Sample Answer for NUR 630 Benchmark- Outcome and Process Measures Included After Question
In a 1,000-1,250-word paper, consider the outcome and process measures that can be used for CQI. Include
the following in your essay:
- At least two process measures that can be used for CQI.
- At least one outcome measure that can be used for CQI.
- A description of why each measure was chosen.
- An explanation of how data would be collected for each (how each will be measured).
- An explanation of how success would be determined.
Page 13 Grand Canyon University 2022 © Prepared on: Feb 11, 2022
- One or two data-driven, cost-efective solutions to this challenge.
Use a minimum of three peer-reviewed scholarly references as evidence.
Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar
with the expectations for successful completion.
You are required to submit this assignment to LopesWrite. A link to the LopesWrite technical support articles is
located in Class Resources if you need assistance.
This benchmark assignment assesses the following programmatic competency:
MSN Leadership in Health Care Systems
6.5: Generate data-driven, cost-efective solutions to organizational challenges.
A Sample Answer For the Assignment: NUR 630 Benchmark- Outcome and Process Measures
Title: 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.
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.
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