Nursing-Using a PICOT Framework and Evidence to Develop Care Practices Using a PICO(T) Framework and Evidence to Develop Care Practices

Nursing-Using a PICOT Framework and Evidence to Develop Care Practices Using a PICO(T) Framework and Evidence to Develop Care Practices

 

Evidence-based practice is essential in nursing since it integrates the best nursing evidence into practice to enhance patient outcomes and safety (Boswell & Cannon, 2018). The PICO (T) research framework can be used to develop care practices for patients. PICOT involves Population/Patient, Intervention, Comparison, Outcome, and Time. This framework can be applied to develop a care plan which enhances patients outcomes. Using secondary sources, this paper will define a practice issue surrounding medication errors. The PICO (T) process will be applied, and sources of evidence identified to answer the clinical question. It will also explain findings from research articles and finally outline the relevance of the key findings.

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Use of the PICO(T) Approach for Reducing Medication Errors

The practice issue identified for solving is developing protocols that will reduce medication-related errors in inpatient departments. The PICO (T) question is: “In adults in inpatient settings, is technology effective in reducing medication errors compared to no intervention?” The population that will be of interest is adults in inpatient wards. The intervention is the use of technology such as the Bar Code Medication Administration (BCMA). BCMA technology involves scanning medications using barcodes to reduce medication-related errors during dispensing of medications (Shah et al., 2016). The comparison in the question is no interventions at all, and the outcome is the reduction of medication errors. This study will not consider sociocultural factors but only hospital-related factors.

Sources of Evidence

The are many sources of evidence that can be used in the EBP for reducing medication errors. This can include randomized controlled models in hospital settings, self-reported medication errors, patient medical chart audits, and competency testing for nurses. Scholarly articles are critical in determining the sources of medication errors and how medication errors can be reduced using EBP models. Medical records audits can be used to identify the things that are done correctly and areas that may need improvement (Azzolini et al.,2019). Incident reports can also be used to reduce medication errors. Incident reports will help identify safety issues and implement interventions to minimize these issues (Carlfjord et al., 2018). They help protect patients since healthcare professionals can learn from their mistakes and identify areas where they went wrong.

Finally, evaluating nurses’ competency in medication administration and dispensing can help address evidence-based factors and barriers that may result in medication-related errors. Education of nurses and clinical simulations can help reduce medication-related errors. The resources of evidence that can be used to answer this question will include scholarly articles related to medication errors, results from simulation models, randomized controlled trials, interviews from nurses, incident reporting, and medical records audits.

Findings from Articles

BCMA technology reduces medication errors through the electronic verification of the five rights of medication administration. The five rights are “right patient, right dose, right drug, right route, and the right time.” (Shah et al., 2016). At the patient’s bedside, nurses scan the barcode on the drug to be administered, their identification badge, and the patient’s identification tools such as a wristband. The data is sent to the software to check and give approvals or warnings (Shah et al., 2016). This information is given in real-time.

Shah et al. (2016) is a systematic review that analyzed articles related to BCMA. The results indicated that BCMA reduced non-timing errors from 11.5% to 6.8% (). It also reduced wrong drug errors, wrong dose errors, wrong route errors, and documentation errors. BCMA also reduced adverse drug events related to non-timing errors (Shah et al., 2016). The article, however, noted that human factors and technical issues should also be considered in the implementation of BCMA technology. BCMA is not effective in completely eliminating medication errors.

Thompson et al. (2018) conducted a study in inpatient nursing units. The results show that after implementing BCMA, decreased reported medication events by over 17%, while nonmedication events reporting increased by 20%. Thompson et al. (2018) also noted that BCMA reduced reported medication administration errors by 43.5%. There was a reduction of patient harm events by 55.4 %, and harmful medication errors decreased to 0.29 per 100 00 medications from 0.69 per 100 000 medications.

Truitt et al. (2016) note

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