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1419.   A hypothetical scenario that could benefit from the collection and access of data is medication errors.  An examination of recent literature on factors that influence patient outcomes affirms that medication errors harm the prospects of positive results. The mistakes are common in our healthcare settings, especially when novices are handling patient concerns. The errors manifest in adverse drug events that result in unwanted complications of hospital care and prolonged stays in medical facilities. In severe circumstances, medical errors result in preventable deaths. According to Agrawal (2009), there at least 1.5 million cases of medication errors in the United States that result in more than 400 000 preventable severe cases. Existing evidence suggests that patients in intensive care units are at the most significant risk of medication errors. According to Gracia, Serrano & Garrido (2019), patients in ICU account for 1.7 medical errors daily. However, informatics presents the potential to eliminate medication errors and promote patient outcomes.  An ideal approach in mitigating medication errors is the use of computerized physician order entry. The process replaces reliance on handwritten notes and reduces errors that stem from the prescription of medication. Besides, the approach improves the completeness of the medicines and augments their legibility. The process supports clinical decisions and avails a means for standardizing healthcare practice.             Critical data may be collected to reduce vulnerability to medication errors. For instance, it would be prudent to capture the patient identifiers correctly. Such include the name, gender, and age. Besides, one should capture essential demographics about a patient, such as their residence, educational level, socio-economic status, and nutritional status. Other categories of data that nurses should be on the lookout for include the current diagnoses, laboratory tests, procedures, and vital signs.             Various approaches may be used in gathering patient data to mitigate the likelihood of medication errors. For instance, the nurse may rely on observations to capture critical patient data. Besides, most of the data would be readily available from electronic health records. However, the nurses should be keen on capturing and retrieving the patient data from the HER.            Critical knowledge may be derived from the essential data of the patient. For instance, the data may form the basis for supporting clinical decisions. Camiré, Moyen & Stelfox (2009) points that data captured in CPOEs is indispensable in offering support to clinical findings. For instance, a study that examined the relationship between the two variables noted a considerable decline in the cases of medication errors in the ICU facility (Camiré, Moyen & Stelfox, 2009). Besides, the nurses may rely on the data to carry out medication reconciliation. For example, for patients in ICU facilities, nurses may be interested in determining whether the discharge medications were similar to contemporary patient records.            A nurse leader may use clinical reasoning and judgment to form knowledge from interactions with patient data from the EHR and CPOE. For example, they may rely on clinical reasoning to enhance the proper labeling of medication. Kruer, Jarrell & Latif (2014) point that medication cups, intravenous (IV) bags, and packaging that have an identical font, size, and color often result in mix-ups in the medication processes that result in medication errors. However, a nurse leader may rely on clinical reasoning and judgment to promote proper medication errors. Besides, they may use their experiences to combat route-specific challenges associated with drug formulation.            Conclusively, medication errors are of grave concern in the medical setting. However, informatics could reduce incidences and severity of medication errors by relying on CPOE and EHR. Critical data that should be captured include correct patient identifies, diagnoses, laboratory tests, and vital signs. Such an approach augments clinical decision-making and mitigates medication errors. (2 references)



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