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Original research
Failure mode and effect analysis applied to improve the medication management process in a pharmacy of a teaching hospital and a proposal for a simplified rating system
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  1. Aïmen Abbassi1,2,
  2. Ahlem Ben Cheikh Brahim1,
  3. Zeineb Ouahchi1,3
  1. 1 Pharmacy, Charles Nicolle Hospital, Tunis, Tunisia
  2. 2 Pharmacognosy, University of Monastir College of Pharmacy, Monastir, Monastir, Tunisia
  3. 3 Clinical Pharmacy, University of Monastir College of Pharmacy, Monastir, Monastir, Tunisia
  1. Correspondence to Dr Aïmen Abbassi, Pharmacy, Hopital Charles Nicolle, 1006 Tunis, Tunisia; abbassi.aimen{at}gmail.com

Abstract

Background Healthcare is not as safe as it should be and medication error remains a significant source of preventable morbidity and mortality among patients.

Objectives To present a failure mode and effect analysis (FMEA) of the medication management process in the pharmacy of the largest teaching hospital in Tunisia. Secondly, to examine the validity of a proposed simplified risk rating method by comparing the degree of concordance with the FMEA rating system in classifying failure modes related to the studied process.

Methods The FMEA method was applied to the medication management process in the pharmacy for 5 months from January 2020. For the traditional FMEA rating system, failure modes were prioritised according to the risk priority number, which considers severity, occurrence and non-detectability. Failure modes were classified for the traditional method considering three categories: accepted, requiring control and critical. The proposed rating system was based on two indices: the number of parts, which reflected severity, and the number of causes according to the 5M method (manpower, machines, material, methods and medium), which reflected occurrence. Failure modes were classified for the proposed method considering three categories: low, medium and high. Failure modes were independently analysed to determine the degree of agreement in ranking of risk between the two studied methods. Prioritised failure modes were targeted by decisions and solutions aiming to reduce risk and enhance safety.

Results Twenty-four failure modes were identified for the six-step process of medication management in a pharmacy (overall criticality=2607). The most critical failure modes were: data error in drugs reception (risk priority number (RPN)=432), break in the cold chain (RPN=320) and non-optimal pharmaceutical analysis (RPN=280). A good agreement was found between the classic FMEA and the proposed rating methods (κ=0.795). A high correlation was shown between the two scorings (r=0.785). Three failure modes were underestimated by the proposed rating method.

Conclusions An FMEA study on the medication management process in a teaching pharmacy showed that FMEA is an effective, proactive risk assessment that enables a better understanding of the studied process. The proposed risk scoring permits a good concordance with the classic method, with the advantage of being fast. Targeting the identified risks will allow integration into a continuous process of improvement and increase patient safety.

  • risk management
  • organization and administration
  • pharmacy administration
  • quality assurance
  • health care
  • quality of health care
  • safety
  • total quality management
  • workforce

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information. Not applicable.

http://dx.doi.org/10.1136/ejhpharm-2021-003013

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    Introduction

    Healthcare is not as safe as it should be and medication error remains a significant source of preventable morbidity and mortality among patients.1 An economic burden is associated with medication error with a mean cost per error ranging from €2.58 to €111 727.08.2 According to studies, the frequency of medical error can reach 16% with four errors per patient, and almost 0.7 errors per medication are reported to have occurred.3 4 The causes of medical error are multiple. The World Health Organization (WHO) reported that 11% of patients experience a medication error, with risk factors including poor coordination of care, cost-related barriers to medical services or medicines, multimorbidity and hospitalisation.5 A critical consequence of medication errors is decreased patient satisfaction and reduced trust of patients in physicians.6

    To prevent medication errors in clinical practice, safety concerns may be included in the risk management plan and subsequently be addressed with routine and/or additional risk minimisation measures.7 8 Risk management is defined as a systematic application of management policies, procedures and practices to the tasks of analysing, evaluating, controlling and monitoring risk.9 The concept of ‘risk management’ originally entered medicine in the United States from the insurance world as a consequence of the medical malpractice crisis.10 The risk management approach can be ensured by a priori methods or a posteriori methods.11 Among these methods, failure mode and effect analysis (FMEA), healthcare FMEA (HFMEA), a derived method and the 5M (manpower, machines, material, methods and medium) method are popular risk management methods commonly used in the healthcare field.12–14

    The FMEA was originally developed as a reliability analysis tool by the US military in the 1940s and used by NASA in the 1960s for safety and quality enhancement in their projects.15 FMEA is a systematic, proactive method for evaluating a process to identify where and how it might fail and to assess the relative impact of different failures, to identify the parts of the process that are most in need of change.16 The resources and expertise required to support FMEA should not be underestimated. The process is time-intensive and, on average, requires of the order of 10 work hours, including four to eight team meetings. In addition, the release of members of the work team from their routine duties to partake in the process in itself has monetary implications.17 The revision of traditional FMEA known as (HFMEA) was introduced in 2001 by the United States Department of Veterans Affairs, as an easier-to-use form of FMEA, to be used specifically in the healthcare setting.18 HFMEA includes some new components that do not derive from FMEA, such as the HFMEA hazard scoring matrix and the HFMEA decision tree.19 Other tools can reinforce the relevance of the results found at the end of an FMEA. The 5M method is a tool that categorises potential causes of a problem in successive detail to identify the root cause. This helps to identify multiple causes that might contribute to a specific effect.20 It is noteworthy that application of the 5M method leads to converging results, thus corroborating the validity of conclusions derived from risk assessment and FMEA.21

    We present in this paper an FMEA study on the medication management process in the pharmacy of the largest teaching hospital in Tunisia. Additionally, we aimed in a second place at examining the validity of a proposed simplified risk rating method by comparing the degree of concordance with the FMEA rating system in classifying failure modes related to the studied process.

    Material and methods

    Study context

    This was a prospective analytical study of risk management applied to the medication management process in the pharmacy of the 1000-bed Charles Nicolle hospital in Tunis, Tunisia. It was started in January 2020 and was carried out over 5 months. The studied process included drug supply through delivering medications to clinical healthcare. This process is described in online supplemental figure S1.

    Supplemental material

    Figure 1
    Figure 1

    Proposed failure mode inventory matrix.

    Study design

    Data collection tools

    The methodology was conducted as described in online supplemental figure S2. Briefly, a 10-member multidisciplinary team of health professionals was constructed, including the pharmacist in charge of the drug sector, the supervisor of the drug sector who is the most experienced agent in the drug sector and eight dispensing agents (pharmacy technicians). The methodology of the FMEA and the proposed rating method were discussed in detail for 1½ hours before the scoring process. Then, the team collectively performed process mapping, in a separate 1½-hour meeting, followed by failure mode mapping with the respective causes and effects through six brainstorming sessions (one session per step), each of about 30 to 120 min depending on the step studied. Each working session included at the beginning a brief reminder of what had been already done before starting the agenda. The work-group animation was provided by a facilitator, an engineer qualified in quality management, who did not intervene in the vote but ensured the good conduction of the methodology. Because this study has been part of an ongoing quality improvement programme, ethical approval was not required.

    Supplemental material

    Figure 2
    Figure 2

    Cumulative criticality per step of the medication management process in the pharmacy of a teaching hospital. FMEA, failure mode and effect analysis.

    Criticality calculation

    To conduct the FMEA, the multidisciplinary team determined the criticality scores for each failure mode by collectively voting on a scale from 1 to 10 for each mode—namely: severity (S), occurrence (O) and no detection (D) (table 1). If a difference of opinion greater than two points on the scale occurred, a second round of voting ensued after discussion of the failure mode. After the second vote, given scores were maintained.22 The average risk priority number (RPN) for each failure mode was calculated after multiplying the three scores (S x O x D). To obtain RPNs as integers, mathematical rounding up was carried out for each RPN value.

    View this table:
    Table 1

    Scoring matrix for the failure mode and effect analysis (FMEA) method

    The proposed method was inspired by a merger of the 5M method, based on five causes and their effects, and the modified HFMEA method, where two indices are considered: occurrence and severity. The aim was to correlate the causes detailed by the 5M method with the occurrence index and to correlate the defined effects with the severity while adopting a scale of 5 as mentioned in the modified HFMEA method.23 Thus, for the proposed rating method, two indices were determined. The first, C, which reflected the occurrence, reported the number of sources of causes per failure mode according to the 5M method—namely, manpower, machines, material, methods and medium.24 The second index P, which reflected the severity, reported the number of parts affected by the failure mode—namely, patient (P1), workforce (P2), medication (P3), environment (P4) and service functionality (P5). The criticality of the failure mode was calculated by multiplying the two indices (C x P). An arbitrary risk scale was adopted divided into three regions: low, medium and high (figure 1). The determination of causes and affected parts was performed by an independent pharmacist, qualified in quality management, not a member of the multidisciplinary team. This pharmacist considered the process cartography and the failure modes as defined by the multidisciplinary team and intervened only in the scoring of the failure modes indices, as defined by the proposed scoring method. The report was delivered at the end of an individual working session of 2 hours.

    Risk prioritising and improvement actions

    For the classic risk management method, prioritisation of risk was conducted considering two limits (mode RPN, mean RPN). Failure modes with RPN higher than max(mode, mean) were considered as critical (targeted by improvement actions). Those with RPN lower than min(mode, mean) were considered as accepted. Between the two limits, failure modes were considered as requiring control.25 For the proposed method, failure modes classified within the high-risk category are considered critical. Improvements were generated via a ninth brainstorming meeting (120 min). The proposed actions were presented and discussed later with the department head to assess their feasibility. A final feedback meeting (30 min) was held to briefly outline the results of the study. Certificates of participation in the study were granted to the agents who took part in the analysis.

    Statistical analysis

    Spearman’s correlation was applied to highlight a possible correlation between rating scores and classification categories. The Kruskal-Wallis test was applied to identify significant difference in criticality between steps. Cohen's κ coefficient was determined to judge the concordance between the scoring systems. Data were analysed using PSPP software (Free Software Foundation, Inc.) for Windows for statistical analysis. For all statistical tests, a critical significance level α of 0.05 was chosen.

    Results

    Medication management process

    The medication management process as performed at our pharmacy, from drug ordering to drug delivery, was described. During the analysis, all listed failure modes were either modes that had been observed by agents or modes which had not been observed but which were likely to occur under working conditions according to the agents’ opinions. The medication management process in the pharmacy comprised six steps, identifying 24 failure modes. Failure modes per step are summarised in online supplemental table S3.

    Supplemental material

    The analyses showed that overall accumulated criticality was 2607. The failure risks with the highest RPNs were: data error in drugs reception (RPN=432), break in the cold chain (RPN=320), non-optimal pharmaceutical analysis (RPN=280), delivery of an expired or damaged product (RPN=256) and incorrect quantification of needs (RPN=168). The RPNs ranged from a minimum of 24 to a maximum of 432. No significant difference was found in mean criticality between steps (p value=0.450). Cumulative criticality per step is given in figure 2. The mean RPN was 109 while the mode was 36.

    Degree of concordance between the two rating systems

    The comparison of failure modes scored by FMEA and by the proposed rating system is given in table 2. Mainly, three failure modes were underestimated by the proposed rating system which gives a concordance of 87.5%. The scatter plot of the FMEA categories versus the proposed scale categories is shown in figure 3.

    Figure 3
    Figure 3

    Degree of concordance between the classic FMEA rating method and the proposed rating method. FMEA, failure mode and effect analysis; RPN, risk priority number.

    View this table:
    Table 2

    Improvement actions to reduce the criticality of higher-priority failure modes related to the medication management process in the pharmacy of a teaching hospital

    A good concordance rate was found between the two scoring methods (κ coefficient=0.795, p value <10−3). Good correlations were found between calculated scores and categories for both rating methods (r=0.785, p value <10−3 and r=0.865, p value <10−3, respectively).

    Improvement actions

    Nine failure modes were considered critical, according to the FMEA rating method. Actions to reduce the criticality of these risks were proposed and are shown in table 2.

    Discussion

    Medication errors can occur at many steps in patient care, from the point of ordering the medication to the time when the patient is administered the drug.26 Medication safety can be enhanced by adopting a risk management method that identifies and prioritises vulnerabilities in a process.27 In this study, we performed FMEA in the pharmacy of the largest teaching hospital in Tunisia to highlight potential vulnerabilities associated with the medication management process. We identified high-priority failure modes, which were targeted for improvement. We propose a simple risk rating method that reduces the time required by the FMEA method.

    The proposed scoring method acts only on the scoring time. The times allocated for process mapping and mapping of failure modes as well as their causes and effects are not affected. In practice, it has been observed that the time dedicated to scoring constitutes at least half of the time dedicated to working meetings (4 hours). This can be explained by the hesitation of the participants, the need for discussion when opinions diverge, the tendency to argue and the need to recall the principle of voting during the meetings. For scoring according to the proposed method, the time allocated was 2 hours;, this was less than the traditional method because it is an individual task.

    Nine critical failure modes were identified which affected key stages of the pharmaceutical activity—namely, estimation of needs, product reception, inventory and delivery. The main failure modes were: wrong reception data, breaking the cold chain, delivery of an expired or damaged product, and non-optimal pharmaceutical analysis. To avoid these risks, the proposed actions focused on training of the workforce, purchase of control and transport equipment and updating of the medication management software. Jain studied the drug management process at the pharmacy level.28 The main failure modes were dispensing the wrong medicine or dose or form, drugs not cross-checked against the order as indented and drugs not used not being returned to the pharmacy. To reduce the criticality, corrective actions have been proposed—mainly, the instauration of the double-checking before delivery. In the study of Castro Vida et al, 99 failures were identified, including 50 failures associated with medicine management and inpatient pharmaceutical care processes, with 11 failures considered as critical.29 The large number of failure modes identified in their study can be explained by more diversified pharmaceutical activities in comparison with our activity: pharmacotechnics and drug compounding, pharmacokinetics, nutrition and research.

    Statistical analysis found that the proposed rating system is in good agreement with the classic rating system. The proposed system was based on two indices. The first corresponds to the number of sources of the failure mode. This index can be correlated with the occurrence of the failure mode: the more causes the failure mode has, the more likely it is to occur. The second index corresponds to the number of parts affected by the failure mode. The more the risk affects parts of the system, the more severe it will be. The proposed system is similar to the modified HFMEA rating system. It is based on determining the severity and occurrence of the failure mode by adopting a five-level rating matrix. Other studies have focused on comparing the rating systems of the FMEA and modified HFMEA methods and concluded that there was good agreement between them.23

    Of the 24 failure modes identified, 21 were classified in the same way by both systems. Only three failure modes (4, 12 and 16) were highly ranked by FMEA, but not by the proposed method of rating. The differences between the FMEA rating method and the proposed rating method can be explained by the difference in sensitivity of the scale (10-point scale vs 5-point scale). Also, the FMEA method is based on a third index, the detectability, which can exalt the difference. Hence, a scoring mismatch can occur between the two systems.

    The proposed rating method offers a holistic approach. It takes into consideration the safety of the patient, and also that of the operator, the product, the environment and the pharmacy functionality. The method aims to preserve the pharmacy’s reputation. Reputation is defined as a group of intangible assets that account for up to 95% of an organisation’s worth.30 This holistic approach is effective to prevent damage to the reputation of an organisation.30 31 A second interest of the proposed rating system is that it focuses only on two indices (severity and occurrence) and does not consider an index equivalent to the detectability. It has been reported in the literature that detectability may induce divergence since its definitions are unclear, and variation in the experience of the team members may occur.32 Thus, the proposed system benefits from the robustness of the 5M method by integrating it into the FMEA method. A last advantage of the proposed system is that it considerably reduces the time for carrying out the rating step (a 50% saving in scoring time) since it is based on a methodical understanding of the process without the need for meetings between members of the multidisciplinary team.

    Limitations

    Although it is an effective method allowing the outcome of a consensual opinion, FMEA is time and resource consuming, requiring a multidisciplinary and experienced team. Also, the prioritisation process can be considered as a limitation given that no standard method is recognised. Finally, the study was limited to the pharmacy-related process and did not include the prescribing and administration steps.

    Conclusion

    In our study, we have performed an FMEA study on the medication management process in a teaching pharmacy. FMEA is an effective, proactive risk assessment that enabled us to better understand the studied process. Additionally, a simplified risk rating method was proposed that provides good concordance with the classic rating method with the advantage of being fast. At the end of this study, targeting the identified risks will allow integration into a continuous improvement process.

    What this paper adds

    What is already known on this subject

    • FMEA (failure mode and effect analysis) is a useful tool to identify risks related to hospital pharmacy healthcare processes.

    • Although it is an effective method, FMEA is a time- and resource-consuming method.

    • The rating system needs to be lightened and the risk of subjectivity within the multidisciplinary team reduced.

    What this study adds

    • A good agreement was found between the classic FMEA and the proposed rating system.

    • The proposed rating system is time saving and reduces subjectivity.

    Data availability statement

    All data relevant to the study are included in the article or uploaded as supplementary information. Not applicable.

    Ethics statements

    Patient consent for publication

    Ethics approval

    This study does not involve human participants.

    Acknowledgments

    Authors thanks Miss Hedia Ounissi, engeneer qualified in quality management, for her contribution to the FMEA as a facilitator.

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    Supplementary materials

    Footnotes

    • EAHP Statement 5: Patient Safety and Quality Assurance.

    • Contributors AA: is the guarantor; conducted the study, interpreted the results, did statistics and contributed to the redaction. ABCB: conducted the study, acquired data, interpreted the results and contributed to the redaction. ZO: supervised the study, approved the final document.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.