Homework answers / question archive / What are the three main takeaways you have gained from this course? How do you plan to use the skills from this course for your academic and professional advancement?   Three getaways from this course: 1- How healthcare IT plays important role in organization, and it is a skill that must be trained properly

What are the three main takeaways you have gained from this course? How do you plan to use the skills from this course for your academic and professional advancement?   Three getaways from this course: 1- How healthcare IT plays important role in organization, and it is a skill that must be trained properly

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What are the three main takeaways you have gained from this course? How do you plan to use the skills from this course for your academic and professional advancement?

 

Three getaways from this course:

1- How healthcare IT plays important role in organization, and it is a skill that must be trained properly.

2- clinical decision support system (CDSS) usage.

3- Significance of artificial intelligence in healthcare.

 

Key points to expand from :

-How healthcare IT plays important role in organization, and it is a skill that must be trained properly

- How case studies, DB topics helped to understand to implement HIT and I understand how to implement in my current profession as a healthcare administrator manager and in research.

Understanding the concept of BIG Data analysis.evolution of health informatics and healthcare IT

 

 

 

How I plan to leverage and use these skills in Healthcare organization: !??

 

“Analyze from the above”.

 

I am including below my colleagues postings to give you some help in writing:

 

Please use other references in APA style format.

 

 

The three main takeaways I have gained from this course include understanding the importance of big data analytics to improve organizational efficiency and benchmarking, the increasing role of AI-based applications to deploy evidence-based practice and EHR data utilization, and public health informatics to build effective health promotion and disease prevention policies. This course has taught me the majority of big data is unstructured, and that this represents about 75 percent of an organization’s data (Mastrian & McGonigle, 2021, p. 312). As described by Dash et al. (2019), through collective big analysis of EHRs, EMRs and other medical data, it is continuously helping to build a “better prognostic framework” to improve patient outcomes (Dash et al., 2019, p.22).

To remain competitive and embrace a value-based care model, administrators and program managers must utilize data analytics and metrics to understand factors impacting hospital length of stay, patient satisfaction, and overall health outcomes. Brossard et al. (2022) demonstrated the relevance of big data analytics (BDA) to solve medical and organizational challenges in hospitals, however in order to benefit from BDA, organizations must align their strategy with their long-term views and adapt organizational capabilities in the value creation process (Brossard et al., 2022, pgs.11-12).

The increasing role of AI in healthcare has the potential to provide data-driven clinical decision support (CDS) for physicians and hospital staff which paves the way for increased revenue potential (Insider Intelligence, 2022). This seems to be the tip of the iceberg in terms of harnessing AI’s capabilities; however, some caveats include algorithmic transparency and  data security which must be vital in this process. As I move forward in my career endeavors, I plan to use the skills and knowledge from this course to continue research efforts in protecting patients’ neurological function perioperatively during high-risk cardiac surgery. Additionally, I am also interested in understanding how data analytics can be used to develop population health strategies, particularly in low-income, underserved communities.

-Dan Adams

References

Brossard, P., Minvielle, E., & Sicotte, C. (2022). The path from big data analytics capabilities to value in hospitals: A scoping review. BMC Health Services Research, 22, 1-16. https://doi.org/10.1186/s12913-021-07332-0

Dash, S., Shakyawar, S.K., Sharma, M. et al. (2019). Big data in healthcare: management, analysis and future prospects. J Big Data 6, 54. https://doi.org/10.1186/s40537-019-0217-0

Insider Intelligence. (2022, April 15). Use of AI in healthcare & medicine is booming – here’s how the medical field is benefiting from AI in 2022 and beyond. Retrieved from: https://www.insiderintelligence.com/insights/artificial-intelligence-healthcare/

Mastrian, K. & McGonigle, D. (2021). Informatics For Health Professionals. 2nd Edition. Jones & Barlett Learning.

 

 

 

RE: Final Week

COLLAPSE

My three takeaways from this course are as follows:

• Prevalance of Artificial Intelligence
• Big data and the importance of data analytics
• Evidence Based Practice (EBP)

Artificial Intelligence is becomming more and more prevalent.  Healthcare systems are moving towards electronic medical records such as an EMR or EHR system.  Updated technology allows for better data collecting, and more people are starting to use wearable devices and other electronics (Nahavandi et al., 2022).  Telehealth is also increasing.  This allows for better access to patients.  This reach can be in a hospital setting or the comfort of a patient's home.  Artificial Intelligence played a vital role in the COVID-19 pandemic.  It allowed for quick forecasting, detection, and diagnosis (Comito & Pizzuti, 2022).  Algorithms allowed for better predictions and accuracy of prevalance.

Big data is a need of the future.  As we move towards better technology, it will be important to have access to a large amount of data.  This will ensure accuracy in analytics and outcomes.  The challenge with this is in policy and regulations (Amicelle, 2022).  How do we collect this data and still protect patient privacy.  There is also the fear of hacking.  Health records have become a huge target in crime and terrorism.  Despite the challenges, I think that the benefits outweigh the risk.  The more global data we have, the more information it can bring.  Healthcare operates with so many variables.  Conditions may be the same, but co-morbididies might require a different treatment plan.  Big data would allow providers to have information at their fingertips and make more informed decisions.

Evidence Based Practice (EBP) requires a large amount of research.  It integrates clinical expertice with the most recent and up to date systematic research (Puljak, 2022).  This is important because it encourages providers and clinicians to also use their own critical thinking.  They can make a decision based on their own previous experiences and have the research and data to support their decision.