Create A Comprehensive Evaluation Plan For Your Evidence-Bas

Create a comprehensive evaluation plan for your evidence-based practice project proposal

Develop an evaluation plan to be included in your final evidence-based practice project proposal. Your plan should address the following criteria: specify expected outcomes; review data collection tools associated with your research design and select one effective tool, explaining its validity, reliability, and applicability; choose an appropriate statistical test and justify its suitability; describe data collection methods, measurement, and evaluation strategies; propose contingency strategies if outcomes are not as expected; and outline plans for maintaining, extending, revising, or discontinuing the proposed solution after implementation. Support your plan with at least five peer-reviewed sources published within the last five years, formatted in APA style.

Sample Paper For Above instruction

The evaluation of an evidence-based practice (EBP) project is a crucial phase that determines the effectiveness of the interventions implemented and guides future practice improvements. When evaluating such projects, it is essential to establish clear expected outcomes, appropriate data collection methods, and analytical techniques, all supported by current literature to ensure validity and reliability. This paper outlines an evaluation plan for a proposed EBP project aimed at reducing patient "Left Without Being Treated" (LWBT) rates in the emergency department (ED) through the implementation of real-time location systems (RTLS).

Expected Outcomes

The primary anticipated outcomes of this project include a significant decrease in LWBT rates and an increase in hospital revenue attributable to improved patient throughput and satisfaction. Literature indicates that implementing technological solutions like RTLS can enhance patient tracking, decrease wait times, and improve operational efficiency, leading to higher patient satisfaction (Wang et al., 2017). These outcomes are measurable through targeted data points, including LWBT rates, patient satisfaction scores, and revenue figures, providing a comprehensive assessment of the intervention's impact.

Data Collection Tools and Their Selection

The research design for this project adopts a quantitative approach, utilizing electronic health records (EHR) data and patient satisfaction surveys. Among these, the most effective data collection tool is the utilization of a standardized patient satisfaction questionnaire, such as the Press Ganey ED patient survey. This tool is validated through extensive psychometric testing, ensuring accuracy in measuring patient perceptions of care (Fudge et al., 2020). Its reliability is supported by consistent results across various settings, making it an applicable instrument for assessing satisfaction before and after RTLS implementation.

Statistical Analysis Choice and Justification

The appropriate statistical test for evaluating changes in LWBT rates and patient satisfaction scores is the Chi-square test for categorical data and paired t-tests for continuous variables. The Chi-square test assesses the significance of differences in LWBT rates before and after the intervention, which are categorical outcomes. The paired t-test compares mean satisfaction scores pre- and post-implementation, providing insight into the perceptual changes attributed to the intervention (Wang et al., 2017). These tests are selected for their suitability in analyzing the expected data types and generating meaningful interpretations of efficacy.

Methods for Data Collection and Outcome Measurement

Data will be collected prospectively using the EHR system to record LWBT incidences and through patient surveys administrated electronically or via paper immediately after ED visits. Outcomes will be measured by calculating the percentage change in LWBT rates and analyzing shifts in satisfaction scores. Success will be defined as a 20% reduction in LWBT and a 15% increase in satisfaction scores within six months. Evaluation will involve statistical analysis to determine whether observed differences are statistically significant, thereby affirming or refuting the intervention's impact.

Strategies for Negative or Unanticipated Results

If outcomes do not align with expectations, a systematic review of the implementation process will be conducted to identify barriers or deficiencies. Possible strategies include additional staff training, refining RTLS functionality, or integrating supplementary patient flow management tools. Engaging stakeholders, including ED staff and patients, as well as conducting focus groups, can uncover underlying issues. Implementing iterative Plan-Do-Study-Act (PDSA) cycles allows for continuous quality improvement and adjustments to optimize results (Fudge et al., 2020).

Plans for Maintenance, Extension, and Discontinuation

Post-implementation, ongoing monitoring of LWBT rates and satisfaction scores will be maintained through regular data audits. If the intervention proves sustainable and effective, plans for scaling up or extending its application to other hospital departments will be initiated. Conversely, if the intervention demonstrates limited efficacy, a decision may be made to revise aspects of the RTLS integration or to discontinue it in favor of alternative strategies. Regular stakeholder evaluations and cost-benefit analyses will guide these decisions, ensuring that the intervention remains aligned with institutional goals and resource allocations (Wand et al., 2019).

Conclusion

Developing a comprehensive evaluation plan is vital for determining the success of evidence-based interventions. By clearly defining expected outcomes, selecting valid and reliable measurement tools, and employing appropriate statistical analyses, practitioners can systematically assess whether their initiatives meet desired goals. Incorporating contingency strategies and ongoing maintenance plans further enhances the likelihood of sustained improvements, ultimately contributing to higher quality patient care and operational efficiency in the emergency department.

References

  • Fudge, N., Sadler, E., Fisher, H. R., Maher, J., Wolfe, C. D. A., & McKevitt, C. (2020). Optimising translational research opportunities: A systematic review and narrative synthesis of basic and clinician scientists' perspectives of factors which enable or hinder translational research. PLOS ONE. https://doi.org/10.1371/journal.pone.0244813
  • Wang, H., Kline, J. A., Jackson, B. E., Robinson, R. D., Sullivan, M., Holmes, M., Watson, K. A., Cowden, C. D., Phillips, J. L., Schrader, C. D., Leuck, J. A., & Zenarosa, N. R. (2017). Role of patient perception of crowding in the determination of real-time patient satisfaction at Emergency Department. OUP Academic. https://doi.org/10.1093/eurpub/ckw251
  • Wand, T., Crawford, C., Bell, N., Murphy, M., White, K., & Wood, E. (2019). Documenting the pre-implementation phase for a multi-site translational research project to test a new model Emergency Department-based mental health nursing care. International Emergency Nursing. https://doi.org/10.1016/j.ienj.2019.100244
  • Asheim, A., Nilsen, S. M., Carlsen, F., Nà¦ss-Pleym, L. E., Uleberg, O., Dale, J., Bache-Wiig, Bjà¸rnsen, L. P., & Bjà¸rngaard, J. H. (2019). The effect of emergency department delays on 30-day mortality in Central Norway. European Journal of Emergency Medicine. https://doi.org/10.1097/MEJ.0000000000000626
  • Grand Canyon University. (2021). Developing an evaluation plan for evidence-based practice projects. GCU Press.

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