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WGU C985 Health care Analytics Questions and Answers Already Passed

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WGU C985 Health care Analytics Questions and Answers Already Passed What is the purpose of healthcare analytics in improving patient care? To analyze patient data to identify trends, improve outcomes, and enhance the quality of care. What is an example of a predictive analytics model in healthcare? A model that forecasts patient readmission rates based on historical data. How does descriptive analytics contribute to healthcare management? It provides insights into past performance, such as patient demographics and treatment outcomes, to guide decision-making. What is the role of electronic health records (EHR) in healthcare analytics? EHRs store patient data that can be analyzed to improve care, identify trends, and reduce errors. How can healthcare analytics help reduce costs for healthcare providers? 2 By identifying inefficiencies, reducing unnecessary tests or treatments, and improving resource allocation. What is the significance of clinical decision support systems (CDSS) in healthcare analytics? They provide healthcare professionals with data-driven insights to assist in making informed clinical decisions. How does data integration support healthcare analytics? It combines data from various sources, like EHRs, insurance claims, and lab results, to provide a comprehensive view of patient care. What type of data is essential for effective healthcare analytics? Patient demographics, clinical outcomes, billing data, and treatment plans. How can healthcare analytics contribute to improving patient satisfaction? By analyzing patient feedback and outcomes to identify areas for improvement in care delivery. What is the importance of data privacy and security in healthcare analytics? 3 It ensures that patient information is protected from unauthorized access, complying with regulations such as HIPAA. How does real-time data analytics improve healthcare outcomes? It allows healthcare providers to make timely decisions, reducing delays in treatment and improving patient care. What is an example of a prescriptive analytics application in healthcare? A system recommending personalized treatment plans based on patient history and data analysis. How does healthcare analytics impact population health management? It helps identify health trends within populations, enabling targeted interventions and resource allocation. What is the role of artificial intelligence (AI) in healthcare analytics? AI can analyze large datasets to uncover patterns and make predictions, enhancing diagnostic accuracy and treatment recommendations.

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WGU C985 Health care Analytics
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WGU C985 Health care Analytics

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WGU C985 Health care Analytics
Questions and Answers Already Passed
What is the purpose of healthcare analytics in improving patient care?


✔✔To analyze patient data to identify trends, improve outcomes, and enhance the quality of

care.




What is an example of a predictive analytics model in healthcare?


✔✔A model that forecasts patient readmission rates based on historical data.




How does descriptive analytics contribute to healthcare management?


✔✔It provides insights into past performance, such as patient demographics and treatment

outcomes, to guide decision-making.




What is the role of electronic health records (EHR) in healthcare analytics?


✔✔EHRs store patient data that can be analyzed to improve care, identify trends, and reduce

errors.




How can healthcare analytics help reduce costs for healthcare providers?


1

,✔✔By identifying inefficiencies, reducing unnecessary tests or treatments, and improving

resource allocation.




What is the significance of clinical decision support systems (CDSS) in healthcare analytics?


✔✔They provide healthcare professionals with data-driven insights to assist in making informed

clinical decisions.




How does data integration support healthcare analytics?


✔✔It combines data from various sources, like EHRs, insurance claims, and lab results, to

provide a comprehensive view of patient care.




What type of data is essential for effective healthcare analytics?


✔✔Patient demographics, clinical outcomes, billing data, and treatment plans.




How can healthcare analytics contribute to improving patient satisfaction?


✔✔By analyzing patient feedback and outcomes to identify areas for improvement in care

delivery.




What is the importance of data privacy and security in healthcare analytics?

2

,✔✔It ensures that patient information is protected from unauthorized access, complying with

regulations such as HIPAA.




How does real-time data analytics improve healthcare outcomes?


✔✔It allows healthcare providers to make timely decisions, reducing delays in treatment and

improving patient care.




What is an example of a prescriptive analytics application in healthcare?


✔✔A system recommending personalized treatment plans based on patient history and data

analysis.




How does healthcare analytics impact population health management?


✔✔It helps identify health trends within populations, enabling targeted interventions and

resource allocation.




What is the role of artificial intelligence (AI) in healthcare analytics?


✔✔AI can analyze large datasets to uncover patterns and make predictions, enhancing diagnostic

accuracy and treatment recommendations.




3

, How can healthcare analytics improve hospital operations?


✔✔By analyzing staffing levels, patient flow, and resource utilization to optimize hospital

management.




What is a common challenge in implementing healthcare analytics?


✔✔The complexity of integrating data from multiple sources and ensuring data quality.




How can predictive analytics help in disease prevention?


✔✔By identifying at-risk populations early, allowing for preventive measures and timely

interventions.




What is the role of dashboards in healthcare analytics?


✔✔Dashboards provide healthcare professionals with real-time, visual representations of key

metrics, aiding in decision-making.




How can healthcare analytics improve the accuracy of diagnoses?


✔✔By analyzing patient data from multiple sources, analytics can highlight potential diagnoses,

aiding in early detection.




4

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