Answer for NURS 8210 WEEK 5 DATA SCIENCE APPLICATIONS AND PROCESSES PREDICTIVE ANALYTICS

Data analytics examines raw data to identify patterns and trends and predict future processes and outcomes. Predictions of these improvements come from identifying the issue, identifying why the problem occurred, predicting what will happen, and identifying ways to make the solution happen (GovLoop, 2016). Predictive analytics uses past and present data and transforms that data into insight to make predictions of future success and improved healthcare outcomes(IDG TECHTalk, 2020).

Predictive Analytics to Support Healthcare

Predictive analytics has the potential to turn information into profit. Predictive analytics aims to promote a proactive rather than reactive healthcare model. Using past and present data, the healthcare system can anticipate negative patterns and reduce the chance of continuing the same problems by implementing new and improved processes. Predictive analysis uses various tools, such as machine learning and data science. Data science is the brain for applications such as Big Data. Big Data can accommodate large amounts of data, but data science organizes, processes, and translates the data to help solve problems. Machine learning then uses this data to learn from and apply the data in various ways, such as robotic surgeries (Mathur, 2023).

Practical Application for Predictive Analytics

Ataman et al. (2023) conducted a study about the effects of diagnostic testing and consultations on emergency department wait times (WT) and length of stay (LOS). The study used t-test and ANOVA inferential statistics. By conducting the study, several variables were identified as contributing factors to extended WT and LOS. A retrospective review using patient data from electronic charts was used to gather data (Ataman et al., 2023). An effective throughput model is essential for the flow of emergency department productivity. Delays cause overcrowding, decreased satisfaction scores, compromised patient outcomes, and loss of revenue. Predictive analytics provides the structure to use this information to predict why delays are persistent, the outcome due to delays, and what changes to make to prevent the delays and improve WT and LOS.