NURS-FPX 4020 Root Cause Analysis (RCA) and Safety Improvement Plan

NURS-FPX 4020 Root Cause Analysis (RCA) and Safety Improvement Plan

NURS-FPX 4020 Root Cause Analysis (RCA) and Safety Improvement Plan

The root-cause analysis (RCA) will explore medication administration errors (MAEs), one of the most prevalent medication errors. It has adverse consequences for patients, healthcare providers, and health facilities. The prevalent MAEs include wrong patient, wrong drug, wrong dose, wrong route, wrong time, dose omission, failure to document, and technical errors (Abdulmutalib & Safwat, 2020). MAEs are associated with increased patient morbidity, adverse drug events (ADEs), prolonged hospital stay, mortality, and increased medical costs. The purpose of this paper is to conduct an RCA of MAEs, apply evidence-based approaches to address the issue, and discuss a safety improvement plan.

Analysis of the Root Cause

MAE is any discrepancy between what a patient is administered or is supposed to be administered and what the prescriber planned in the original order. MAE is one of the most prevalent adverse events for hospitalized patients and the most common cause of preventable death (Abdulmutalib & Safwat, 2020). In the medical-surgical unit, a nurse prescribed a patient allergic to penicillin with Co-Amoxiclav 1g IV. After three hours, the patient developed itching, swelling, skin rash, and difficulty breathing. The unit’s resident noticed the allergic reaction during clinical rounds and immediately prescribed an antihistamine before the patient’s condition worsened. Although the allergic reaction did not cause severe harm to the patient, adverse consequences could have occurred if the resident did not identify the ADE early enough. The patient’s family members learned of the incident and complained to the management that their patient was mismanaged.

During the analysis of the medication error, it was found that the resident had changed the treatment plan from Ceftriaxone to Co-Amoxiclav but did not check the patient’s drug allergies. Besides, the nurse did not check whether the patient was allergic to penicillin when the treatment was changed. The dispensing pharmacist did not double-check if the patient had any drug allergies before dispensing the drug to the nurse. Furthermore, the hospital did not have a clinical decision support system (CDSS) to alert the physician of the patient’s allergies and guide him in prescribing the most appropriate medication. It was also identified that the nurse had a high patient workload and thus did not have adequate time to check the patient’s allergies in the EHR or ask the patient about existing allergies before administering the drug. Nurses in the medical-surgical unit reported that the high workload led to increased work pressure, which lowers their attention levels when administering medication. Besides, the high workload was associated with fatigue and burnout, which affected nurses’ ability to provide quality care.

Application of Evidence-Based Strategies

One of the evidence-based approaches to addressing the MAE issue is maintaining adequate nurse staffing and optimizing nursing workflow to mitigate the problem of high nurse workload. Nurse staffing ratios significantly influence the incidence of medication errors in hospitals (Abdulmutalib & Safwat, 2020). Nurses’ workflow is also essential to ensuring medication safety during drug administration and patient monitoring. Another strategy is to implement effective medication reconciliation approaches. An effective medication reconciliation process entails comparing a patient’s current treatment regimen against the clinician’s admission, transfer, or discharge orders to discover discrepancies (Mutair et al., 2021). It integrates the need for patient information and expert review of drugs, interactions, and side effects. Al Anazi (2021) asserts that focusing more on having an effective medication process, like pharmacist-led medication review, obtaining accurate medication histories, medication reconciliation, and using discharge surveys, can identify and prevent numerous medication discrepancies. This can avert incidences of ADEs and associated costs for patients and healthcare facilities.

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Adopting appropriate technology is another evidence-based approach to addressing ADEs. Implementing suitable technology in storing, administering, and monitoring medications increase medication safety. The applicable technology includes barcode medication administration (BCMA) which improves patient identification. Radiofrequency identifiers can be adopted to improve medication storage, computerized decision support systems (CDSS) to help identify high-risk medications and surveillance systems that enable clinicians to quickly detect adverse events (Moghadam et al., 2020). In addition, the organization can create an improvement-oriented working environment, which is crucial to attaining medication safety (Mutair et al., 2021). Organizational support encourages voluntary reporting of medication errors, especially if the organization has created an environment that supports non-punitive reporting.

Improvement Plan with Evidence-Based and Best-Practice Strategies

The safety improvement plan to address MAEs in the medical-surgical unit is implementing a CDSS. CDSS is one of the IT-based strategies identified as a promising approach to preventing medication errors. Shahmoradi et al. (2021) explain that the CDSS is regarded as one of the most useful and efficient tools for improving prescription, preventing adverse events, and promoting correct drug dosing. The CDSS has drug-allergy and drug-drug interaction checks and drug recommendations that guide the physician in prescribing the correct medication. CDSS helps to minimize medication errors, ADEs, and drug interactions and enhances patient safety and drug prescriptions. Shahmoradi et al. (2021) found evidence that adopting CDSS enhances clinical outcomes through reduced prescription errors and improved quality and safety of prescribed medications.

The anticipated outcomes from implementing the CDSS include using evidence-based guidelines in clinical decision-making and improved quality of care. The CDSS is expected to reduce medication errors and associated side effects as well as save patients and the hospital high costs. Moreover, it is expected to improve the efficiency of patient care and save the physicians’ time usually spent going through manual clinical guidelines (Sutton et al., 2020). The CDSS plan will be implemented within roughly six months. The system will be integrated into the EHR and CPOE systems, which will help to improve the system’s effectiveness. It will first be implemented in the medical-surgical unit and later in other hospital units after successful adoption in the pilot units.

Existing Organizational Resources

            The implementation of the CDSS will be facilitated by existing organizational IT resources like the EHR and CPOE. The CDSS will be integrated into these systems, and implementation will be cheaper since they already exist. Other IT resources needed for the success of the CDSS plan include cloud computing and an ICD system for classifying and coding diagnoses and medical procedures (Moghadam et al., 2020). The personnel needed in implementation include health informaticists, project manager, lead super user, and lead practitioners. Furthermore, financial resources will be needed to purchase the CDSS, implement, and regularly maintain it.

Conclusion

The RCA conducted due to an MAE in the medical-surgical unit revealed that physicians, nurses, and pharmacists did not cross-check contraindications before prescribing, dispeansing, and administering medications. A high nursing workload and a lack of a CDSS also contributed to medication errors. Strategies to address MAEs include adequate nurse staffing, optimizing nursing workflow, medication reconciliation process, adopting appropriate technology, and creating an improvement-oriented working environment. The proposed improvement plan is adopting a CDSS, which focuses on safety features in prescription medications, thus improving the quality of care.

References

Abdulmutalib, I., & Safwat, A. (2020). Nursing strategies for reducing medication errors. Egyptian Journal of Nursing and Health Sciences1(1), 77–98. DOI: 10.21608/ejnhs.2020.80266

Al Anazi, A. (2021). Medication reconciliation process: Assessing value, adoption, and the potential of information technology from pharmacists’ perspective. Health Informatics Journal27(1), 1460458220987276. https://doi.org/10.1177/1460458220987276

Moghadam, S. T., Sadoughi, F., Velayati, F., Ehsanzadeh, S., & Poursharif, S. (2020). The effects of clinical decision support system for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis. https://doi.org/10.1186/s12911-020-01376-8

Mutair, A. A., Alhumaid, S., Shamsan, A., Zaidi, A. R. Z., Mohaini, M. A., Al Mutairi, A., Rabaan, A. A., Awad, M., & Al-Omari, A. (2021). The effective strategies to avoid medication errors and improving reporting systems. Medicines (Basel, Switzerland)8(9), 46. https://doi.org/10.3390/medicines8090046

Shahmoradi, L., Safdari, R., Ahmadi, H., & Zahmatkeshan, M. (2021). Clinical decision support systems-based interventions to improve medication outcomes: a systematic literature review on features and effects. Medical Journal of the Islamic Republic of Iran35, 27. https://doi.org/10.47176/mjiri.35.27

Sutton, R. T., Pincock, D., Baumgart, D. C., Sadowski, D. C., Fedorak, R. N., & Kroeker, K. I. (2020). An overview of clinical decision support systems: Benefits, risks, and strategies for success. NPJ Digital Medicine3(1), 1-10. https://doi.org/10.1038/s41746-020-0221-y