LorraineSolar5 at 16:24, 30 December 2020

2020-12-30T16:24:27Z

KandiceChumley8: Created page with "Big data in the medical industry is about to get even bigger due to the move toward electronic health records. Electronic medical records are obtaining a boost due to the impl..."

2020-12-30T16:16:26Z

Created page with "Big data in the medical industry is about to get even bigger due to the move toward electronic health records. Electronic medical records are obtaining a boost due to the impl..."

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Big data in the medical industry is about to get even bigger due to the move toward electronic health records. Electronic medical records are obtaining a boost due to the implementation of the Affordable Care Act. As such, medical researchers may expect a tremendous influx of healthcare data to analyze. The scientific community is abuzz about the potential for big data in the medical research arena. In line with Science 2.0, a science blog, several of the clearest opportunities recently identified in this particular area revolve around reducing costs in several key areas: High-cost patients - Did you realize that just five percent of patients account for roughly half of all US healthcare costs? By targeting these high-cost patients, big data has the possibility to make a tremendous effect on total healthcare spending inside the usa. This is a good example of the Pareto principle at the workplace. Readmissions - With nearly one third of readmissions deemed to be preventable, using big data to predict which patients are at a high risk of readmission could lead to better interventions and reduced re-admissions. Triage - Big data could be used to improve the triage process by applying algorithms to send patients to the correct unit for care and ensuring that everyone involved with providing that care is promptly informed through the process. Decompensation - Decompensation refers to a patient's worsening health condition. Patient monitoring tools such as heart rate and blood pressure monitors are used to measure a patient's current condition. Using big data, researchers could be better able to determine the risk of decompensation, allowing healthcare providers to intervene before the patient's condition worsens. Adverse events - No one wishes to suffer from an adverse health event for example infection, a drug reaction, [https://online.cisl.edu/profile/64118/Colin best scientists] or renal failure. These events often end in death, yet will often be preventable. Big data could make huge gains in both preventing adverse events and slashing their associated costs. Diseases affecting multiple organ systems - Systemic diseases that affect multiple organ systems are among the costliest to treat and manage. Using big data, medical researchers might be better able to predict the likely progression of a disease which, in turn, would help healthcare providers develop a far more effective, and even more cost-effective, treatment plan. While these areas all represent significant opportunities for medical researchers and also the medical sector at large, how can researchers possibly make experience of all that data? As outlined by Dolphin, "Big Data relates to the very fact that today's business intelligence systems are experiencing record levels of data growth from terabytes to petabytes and beyond. The challenge is in maximizing the opportunity for real-time business intelligence while minimizing the impact of exploding data volume on productivity and total cost of ownership (TCO)." This really is done through the use of business intelligence and data archiving software. With the proper tools in hand, medical researchers have the ability to make sense of the sheer volumes of healthcare data from the past, present, and future.

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−	Big data in the medical industry ~~is about~~ to get even bigger ~~due~~ to the move toward electronic ~~health~~ records. Electronic medical records are ~~obtaining~~ a boost ~~due to~~ the implementation of the Affordable Care Act. ~~As such~~, medical researchers may ~~expect~~ a ~~tremendous~~ influx of healthcare data to analyze.<br><br>The scientific community is abuzz about the potential for big data in the medical research arena. In ~~line~~ with Science 2.0, a science blog, ~~several~~ of the clearest opportunities recently identified in this ~~particular~~ area revolve around reducing costs in several key areas:<br><br>High-cost patients - Did you ~~realize~~ that just five percent of patients account for roughly half of all US healthcare costs? By targeting these high-cost patients, big data has the ~~possibility~~ to make a ~~tremendous effect~~ on total healthcare spending ~~inside~~ the ~~usa~~. This is a ~~good~~ example of the Pareto principle at the workplace.<br><br>Readmissions - With nearly one third of readmissions deemed to be preventable, using big data to predict which patients are at a high risk of readmission could lead to better interventions and reduced re-admissions.<br><br>Triage - Big data could be used to ~~improve~~ the triage process by applying algorithms to send patients to the correct unit for care and ensuring that ~~everyone~~ involved ~~with~~ providing that care is promptly informed ~~through~~ the process.<br><br>Decompensation - Decompensation refers to a patient's worsening health condition. Patient monitoring tools ~~such as~~ heart rate and blood pressure monitors are used to measure a patient's current condition. Using big data, researchers ~~could~~ be better able to determine the risk of decompensation, allowing healthcare providers to intervene ~~before~~ the patient's condition worsens.<br><br>Adverse events - No one ~~wishes~~ to suffer from an adverse health event ~~for example~~ infection, a drug reaction, ~~[https://online.cisl.edu/profile/64118/Colin best scientists]~~ or renal failure. These events often ~~end in~~ death, yet ~~will~~ often be preventable. Big data could make huge gains in both preventing adverse events and slashing their associated costs.<br><br>Diseases affecting multiple organ systems - Systemic diseases that affect multiple organ systems are among the costliest to treat and manage. Using big data, medical researchers ~~might~~ be better able to predict the likely progression of a disease which, in ~~turn~~, would help healthcare providers develop a ~~far~~ more effective, and ~~even~~ more cost-effective, ~~treatment plan~~.<br><br>While these areas all represent significant opportunities for medical researchers and ~~also~~ the ~~medical sector~~ at large, how can researchers possibly make experience of all that data? As outlined by Dolphin, "Big Data relates to the very fact that today's business intelligence systems are experiencing record levels of data growth from terabytes to petabytes and beyond. The challenge is in maximizing the opportunity for real-time business intelligence while minimizing the impact of exploding data volume on productivity and total cost of ownership (TCO)."<br><br>This really is done ~~through~~ the use of business intelligence and data archiving software. With the proper tools in hand, medical researchers ~~have~~ the ability to make sense of the sheer volumes of healthcare data from the past, present, and future.	+	Big data in the medical industry will be close to to get even bigger thanks to the move toward electronic medical records. Electronic medical records are receiving a boost as a result of the implementation of the Affordable Care Act. Consequently, medical researchers may anticipate a massive influx of healthcare data to analyze.<br><br>The scientific community is abuzz about the potential for big data in the medical research arena. In accordance with Science 2.0, a science blog, some of the clearest opportunities recently identified in this area revolve around reducing costs in several key areas:<br><br>High-cost patients - Did you know that just five percent of patients account for roughly half of all US healthcare costs? By targeting these high-cost patients, big data has the potential to make a big influence on total healthcare spending in the united states. This really is a great example of the Pareto principle at the workplace.<br><br>Readmissions - With nearly one third of readmissions deemed to be preventable, using big data to predict which patients are at a high risk of readmission could lead to better interventions and reduced re-admissions.<br><br>Triage - Big data could be also used to enhance the triage process by applying algorithms to send patients to the correct unit for care and ensuring that everybody involved in providing that care is promptly informed throughout the process.<br><br>Decompensation - Decompensation refers to a patient's worsening health condition. Patient monitoring tools for example heart-rate and blood pressure monitors are used to measure a patient's current condition. Using big data, researchers might be better able to determine the risk of decompensation, [https://institutosanfernando.edu.pe/forums/users/colinhndrcks quality researcher] allowing healthcare providers to intervene prior to the patient's condition worsens.<br><br>Adverse events - No-one desires to suffer from an adverse health event such as infection, a drug reaction, or renal failure. These events often contribute to death, yet are often preventable. Big data could make huge gains in both preventing adverse events and slashing their associated costs.<br><br>Diseases affecting multiple organ systems - Systemic diseases that affect multiple organ systems are among-the costliest to treat and manage. Using big data, medical researchers could possibly be better able to predict the likely progression of a disease which, in return, would help healthcare providers develop a more effective, and more cost-effective, course of action.<br><br>While these areas all represent significant opportunities for medical researchers and the health care industry at large, how can researchers possibly make experience of all that data? As outlined by Dolphin, "Big Data relates to the very fact that today's business intelligence systems are experiencing record levels of data growth from terabytes to petabytes and beyond. The challenge is in maximizing the opportunity for real-time business intelligence while minimizing the impact of exploding data volume on productivity and total cost of ownership (TCO)."<br><br>This really is done throughout the use of business intelligence and data archiving software. With the proper tools in hand, medical researchers possess the ability to make sense of the sheer volumes of healthcare data from the past, present, and future.

Quality Scientists 2 - Revision history

LorraineSolar5 at 16:24, 30 December 2020

KandiceChumley8: Created page with "Big data in the medical industry is about to get even bigger due to the move toward electronic health records. Electronic medical records are obtaining a boost due to the impl..."