How can the failure mode and effect analysis improve the working processes in the ART center?

OBJECTIVE(S)

Assisted reproductive technology (ART) Centers and laboratories perform complex tasks with patients and their gametes/embryos daily. The degree of problems/non-conformances in such surroundings must be minimized at zero point. This study aimed to establish the proper risk management system with well-defined process steps to prevent and eliminate problems/non-conformances.

STUDY DESIGN

Failure mode and effect analysis (FMEA) was introduced in the ART Center and the IVF laboratory. ART Center working processes were grouped into the categories of Clinical procedures, Forms, Identification, Personnel, Patients, and Facility. Working processes in the IVF laboratory were grouped into the categories of Consumables, Media, Equipment, Personnel, Working space, and Procedures. The traceability and safety of the working processes were evaluated before and after corrective measures regarding risk priority number (RPN). The severity (S), occurrence (O), and detection (D) index of problems/non-conformance were scaled from 1 to 5. The RPN was calculated by multiplying the SOD index, and the cut-off value for RPN was ≥12.

RESULTS

The increased RPN was found in the following working processes of the ART Center: Embryo transfer and pregnancy (RPN = 18) in the category of Clinical procedures; Informed consents and agreements (RPN = 16) in the category Forms; Continuous education of the knowledge and skills (RPN = 12) in Personnel category; Space conditions (RPN = 24) and Equipment (RPN = 12) in the category Facility. In the IVF laboratory, increased RPN was found in the following working processes: Production of the plasticware (RPN = 12), Transport (RPN = 12) and Storage (RPN = 12) in the category Consumables; Media production (RPN = 16) in category Media; Alarm notification system for the critical equipment (RPN = 12) in category Equipment; Personnel number and qualifications (RPN = 12), Standard operative procedures (SOP) (RPN = 12) and Continuous education of the knowledge and skills (RPN = 12) in category Personnel; Working conditions (RPN = 18) and Security (RPN = 20) in Working space; Patient identification (RPN = 20), Biological samples identification (RPN = 20), Records (RPN = 12), ART procedure (RPN = 30), Embryo transfer (RPN = 30) and Cryopreservation and thawing of biological samples (RPN = 30) in category Procedures. According to the RPN score, corrective measures were implemented. Most RPN scores were reduced after the implementation of the electronic witnessing system in patient/sample tracing steps. Phases Patient identification and Biological sample identification showed a double reduction of RPN scores, from 20 to 10. Also, for critical steps in ART procedures, Embryo transfer, Cryopreservation, and thawing of biological samples, the RPN score was reduced from 30 to 10. Proper education of personnel was another corrective measure that significantly contributed to a reduction of RPN scores in most of the categories.

CONCLUSION(S)

The FMEA analysis is useful in recognizing the critical steps of an ART Center. The RPN scores for patient traceability were successfully reduced using the electronic witnessing system. Nonetheless, the study has certain limitations, as FMEA is highly dependent on the specific healthcare organization, adherence to national guidelines, and the subjective nature of SOD and RPN evaluations.

Improved prospective risk analysis for clinical laboratories compensated for the throughput in processes

BACKGROUND

Practical application of prospective risk analysis (PRA) in clinical laboratories should reflect processes as they are carried out, while making the PRA results obtained from different processes comparable. This means that not only STAT and standard testing and testing for critical and less critical parameters should be distinguished (as published), but also that the throughput in processes and process steps should be taken into account.

METHODS

Building on our previously published PRA, a method was developed to compensate for the throughput in processes and process steps. A factor T, related to the actually observed throughput, was introduced in the risk score calculation. Introduction of this compensation factor leads to different overall risk scores. The criteria by which the risk scores are evaluated were modified accordingly.

RESULTS

Introduction of a factor in the PRA to compensate for throughput leads to a change in the risk score for various conceivable failures in process steps. As compared to the PRA in which no compensation for throughput is made, in a process with low throughput the risk score for various conceivable failures in process steps comes out higher after introduction of the compensation factor, while in a process with high throughput various risk scores come out lower.

CONCLUSIONS

Introduction of a factor to account for the throughput in a process (and process steps) leads to an improved, more realistic PRA, the results of which makes the risk scores of different processes (and process steps) better comparable to each other.