A PROACTIVE RISK MANAGEMENT USING FAILURE MODE AND EFFECTS ANALYSIS FOR INFUSION THERAPY IN A TERTIARY HOSPITAL INTENSIVE CARE UNIT IN EGYPT

Acta Medica Mediterranea, 2015, 31: 195 A PROACTIVE RISK MANAGEMENT USING FAILURE MODE AND EFFECTS ANALYSIS FOR INFUSION THERAPY IN A TERTIARY HOSPITAL INTENSIVE CARE UNIT IN EGYPT AL TEHEWY M*, EL HOSSEINI M*, HABIL I*, ABDEL MAABOUD M**, ABDEL RAHMAN S* *Healthcare Quality Unit, Department of Community Medicine, Ain Shams Faculty of Medicine, Cairo - **Intensive Care Unit, Ain Shams University Hospitals - Cairo, Egypt ABSTRACT Aims: to apply a Failure Mode & Effects Analysis (FMEA) for infusion therapy in Ain Shams University hospital ICU for the ultimate purpose of proactively averting risks associated with such therapy. Materials and methods: A multidisciplinary FMEA team was formed. The team started by drawing a detailed flow chart of the infusion process and identified the potential failure modes. After listing effects of each failure mode, the severity, occurrence and detection ability were given scores resulting in a risk priority number (RPN). A Pareto analysis was used to prioritize the different failure modes according to their RPN. Improvement actions were suggested and implemented for the selected failure modes. Evaluation of the intervention was performed by re-calculating the RPN, satisfaction survey for the medical staff in the Intensive care unit (ICU) and measuring medication errors pre and post intervention. Results: A total of 11 failure modes with highest RPN scores including bringing wrong medication during preparation, wrong documentation and administration of the wrong medication were selected for improvement. The implemented improvements included designing new medication sheet, training, proper labeling of drugs to avoid the look alike medication, correctly identifying the patients, policy to avoid transcription, double checking in some steps of the process as well as some changes in the maintenance system. Overall, the improvements carried out were satisfying the medical staff of the unit, reduced the pre-intervention RPN and medication errors. Conclusion: Application of the FMEA in the ICU proved to be effective in proactively correcting potential failures in the infusion process and has impact on medical staff satisfaction. Key words: Failure Mode Effects Analysis, Infusion, Intensive Care Unit, Egypt. Received June 18, 2014; Accepted October 02, 2014 Introduction According to the National Coordinating Council for Medication Error Reporting and Prevention, medication error is defined as any preventable event that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the health care professional, patient, or consumer. Such events may be related to professional practice, health care products, procedures, and systems, including prescribing, order communication, product labeling, packaging, and nomenclature, compounding, dispensing, distribution, administration, education, monitoring, and use (1). Intravenous medications are associated with the main bulk of adverse drug events (2) and result in the most serious outcomes of medication errors (3). The magnitude of medication errors varies in different countries; although agreed to be an increasing problem. In developed countries, the rate of medication errors varies from 5-10% among patients (4). In developing countries, the rates of medication errors reported are much higher (5,6). Consequences of medication errors are diverse and serious. Researches have shown that 5-8% of hospital admissions are related to adverse drug events (7,8). Other consequences include prolonged hospital stay, additional resource utilization, time away from work, and poor patient satis-

196 Al Tehewy M, El Hosseini M et Al faction (9,10). Otherwise, a United States study estimated that the cost of drug related problems in the ambulatory setting exceeded 177 billion US Dollars in the year 2000 (11). In Australia, a cost of 660 million AUS Dollars per year was estimated for admissions caused by medications problems (12). Failure Mode and Effects Analysis (FMEA) is an industrial tool developed for proactively preventing the risk rather than reacting and managing the risk after its occurrence. It has gained large acceptance in the healthcare sector and increasingly been the subjects of researches and healthcare interventions (13). It has now been a requirement in most accreditation programs. The aim of the current study was to apply a Failure Mode & Effects analysis for infusion therapy in Ain Shams University hospital Intensive Care Unit (ICU) for the ultimate purpose of proactively averting risks associated with such therapy. Matherials and methods This study was carried out in the emergency ICU of Ain-Shams University Hospital in Cairo from January 15th, 2010 to end of April 2011. This Unit is composed of 8 beds and is operated by 10 nurses and 7 physicians. Description of the FMEA project The steps of Failure Mode and Effects Analysis (FMEA) in the current study are the 10 steps suggested by McDermott et al (14). In summary, these steps are: review process, brainstorm potential failure modes, list potential effects of each failure mode, assign severity, occurrence and detection rankings, calculate the Risk Priority Number (RPN) for each failure mode, prioritize the failures modes for action, take action to eliminate or reduce the high risk failure modes and calculate the resulting RPN as the failure modes are reduced. The FMEA team was composed of ICU director, one of the ICU physician, and two ICU nurses. The quality coordinator acts as a facilitator for this FMEA project. An orientation session about the FMEA was carried out at the start of this project by the quality coordinator. Initially, the process was drawn using a detailed flow chart, then brainstorming sessions were held to identify potential failure modes and their effects. Evaluating the risk of failure The relative risk of a failure and its effects are composed of three factors in FMEA process: Severity, Probability of Occurrence, and Detection Capability. The severity (S) is the consequence of the failure should it occur. The occurrence (O) is the likelihood of a failure mode occurring. The detection (D) is the ability to catch the error before causing patient harm. A scoring rating scale from 1 to 10 was used for severity, occurrence and detection (15). For each step a risk priority number (RPN) was calculated = (Severity * Occurrence * Detect ability) Since scores are 1-10, the resultant Risk Priority Number scored 1-1000. The team identified the failure modes with high RPN using Pareto chart. These were the items target for the corrective actions. Evaluation of the interventions RPN was recalculated after the interventions. Additionally, a satisfaction questionnaire with 5 points Likert scale for the proposed interventions was carried out for all Physicians and nurses working in the ICU after 4 months from implementation. An observational checklist was designed and used to calculate the errors associated with infusion therapy pre and post intervention. The checklist included prescription order review, observation of preparation as well administration of IV infusion. Results Figure 1 describes a flow chart of the infusion process carried out in the ICU. The nurse performed transcription of the prescribed order twice during the process. The prescribed order was transcribed first in a specific register where the nurse note all prescribed orders in order to get all the medications once from the medication closet; then the nurse transcribes the order again in a medication sheet for the patient and signs in front of it after implementation of the order. As shown in table 1, the possible failure modes were suggested by the FMEA team for every step in the infusion process. The RPN score was calculated for every failure mode. The highest RPN scores were calculated for bringing wrong

A proactive risk management using failure mode and effects analysis for infusion therapy... 197 medication during preparation, wrong documentation and administration of the wrong medication. Such failure modes would have severe adverse effects to the patient as well as low detection potential. A Pareto chart was done to determine the higher priority failures modes (Figure 2). The team decided to select those failure modes responsible for 58% of total RPN scores calculated, which are presented in table 2 together with their suggested improvement actions. Figure 2: Pareto chart of the different failure modes according to their RPN scores. The team selected 11 failure modes out of total 37 failure modes that represent 57.9% of total RPN scores. Figure 1: Flow chart of infusion therapy in ICU. The flow of process starts by prescribing the order till the nurse finishes the administration of the drug and removes the IV line. Table 1: RPN calculation for potential failure modes in the infusion process. Table 2: Suggested remedies according to Pareto prioritization. The actions suggested comprised: a) Designing a new medication sheet that include a space for prescription and a space to document the administration and monitoring corresponding to the prescribed drug in the same sheet. This sheet prevents transcription and improves monitoring and documentation. b) Labeling look alike, sound alike (LASA) and concentrated medications and placement in different places. c) Continuous training of nurses and doctors accompanied by On Job training and practice booklet. d) Double check by 2 nurses mechanism dur-

198 Al Tehewy M, El Hosseini M et Al ing administration of medication and in setting the rate of infusion. e) Buying spare infusion pumps and applying maintenance mechanism for infusion pumps (through contracted company and training of special team in hospital). f) Posting guiding sheet for calculation of doses and rates of commonly used medications in the ICU. g) Ensuring correctly identifying the patient by name and hospital number using a wristband for each patient, showing name of patient and his hospital number. f) Development and approval of a comprehensive policy for management of intravenous (IV) drug infusion including all previous improvements. Table 4: Comparison of medication errors pre and post intervention. Discussion Table 3: Evaluation of the intervention activities. Table 3 shows that the ICU medical staff expressed high satisfaction in all applied improvement interventions and the re-calculated RPN decreased considerably after these interventions. From another view, the medical errors associated with infusion therapy were observed in 208 infusion settings before implementation the FMEA and in 196 settings after the implementation. Infusion therapy associated errors were significantly reduced after the improvement actions carried out in ICU in all aspects, except asking for patient name and explaining the procedure to the patient during administration of the infusion (table 4). Although widely used in industrial design and quality management, particularly in high reliability industries, FMEA has not been used in health care except recently. It has been advocated as a useful tool for proactive risk assessment as recommended by the Joint Commission on Accreditation of Healthcare Organizations (13). The current work was done in a university hospital in Egypt that has just established a quality infrastructure in its system and step its first steps in this field. Many recommended systems already in place in many hospitals abroad like management of lookalike and sound alike medications are still lacking. Such initial quality improvement or quality projects, alongside its added quality value, may promote change in the quality culture in such hospitals. Double check, as a proactive intervention, was used in the current study in 2 occasions. The first time, was used while injecting the medication into the solution. In this occasion, it was assumed that there is potential of injecting wrong medication into the solution due to misreading the drug from the doctor prescription. The intervention suggested was that one nurse revise medication sheet and tells another (same nurse that brought the medication) who prepares and then administer the medication. Thus this second check at time of administration by

A proactive risk management using failure mode and effects analysis for infusion therapy... 199 another nurse may overcome even if a wrong medication was brought from the shelf initially. The second occasion for using the double check was during setting the rate of solution. Double check procedure for high-alert medications is a strategy that has been widely promoted in healthcare to help detect potentially harmful errors before they reach patients (15). Although debatable for its effectiveness (16), yet improper application may be misleading its effect. Numerous studies have demonstrated the ability of independent double checks to detect up to 95% of errors (17, 18). Transcription related errors are very common in the medication system (19,20). Efforts to reduce such transcription errors commonly pooled towards development of electronic computerized system for prescription and handling orders in different settings (20, 21). In our case, such solution was remote due to financial constraints. The alternate solution was designing a new medication sheet where the drugs are written only once in the doctor order then nurse signs upon administration and remarks its monitoring in the corresponding space. This new medication sheet gained average satisfaction from the working staff and relatively, was the least satisfying among all other interventions. Such attitude is expected in initial phases of similar interventions, where lack of familiarity may pose anxiety and worry (22). However, this result is short termed and it is not known whether staff will be acquainted with such new sheet over the time Dose calculations are a common contributor to medication errors (23, 24). The calculations involved in delivering continuous infusionsare more complex and may be more error prone than calculations for intermittent dosing. Moreover, medication errors for the types of medications administered by continuous infusion may have a higher likelihood of harm. Continuous infusion may also differ from other drug delivery processes as infusions may be formulated at the point of care with high frequency because of their common use in emergencies. Electronic dose calculator is a common suggested way to overcome problem of dose calculations (25). In the current study, a guiding sheet for dose calculations was designed and posted for the most common drugs used in the ICU. A pro-factor for implementation of such sheet is the limited number of drugs used for IV infusions in our ICU. Limitation of the study The failures modes identified in this process of infusion therapy as well the corrective interventions were achieved though brainstorming sessions that depend thoroughly on the members of team. Thus, potential some failure modes or corrections may be unintentionally missed or overlooked, but this represents the best effort done by the team. The corrections suggested by the team took into consideration applicability in our institution. Satisfaction of the staff was measured after 4 months from the implemented interventions that express short term outcome. This study was done only in one ICU in one teaching hospital in Egypt, and its results cannot be extrapolated to other hospitals or settings unless having comparable situation. Conclusions The current study applied a proactive risk management model (FMEA) on infusion therapy in an ICU. The FMEA model proved to be effective in reducing medication errors associated with infusion therapy and gaining satisfaction of the ICU medical staff. References 1) National Coordinating Council for Medication Error Reporting and Prevention. http://www.nccmerp.org 2013. Last accessed February 2013. 2) Kaushal R, Bates DW, Landrigan C, McKenna KJ, Clapp MD, Federico F, Goldmann DA.. Medication errors and adverse drug events in pediatric inpatients. JAMA. 2001 Apr 25; 285(16): 2114-20. 3) Hicks RW, Becker SC. An overview of intravenousrelated medication administration errors as reported to MEDMARX, a national medication error-reporting program. J InfusNurs 2006 Jan-Feb; 29(1): 20-7. 4) C. Y. Lu, E. Roughead. Determinants of patient-reported medication errors: a comparison among seven countries. Int J ClinPract 2011; 65(7): 733-40. 5) Khoja T, Neyaz Y, Qureshi NA, Magzoub MA, Haycox A, Walley T. Medication errors in primary care in Riyadh City, Saudi Arabia. East Mediterr Health J 2011 Feb; 17(2): 156-9. 6) Kandil M, Sayyed T, Emarh M, Ellakwa H, Masood A. Medication errors in the obstetrics emergency ward in a low resource setting. J Matern Fetal Neonatal Med. 2012 Aug; 25(8): 1379-82. 7) Beijer HJM, de Blaey CJ. Hospitalisations caused by adverse drug reactions (ADR): a meta-analysis of observational studies. Pharm World Sci 2002; 24: 46-54. 8) Winterstein AG, Sauer BC, Hepler CD, Poole C. Preventable drug related hospital admissions. Ann Pharmacother 2002; 36: 1238-48. 9) Bates DW, Spell N, Cullen DJ et al. The costs of adverse drug events in hospitalized patients. Adverse

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