Scenario

You are a member of a planning committee in your organization whose purpose is to research and report on future trends in the field of informatics. You will look at future trends in informatics that can improve your organization’s health care strategy and day-to-day patient care. In addition, you will consider how the technology is designed and whether your co-workers or patients will be willing and able to use it. You are preparing a report that will be delivered to your committee’s sponsoring executive.

Identify the stakeholders in your organization that you would be presenting to. This is the first step in what will ultimately be a formal 5-year plan proposal for technology investments and resource allocation, which will be delivered to your board of directors for approval.

Create a report that outlines the 3 hottest trends that are forecast for informatics. Use data to support your conclusion. This will provide you with timely knowledge of what is happening in the field.

Answer the following questions in your report:
How would your selected trends affect patient outcomes?
How can these technologies be used to address specific challenges facing the health care industry? For example, AI can be used to develop personalized treatment plans.
What are the steps that need to be taken to implement these technologies? This could include discussing the costs, risks, and challenges associated with implementation.

Provide examples of how each trend is already being used to improve health care. This could include examples from other hospitals, health systems, or even other industries.

Develop your report as a presentation by writing a
1,050- to 1,400-word paper formatted according to APA guidelines

 

Sample solution

Dante Alighieri played a critical role in the literature world through his poem Divine Comedy that was written in the 14th century. The poem contains Inferno, Purgatorio, and Paradiso. The Inferno is a description of the nine circles of torment that are found on the earth. It depicts the realms of the people that have gone against the spiritual values and who, instead, have chosen bestial appetite, violence, or fraud and malice. The nine circles of hell are limbo, lust, gluttony, greed and wrath. Others are heresy, violence, fraud, and treachery. The purpose of this paper is to examine the Dante’s Inferno in the perspective of its portrayal of God’s image and the justification of hell. 

In this epic poem, God is portrayed as a super being guilty of multiple weaknesses including being egotistic, unjust, and hypocritical. Dante, in this poem, depicts God as being more human than divine by challenging God’s omnipotence. Additionally, the manner in which Dante describes Hell is in full contradiction to the morals of God as written in the Bible. When god arranges Hell to flatter Himself, He commits egotism, a sin that is common among human beings (Cheney, 2016). The weakness is depicted in Limbo and on the Gate of Hell where, for instance, God sends those who do not worship Him to Hell. This implies that failure to worship Him is a sin.

God is also depicted as lacking justice in His actions thus removing the godly image. The injustice is portrayed by the manner in which the sodomites and opportunists are treated. The opportunists are subjected to banner chasing in their lives after death followed by being stung by insects and maggots. They are known to having done neither good nor bad during their lifetimes and, therefore, justice could have demanded that they be granted a neutral punishment having lived a neutral life. The sodomites are also punished unfairly by God when Brunetto Lattini is condemned to hell despite being a good leader (Babor, T. F., McGovern, T., & Robaina, K. (2017). While he commited sodomy, God chooses to ignore all the other good deeds that Brunetto did.

Finally, God is also portrayed as being hypocritical in His actions, a sin that further diminishes His godliness and makes Him more human. A case in point is when God condemns the sin of egotism and goes ahead to commit it repeatedly. Proverbs 29:23 states that “arrogance will bring your downfall, but if you are humble, you will be respected.” When Slattery condemns Dante’s human state as being weak, doubtful, and limited, he is proving God’s hypocrisy because He is also human (Verdicchio, 2015). The actions of God in Hell as portrayed by Dante are inconsistent with the Biblical literature. Both Dante and God are prone to making mistakes, something common among human beings thus making God more human.

To wrap it up, Dante portrays God is more human since He commits the same sins that humans commit: egotism, hypocrisy, and injustice. Hell is justified as being a destination for victims of the mistakes committed by God. The Hell is presented as being a totally different place as compared to what is written about it in the Bible. As a result, reading through the text gives an image of God who is prone to the very mistakes common to humans thus ripping Him off His lofty status of divine and, instead, making Him a mere human. Whether or not Dante did it intentionally is subject to debate but one thing is clear in the poem: the misconstrued notion of God is revealed to future generations.

 

References

Babor, T. F., McGovern, T., & Robaina, K. (2017). Dante’s inferno: Seven deadly sins in scientific publishing and how to avoid them. Addiction Science: A Guide for the Perplexed, 267.

Cheney, L. D. G. (2016). Illustrations for Dante’s Inferno: A Comparative Study of Sandro Botticelli, Giovanni Stradano, and Federico Zuccaro. Cultural and Religious Studies4(8), 487.

Verdicchio, M. (2015). Irony and Desire in Dante’s” Inferno” 27. Italica, 285-297.

Sample Answer

Sample Answer

 

 

Future Trends in Informatics for Healthcare Strategy

Introduction

As a member of the planning committee focused on the future of informatics in our organization, it is essential to identify trends that can enhance our healthcare strategy and improve day-to-day patient care. This report outlines three prominent trends in informatics: Artificial Intelligence (AI), Telehealth, and Big Data Analytics. It discusses their potential impact on patient outcomes, application in addressing healthcare challenges, implementation steps, and examples of successful use in the healthcare industry.

Stakeholders

The stakeholders who will be presented with this report include:

– Executive Leadership: CEO, COO, and CFO
– Clinical Staff: Physicians, nurses, and allied health professionals
– IT Department: Chief Information Officer (CIO) and IT specialists
– Quality Improvement Team: Patient care coordinators and data analysts
– Finance Department: Budget analysts and financial officers
– Patient Advocacy Groups: Representatives from patient support organizations

Trend 1: Artificial Intelligence (AI)

Impact on Patient Outcomes

AI has the potential to dramatically improve patient outcomes through enhanced diagnostics, personalized treatment plans, and predictive analytics. For instance, AI algorithms can analyze medical imaging and identify conditions such as tumors or fractures with greater accuracy than human radiologists (Esteva et al., 2019).

Addressing Healthcare Challenges

AI can streamline administrative processes like scheduling and billing, allowing healthcare providers to focus more on patient care. Additionally, AI can be used to develop personalized treatment plans by analyzing a patient’s genetic information alongside their health history (Topol, 2019).

Implementation Steps

1. Assessment of Needs: Identify specific areas where AI can be integrated into existing workflows.
2. Vendor Selection: Choose reliable AI technology vendors with proven solutions.
3. Training: Provide comprehensive training for clinical and administrative staff.
4. Pilot Programs: Initiate pilot programs to assess AI effectiveness before full-scale implementation.
5. Evaluation and Feedback: Continuously monitor performance and gather feedback for improvements.

Examples

AI is already being applied in various healthcare settings. For example, the Stanford University Medical Center developed an AI tool that identifies pneumonia from chest X-rays with an accuracy comparable to expert radiologists (Rajpurkar et al., 2017). Furthermore, companies like IBM Watson are leveraging AI to assist oncologists in identifying personalized cancer treatment options based on vast datasets of clinical studies.

Trend 2: Telehealth

Impact on Patient Outcomes

Telehealth has proven to enhance access to care, particularly for patients in rural or underserved areas. Studies show that telehealth can lead to quicker diagnoses and improved management of chronic diseases (Bashshur et al., 2016).

Addressing Healthcare Challenges

Telehealth addresses several challenges in the healthcare industry, such as staff shortages and high patient volumes. It reduces the need for physical office visits, thereby minimizing exposure to infectious diseases—a consideration highlighted during the COVID-19 pandemic.

Implementation Steps

1. Technology Infrastructure: Invest in secure telehealth platforms that comply with HIPAA regulations.
2. Policy Development: Establish clear policies regarding telehealth services, including reimbursement protocols.
3. Staff Training: Provide training for healthcare providers on using telehealth technologies effectively.
4. Patient Education: Educate patients about the benefits of telehealth and how to access services.

Examples

Organizations like Mayo Clinic have successfully implemented telehealth services that allow patients to consult with specialists from remote locations. Data from the COVID-19 pandemic indicated that telehealth visits increased by over 1500% in March 2020 compared to the previous year (Centers for Disease Control and Prevention [CDC], 2020).

Trend 3: Big Data Analytics

Impact on Patient Outcomes

Big Data Analytics provides healthcare organizations with insights into population health trends, enabling proactive interventions that can reduce hospital readmissions and improve overall patient care (Kumar et al., 2020).

Addressing Healthcare Challenges

Big data can help identify patterns related to disease outbreaks, patient demographics, and treatment efficacy. By analyzing large datasets, healthcare providers can tailor public health initiatives and resource allocation effectively.

Implementation Steps

1. Data Collection: Develop systems for collecting relevant healthcare data across departments.
2. Data Integration: Invest in technologies that integrate data from various sources (EHRs, wearables).
3. Analytical Tools: Implement analytics tools capable of processing large datasets.
4. Privacy Considerations: Establish protocols to ensure patient data privacy and compliance with regulations.

Examples

The University of California, San Francisco (UCSF) employs big data analytics to improve patient outcomes by analyzing treatment patterns and patient responses in real-time. They utilize predictive analytics to anticipate patient needs and allocate resources accordingly.

Conclusion

Integrating AI, Telehealth, and Big Data Analytics into our healthcare strategy presents an opportunity to significantly enhance patient care and operational efficiency. Each trend offers unique advantages that can address specific challenges in the industry while improving patient outcomes. As we move forward with this formal proposal for technology investments, it is crucial to consider stakeholder input, implementation strategies, and examples of success from other organizations.

By embracing these trends, we not only position ourselves at the forefront of innovation in healthcare but also reaffirm our commitment to providing high-quality care for our patients.

References

– Bashshur, R., Shannon, G., Smith, B. R., & Woodward, H. I. (2016). The Empirical Foundations of Telemedicine Interventions in Primary Care. Telemedicine and e-Health, 22(5), 347–353.
– Centers for Disease Control and Prevention (CDC). (2020). COVID-19 Pandemic Planning Scenarios.
– Esteva, A., Kuprel, B., Novoa, R. A., et al. (2019). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115–118.
– Kumar, S., Kumar, A., & Bansal, S. (2020). Big Data Analytics in Healthcare: A Comprehensive Review. Journal of Healthcare Engineering, 2020.
– Rajpurkar, P., Irvin, J., Zhu, K., et al. (2017). CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning. arXiv preprint arXiv:1711.05225.
– Topol, E. J. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books.

This report can be formatted according to APA guidelines as needed for submission or presentation purposes.

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