Benchmark Outcome and Process Measures Essay

Benchmark Outcome and Process Measures Essay

Outcome and Process Measures

Health care organizations play a valuable role in restoring patients’ health and enabling populations to live healthily. Accomplishing this goal requires health care organizations to adopt many practices seeking to respond to patients’ specific needs. Quality improvement is also crucial to ensure that better outcomes can be achieved as time advances. As a result, continuous quality improvement (CQI) is integral in health care delivery. Like many other practice areas, health care organizations should evaluate results as far as CQI is concerned. The purpose of this paper is to discuss process and outcome measures that can be used for CQI.

Process Measures for CQI

Health care organizations cannot achieve the desired outcomes without improving health care processes. Process measures for quality improvement indicate health care providers’ efforts to improve health (Pantaleon, 2019). The focus can be on patients or healthy people. A suitable example of process measure is the proportion of patients with diabetes receiving preventive services such as education. For better results in this area, health care providers may also record the number of patients tested for diabetes and receive appropriate health education. In health practice, education can be through education sessions, educational materials such as booklets and pamphlets, or continuous communication through calls or text messaging, among other forms of patient engagement.


The other process measure is the waiting time in the emergency department. Pantaleon (2019) explained that process measures indicate positive or negative health outcomes. They inform patients and stakeholders about the medical care expected in a particular facility. Waiting time varies depending on the number of health care providers and technologies that a facility uses. High waiting time indicates poor processes and the probability of adverse patient outcomes.

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Outcome Measures for CQI

Health care processes influence outcomes that vary depending on the quality of processes. Kampstra et al. (2018) defined outcome measures as a reflection of the impact of health care services or interventions used to address patients’ health. An outcome measure suitable for continuous quality improvement is the rate of hospital-acquired infections (HAIs) in the emergency department. Such infections are caused by bacterial, fungal, and viral pathogens, indicating safety problems in health care settings. Considering that the desired health care quality cannot be achieved without addressing safety issues, HAIs can accurately show adverse outcomes or health care quality below the expected standards. An in-depth analysis of their cause is crucial to determine the most effective intervention.

Why Each Measure was Chosen

Health care providers should always make correct decisions regarding care and quality improvement. The first measure (proportion of patients with diabetes receiving preventive services) was selected since it promotes preventive health. Through preventive health interventions, health care organizations receive better health outcomes since the number of patients seeking care reduces significantly. The proportion of patients receiving such services further informs health care providers whether any changes are required depending on the flow of patients. The second process measure is waiting time. McIntyr and Chow (2020) described waiting time as a leading indicator of the quality of health care services since it can worsen health outcomes during treatment. It is a priority process measure since it deteriorates patients’ health and reduces health gains. The main reason for its selection is that it affects outcomes in almost all patient care areas.

As an outcome measure, the rate of HAIs was selected due to its multifaceted nature. Firstly, HAIs indicate poor processes such as poor ventilators and catheters and contamination. Secondly, HAIs indicate that patient safety is not guaranteed, and patients are at risk of extended hospital stays, health complications, and readmissions (Boehme et al., 2018). Thirdly HAIs indicate that health care facilities do not meet the expected threshold regarding patient safety, care quality, and overall performance. The impacts of HAIs on health are far-reaching, and it should be a priority area when improving care quality in health care facilities.

Data Collection

Data enhances decision-making. It enables health care providers to visualize the current performance against the expected performance. As a result, each area should be measured using data. Clinical records can be used to collect data on the patients with diabetes receiving preventive health services. Patient surveys can be used to assess waiting time and patients’ experiences with care (Alarcon-Ruiz et al., 2019). A general observation of the processes can also inform whether patients receive prompt services or wait longer than expected. Administrative data on HAIs and standardized clinical records can help to measure HAIs accurately. Patient surveys can be used alongside such data sources to provide a more detailed analysis of the situation.

Determining Success

Measuring a process or an outcome informs health care providers about the current performance. The data indicate areas that should guide continuous improvement and the work intensity required to achieve the desired outcomes. One of the most common methods for determining success is assessing performance over time. For instance, an increase in the percentage of patients with diabetes receiving preventive health education would accurately indicate success. The level of patient-provider engagement would be another indicator of success. Patients receiving education would ask providers questions regarding the health tips as they adjust their lifestyle to match care providers’ recommendations. Success can also be determined by comparing an organization’s performance to the national benchmark, typical in HAIs. As the organization does everything possible to reduce HAIs, it should also compare the progress against the national benchmark. Better performance than the national benchmark would reliably indicate success.


Continuous quality improvement is challenging since it requires health care providers to collaborate, be highly updated, and use modern approaches to improve processes and outcomes. Data to guide decision-making must also be accurate and updated progressively. One of the most effective solutions to this challenge is using multiple data sources. As earlier mentioned, patient surveys, standardized clinical records, and administrative data should be used jointly. Combining such data implies using a mixed-methods approach, which provides contextualized and generalizable insights from the data (Regnault et al., 2018). A combined data collection and data analysis approach gives more in-depth insights regarding a situation leading to more informed decisions. Such decisions sustain quality for a long time, saving health care facilities massive resources involved in irregular quality improvement practices or forced by circumstances.


Health care organizations must embrace CQI to ensure that care quality remains at top levels. However, they must be guided by their performance through process and outcome measures. As discussed in this paper, process measures involve what health care organizations do to improve health. Outcome measures are the impacts of everyday processes to optimize health outcomes. Irrespective of the measure, accurate data is crucial to guide decision-making. Combining methods is the best data collection approach to give detailed (contextualized and generalizable) insights on the performance.


Alarcon-Ruiz, C. A., Heredia, P., &Taype-Rondan, A. (2019). Association of waiting and consultation time with patient satisfaction: Secondary-data analysis of a national survey in Peruvian ambulatory care facilities. BMC Health Services Research19(1), 1-9.

Boehme, A. K., Kulick, E. R., Canning, M., Alvord, T., Khaksari, B., Omran, S., …&Elkind, M. S. (2018). Infections increase the risk of 30-day readmissions among stroke survivors: Analysis of the national readmission database. Stroke49(12), 2999-3005.

Kampstra, N. A., Zipfel, N., van der Nat, P. B., Westert, G. P., van der Wees, P. J., & Groenewoud, A. S. (2018). Health outcomes measurement and organizational readiness support quality improvement: A systematic review. BMC Health Services Research18(1), 1-14.

McIntyre, D., & Chow, C. K. (2020).Waiting time as an indicator for health services under strain: A narrative review. INQUIRY: The Journal of Health Care Organization, Provision, and Financing57, 0046958020910305.

Pantaleon, L. (2019). Why measuring outcomes is important in health care. Journal of Veterinary Internal Medicine33(2), 356–362.

Regnault, A., Willgoss, T., Barbic, S., & International Society for Quality of Life Research (ISOQOL) Mixed Methods Special Interest Group (SIG) (2018). Towards the use of mixed methods inquiry as best practice in health outcomes research. Journal of patient-reported outcomes2(1), 19.


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.
One or two data-driven, cost-effective 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 Success Center.

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.

Benchmark Information

This benchmark assignment assesses the following programmatic competency:

MSN Leadership in Health Care Systems

6.5: Generate data-driven, cost-effective solutions to organizational challenges.

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