Description
Practice Issue and PICOT Statement
Medication errors are a serious healthcare quality threat since they contribute to mild to severe complications, including longer hospitalization and death. Statistics report that medication errors cost $42 billion annually worldwide, which is about 0.7% of the total global health expenditure (Manias et al., 2020). Medication errors harm about one and a half million patients annually (“Medication Errors | AMCP.org,” 2022). Medication errors can be reduced by different interventions, including investing in technology and human resources.
The PICOT question is:
The population is the sample of subjects affected by the nursing practice problem. In medication errors, the population affected ranges across all patient characteristics and ages. This includes children, adolescents, and the elderly of any gender (Tansuwannarat et al., 2022).
Interventions refer to the practices, treatments, and strategies that can reduce the ensuing nursing problem. Medication errors can be reduced by using computerized data entry systems to lower prescription errors by pharmacists (Manias et al., 2020).
The comparison illustrates the existing strategies that can act as a reference to assess the effectiveness of the suggested intervention. The comparative strategy for this problem would be the training of pharmacists. While training programs help create patient safety awareness, they can be used to evaluate the effectiveness of computerized data entry systems in lowering prescription errors (Manias et al., 2020).
Outcome refers to the expected results that define the effectiveness of the suggested intervention. Medication errors can be reduced by increased patient safety and lower rates of prescription errors (Manias et al., 2020).
Time refers to the period in which the problem would be addressed. For this project, the chosen timeframe is 6-8 weeks.
“Will medication error rates impacting patients in the chosen medical setting (P) after using computerized data entry systems (I) compared to training pharmacists (C) will be reduced (O) after 6-8 weeks of intervention implementation (T)?”
Article no.
Article no. 1
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Article no. 5
- Full reference for the article (APA 7th)
- Chen, Y., Wu, X., Huang, Z., Lin, W., Li, Y., Yang, J., & Li, J. (2019). Evaluation of a medication error monitoring system to reduce the incidence of medication errors in a clinical setting. Research in Social and Administrative Pharmacy, 15(7), 883-888.
Kenawy, A. S., & Kett, V. (2019). The impact of electronic prescription on reducing medication errors in an Egyptian outpatient clinic. International journal of medical informatics, 127, 80-87.
Afreen, N., Padilla-Tolentino, E., & McGinnis, B. (2021). Identifying Potential High-Risk Medication Errors Using Telepharmacy and a Web-Based Survey Tool. Innovations in pharmacy, 12(1), 10.24926/iip.v12i1.3377.
Corny, J., Rajkumar, A., Martin, O., Dode, X., Lajonchère, J. P., Billuart, O., … & Buronfosse, A. (2020). A machine learning–based clinical decision support system to identify prescriptions with a high risk of medication error. Journal of the American Medical Informatics Association, 27(11), 1688-1694.
Slight, S. P., Tolley, C. L., Bates, D. W., Fraser, R., Bigirumurame, T., Kasim, A., … & Watson, N. W. (2019). Medication errors and adverse drug events in a UK hospital during the optimisation of electronic prescriptions: a prospective observational study. The Lancet Digital Health, 1(8), e403-e412.
Purpose
The purpose of this study was to evaluate the effectiveness of the Medication Error Monitoring System for the reduction of medication errors in a maternity and a childcare hospital, specifically the Xiamen Maternity and Child Care Hospital.
The purpose of this study was to assess the impact of electronic prescriptions on the rates and types of medication errors regarding the prescribing and dispensing phases. Also, this research had the objective of formulating recommendations regarding the use of electronic prescriptions in Egyptian outpatient clinical settings.
The purpose of this study was to capture the total number of medications per patient, with a focus on high-risk medications since they are linked with a higher likelihood of causing significant harm, prolonged hospitalizations, or even death if used in error.
The purpose of this study was to improve patient safety and clinical outcomes by reduction of the risk of prescribing errors. To improve patient safety, the researchers tested
the accuracy of a hybrid clinical decision support system designed for prioritizing prescription checks.
The purpose of this study was to assess whether the number and type of medication errors changed when optimization over time of an electronic prescribing system in a UK hospital happened.
Research Method
The main method used was error reporting by physicians and pharmacists. Researchers collected data twice and then compared the results. Between the two data collection periods, pharmacists were trained in using medication error monitoring systems. This study is designed based on the before-after design, where two data sets of different periods are compared.
The research was conducted by collecting retrospective data. Medication errors and correction interventions were collected after reviewing the incident reports obtained from the outpatient pharmacy in a specialized hospital in Egypt. “Outcome measures are prescribing and prescription errors, dispensing errors, error
-free prescriptions, pharmacy call-backs and phone calls for five months before and five months after the electronic system implementation.” This study is designed based on the before-after design, where two data sets of different periods are compared.
The method of this study was that trained pharmacy technicians used a secure web platform to complete a survey regarding medication history. Researchers developed a list of high-risk drugs using scholarly databases and then classified medications collected by surveys. This is a pilot study.
This research used collated data from electronic health records over a period of 18 months. The researchers calculated inferred scores at a patient level using a hybrid approach of machine learning and a rule-based expert system. A Clinical pharmacist analyzed randomly selected perception orders over two weeks to corroborate the researchers’ findings. Inferred scores and pharmacist’s reviews were compared using the area under the receiving-operating characteristic curve
and the area under the precision-recall curve. And those metrics were compared with the existing tools of computerized
alerts generated by a clinical decision support (CDS) system and a literature-based multicriteria query prioritization technique.
This is a prospective observational study conducted at a tertiary-care teaching hospital.
A negative-binomial model and a Poisson model were used to identify factors related to medication error rates.
Participants
Physicians and pharmacists in the Xiamen Maternity
and Child Care Hospital (participants number not indicated).
Pharmacists in outpatient settings in Egypt, 4 to 5 pharmacists were present in the pharmacy
during the two phases.
There were six participating hospital sites. Six full-time trained pharmacy technicians were the participants.
Pharmacists collected data from electronic health records. Also,
“over a 2-week period, a fully trained clinical pharmacist routinely
analyzed randomly selected patient prescription orders on all wards
and made a note of the interventions that followed.”
The participants were eight senior clinical pharmacists who reviewed patients’ records and collected data across four adult wards. The eight senior clinical pharmacists also recorded instances where the electronic prescribing system was linked to an error.
Data Collection Methods
Data were collected by error reporting done by physicians and
Pharmacists in the chosen setting.
Pharmacists collected data by reviewing retrospective data over ten months (five months using hand-written prescriptions and five months using electronic health records. Data was collected using a medication error form according to the American society of health system pharmacists guide. The data collection form consisted of two parts; the first part enclosed the medication error classifications, while the second part included action taken to correct the error.
Data were collected by an electronic data collection tool. The researchers used a secure web platform, and the data collected included patient-specific information, the number and type of high-risk medications, and potential medication errors.
Data were collected from electronic health records. Data were collected on 94720 hospitalizations and a total of 61611 patients.
Data were collected from electronic health records. Data were collected in four separate periods. During data collection, “all medication errors and potential and actual adverse drug events were documented.”
Also, “Pharmacists also recorded instances where the electronic prescribing system contributed to an error (system-related errors).”
Study Findings
Between the two periods, the total medication errors were reduced by 27%. The success rate of pharmacy interventions increased from 95.25%
to 96.88%. In conclusion, the medication error monitoring system is effective in monitoring error data which leads to a reduction in reported medical errors.
The electronic prescription system, compared to hand-written prescriptions, led to a 2% reduction in prescribing errors, a 1.2% decrease in dispensing errors, and an 18.2% increase in error-free participants. Electronic prescribing coupled with pharmacists’ training is able to reduce prescribing and dispensing errors in outpatient clinics.
After 191 patient records were completed by the survey tool, 1088 medications were recorded, 41% were high-risk medications, and 42% of the medication errors were classified as high risk. 58% of high-risk medication orders have a potential contribution to medication errors during patient admission and discharge. As a result, this web-based survey tool improved the quality and efficiency of potential error identification.
The innovative digital tool designed by the researchers was notably more accurate than the clinical digital support system and the multicriteria query at intercepting potential prescription errors. The novel hybrid decision support system improved both the accuracy and reliability of perception checks in the hospital setting.
5796 primary medication errors were recorded over four time periods. There was no change in the rate of primary medication errors per admission over the observation periods. On the other hand, the overall rate of different types of medication errors decreased over the four periods. Also, it was found that there is a reduction in the rates of potential adverse reactions over time.
Limitations of the study
The study was not controlled, and it only focused on prescribing and dispensing phases.
Limitations included that the study did not completely compare the hand-written and electronic systems. The before-after study design has disadvantages including no randomization or control groups.
The development of the tool had limitations, such as the fact that vitamins or supplements information was limited to the total number of medications and medication errors identified.
The results of this study are limited since the study was conducted in a single hospital setting. Also, neonatology and intensive care units were not included in this study.
Limitations included that different clinical pharmacists collected data for three of the study wards over the study periods. Moreover, generalizability is limited due to the fact that data collection occurred at one hospital.
Relevance to the practice issue and/or proposed intervention
This study showed that a type of computerized data entry system is effective in reducing medication errors which are directly linked to the PICOT statement.
This study studied the impact of using electronic prescribing system and pharmacists’ training on reducing prescribing and dispensing medical errors, which is directly linked to the PICOT statement.
This study examined the effectiveness of a web-based survey used by pharmacists in detecting errors, which is moderately linked to the PICOT statement.
The participant was a fully trained pharmacist, which reflects the importance of training pharmacists to reduce medical errors by using computerized systems, which is moderately linked to the PICOT statement.
This study examined the effectiveness of an electronic prescribing system used by pharmacists in detecting errors, which is moderately linked to the PICOT statement.
References
Afreen, N., Padilla-Tolentino, E., & McGinnis, B. (2021). Identifying Potential High-Risk Medication Errors Using Telepharmacy and a Web-Based Survey Tool. Innovations in pharmacy, 12(1), 10.24926/iip.v12i1.3377.
Chen, Y., Wu, X., Huang, Z., Lin, W., Li, Y., Yang, J., & Li, J. (2019). Evaluation of a medication error monitoring system to reduce the incidence of medication errors in a clinical setting. Research in Social and Administrative Pharmacy, 15(7), 883-888.
Corny, J., Rajkumar, A., Martin, O., Dode, X., Lajonchère, J. P., Billuart, O., … & Buronfosse, A. (2020). A machine learning–based clinical decision support system to identify prescriptions with a high risk of medication error. Journal of the American Medical Informatics Association, 27(11), 1688-1694.
Kenawy, A. S., & Kett, V. (2019). The impact of electronic prescription on reducing medication errors in an Egyptian outpatient clinic. International journal of medical informatics, 127, 80-87.
Manias, E., Kusljic, S., & Wu, A. (2020). Interventions to reduce medication errors in adult medical and surgical settings: a systematic review. Therapeutic advances in drug safety, 11, 2042098620968309.
Medication Errors | AMCP.org. (2022). Retrieved 28 September 2022, from https://www.amcp.org/about/managed-care-pharmacy-101/concepts-managed-care-pharmacy/medication-errors
Slight, S. P., Tolley, C. L., Bates, D. W., Fraser, R., Bigirumurame, T., Kasim, A., … & Watson, N. W. (2019). Medication errors and adverse drug events in a UK hospital during the optimisation of electronic prescriptions: a prospective observational study. The Lancet Digital Health, 1(8), e403-e412.
Tansuwannarat, P., Vichiensanth, P., Sivarak, O., Tongpoo, A., Promrungsri, P., Sriapha, C., … & Trakulsrichai, S. (2022). Characteristics and Consequences of Medication Errors in Pediatric Patients Reported to Ramathibodi Poison Center: A 10-Year Retrospective Study. Therapeutics and Clinical Risk Management, 18, 669.
NR505 Week 7 Assignment: Evidence-based Practice Project Proposal
Student Name: Student Name
Date: April 17, 2022
Overview and Significance of the Practice Issue
Several baby boomer-aged nurses retiring and other nurses transferring to less acute units have caused a shortage of critical care nurses at Southwest General Hospital (SWGH). Statistics reflect that the nursing shortage will continue due to these factors resulting in the demand for acute care nurses outpacing the supply of qualified individuals. The current turnover rate of critical care nurses averages 18.7%, with organizational costs of replacing one nurse nearing $40,000 (NSI Nursing Solutions, Inc. [NSI], 2021).
The current recruitment practices at SWGH do not include hiring new graduate nurses (NGN) directly to the intensive care unit (ICU) due to inexperience, lack of available staff resources, or inadequate NGN orientation programs. Recruitment and retention of NGNs to critical care environments is complex. It requires efforts to bridge a practice readiness gap or risk nearly 24% of NGNs leaving positions within their first year of employment (Baudoin et al., 2022; NSI, 2021). Baudoin et al. (2022) recommended that hospitals enable NGN hires into acute care environments, provided programs exist to provide adequate learning to ensure successful transitions to practice.
PICOT Statement
Will implementing a new graduate nurse NGN (P) critical-care internship and residency program (I) at SWGH help integrate NGNs to improve ICU recruitment and retention rates (O) compared to no critical-care nurse internship and residency program (C) during a 12-to-16-week timeframe (T)?
P- Population and Problem: SWGH does not consider NGNs for ICU employment. The ICU has poor critical-care nurse recruitment and long-term retention of nurses.
I – Intervention: Introduction of a multi-faceted NGN critical care internship and residency program utilizing unit-specific orientation, supportive mentors, detailed preceptor/preceptee roles, and regular feedback. A focus group of key SWGH stakeholders representing clinical educators, internship program directors, experienced ICU nurse leaders as preceptors, and nurse managers to plan, implement and perform regular evaluations (Bakon et al., 2018).
C – Comparison: SWGH does not have a residency program that supports the transition of NGN to the ICU. Bakon et al. (2018) emphasized lack of proper NGN orientations leads to more staff turnover, increased hospital costs, preceptor burnout, and poor unit morale.
O – Outcome: SWGH’s successful integration, recruitment, and retention of NGNs in the ICU as indicated by NGN retention rates greater than 90%. According to a literature review by Asber (2019), NGN residency programs improved NGN retention rates, accounting for first-year retention rates ranging from 74% to 100%.
T – Timeframe: A 12 to 16-week intensive internship with an ICU nurse mentor is planned with a proposed follow-up residency period to provide ongoing support. In a Canadian study by Rush et al. (2014, as cited in Bakon et al., 2018), NGNs reported needing the most help transitioning during the first three months after graduation.
Proposed Intervention and Expected Outcome
To improve the recruitment and retention of new graduate nurses to SWGH’s ICU, I recommend implementing a multi-faceted NGN critical care nurse internship and residency program. A focus group of clinical educators, experienced nurses, and associated nursing program faculty is needed to design, plan and implement an intense NGN ICU internship. The program would include a combination of organizational and unit-specific orientations, experienced nurse preceptors and mentors guiding safe clinical skills development, and scheduled evaluations and feedback opportunities over 12 to 16 weeks. There is significant evidence that nurse residency and internship programs improve an NGN’s clinical skills, confidence, and professional development to support a successful transition to practice (Bakon et al., 2018).
Outcomes of the successful integration of an NGN ICU internship program will be measured by greater than 90% of NGN retention rates beyond the first year of hire. Asber (2019) indicated in a literature review that NGN residency programs improved first-year retention rates by74% to 100%.
Synthesis of Evidence to Support the Proposed Intervention
There are countless research studies examining measures to mitigate factors that compound the nursing shortage issue related to nurses retiring and high turnover rates of NGNs. The evidence supports that using nurse residency and internship programs is vital for ensuring the successful transition of NGNs and sustaining the workforce. The predominant factor obtained from scholarly literature sources highlighted the utilization of nurse preceptors and mentors are crucial for NGNs to develop the knowledge, skills, and attitudes necessary to become competent nurses. Study findings by Degrande (2018), Özkaya Sa?lam et al. (2021), and Van Patten and Bartone (2019) confirmed the use of preceptors and mentors enables NGNs to have a positive experience while successfully transitioning to professional practice. Degrande and Özkaya Sa?lam et al. found that guidance and collaboration offered by preceptors and mentors reduced stress and helped NGNs overcome fears related to working with acutely ill patients, allowing improved confidence and critical skills development. Likewise, Van Patten and Bartone reported that the combination of preceptorship and debriefing processes reduced stress, enabling a more positive and productive learning experience. The common themes of the research provided reinforced how providing adequate supportive, educational resources and personnel with well-structured programs are vital for enhancing the NGN’s experience influencing a positive practice transition. Quantitative findings by Yao et al. (2021) supported evidence that enhancing student nurses’ professional identity and self-efficacy improve competencies by 48% and 52%, respectively. The study’s findings can be translated to support the inclusion of internship strategies targeting self-efficacy and professional development. Additional research by Zhang et al. (2019) provided quantifiable evidence that extensive use of one-on-one mentorships in NGN internships improved first, second and third-year turnover rates at 3.77%, 3.48%, and 8.11% compared to no mentorship turnover rates of 14.07%, 9.36%, and 14.19%.
It is prudent to acknowledge several limitations presented by the scholarly research provided. Degrande et al. (2018), Özkaya Sa?lam et al. (2021), and Zhang et al. (2019) all expressed that the use of small participant sample sizes or single-site studies minimized the transferability and generalization of findings. Research by Van Patten and Bartone (2019) noted that the data obtained from a single point in time using a pre-designed Versant RN Residency curriculum impaired the transferability of findings to other facilities that use different residency programs. Similarly, Yao et al. (2021) emphasized caution against over-generalizing the results of their study because the requirements and structures of nursing internship and residency programs vary in every country.
Stakeholder Implications
The existing shortage and poor recruitment and retention of ICU nurses at SWGH impact several stakeholders at the organization’s micro, meso, and macro levels. Hospital directors and financial officers at the macro-level are burdened by the costs of high nursing attrition rates, which can average $5 million annually (NSI, 2021). The proposed evidence-based intervention may help increase nurse recruitment and retention rates, allowing financial resources for additional investments and healthcare improvement projects.
Meso-level stakeholders affected by poor ICU nurse recruitment and retention include nurse managers, clinical educators, and human resource directors. Nursing management is tasked with ensuring the ICU is appropriately staffed with adequately trained nurses that support quality, safe patient care. At the same time, human resource directors are challenged with developing innovative ways to recruit new staff or, in many cases, offer sign-on bonuses that add to the expense of hiring. Adding an NGN critical care internship for hire and residency program may be a more effective and less costly ICU nurse recruitment strategy.
Frontline nurses, physicians, families, and patients at the micro-level are most notably impacted by inadequate staffing in the ICU related to poor nurse recruitment and retention. In a cross-sectional survey, Ball et al. (2018) noted that every additional patient assigned to a nurse increases a patient’s chance of dying by 7% within 30 days of admission. Increased patient-to-nurse ratios in the ICU are associated with poor patient outcomes associated with missed nursing care and emotionally and physically exhausted nursing staff (Ball et al., 2018; Guo et al., 2017). High turnover rates also stress nurse preceptors and mentors who become tired of frequently training new unit nurses. Maintaining the objective of increased retention and recruitment of NGN nurses directly to the ICU will alleviate the stressors and costs associated with inadequate staffing ratios and high nurse attrition rates.
References
Asber, S. R. (2019). Retention outcomes of new graduate nurse residency programs. JONA: The Journal of Nursing Administration, 49(9), 430–435. https://doi.org/10.1097/nna.0000000000000780
Bakon, S., Craft, J., Wirihana, L., Christensen, M., Barr, J., & Tsai, L. (2018). An integrative review of graduate transition programmes: Developmental considerations for nursing management. Nurse Education in Practice, 28, 80–85. https://doi.org/10.1016/j.nepr.2017.10.009
Ball, J. E., Bruyneel, L., Aiken, L. H., Sermeus, W., Sloane, D. M., Rafferty, A., Lindqvist, R., Tishelman, C., & Griffiths, P. (2018). Post-operative mortality, missed care and nurse staffing in nine countries: A cross-sectional study. International Journal of Nursing Studies, 78, 10–15. https://doi.org/10.1016/j.ijnurstu.2017.08.004
Baudoin, C. D., McCauley, A., & Davis, A. H. (2022). New graduate nurses in the intensive care setting. Critical Care Nursing Clinics of North America, 34(1), 91–101. https://doi.org/10.1016/j.cnc.2021.11.007
DeGrande, H., Liu, F., Greene, P., & Stankus, J.-A. (2018). The experiences of new graduate nurses hired and retained in adult intensive care units. Intensive and Critical Care Nursing, 49, 72–78. https://doi.org/10.1016/j.iccn.2018.08.005
Guo, Y., Luo, Y., Lam, L., Cross, W., Plummer, V., & Zhang, J. (2017). Burnout and its association with resilience in nurses: A cross-sectional study. Journal of Clinical Nursing, 27(1-2), 441–449. https://doi.org/10.1111/jocn.13952
NSI Nursing Solutions, Inc. (2021). 2021 NSI na
