revised calling criteria to include triggers for hypothermia and high systolic blood pressure.

Failure mode and effects analysis for proactive healthcare risk evaluation: A systematic literature review

RATIONALE, AIMS, AND OBJECTIVES

Failure mode and effects analysis (FMEA) is a valuable reliability management tool that can preemptively identify the potential failures of a system and assess their causes and effects, thereby preventing them from occurring. The use of FMEA in the healthcare setting has become increasingly popular over the last decade, being applied to a multitude of different areas. The objective of this study is to review comprehensively the literature regarding the application of FMEA for healthcare risk analysis.

METHODS

An extensive search was carried out in the scholarly databases of Scopus and PubMed, and we only chose the academic articles which used the FMEA technique to solve healthcare risk analysis problems. Furthermore, a bibliometric analysis was performed based on the number of citations, publication year, appeared journals, authors, and country of origin.

RESULTS

A total of 158 journal papers published over the period of 1998 to 2018 were extracted and reviewed. These publications were classified into four categories (ie, healthcare process, hospital management, hospital informatization, and medical equipment and production) according to the healthcare issues to be solved, and analyzed regarding the application fields and the utilized FMEA methods.

CONCLUSION

FMEA has high practicality for healthcare quality improvement and error reduction and has been prevalently employed to improve healthcare processes in hospitals. This research supports academics and practitioners in effectively adopting the FMEA tool to proactively reduce healthcare risks and increase patient safety, and provides an insight into its state-of-the-art.