What should be my reply to the below post - The recommendation of the best possible way to solve a problem is the primary focus of prescriptive analytics. As previously discussed in this course, prescriptive analytics relies on the data derived from descriptive and predictive analytics. However, it puts more weight and importance on actionable insights rather than observed information. Descriptive analytics provides data on what has happened, predictive analytics emphasizes possible outcomes from that data, and prescriptive analytics utilizes the best results to suggest options. Furthermore, the effectiveness of decision-making outcomes derived from prescriptive analytics depends on the extent to which future events or potential threats are leveraged, offering a framework for their analysis and interpretation. Prescriptive analytics exploits data-driven techniques used to formulate recommendations and decisions based on the statistical results of computational prototypes Prescriptive analytics provide benefits and can be advantageous in the healthcare industry as it uses large numbers of data to make recommendations to help healthcare providers make better decisions by suggesting optimal treatment plans that improve healthcare quality, delivery, and patient outcomes (Fernandes,2024). Trends in modeling include model libraries and the development of solution technique libraries. These codes are readily available in the organizations web infrastructure and can be run directly for free. They can also be downloaded and run on a local computer. Managers, even those who have limited experience with these types of codes, can have access to optimization and simulation packages that are useful in decision-making. There is also a trend in using cloud-based tools and software for easy storage, access, and running programs for performance, optimization, simulation, and other prescriptive modeling software. Modeling is not frequently used in healthcare because of several challenges in implementation. Real-time data is not always readily accessible within the Electronic Health Record Systems. Since medical devices need to display the current patient status at any given time (i.e., vital signs), this poses a risk to patient safety, especially when this information must be delivered without disrupting workflow or causing additional fatigue to the healthcare professional. In addition, data bias in healthcare can happen with prescriptive modeling use. Data bias can compromise and undermine the integrity of data analytics in healthcare and may lead to potentially inaccurate and misguided recommendations that may be detrimental to patient outcomes Decision modelingDecision modeling using spreadsheets is widely used because of its flexibility. It is widely recognized as an easy-to-use program that develops different types of applications in business and healthcare. The first benefit of using a spreadsheet is it can combine multiple functions.