https://padlet.com/simmlaci2980/watchDM An innovation intended for early detection of heart failure in Type II Diabetics en-us 2019-09-28 15:26:15 UTC 2025-12-06 21:53:58 UTC hello@padlet.com simmlaci2980 https://padlet.com/simmlaci2980/watchDM/wish/390882299 Heart failure continues to be one of the leading causes of death in the United States. Understanding the significant impact of heart failure is ideally the foundation in preventing HF in patients. ]]> 2019-09-28 16:08:36 UTC https://padlet.com/simmlaci2980/watchDM/wish/390882299 simmlaci2980 https://padlet.com/simmlaci2980/watchDM/wish/390882680 CDC does a great job of putting statistics into perspective for clinicians. Understanding Type II diabetes will help incorporate chronic disease management interventions in preventing HF in this specific population.]]> 2019-09-28 16:11:13 UTC https://padlet.com/simmlaci2980/watchDM/wish/390882680 simmlaci2980 https://padlet.com/simmlaci2980/watchDM/wish/390886135 Chronic disease management is necessary in the role of the practitioner. Simple tools, such as this, are a great asset. This video addresses my personal opinion and rationale on the Watch- DM assessment tool.]]> 2019-09-28 16:34:36 UTC https://padlet.com/simmlaci2980/watchDM/wish/390886135 simmlaci2980 https://padlet.com/simmlaci2980/watchDM/wish/390886780 Summary: the Watch-DM is a tool that is generated by using an algorithm from specific patient information that determines the probability of a type II DM patient developing HF. The algorithm is calculated by a smart computerized system (machine learning) to reflect results. Results are easy to read and available to be placed in the patient charts for coordination of care. ]]> 2019-09-28 16:38:56 UTC https://padlet.com/simmlaci2980/watchDM/wish/390886780 simmlaci2980 https://padlet.com/simmlaci2980/watchDM/wish/390887278 -Early intervention to prevent heart failure 
-Convenient tool for clinicians 
-Can be integrated with medial records 
-High number of participants 
-High rate of heart failure rates reflecting accuracy of current innovation 
-Strong in prediction of heart failure with primary analysis of ejection fraction

]]> 2019-09-28 16:42:22 UTC https://padlet.com/simmlaci2980/watchDM/wish/390887278 simmlaci2980 https://padlet.com/simmlaci2980/watchDM/wish/390887654 - Require patient compliance 
 -Predictors of heart failure may have evolved since statistical analysis (1999-2009)
-Lacked prediction of heart failure in secondary measures, outside of ejection fraction

]]> 2019-09-28 16:44:30 UTC https://padlet.com/simmlaci2980/watchDM/wish/390887654 simmlaci2980 https://padlet.com/simmlaci2980/watchDM/wish/390888274 [Angelica (analytical), Ivy (individualization), Pablo (positivity), Matthew (maximizer), Abraham (arranger)]
My top five strengths are learner, achiever, communicator, strategic, and responsibility. I chose my five team mates specifically for the reasoning that all five have different strengths than I have myself. I believe a team of diversity will better target the general population in health prevention and promotion rather than a team of common factors. ]]> 2019-09-28 16:50:08 UTC https://padlet.com/simmlaci2980/watchDM/wish/390888274 simmlaci2980 https://padlet.com/simmlaci2980/watchDM/wish/390893992 Science Daily. (2019). Predicting risk of heart failure for diabetes patients with help from learning machine. Science News. Retrieved from https://www.sciencedaily.com/releases/2019/09/190913191451.htm]]> 2019-09-28 17:39:37 UTC https://padlet.com/simmlaci2980/watchDM/wish/390893992