Multifactorial Medication Mishap Case Study – Week 2 Solution

This article covers Multifactorial Medication Mishap Case Study.

Instructions

Read the Multifactorial Medication Mishap case study.

https://psnet.ahrq.gov/web-mm/multifactorial-medication-mishap

Complete the Root Cause Analysis Worksheet to analyze the case. (SEE ATTACHMENTS)

Multifactorial Medication Mishap Case Study:

The Case A previously healthy 50-year-old man was hospitalized while recovering from an uncomplicated spine surgery. Although he remained in moderate pain, clinicians planned to transition him from intravenous to oral opioids prior to discharge.

The patient experienced nausea with pills but told the bedside nurse he had taken liquid opioids in the past without difficulty. The nurse informed the physician that the patient was having significant pain and liquid opioids had been effective in the past.

When the physician searched for liquid oxycodone in the computerized prescriber order entry (CPOE) system, multiple options appeared on the list — two formulations for tablets and two for liquid (the standard 5 mg per 5 mL concentration and a more concentrated 20 mg per mL formulation).

At this hospital, the CPOE system listed each choice twice, one entry with the generic name and one entry with a brand name. In all, the physician saw eight different choices for oxycodone products. The physician chose the concentrated oxycodone liquid product and ordered a 5-mg dose.

All medication orders at the hospital had to be verified by a pharmacist. The pharmacist reviewing this order recognized that the higher concentration was atypical for inpatients but assumed it was chosen to limit the volume of fluid given to the patient.

The pharmacist verified the order and, to minimize the risk of error, added a comment to both the electronic medication administration record (eMAR) and the patient-specific label that the volume to be given was 0.25 mL (5 mg). For added safety, the pharmacist personally retrieved, labeled, and delivered the drug and a calibrated syringe to the bedside nurse to clarify that this was a high concentration formulation for which the volume to administer was 0.25 mL (a smaller volume than would typically be delivered).

Shortly thereafter, the nurse went to the bedside to administer the drug to the patient for his ongoing pain. She gave the patient 2.5 mL (50 mg) of liquid oxycodone, a volume that she was more used to giving, and then left for her break. A covering nurse checked on the patient and found him unconscious — a code blue was called.

The patient was given naloxone (an agent that reverses the effect of opioids), and he responded well. He was transferred to the intensive care unit for ongoing monitoring and a continuous infusion of naloxone to block the effect of the oxycodone. By the following morning, the patient had returned to his baseline with no apparent adverse effects.

Write a 525 word-summary in which you: 

1. Explain why a root cause analysis was appropriate for this situation.
2. Analyze the impact of using tools like RCA, FMEA, and PDSA on the quality and safety of patient care.

Cite a minimum of two peer-reviewed or evidence-based sources published within the last five years to support your summary in an APA-formatted reference page.

Solution

Multifactorial Medication Mishap Case Study

Explain Why A Root Cause Analysis Was Appropriate For This Situation

This situation is a typical medication error that is common in clinical settings. Medication errors are caused by different elements or more than one practitioner. In this case, several latent errors contributed to the patient’s harm.  

Root cause analysis (RCA) is a structured approach to ascertaining the causal factors of medical errors and adverse events to define precautionary measures (Charles et al., 2016). RCA personnel assesses system factors contributing to or causing medication errors and adverse events other than human errors. The RCA’s ultimate goal is to determine what went wrong, why such errors happen, and how to keep it from recurring. 

The RCA of this risky medication error in which the nurse administered the wrong dosage shows additional flaws in the nursing setting contributing to the adverse patient outcome. Therefore, the RCA is appropriate for this situation because it safeguards patients by characterizing and modifying risk factors in the healthcare system that may bring injury. (Charles et al., 2016). In this case, the RCA team will identify the human and system-related factors contributing to the nurse’s actions, jeopardizing the patient’s safety.

For instance, the RCA will uncover the following error (1) the mishap in the hospital’s computerized prescriber order entry (CPOE). (2) The failure of the bedside nurse to check the comment made by the pharmacist on the electronic medication administration record (eMAR). (3) The nurse’s ignorance of the pharmacist’s patient-specific labels and use of the calibrated syringe.

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Through these outcomes, the hospital can put measures such as an update of computerized prescriber order entry, appropriate communication channels between medical personnel, and cautions against the ignorance of colleague’s comments. Moreover, this would make it difficult for clinical personnel to make errors, detect, and correct errors before they occur.

The impact of RCA, FMEA, and PDSA on the quality and safety of patient care

RCA assesses and highlights the causes and contributing factors to an adverse clinical situation. The hospital can take actions, which would prevent future recurrence (Martin-Delgado, Martínez-García, Aranaz, Valencia-Martín, & Mira, 2020). Besides, the hospital can measure planned interventions to determine, thereby guiding an in-depth understanding of the clinical mishaps, appraisal of nursing practices, and quality aspect, thus, ensuring quality and safe patient care.

Like RCA, the Failure Mode and Effects Analysis (FMEA) is a healthcare tool used to reduce error and improve healthcare processes, thus, improving healthcare quality and safety.  The healthcare FMEA process identifies potential mishaps and their causes to guide preventive measures (Liu, Zhang, Ping, & Wang, 2020).

Besides, healthcare FMEA provides guidelines on improving current clinical services, leading to enhance patient safety and quality care services. Lastly, RCA can guide clinical personnel to avoid focusing on specific sources of error but a systematic approach to medication errors. This would allow correction of underlying system failures, leading to improved quality of care services and patient safety.

PDSA (Plan-Do-Study-Act) is a practical problem-solving healthcare model established to improve clinical processes through a guided change of defective practices. Coury et al. (2017) argue that PDSA is a crucial model for quality improvement initiatives in healthcare systems.

This is because its methods ensure the quality and consistency of proposed changes, adapt the new processes to the desired context, and minimize risks of harm and unintended consequences to patients (Knudsen et al., 2019). Therefore, understanding PDSA functions can facilitate care quality and patient safety initiatives, leading to an evidence-based intervention in daily clinical processes.  

References

Charles, R., Hood, B., Derosier, J. M., Gosbee, J. W., Li, Y., Caird, M. S., … & Hake, M. E. (2016). How to perform a root cause analysis for workup and future prevention of medical errors: a review. Patient safety in surgery, 10(1), 1-5. 10.1186/s13037-016-0107-8

Coury, J., Schneider, J. L., Rivelli, J. S., Petrik, A. F., Seibel, E., D’Agostini, B., … & Coronado, G. D. (2017). Applying the Plan-Do-Study-Act (PDSA) approach to a large pragmatic study involving safety net clinics. BMC health services research, 17(1), 1-10. 10.1186/s12913-017-2364-3

Knudsen, S. V., Laursen, H. V. B., Johnsen, S. P., Bartels, P. D., Ehlers, L. H., & Mainz, J. (2019). Can quality improvement improve the quality of care? A systematic review of reported effects and methodological rigor in plan-do-study-act projects. BMC health services research, 19(1), 1-10. https://doi.org/10.1186/s12913-019-4482-6

Liu, H. C., Zhang, L. J., Ping, Y. J., & Wang, L. (2020). Failure mode and effects analysis for proactive healthcare risk evaluation: a systematic literature review. Journal of evaluation in clinical practice, 26(4), 1320-1337. 10.1111/jep.13317

Martin-Delgado, J., Martínez-García, A., Aranaz, J. M., Valencia-Martín, J. L., & Mira, J. J. (2020). How Much of Root Cause Analysis Translates into Improved Patient Safety: A Systematic Review. Medical Principles and Practice, 29(6), 524-531. https://doi.org/10.1159/000508677

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