Writing Homework Help

Please reply to each DQ with 100-200 words each. thank you

Sharren:

Understanding patterns an trends in data helps the organizations to forecast and plan for strategies to implement thus saving time. Identification of trends and patterns can help predict supply of skills that may be available in the future and project the future workforce supply needed thus saving time (Ford, 2021). It helps to develop more thorough and insightful diagnosis and interventions to provide quality patient care. The outcomes can be predicted or estimated base on the patterns and trends of data that is being collected such as length of stay, Patients who will not benefit from surgery, complications, patients risk for sepsis or other hospital acquired illness, possible co-morbid conditions and patients risk for fall.

The organization can plan ahead of time or can use the best strategies to solve the problem to reduce the cost of healthcare and can save both time and money.

Reference

Ford, J. (2021, March 21). What is the importance of understanding patterns and trends in data? AnswersToAll. Retrieved November 20, 2021, from https://answerstoall.com/common-questions/what-is-the-importance-of-understanding-patterns-and-trends-in-data/.

Margarete:

Patterns and trends in healthcare data can lead to a better understanding of the current state of a metric, and the direction it is likely to go in the future. Studying trends can enable predictive analytics so that the healthcare organization can plan for the future, create better strategies, and save money. For patients, it can help determine what treatment plan is most likely to be successful for an individual, which patient may be at a higher risk for a certain condition, and lead to improved patient outcomes overall. Some of the benefits that can come from analyzing trends in data include “analyzing patient characteristics and the cost and outcomes of care to identify the most clinically and cost effective treatments and offer analysis and tools, thereby influencing provider behavior; applying advanced analytics to patient profiles (e.g., segmentation and predictive modeling) to proactively identify individuals who would benefit from preventative care or lifestyle changes; broad scale disease profiling to identify predictive events and support prevention initiatives; collecting and publishing data on medical procedures, thus assisting patients in determining the care protocols or regimens that offer the best value; identifying, predicting and minimizing fraud by implementing advanced analytic systems for fraud detection and checking the accuracy and consistency of claims; and, implementing much nearer to real-time, claim authorization; creating new revenue streams by aggregating and synthesizing patient clinical records and claims data sets to provide data and services to third parties, for example, licensing data to assist pharmaceutical companies in identifying patients for inclusion in clinical trials” (Raghupathi & Raghupathi, 2014).

Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and potential. Health information science and systems, 2, 3. https://doi.org/10.1186/2047-2501-2-3

Adeyiga:

Understanding data patterns and trends are critical because if an organization wants to make the most of these analytical tools and develop analyses and outcomes that will help it meet its goals and flourish in its chosen market, it has to have a fundamental awareness of data patterns and trends. If a company wants to succeed, it must be able to recognize patterns and trends in data as it aspires to create clear, precise outcomes (Petersson,2019). It also aids corporations and organizations in predicting and planning, as well as putting theories and tactics to the test. When big data is synthesized and analyzed, the aforementioned associations, patterns, and trends can be discovered, allowing healthcare providers and other stakeholders in the healthcare delivery system to develop more thorough and insightful diagnoses and treatments, resulting in higher-quality care (Belcher, 2005).

Data patterns and trends provide a bird’s-eye view of the present and potential audiences attitudes and behaviors. Organizations can use trends to peep into the minds of present and potential audiences, revealing difficulties and possibilities (Dellmuth, 2020). The ability to understand data patterns might assist the organization to decide where to focus further information gathering efforts. As an example. The choice of ARIMA or Holt-Winter series forecasting for a given datasheet will be determined by the datasheet’s trends and patterns (Alam, 2020).

Organizations need to be able to identify trends and patterns in order to save time. When patterns are identified, tasks become easier to complete, and issues become easier to solve since we can employ the same problem-solving method wherever the pattern exists. The more patterns we can find, the easier and faster it will be to solve the problem. Trends and patterns can be easily identified, providing evidence to assist you to make better decisions and save time for your company. Organizations can use trend analysis to swiftly identify areas where they are underperforming and save time by doing so (Petersson,2019). Organizations may foresee and plan for plans to adopt by understanding patterns and trends in data. This saves time. Trends and patterns can be used to forecast the supply of abilities that will be accessible in the future and project the future as a result, there will be a reduction in the amount of time. It assists organizations in producing reports and results, so assisting them in achieving their objectives and saving time

Trend analysis will aid your company by allowing you to identify areas where your company is functioning effectively as well as areas where it is not (Petersson,2019). As a result, it provides useful evidence to aid in making informed decisions about your longer-term strategy and how you will implement it. The organization can be easily secure for future purposes, along with saving time.

Reference

Alam, M. (2020, August 30). Comparing the performance of forecasting models: Holt-Winters vs ARIMA. Medium. https://towardsdatascience.com/comparing-the-performance-of-forecasting-models-holtwinters-vs-arima-e226af99205f. Belcher, B., Ruíz-Pérez, M., & Achdiawan, R. (2005). Global patterns and trends in the use and management of commercial NTFPs: implications for livelihoods and conservation. World development, 33(9), 1435-1452.