Assignment: HSNCB 376 Competency 2

Assignment: HSNCB 376 Competency 2

Assignment: HSNCB 376 Competency 2

Apply Competency 2

Your organization has made it a priority that safety is taken into consideration in clinical decisions. There is an opportunity to find an informatics or technology solution to improve safety and overall patients€™ well-being.

You are helping your director look at possible solutions. You want to show her that you can assess how potential solutions always guarantee patients€™ safety.

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You will prepare a 600-word report of your findings; provide a detailed description of at least two viable solutions and include your rationale for selecting one over the other. Many people, including your director, are visual thinkers and want to see” a table or chart in addition to text.

Determine what criteria are important, safety being foremost.

You may also consider:

Ease of use

Clarity
Time
You know it’s important that you show your director you have considered any relevant regulatory, legal, or ethical issues.

Include a minimum of 3 peer-reviewed sources and develop an APA-formatted reference page. Use the APA Style Guide, 7th Edition.

Assignment: HSNCB 376 Competency 2 Sample

Informatics and its related technology are at the core of providing better care and patient safety. Informatics entails the integration of nursing science with other areas to identify, manage, and communicate data, information. Knowledge as well as wisdom to care providers. Patient safety emanates from system’s efficiencies and abilities to identify adverse events (Choudhury & Asan, 2020). The purpose of this paper is to offer a report on potential informatics solutions to enhance and guarantee patient safety.

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Description of the Findings

The use of artificial intelligence in health care offers increased opportunities for providers and healthcare facilities to deliver precision care through components like clinical decision support system (CDSS) and predictive analytics. Patient safety is a core part of quality care and improved outcomes as healthcare organizations can only get reimbursed by health insurance companies through Centers for Medicare and Medicaid Services (CMS) when they meet the set quality levels through patient survey tools like the Hospital Consumer Assessment of Healthcare Provider and Systems (HCAHPS) (CMS, 2019). The two potential informatics solutions to guaranteeing patient safety include use of predictive analytics and clinical decision support.

Real-time data surveillance and analysis is critical in ensuring that nurses and healthcare organizations can detect any adverse events and institute interventions. For instance, syndromic surveillance helps public health officials and nurses in emergency departments to identify and detect symptoms in the general populations and among patients to develop appropriate interventions or responses. In their study, Keim-Malpass et al. (2021) explore the interaction between nursing and predictive analytics in monitoring patients in acute and intensive care settings in response to COVID-19 pandemic and as a long-term way of improving patient safety. The study asserts that through this solution, nurses improve their cognition to make complex clinical decisions. It also allows them to make early detections of patients at risks of decompensation.

Again, studies show that as a component of nursing informatics, clinical decision support systems (CDSS) can improve patient safety in diverse healthcare settings (Ohno-Machado, 2018). Clinical decision support systems (CDSS) help providers reduce the rate of medical errors through effective use of electronic medical records (EMRs), minimize unnecessary or duplicate testing and other components of diagnostic tests, and reduce the overall length of stay as well as prevalence of hospital-acquired infections and conditions.  In their study, Sutton et al. (2020) note that CDSS tools are effective for patient outcomes as well as the performance of clinicians for diverse diseases like diabetes and hypertension as well as cardiovascular disease. Clinicians can also leverage CDSS to prescribe medications with increased precision and accuracy levels that enhance the overall patient safety.

Rationale and Selection of Predictive Analytics

Both predictive analytics and clinical decisions support systems (CDSS) are critical and beneficial components of informatics and healthcare technologies. However, increased evidence shows that predictive analytics are well-positioned to help nurses and healthcare organizations improve patient safety because they are based on increased use of artificial intelligence (AI) (Feldman et al., 2018). The implication is that predictive analytics can be deployed in diverse healthcare approaches and applications, including CDSS. For instance, the increased role of nurses like monitoring acute patients require them to use interventions that have better rates of accuracy and precision (Ohno-Machado, 2018). Consequently, they can use predictive analytics-based tools like syndromic surveillance, to detect any changes that may lead to adverse events.

Conclusion

The use of predictive analytics in informatics is premised on the need to improve quality of care and guarantee patient safety. Therefore, the approach will help the organization guarantee patient safety and improve overall outcomes. As such, it offers broader applications compared to clinical decision support system (CDSS). Further, it improves nurses’ abilities in their nursing process by expediting it, critical thinking to augment their reasoning, organizes their thinking to enhance structure and clinical decision support to implement evidence-based practice (EBP) care interventions.

Infographics on the Benefits of Predictive Analytics

References

Centers for Medicare and Medicaid Services (CMS) (2019). HCAHPS: Patients’ Perspectives of

Care Survey. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/HospitalHCAHPS

Sutton, R. T., Pincock, D., Baumgart, D. C., Sadowski, D. C., Fedorak, R. N., & Kroeker, K. I.

(2020). An overview of clinical decision support systems: benefits, risks, and strategies for success. NPJ digital medicine, 3(1), 1-10. DOI:https://doi.org/10.1038/s41746-020-0221-y

Choudhury, A., & Asan, O. (2020). Role of artificial intelligence in patient safety outcomes:

            systematic literature review. JMIR medical informatics, 8(7), e18599. doi: 10.2196/18599

Feldman, S. S., Buchalter, S., & Hayes, L. W. (2018). Health information technology in

healthcare quality and patient safety: literature review. JMIR medical informatics, 6(2), e10264. doi: 10.2196/10264

Keim-Malpass, J., & Moorman, L. P. (2021). Nursing and precision predictive analytics

monitoring in the acute and intensive care setting: An emerging role for responding to COVID-19 and beyond. International journal of nursing studies advances, 3, 100019. doi: 10.1016/j.ijnsa.2021.100019

Ohno-Machado, L. (2018). The role of informatics in promoting patient safety. Journal of the

American Medical Informatics Association, 25(7):773, https://doi.org/10.1093/jamia/ocy079