WGU FINAL - D549 Task 2
With Complete Solution
D549 – Exploring Emerging Trends in HA
Task 2
Josh Cryer
A Plan of Attack for Using AI in Healthcare Decision-Making at Cedar Bend Hospital
Cedar Bend Hospital has a big chance to improve patient experiences and productivity by
incorporating artificial intelligence (AI) into medical decisions. With an emphasis on
accomplishing the medical center's strategic goals, this article presents a workable approach to
execution that was developed through an examination of AI trends in medicine. It also looks at
how a cross-functional group may help with deployment and issue mitigation. Diego Garcia is an
old patient with long-term physical and mental health issues. His story highlights the challenges
faced by rural medical professionals and the prospective advantages of integrating AI.
Two SMART (Specific, Measurable, Achievable, Relevant, and Time-Bound) objectives have
been set by Cedar Bend Hospital to guarantee the effective application of AI in medical decision-
making.
The initial goal is to achieve a 90% rate of acceptance amongst ED doctors by implementing an
AI-powered clinical decision support system in the Er over a period of six months. Having an
explicit 6-month time limit, the target is time-limited and related to the hospital's goals of
introducing digital medical equipment and enhancing the treatment of patients. It is additionally
, particular in that it focuses on the emergency department and is quantifiable via the rate of
acceptance.
Following the first nine months of the AI system's implementation, the next target is to cut down
on Emergency patient waiting periods by 25%. Given a 9-month post-implementation time limit,
this objective is time-limited and explicitly sets the length of the wait. It is also measurable via
time monitoring, realistic with good execution, and important for enhancing the patient
experience and operational effectiveness.
Cedar Bend Hospital has put in place an effective management and management team with three
main responsibilities to manage the AI deployment strategy. In addition to coordinating with IT
With Complete Solution
D549 – Exploring Emerging Trends in HA
Task 2
Josh Cryer
A Plan of Attack for Using AI in Healthcare Decision-Making at Cedar Bend Hospital
Cedar Bend Hospital has a big chance to improve patient experiences and productivity by
incorporating artificial intelligence (AI) into medical decisions. With an emphasis on
accomplishing the medical center's strategic goals, this article presents a workable approach to
execution that was developed through an examination of AI trends in medicine. It also looks at
how a cross-functional group may help with deployment and issue mitigation. Diego Garcia is an
old patient with long-term physical and mental health issues. His story highlights the challenges
faced by rural medical professionals and the prospective advantages of integrating AI.
Two SMART (Specific, Measurable, Achievable, Relevant, and Time-Bound) objectives have
been set by Cedar Bend Hospital to guarantee the effective application of AI in medical decision-
making.
The initial goal is to achieve a 90% rate of acceptance amongst ED doctors by implementing an
AI-powered clinical decision support system in the Er over a period of six months. Having an
explicit 6-month time limit, the target is time-limited and related to the hospital's goals of
introducing digital medical equipment and enhancing the treatment of patients. It is additionally
, particular in that it focuses on the emergency department and is quantifiable via the rate of
acceptance.
Following the first nine months of the AI system's implementation, the next target is to cut down
on Emergency patient waiting periods by 25%. Given a 9-month post-implementation time limit,
this objective is time-limited and explicitly sets the length of the wait. It is also measurable via
time monitoring, realistic with good execution, and important for enhancing the patient
experience and operational effectiveness.
Cedar Bend Hospital has put in place an effective management and management team with three
main responsibilities to manage the AI deployment strategy. In addition to coordinating with IT
