NURS FPX 8012 Assessment 2 Proposal for a Change Sample:

There is an issue at Villa Health, the ITDS team does not have enough personnel to support the nurses in providing quality care to patients. This implies that people aren’t receiving the care they require as promptly as they should. We must make changes to ensure that patients receive the treatment that they are legally and ethically entitled to. We want a system in which patients and nurses can access care more quickly and efficiently.

This will improve Villa Health’s patient experience as well as community health. We plan to utilize a Clinical Decision Support (CDS) system. This method will allow workers and nurses to respond faster when patients want assistance. It will save patient information and how to assist them. We will collect information in real time from various locations where nurses, physicians, and patients interact. The CDS system will also improve communication through email, text messaging, and reports (Sutton & Pincock, 2020). This paper discusses this concept and the potential complications that can arise.

Standards and Specifications Criteria

The Agency for Healthcare Research and Quality (AHRQ) has established guidelines for Clinical Decision Support (CDS) systems, which are shared through the National Quality Strategy (NQS) framework, as specified by the Affordable Care Act (Agency for Healthcare Research and Quality, 2019). NQS identifies three aims and six priority areas for a successful CDS system.

It also offers four levels of implementation (L1–L4). At L1, the approach begins by identifying a problem and conducting research to provide recommendations. L2 includes transforming these recommendations into a legally binding strategy. L3 moves on to employ HL7 Arden Syntax or similar methodology to establish a formal schema. Finally, L4 comprises creating an IT health architecture based on this framework. Common designs include a Shareable Active Guideline Environment (SAGE) and a System for Evidence-Based Advice via Simultaneous Transaction with an Intelligent Agent over a Network (SEBASTIAN).

Comparison of Technologies

Health IT systems are typically assessed based on a variety of criteria, including the features they give, the support they provide, their capacity to analyze data in real-time, and their scalability as the number of users grows (Jen & Korvek, 2023). Furthermore, comparisons may be made based on how valuable they are to various users, including nurses, physicians, and staff, as well as their decision-support system capabilities.

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Legal and Ethical Issues

The new Clinical Decision Support (CDS) system must adhere to government legislation and guidelines regarding healthcare delivery and patient data. This implies that patient information must be kept secret and only accessed by authorized personnel. The system should have appropriate controls in place for who can access the data and how it is kept and shared, as required by the ACA and other laws (Wasylewicz & Scheepers-Hoeks, 2020). Even if these systems do not have their own set of rules, they must abide by general laws. For example, hospital administration might be held liable if something goes wrong, hence CDS system designers should aim to minimize risks while implementing the system.

Ethical issues are equally important while developing the CDS system (CASTILLO, et al., 2020). For example, the system should consider patients’ vulnerabilities while in the hospital and make it easy for them to obtain assistance as needed.

Related Assessments:

NURS FPX 8012 Assessment 1

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NURS FPX 8012 Assessment 4

NURS FPX 8012 Assessment 5

Technology Impact

A more effective workflow focused on patient well-being is one of the anticipated benefits of using a Clinical Decision Support (CDS) system. Nurses, physicians, technical staff, and hospital personnel will have real-time access to diagnostic and patient data, enabling faster and more effective decision-making and potentially improving treatment quality.

However, there are some possible drawbacks to consider. Nurses can over-rely on the system and ignore physical checks on patients, presuming that the system’s notifications are adequate (Liyew et al., 2021). If the system is not properly planned or executed, it could actually decrease rather than increase communication efficiency. This emphasizes the significance of proper preparation and execution in order to maximize the benefits of the CDS system while avoiding its shortcomings.

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Future Relevance

A long-term impact is anticipated from the planned Clinical Decision Support (CDS) system, which should be used with regular maintenance and upgrades for at least five to ten years. This longer duration is due to the increasing trend of digitizing and computerizing numerous parts of healthcare. The move is motivated by the need for increased efficiency, productivity, and more access to healthcare services.

Decision support systems, such as the CDS, are increasingly acknowledged for their ability to help nurses and physicians make better-informed judgments without replacing their expertise (Sutton & Pincock, 2020). They help to improve the quality of provided. Given these considerations, the suggested CDS solution is expected to stay relevant far into the future, in line with the changing environment of healthcare digitalization and the increased dependence on decision-support technology.

Stakeholder Influence

Internal stakeholders, including patients, nurses, physicians, and hospital personnel, are directly involved in the Clinical Decision Support (CDS) system. To properly involve them, senior management should have frequent meetings to discuss the rationale for using the CDS system. Their comments and ideas should be carefully evaluated during the system design process.

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External stakeholders such as government authorities, ethical boards, and investors also play an important role. Written communication and scheduled meetings should be used to engage them in conversations regarding the system’s necessity, related expenses, and predicted returns on investment (Prabavathi & Nagasubramani, 2020). This participation assures openness and adherence to external norms and expectations.

Conclusion

The plan to establish a Clinical Decision Support (CDS) system at Villa Health shows potential for improving patient care and optimizing healthcare procedures. By following to established standards, resolving legal and ethical concerns, and engaging both internal and external stakeholders, the CDS system has the potential to greatly improve the quality and efficiency of healthcare delivery. With careful design and continuing maintenance, the suggested solution will stay relevant and valuable in the ever-changing field of healthcare technology for many years to come.

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References

Agency for Healthcare Research and Quality. (2019, June). Clinical Decision Support. Ahrq.gov. https://www.ahrq.gov/cpi/about/otherwebsites/clinical-decision-support/index.html

CASTILLO, RANIELLE S. MSN, RN, CPN , & KELEMEN, ARPAD PhD. (2020, July 12). CEArticlePrint. Nursingcenter.com. https://www.nursingcenter.com/lnc/ce_articleprint?an=00024665-201307000-00003

Jen, M. Y., & Korvek, S. J. (2023, June 20). Health Information Technology. PubMed; StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK470186/

Liyew, B., Tilahun, A. D., & Kassew, T. (2021). Practices and Barriers towards Physical Assessment among Nurses Working in Intensive Care Units: Multicenter Cross-Sectional Study. BioMed Research International, 2021(PMC8294977). https://doi.org/10.1155/2021/5524676

Prabavathi, R., & Nagasubramani, P. C. (2020). (PDF) Effective oral and written communication. ResearchGate. https://www.researchgate.net/publication/325087759_Effective_oral_and_written_communication

Sutton, R., & Pincock, D. (2020). An overview of clinical decision support systems: benefits, risks, and strategies for success. NPJ Digital Medicine, 3(1), 1–10. https://doi.org/10.1038/s41746-020-0221-y

Wasylewicz, A. T. M., & Scheepers-Hoeks, A. M. J. W. (2020). Clinical Decision Support Systems. Fundamentals of Clinical Data Science, 10.1007(978-3-319-99713-1_11), 153–169. https://doi.org/10.1007/978-3-319-99713-1_11

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