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D260 Task #1: Emerging Issues And Trends In HIM Sarah E.
Smith
College of Health Professions, Western Governors University
Diana Gardner
,2
A.1. Issue Or Trend
For this task, I've selected an emerging technology issue or trend found under Domain
III: informatics, analytics, and data use. The application of artificial intelligence (AI)-based
technologies and machine learning (ML) have become increasingly prevalent in healthcare
informatics and is a newer problem that must be investigated. AI and ML technology
applications can potentially transform the health information management (HIM) field by
enhancing decision-making procedures, data analytics, and patient outcomes. (Davenport &
Kalakota, 2019)
A.2. Why The Issue Or Trend Was Chosen
I have chosen artificial intelligence (AI)-based technologies and machine learning (ML)
in healthcare informatics as my research subjects because they can potentially transform the
healthcare industry and greatly enhance data analytics, decision-making processes, and patient
outcomes. AI and ML technologies in the healthcare industry can potentially improve diagnostic
accuracy, evidence-based treatment recommendations, and patient care outcomes. In
healthcare informatics, we can effectively implement AI and ML to support data-driven
healthcare practices and contribute by comprehending and studying their consequences,
difficulties, and opportunities. (Davenport & Kalakota, 2019)
A.3. Professional Sources
As I researched artificial intelligence (AI)-based technologies and machine learning (ML)
in healthcare informatics, it became evident to me that these advancements are not just
, 3
innovative but can bring about significant transformations to the healthcare industry in the
future.
The healthcare industry will continue to depend on Artificial intelligence (AI)
technologies. Due to the complexity and growth of data information in the field, it will be used
even more. Insurance payers, healthcare providers, and life sciences organizations already use
various AI technologies. The key application categories include patient engagement and
adherence, recommendations for diagnosis and treatment, and administrative tasks. Even
though there are multiple situations in which AI can now perform healthcare duties just as well
as humans do or better, AI implementation issues keep many healthcare professional jobs safe
from becoming extensively automated any time soon. (Davenport & Kalakota, 2019)
The healthcare industry is beginning to enter a new chapter due to artificial intelligence
(AI) and machine learning (ML), with the potential to fundamentally transform the practice of
medicine by managing resources, promoting the discovery of new therapeutics, and enhancing
clinical outcomes. However, using these new AI-based technologies in healthcare also raises
troublesome legal, moral, and practical issues. In this year (2023) alone, we have observed
many instances of ML and AI-based technology activities in the media that have highlighted the
significance of their advances and their subsequent consequences, which has led to attempts to
control their unbridled expansion. After watching AI technology exponentially rise, some
business leaders petitioned for a six-month hiatus from its progression, only to witness others
take continued advantage of the target-rich opportunities. That kind of tug-of-war highlights the
need for the careful investment and deployment of AI and ML technologies. (Shanti, 2023)
D260 Task #1: Emerging Issues And Trends In HIM Sarah E.
Smith
College of Health Professions, Western Governors University
Diana Gardner
,2
A.1. Issue Or Trend
For this task, I've selected an emerging technology issue or trend found under Domain
III: informatics, analytics, and data use. The application of artificial intelligence (AI)-based
technologies and machine learning (ML) have become increasingly prevalent in healthcare
informatics and is a newer problem that must be investigated. AI and ML technology
applications can potentially transform the health information management (HIM) field by
enhancing decision-making procedures, data analytics, and patient outcomes. (Davenport &
Kalakota, 2019)
A.2. Why The Issue Or Trend Was Chosen
I have chosen artificial intelligence (AI)-based technologies and machine learning (ML)
in healthcare informatics as my research subjects because they can potentially transform the
healthcare industry and greatly enhance data analytics, decision-making processes, and patient
outcomes. AI and ML technologies in the healthcare industry can potentially improve diagnostic
accuracy, evidence-based treatment recommendations, and patient care outcomes. In
healthcare informatics, we can effectively implement AI and ML to support data-driven
healthcare practices and contribute by comprehending and studying their consequences,
difficulties, and opportunities. (Davenport & Kalakota, 2019)
A.3. Professional Sources
As I researched artificial intelligence (AI)-based technologies and machine learning (ML)
in healthcare informatics, it became evident to me that these advancements are not just
, 3
innovative but can bring about significant transformations to the healthcare industry in the
future.
The healthcare industry will continue to depend on Artificial intelligence (AI)
technologies. Due to the complexity and growth of data information in the field, it will be used
even more. Insurance payers, healthcare providers, and life sciences organizations already use
various AI technologies. The key application categories include patient engagement and
adherence, recommendations for diagnosis and treatment, and administrative tasks. Even
though there are multiple situations in which AI can now perform healthcare duties just as well
as humans do or better, AI implementation issues keep many healthcare professional jobs safe
from becoming extensively automated any time soon. (Davenport & Kalakota, 2019)
The healthcare industry is beginning to enter a new chapter due to artificial intelligence
(AI) and machine learning (ML), with the potential to fundamentally transform the practice of
medicine by managing resources, promoting the discovery of new therapeutics, and enhancing
clinical outcomes. However, using these new AI-based technologies in healthcare also raises
troublesome legal, moral, and practical issues. In this year (2023) alone, we have observed
many instances of ML and AI-based technology activities in the media that have highlighted the
significance of their advances and their subsequent consequences, which has led to attempts to
control their unbridled expansion. After watching AI technology exponentially rise, some
business leaders petitioned for a six-month hiatus from its progression, only to witness others
take continued advantage of the target-rich opportunities. That kind of tug-of-war highlights the
need for the careful investment and deployment of AI and ML technologies. (Shanti, 2023)
