NUR 630 Benchmark – Outcome and Process Measures

Grand Canyon University NUR 630 Benchmark – Outcome and Process Measures– Step-By-Step Guide

This guide will demonstrate how to complete the Grand Canyon University  NUR 630 Benchmark – Outcome and Process Measures assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.

How to Research and Prepare for NUR 630 Benchmark – Outcome and Process Measures                          

Whether one passes or fails an academic assignment such as the Grand Canyon University  NUR 630 Benchmark – Outcome and Process Measures depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.

After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.

How to Write the Introduction for NUR 630 Benchmark – Outcome and Process Measures                          

The introduction for the Grand Canyon University  NUR 630 Benchmark – Outcome and Process Measures is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.

How to Write the Body for NUR 630 Benchmark – Outcome and Process Measures                          

After the introduction, move into the main part of the NUR 630 Benchmark – Outcome and Process Measures assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.

Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.

How to Write the Conclusion for NUR 630 Benchmark – Outcome and Process Measures                          

After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.

How to Format the References List for NUR 630 Benchmark – Outcome and Process Measures                          

The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.

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Sample Answer for NUR 630 Benchmark – Outcome and Process Measures

Healthcare facilities have an ethical responsibility to provide high-quality care in safe settings. To sustain high outcomes, healthcare facilities should embrace continuous quality improvement (CQI) and adopt robust systems to enable health professionals to provide competent care. In the multidimensional health practice, CQI represents a quality management process where health teams evaluate their performance and develop interventions to improve procedures (Tibeihaho et al., 2021). CQI contributes significantly to more effective and simplified techniques that apply scientific solutions to improve routine processes. The purpose of this paper is to describe process and outcome measures that can be used for CQI.

Process Measures for CQI

Healthcare facilities committed to achieving high outcomes must continually improve care processes. According to Ogrinc (2021), process measures evaluate nursing professionals’ actions to influence a particular result. In this case, process measures represent the evidence-based practices that care facilities use in daily practice to systematize their improvement efforts. One such measure is the frequency of intentional rounding for hospitalized patients. Intentional rounding is among the measures that organizations use to prevent patient falls and other adverse events like pressure ulcers (Di Massimo et al., 2022). The other process measure that can be used for CQI is the percentage of patients receiving fall-related education. Pivotal in informed decision-making, patient education improves health literacy to enable patients to avoid risks at home, care facilities, and other areas.

Outcome Measures for CQI

Healthcare professionals and leaders design care improvement programs seeking to achieve specific outcomes. As a reflection of the impact of health interventions, outcome measures assess the result of a process (Ogrinc, 2021). Therefore, they are more important than process measures since they represent the consequences of actions. A suitable outcome measure for CQI in the current data-driven practice is the hospital-acquired infections (HAIs) rate. Paling et al. (2020) describes HAIs as a significant threat to patient safety since they are contracted in a care facility as a patient gets treatment for other diseases. Their presence insinuates the need for improved procedures to prevent their occurrence. Patient waiting time in the emergency department is another suitable outcome measure for CQI. Leading causes of high waiting time include high bed occupancy and inadequate staffing that cannot effectively respond to high patient occupancy (Paling et al., 2020). Longer waiting times underscore the need for interventions to optimize outcomes.

A Description of Why Each Measure was Chosen

The desire to improve care quality prompts nursing professionals to focus on the aspects that profoundly impact patient outcomes. The same reason was considered when selecting the frequency of intentional rounding for hospitalized patients as a process measure. Gliner et al. (2022) found that nurses’ hourly rounding could be pivotal in reducing patient falls and improving patient satisfaction. Therefore, measuring this frequency and ensuring it is conducted regularly is essential for better patient outcomes. Intentional rounding also improves patients’ perception of care. The number of patients receiving fall-related education was chosen since improving the intervention would help to reduce the adverse effects of patient falls in hospitals.

HAIs and high waiting times in the emergency department are leading causes of health complications, patient mortality, and healthcare spending. As Suksatan et al. (2022) suggested, HAIs should be prevented to avoid associated effects such as disability, transfer of infectious diseases, and reduced trust in the care system. The implication is that using these process and outcome measures as the reference for quality improvement would have multifaceted impacts. The other reason for their selection is their incidence and ability to quantify them. According to the World Health Organization, HAIs are the commonest adverse events in healthcare facilities, irrespective of their size and resources (Stewart et al., 2021). As a cause of extended hospital stays and patient distress, preventing them is critical for care quality that aligns with patients’ expectations.

Data Collection for Each Measure

In the current data-driven practice, healthcare professionals should collect and evaluate data from multiple sources and diverse formats to inform decisions. The best way to collect data for the frequency of intentional rounding is by obtaining it from health records. These records have sufficient details on the number of times nurses visit a particular patient and the specific time. Clinical records also have reliable data about the number of patients receiving patient education. Such data could be retrieved to obtain the number of patients educated on patient falls against bed occupancy. Patient waiting time could be calculated by calculating the time between a patient’s arrival in the department and when a health professional attends to them. In most instances, HAIS’ rate is calculated as the number of infections per 100,000 occupied bed days (Stewart et al., 2021). Using a similar approach, the rate of HAIs can be calculated by dividing the reported cases by the volume of patients per month.

How Success Would Be Determined

Process and outcome measures are pivotal in driving positive change in healthcare settings. They help organizational leaders implement effective interventions to improve care quality (Ogrinc, 2021). Success determination implies evaluating whether CQI interventions achieved the desired goals. In this scenario, a comparative analysis of outcomes before and post-intervention would accurately indicate whether positive change was realized. For instance, increasing the number of educated patients and significantly reducing patient falls are reliable indicators of positive change. Reducing the incidence of HAIs and waiting time after implementing quality improvement projects would also indicate success.

Data-Driven, Cost-Effective Solutions

CQI and related responses to drive higher outcomes encounter numerous challenges. An appropriate data-driven, cost-effective approach is to foster a culture of evidence-based practice (EBP) in healthcare settings. Such a culture is characterized by an incessant commitment to promoting change that leads to high-quality care and reduced costs (Sharplin et al., 2019). In such cultures, CQI is readily embraced by individuals and teams. The other effective solution is to evaluate healthcare processes and outcomes continually. This practice could be organization-wide or across departments as resources allow. It would help organizations to have ready and measurable data to assess care quality and intervene appropriately.

Conclusion

Healthcare facilities should ensure that patients receive care that aligns with the expected quality. To achieve this goal, health organizations should measure quality using process and outcome indicators and improve where necessary. As discussed in this paper, process measures like the frequency of falls and the number of patients receiving fall-related education are suitable process measures for quality improvement. Patient waiting time and the rate of HAIs are appropriate outcome measures for quality improvement. These measures should be continually evaluated as organizations foster a safety culture to sustain the desired performance.

References

Di Massimo, D. S., Catania, G., Crespi, A., Fontanella, A., Manfellotto, D., La Regina, M., … & INTENTO Study Group. (2022). Intentional rounding versus standard of care for patients hospitalised in internal medicine wards: Results from a cluster-randomised nation-based study. Journal of Clinical Medicine, 11(14), 3976. https://doi.org/10.3390%2Fjcm11143976

Gliner, M., Dorris, J., Aiyelawo, K., Morris, E., Hurdle-Rabb, D., & Frazier, C. (2022). Patient falls, nurse communication, and nurse hourly rounding in acute care: Linking patient experience and outcomes. Journal of Public Health Management and Practice: JPHMP, 28(2), E467–E470. https://doi.org/10.1097/PHH.0000000000001387

Ogrinc, G. (2021). Measuring and publishing quality improvement. Regional Anesthesia & Pain Medicine, 46(8), 643-649. http://dx.doi.org/10.1136/rapm-2020-102201

Paling, S., Lambert, J., Clouting, J., González-Esquerré, J., & Auterson, T. (2020). Waiting times in emergency departments: exploring the factors associated with longer patient waits for emergency care in England using routinely collected daily data. Emergency Medicine Journal: EMJ, 37(12), 781–786. https://doi.org/10.1136/emermed-2019-208849

Sharplin, G., Adelson, P., Kennedy, K., Williams, N., Hewlett, R., Wood, J., Bonner, R., Dabars, E., & Eckert, M. (2019). Establishing and sustaining a culture of evidence-based practice: an evaluation of barriers and facilitators to implementing the best practice spotlight organization program in the Australian healthcare context. Healthcare (Basel, Switzerland), 7(4), 142. https://doi.org/10.3390/healthcare7040142

Stewart, S., Robertson, C., Pan, J., Kennedy, S., Dancer, S., Haahr, L., … & Reilly, J. (2021). Epidemiology of healthcare-associated infection reported from a hospital-wide incidence study: considerations for infection prevention and control planning. Journal of Hospital Infection, 114, 10-22. https://doi.org/10.1016/j.jhin.2021.03.031

Suksatan, W., Jasim, S. A., Widjaja, G., Jalil, A. T., Chupradit, S., Ansari, M. J., … & Mohammadi, M. J. (2022). Assessment effects and risk of nosocomial infection and needle sticks injuries among patents and health care worker. Toxicology Reports, 9, 284-292. https://doi.org/10.1016/j.toxrep.2022.02.013

Tibeihaho, H., Nkolo, C., Onzima, R. A., Ayebare, F., & Henriksson, D. K. (2021). Continuous quality improvement as a tool to implement evidence-informed problem solving: experiences from the district and health facility level in Uganda. BMC Health Services Research, 21, 1-11. https://doi.org/10.1186/s12913-021-06061-8

This is insightful Tanya, FMEA is a quality improvement tool that can be used to identify potential sources of errors or defects in a process. It is typically used during the design phase of a project, but can also be employed during manufacturing or service delivery (Doshi & Desai, 2017). FMEA involves listing all potential failure modes for a process, along with the potential effects of each failure mode. The aim is to then identify and implement controls or corrective actions that will eliminate or mitigate the risks associated with each failure mode. When used effectively, FMEA can be an invaluable tool for reducing errors and defects in any process (Kholif et al., 2018). Failure mode and effects analysis is a powerful quality improvement tool that can be used to identify potential failure modes in a process and determine the associated effects. Additionally, FMEA can be used to prioritize quality improvement initiatives based on the potential severity of the identified failure modes (Jain, 2017). When used correctly, FMEA can be an extremely valuable asset in any organization’s quality improvement arsenal.

References

Doshi, J., & Desai, D. (2017). Application of failure mode & effect analysis (FMEA) for continuous quality improvement-multiple case studies in automobile SMEs. International Journal for Quality Research, 11(2), 345. http://www.ijqr.net/journal/v11-n2/7.pdf

Jain, K. (2017). Use of failure mode effect analysis (FMEA) to improve medication management process. International Journal of Health Care Quality Assurance. https://www.emerald.com/insight/content/doi/10.1108/IJHCQA-09-2015-0113/full/html

Kholif, A. M., Abou El Hassan, D. S., Khorshid, M. A., Elsherpieny, E. A., & Olafadehan, O. A. (2018). Implementation of model for improvement (PDCA‐cycle) in dairy laboratories. Journal of Food Safety, 38(3), e12451. https://doi.org/10.1111/jfs.12451