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NHS-FP6004 Dashboard Metrics Evaluation

Paper Details

School: Capella University
Subject: Nursing
Topic: Dashboard metrics associated with benchmarks set
Course: NHS-FP6004
Referencing: APA
Pages: 7



Dashboard metrics associated with benchmarks set

Dashboards are data driven clinical decisions support used in analysis of data from multiple data sets. Dashboards are useful in promoting data driven decisions making and evidence based clinical approaches (Thorlund et al., 2020). Therefore, dashboard tools are critical in the healthcare sector as they assist in analysis and comprehension of data into a readable and easy format. This implies that dashboard metrics enable for analysis of shortfalls in an entity’s key performance indicators (KPI). Presentation of multiple data using color-coded graphical display that is easy to read can enhance understanding of organization’s performance. According to Dagliati et al., (2018) the adoption of visual approaches in reporting a healthcare’s performance allows for establishing the actual condition or performance.

The scope of this paper is to evaluate the current organization concerning the presented metrics and comparing with the benchmarks set forth by the government laws and policies at both the state, local and Federal levels. Besides, this report will advocate for ethical action to address benchmark underperformance and the potential for improving the overall quality of care and performance as reflected on the performance dashboard. From the analysis of the entity’s diabetic dashboard metrics, it’s evident that there is a need to address these shortfalls to enhance improvement in deliver of quality care.

Dashboard metrics associated with government benchmarks

The healthcare organization’s diabetes benchmark data is an indicator of how the entity is performing relating to diabetes management. This data is also critical in informing stakeholders on how well the organization is able to test and screen patients with diabetes. The benchmark data incorporate different screening and testing interventions such as eye examination, foot exams and HgbA1C. These are some of the most critical parameters that inform on the etiology of diabetes in patients. From a critical examination of the patient’s case, it’s evident that there are certain metrics that need to be improved it at all the healthcare facility will attain its strategic objectives. The results indicate a gradual decrease in eye exam from Q1 of 2019 to Q4 of the same year. The diabetic foot exams decreased substantially from the first quarter of 2018 to the fourth quarter of 2019. In the subsequent year, there was an increase in HgbA1C exams in Q1 and a decline in the other three quarters. This benchmark has portrayed a dismal performance throughout 2019 in comparison to the previous year therefore, warranting an in-depth assessment. The implications of this aspect are that the healthcare entity has not advanced significant resources towards this area. Therefore, a reduction in patient’s care could be witnessed in the facility due to these variations. Besides, underperformance of this metric indicates that the patients and the community could experience negative health consequences such as increased mortality and morbidity attributed to diabetes due to this aspect.

NHS-FP6004 Dashboard Metrics Evaluation

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As cited by Schnell, Crocker & Weng (2017), conducting HgbA1C examination for diabetes patients is imperative as it leads to screening for pre-diabetic conditions. The advantages of this screening leads to determination of the blood sugar levels which are an indicator of diabetes exposure. Studies have shown that elevated levels of HgbA1C can imply that there is unmanaged blood glucose which is lethal for the overall health of an individual. Gardiner et al., (2018) argues that this condition can also be implicated for causing kidney complications, heart diseases, optical dysfunctions and certain types of cancers. Therefore, it’s fundamental for our health care facility to address the poor performance of this benchmark to increase individual and community health.

One of the fundamental aspects in dashboard metrics analysis is to understand their association with the government benchmarks. The Agency for Healthcare Research and Quality (AHRQ) indicates that better performance of a healthcare entity concerning diabetes benchmarks implies higher values measured. The national benchmark cites that the benchmark for patients who are 40 years and above who get more than 2 HgbA1C annually should be 79.5. This implies that our facility made significant steps in reaching this benchmark in the Q4 of 2019 with 174 exams.

Challenges posed by prescribed benchmarks

Every healthcare entity faces challenges of resources in facilitating sustainable operations (Oueida, Aloqaily & Ionescu, 2019). This is the same case for our healthcare entity as limited resources could pose a threat to attaining the government benchmarks. Lack of adequate resources imply that the entity will attain limited community outreach. As noted by Esteva et al., (2019), the nature of relationships between a health care entity and the community is critical in delivering quality care. This implies that the ability of a healthcare entity to engage with the community will lead to reduced readmission rates, lowered hospitalization and compliance to treatment modalities. However, an assumption is made that a healthcare entity fails to build personalized relationships with the community. This implies that there can be lack of trust and success may not be attained concerning the hemoglobin diabetes metric.

Benchmark underperformance

The underperformance of the HgbA1C in the healthcare organization has the potential of reducing the overall quality of care for the patients and the community. The improvement in this benchmark will lead to improvement in positive health outcomes in the community. According to Lim et al., (2018), screening for diabetes and elevated blood sugar is an invaluable undertaking in facilitating early interventions. Besides, the assessment of diabetes among the community members is crucial in improving the overall quality of care for the patients. This implies that underperformance of this benchmark implies a deterioration in the overall health outcomes.

From the analysis of the presented data, there is an overarching need to create a plan that will increase screening compliance as recommended by the state, federal and local regulations. One of the imperative undertakings in improving the underperformed metric is to conduct continuous training on the healthcare staff to enable attainment of positive outcomes. The greatest opportunity for improving the overall quality of care therefore lies in improving the practical skills of nurses and care takers. Poor performance in the dashboard metric will therefore, require advanced knowhow in HgbA1C assessment. Bissett et al., (2010) argue that updating the inter-professional team on current practices in diabetes management is a crucial aspect in improving patient’s overall outcomes. These will improve the poor benchmark performance and lead to increase in overall quality of care.

Ethical action to address the benchmark underperformance

The healthcare facility should adopt ethical directives aimed at improving the overall health outcomes for the community. According to Thomas and Mathew (2020), the beneficence principle mandates healthcare professionals to treat the patients ethically through giving them autonomy and respecting their decisions. Acting within this ethical guideline will ensure an improvement in the underperformed benchmark to improve the well-being. The healthcare facility should act within the domains of this ethical principle through engaging the community in health promotion activities. Besides, it would be the interest of the entity to make patients follow ups to determine their recovery speed and avert the need for readmission due to exacerbations of diabetes. The organization could also deploy social workers to educate the community on screening for diabetes in primary care entities. This implies that the actions taken by stakeholders will lead to improvement of professional skills and community knowhow related to the underperforming benchmark.


Despite the performance of the healthcare entity in the community, there are some benchmarks that that are lagging and which need to be improved related to HgbA1C examination. This parameter can have a negative consequence on the performance and sustainability of the healthcare entity. The healthcare organization will therefore need to increase staff training and community education on diabetes screening in a bid to increase positive health outcomes for the patients and community.



Agency for Healthcare Research and Quality. National Healthcare Quality and Disparities Reports. NHQDR Web Site – National Diabetes Benchmark Details.

Bissett, S. M., Preshaw, P. M., Presseau, J., & Rapley, T. (2020). A qualitative study exploring strategies to improve the inter-professional management of diabetes and periodontitis. Primary care diabetes, 14(2), 126-132.

Dagliati, A., Sacchi, L., Tibollo, V., Cogni, G., Teliti, M., Martinez-Millana, A., … & Bellazzi, R. (2018). A dashboard-based system for supporting diabetes care. Journal of the American Medical Informatics Association, 25(5), 538-547.

Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., … & Dean, J. (2019). A guide to deep learning in healthcare. Nature medicine, 25(1), 24-29.

Gardiner, F. W., Nwose, E. U., Bwititi, P. T., Crockett, J., & Wang, L. (2018). Blood glucose and pressure controls in diabetic kidney disease: narrative review of adherence, barriers and evidence of achievement. Journal of Diabetes and its Complications, 32(1), 104-112.

Lim, W. Y., Ma, S., Heng, D., Tai, E. S., Khoo, C. M., & Loh, T. P. (2018). Screening for diabetes with HbA1c: Test performance of HbA1c compared to fasting plasma glucose among Chinese, Malay and Indian community residents in Singapore. Scientific reports, 8(1), 1-9.

Oueida, S., Aloqaily, M., & Ionescu, S. (2019). A smart healthcare reward model for resource allocation in smart city. Multimedia tools and applications, 78(17), 24573-24594.

Schnell, O., Crocker, J. B., & Weng, J. (2017). Impact of HbA1c testing at point of care on diabetes management. Journal of diabetes science and technology, 11(3), 611-617.

Thomas, V. M., & Mathew, A. (2020). Truth-telling: Apply the principle of beneficence. Cancer Research, Statistics, and Treatment, 3(2), 359.

Thorlund, K., Dron, L., Park, J., Hsu, G., Forrest, J. I., & Mills, E. J. (2020). A real-time dashboard of clinical trials for COVID-19. The Lancet Digital Health, 2(6), e286-e287.

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