I work at clinics and medical offices where we focus on diagnosing and treating outpatients. The primary goal of this facility is to offer preventative care and other essential diagnoses at the convenience of a patient. The quality metric that our clinics focus on and monitor is analyzing errors. As Vahidi et al. (2018) claim, medical errors can occur at every phase of diagnosis and treatment, posing a severe healthcare problem and impending patient safety. Atanasov et al. (2020) further indicate that these errors are the key cause of patient morbidity and mortality, whereas medical errors are the third cause of death in the US. Our facility analyzes errors via root cause analysis (RCA), a structured method of analyzing serious adverse events. The principle of RCA is to ascertain the causal factors that contribute to and increase the prospect of errors while circumventing the ruse of focusing on mistakes by persons. The importance of this analysis is that it utilizes a systems approach to identifying both active and latent errors. Therefore, analyzing errors is crucial to identifying the underlying factors that cause an error and approaches that can be used to reduce the associated risks.
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Existing data prove that medical errors are common in most healthcare facilities and have adverse effects on patients. According to Vahidi et al. (2018), medical error is the underlying cause of deaths and disabilities of millions of patients globally, and most of these errors are preventable. Medical errors also contribute to increased health costs by $17 to $19 billion annually. Zhou et al. (2018) report that medication errors are the primary cause of adverse drug events (ADEs), which causes unnecessary hospital admissions, patient dissatisfaction, and patient harm. Such alarming data calls for an effective way of preventing these errors. Consequently, the ability to analyze the underlying factors that encourage these errors is key to their prevention.
Analyzing errors in healthcare is paramount since it identifies the various types of errors, their impact on patient care, contributing factors, and the existing counteractive and preventive strategies for these errors. The two major types of analyzing errors metric focus on are active and latent errors. Active errors occur at a point in the line between people and a complex system, while latent errors are the existing problems within the healthcare system that lead to adverse events. Further, analyzing errors identifies the impact that medical errors have on patients. For instance, Atanasov et al. (2020) posit that apart from causing patient suffering and harm, medical errors result in emotional and mental effects on the patient’s relatives and the healthcare givers. Analyzing errors is also crucial to identifying the causative factors such as the work environment, staffing, team environment, patient characteristics, and task-related issues that can stimulate medical errors. Preventive measures against healthcare errors include integrating technology in patient treatment for ease of accessing their information, encouraging patients to speak up if they have a concern or a question, and having the patient accompanied by a family member or a friend when they are seeking medical care.
The ability to analyze errors has positive effects on patient care. This metric enhances patient safety by alerting patients from suffering adverse outcomes when seeking medical care (Karande et al., 2021). Thus, executing an RCA on healthcare errors aims to investigate the cause of the error and ways of enhancing the system and processes to reduce the odds of recurrence. Besides, analyzing errors aids in identifying and reducing the causative factors of errors in the future for better and improved patient safety. This comes in line with our hospital’s policy of prioritizing patient safety by minimizing cases of errors throughout their treatment.
I interviewed doctor C. Ying (personal communication, January 30, 2022), a nurse manager in our work, on the use and efficiency of analyzing errors at our place of work. C. Ying (personal communication, January 30, 2022) claimed that they had used the analyzing errors metric for five years. The hospital has used the RCA method to monitor compliance with this quality metric. Rodziewicz et al. (2021) argue that RCA is key to identifying the contributing factors that cause disparities in performance. Similarly, C. Ying (personal communication, January 30, 2022) insisted that RCA aids them in identifying the hidden cause of errors and their source. The hospital also relies on an RCA team whose work focuses on the systems and processes that yield errors to ensure that they comply with the metric. C. Ying (personal communication, January 30, 2022) also added that the team collects data on changes within the systems and processes that will enhance performance and reduce errors in healthcare. Complying with this metric allows the organization to identify causative factors of both active and latent errors, which significantly affect compensation. C. Ying (personal communication, January 30, 2022) claimed that their ability to identify the sources of errors, such as staffing, helps them determine the number of nurses that should be working at a certain time, which influences their workforce. C. Ying (personal communication, January 30, 2022) confirmed that they are accountable to the Joint Commission, which requires them to conduct an RCA after every sentinel event. In an instance where they report poor performance, the Joint Commission executes onsite reviews to identify the cause of the error that threatened a patient’s health and safety (Peerally et al., 2017). C. Ying (personal communication, January 30, 2022) further claimed that their established goal with analyzing errors metric is to promote patient safety by identifying factors that escalate the probability of errors occurring and eliminating them for better healthcare delivery. For the past two years, C. Ying (personal communication, January 30, 2022) posited that they had achieved their set goals of reducing patient harm, unnecessary admissions, and reduced morbidity and mortality rates associated with medical errors. (C. Ying, personal communication, January 30, 2022).
There are various provider-specific metrics for nurse practitioners (NP) in every healthcare institution. Patient care is one of the metrics used to assess the efficiency of analyzing errors. NPs should focus on the quality of care by following the standards set by the insurance companies that reimburse medical fees depending on the standards set. These compliances are set to ensure that NP’s perform well and their earnings depend on their care to both inpatients and outpatients. Besides, the clinical skills of the NPs are used to assess the efficiency of analyzing errors. NPs should have a skill set to perform various procedures or diagnose illnesses without making errors (Kleinpell & Kapu, 2017). Lastly, NPs should work on enhancing their relative value units (RVUs) as a measure of their improved productivity level. NPs should focus on developing their RVUs while promoting a patient’s well-being by avoiding errors. This way, they promote patients’ safety while increasing the productivity and profit generated to the institution.
An instance when RCA was used is when a 4-year-old girl with a brain tumor was given 600 mg of methotrexate after the tumor was removed. The girl developed seizures and later died. It was later noted that the prescription was wrong, as methotrexate was 20 times great for this patient. The doctor who administered this dosage was unaware that it applied to the intravenous drips only. The case was conveyed to The Joint Commission, which led to the RCA investigation. The outcome was to educate the entire medical staff on drug administration and dosage.
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A problem area that exists in the RCA is the use of poorly designed risk controls. RCA focuses on preventing similar events from recurring. To come up with counteractive measures, the RCA team settles for weaker solutions, such as administrative ones and not the latent causes of the error, such as the used technology (Peerally et al., 2017). I would improve on this by offering sufficient guidance to the affected practitioner or department. Throughout the module, I have learned that caregivers must improve the care process by learning how to provide the existing therapies effectively to improve patient outcomes. As an adult gerontological nurse practitioner (AGNP), I have learned that promoting patient safety is crucial to their wellness. Therefore, as an AGNP, I will identify the risk factors that may affect the health status of my patients. I will educate them on ways of enhancing their health outcomes by being cautious of the treatment process to identify or prevent any medical error that can threaten their welfare. Similarly, as a registered nurse (RN), I will be keen when assessing and identifying patients’ needs. I have discovered that misdiagnosis of errors can occur during the initial treatment stage, which is a common medical error (Kleinpell & Kapu, 2017). Thus, I will ensure that I am extra cautious when diagnosing my patients, especially when dealing with those high-risk diagnoses such as cancer and heart diagnoses.
Atanasov, A. G., Yeung, A. W. K., Klager, E., Eibensteiner, F., Schaden, E., Kletecka-Pulker, M., & Willschke, H. (2020). First, do no harm (gone wrong): Total-scale analysis of medical errors in scientific literature. Frontiers in Public Health, 8, 639.
Karande, S., Marraro, G. A., & Spada, C. (2021). Minimizing medical errors to improve patient safety: An essential mission ahead. Journal of Postgraduate Medicine, 67(1), 1.
Kleinpell, R., & Kapu, A. N. (2017). Quality measures for nurse practitioner practice evaluation. Journal of the American Association of Nurse Practitioners, 29(8), 446-451.
Peerally, M. F., Carr, S., Waring, J., & Dixon-Woods, M. (2017). The problem with root cause analysis. BMJ Quality & Safety, 26(5), 417-422.
Rodziewicz, T. L., Houseman, B., & Hipskind, J. E. (2021). Medical Error Reduction and Prevention. In StatPearls [Internet]. StatPearls Publishing.
Vahidi, S., Mirhashemi, S. H., Noorbakhsh, M., & Taleghani, Y. M. (2018). Clinical errors: Implementing root cause analysis in an area health service. International Journal of Healthcare Management, 1-12.
Zhou, S., Kang, H., Yao, B., & Gong, Y. (2018). Analyzing medication error reports in clinical settings: an automated pipeline approach. In AMIA Annual Symposium Proceedings (Vol. 2018, p. 1611). American Medical Informatics Association.