Benchmark-Outcome and Process Measures Essay

Benchmark-Outcome and Process Measures Essay

Benchmark-Outcome and Process Measures Essay

Health care organizations and systems make efforts to continually improve the quality of care offered to patients and health populations. Continuous quality improvement is a deliberate yet defined process aimed at activities that are responsive to community health needs and demonstrating baseline performance, setting goals, and monitoring the impacts of changes to health care delivery processes (Kyle et al., 2021). The Agency for Healthcare Research and Quality (AHRQ) asserts that different types of health care quality measures assess and compare the quality offered by organizations. These measures include structure, process, and outcome. The essence of this paper is to explore the outcome and process measures that organizations can use in continuous quality improvement (CQI).

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Two Process Measure for CQI

Continuous quality improvement is a progressive and ongoing effort to attain measurable improvements in the efficiency, effectiveness, accountability, and performance, outcomes, and other indicators of quality for health care organizations. Process measures show what a health organization or provider does in maintenance or improvement of health for both health populations and for individuals diagnosed with health care conditions. Process measures reflect the standard accepted recommendations in clinical practice (Borsky et al., 2018). Process measures allow consumers to know the expected services for certain condition and contribute to the attainment of quality outcomes. The two process measures that can be utilized for CQI include feedback on if patient receive the right care, and the rate at which the patient got the right care. These measures emerge from the existing link between process and outcomes.

One Outcome Measure for CQI

Outcome measures show the effect of the health care service or intervention on the health situation of patients and health populations. Outcome measures show the “gold standard” in measuring quality. However, outcomes come due to several factors that can be beyond the control of an organization or healthcare provider. One outcome measure that can be deployed in enhancing continuous quality improvement (CQI) is rate of patients who die because of surgery (surgical mortality rates) (Ou et al., 2017). AHRQ advances that providers can mitigate outcome measures through using risk-adjustment methods that entail mathematical models to correct the different characteristics within a selected health population like patient health status.

Description for Selecting Each Measure

Measures to improve healthcare delivery are essential in attainment of continuous quality improvement as they demonstrate efforts by providers to offer best care and attainment of patient outcomes. Most of the quality measures in health applied in public reporting to inform policy changes are either process or outcome measures. These measures establish if providers are following the protocols and policy mandates as elucidated in existing standards (Borsky et al., 2018). For instance, the selected process measures seek to answer questions on whether patients got the right care, and the rate at which the patients received the right care. These two measures were selected since they mirror the ability of a provider to offer the right interventions for patients with different condition at different times in their disease journey or process. Patients are treated in the right way to attain desired outcomes. The implication is that the chosen process measures elucidate the need for right interventions by engaging and involving patients in their treatment and care plans.

The percentage of patients succumbing due to surgical interventions is essential in informing providers of the need to seek effective risk management approaches to care delivery. Surgical mortality rate that includes perioperative surgical deaths is a critical outcome measure as they demonstrate the type of care given to such patients by providers (Linecker et al., 2017). As a measure of outcome, these rates implore providers to develop responsive processes and interventions to reduce the causes of such deaths like complications.

Data Collection for Each Measure

Data is an essential part of understanding the different quality measures, from process to outcome because they are linked. Data is an important tool that informs and motivates providers in any healthcare setting. Collection of data for these two types of measures allows providers to assess the level of quality interventions and risk management approaches to mitigate their occurrence (Al Omar et al., 2018). For instance, trend charts are established to highlight desired quality improvement data measures. These charts are also vital in communicating the level of progress made to attain quality care in healthcare facilities for patients and health populations.

Data collection needs to be customized and minimized to assess the most important aspects concerning the elimination of certain measures that lead to poor quality care provision. The data for process measures can be collected through process flow charts. These charts are vital as they assist providers and facilities to outline all the processes that impact outcomes. Data on surgical mortality can be collected from the existing facilities’ registers on the number of patients dying due to surgery related complications and events, both perioperative and postoperative situations (Izumisawa et al., 2022). The data can also be extracted manually from patient’s medical charts by adhering to existing data protection protocols. The use of manual chart remains the standard in healthcare in collecting such data.

Determining Success

Effective and successful evaluation and measures are important for continuous quality improvement. Healthcare organizations and providers need to identify standards that will allow them to determine if their interventions on enhancing process and outcome measures are successful and effective. The use of benchmarking is considered as one of the most appropriate ways to determine success of CQI measures, particularly process and outcome measures (Wind & Van Harten, 2017). Quality performance and patient safety benchmarking are the best ways to determine success of quality care improvement. The process and quality measures identified in this paper require the use of both performance and patient safety benchmarking.

Quality performance benchmarking will evaluate the success of the process and outcome measures. Patient safety benchmarking will be deployed to reduce the rate of surgical deaths by developing risk-adjustment approaches among the providers. The main aim of these two approaches to benchmarking is determining areas that need improvement and the attainment of the Quadruple goals of healthcare. The approach will involve taking the outcome and process metrics on perioperative and postoperative surgical mortality rates, the percentage of patients getting the right care, and the nature of feedback on if they are getting the appropriate care (Al Omar et al., 2018). The data would then be compared to best standards from other facilities and providers to assess areas that need improvement to enhance patient safety and quality of care delivered.

Cost-Effective Solution

Data collected from healthcare facilities plays an essential role in establishing cost-effective solutions to challenges faced in mitigating surgical mortality and inappropriate care. Big data in health care is a huge challenge in effective deployment of the collected information to make necessary decisions to enhance quality. Leveraging this data can help organizations make critical decisions to enhance quality care. In this case, providers can use virtual reality and cloud-based solutions to store data for effective sharing and exchange to enhance interoperability (Al Omar et al., 2019). These two approaches allow providers to share information in different healthcare settings so that they can make informed choices and attain positive healthcare results. Technologies are also privacy-focused as they enable providers to protect patient data. Further, transitional points of care also contain data that providers can use to enhance patient safety, especially to mitigate surgical-related mortality rates.

Conclusion

Continuous quality improvement (CQI) is vital in healthcare as it allows providers to enhance quality and patient safety. CQI entails both process and outcome measures which are fundamental as they contribute to desirable results and realization of the Quadruple Aim model’s goals. Therefore, providers and organizations should collect relevant data from different sources for effective evaluation on outcome and process measures. Benchmarking can allow organizations to compare performance and ensure the success of quality improvement efforts. CQI allows hospitals to optimize care provision and meet quality care goals.

References

Al Omar, A., Bhuiyan, M. Z. A., Basu, A., Kiyomoto, S., & Rahman, M. S. (2019). Privacy-

friendly platform for healthcare data in cloud based on block chainenvironment. Future generation computer systems, 95, 511-521. https://doi.org/10.1016/J.FUTURE.2018.12.044

Borsky, A., Zhan, C., Miller, T., Ngo-Metzger, Q., Bierman, A. S., & Meyers, D. (2018). Few

Americans receive all high-priority, appropriate clinical preventive services. Health

Affairs, 37(6), 925-928. https://doi.org/10.1377/hlthaff.2017.124

Brennan, S., McKenzie, J. E., Whitty, P., Buchan, H., Green, S., Bosch, M., Fiander, M., Strobel,

1. A., Donoghue, E., Page, M. J., Yost, J., & Gonçalves‐Bradley, D. C. (2017).

Continuous quality improvement: effects on professional practice and healthcare

outcomes in primary care. The Cochrane Database of Systematic Reviews, 2017(11),

CD003319. https://doi.org/10.1002/14651858.CD003319.pub3

Izumisawa, Y., Endo, H., Ichihara, N., Takahashi, A., Nawata, K., Shiraishi, H., … & Motomura,

35. (2022). Association between prehospital transfer distance and surgical mortality in emergency thoracic aortic surgery. The Journal of thoracic and cardiovascular surgery, 163(1), 28-35. https://doi.org/10.1016/j.jtcvs.2019.05.001.

Kyle, K. W., Nelson, L. P., & Chapman, R. L. (2021). Quality Improvement. In Comprehensive

            Healthcare Simulation: ECMO Simulation (pp. 171-176). Springer, Cham.

Linecker, M., Björnsson, B., Stavrou, G. A., Oldhafer, K. J., Lurje, G., Neumann, U., … &

Petrowsky, H. (2017). Risk adjustment in ALPPS is associated with a dramatic decrease in early mortality and morbidity. Annals of surgery, 266(5), 779-786.

https://doi.org/ 10.1097/SLA.0000000000002446.

Ou, L., Chen, J., Hillman, K., Flabouris, A., Parr, M., Assareh, H., & Bellomo, R. (2017). The

impact of post-operative sepsis on mortality after hospital discharge among elective

surgical patients: a population-based cohort study. Critical Care, 21(1),

34. https://doi.org/10.1186/s13054-016-1596-7

Wind, A., & Van Harten, W. H. (2017). Benchmarking specialty hospitals, a scoping review on theory and practice. BMC health services research, 17(1), 245. https://doi.org/10.1186/s12913-017-2154-y

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In a 1,000-1,250-word paper, consider the outcome and process measures that can be used for Continuous Quality Improvement (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.