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what do you think is potentially the greatest organizational benefit of using predictive analytics in patient care?

what do you think is potentially the greatest organizational benefit of using predictive analytics in patient care?

With the capabilities that informatics brings to the health care sector come the responsibility of considering the legal and ethical outcomes of using patient data, even if it is anonymous, to inform policies, practices, and patient costs of receiving care. This week you study the use and implications of predictive analytics aimed at personalizing and improving patient care.

 

Respond to the following in a minimum of 175 words:

Research an example of the use of predictive analytics in health care and share the link in your post. Summarize the application, its benefits, and potential drawbacks. Do you think the benefits are worth the potential risks and drawbacks?

Is predictive analytics that uses genomics racist, sexist, homophobic, or discriminatory in other ways? Defend your answer using course and industry sources.

As a health care administrative professional, what do you think is potentially the greatest organizational benefit of using predictive analytics in patient care?

 

 

R1

Hi class a great way of predictive analytics is when bad diseases are being watched. I feel this is how they monitor everybody people with diabetes high blood pressure and things like that. But like I have stated in one of my post I feel that not everybody get the same treatment when it comes to certain diseases. And what I mean by that like for example people with cancer they have so many cancer places where patients can get tried but I feel the real good ones are the ones for people who has to pay out of pocket. Now I can be wrong about this but I’ve watched 3 people I know with cancer 2 of them were using health insurance and they didn’t make it and one that lives high class and they paid out of pocket to go to a real good treatment place and they survived. I don’t know like I said I could be wrong about this maybe it’s all in the dna the body all in how the person was taking care of themselves once’s they found out they had cancer I don’t know. Also I feel that predictive analytics is also virtual care but it should be done once the patient leaves they sight I feel that they should have treatment for patients who are bed bound at home and can’t make it to the hospital. I know some places may have it but to actually get it started it shouldn’t be a hassle theirs people that actually need things like physical therapy and can’t get it.

 

https://www.ibm.com/products/health-insights?gclid=EAIaIQobChMIhLjyiYDx9wIVhMyGCh0DjQSrEAAYAyAAEgLkCPD_BwE&gclsrc=aw.ds

 

 

R2

One example of predictive analytics in healthcare is detecting early signs of patients deterioration in the ICU and also is the general ward. By using predictive analytics in the ICU where the patients are critical and their lives can depend on a new line of treatment within minutes to help avoid them from deteriorating even more quickly, predictive analytics and predictive algorithms can help find out the what intervention is needed within minutes. When using predictive analysts can also help the doctors and nurses estimate risk of the patient’s death. This would help when the nurses are discharging patients to see if the patient should really be discharged or if the risk is too great for them not to stay at the hospital. I would have to say that the greatest benefit in using predictive analytics is to continue to intervene when the patient is not getting better and figure out a different treatment plan that will allow the patient to continue to live a full life. Predictive analysts that use genomics is not being racist, sexist, homophobic, or discriminatory because this would allow disease to be detected if it runs in the immediate family or from relatives that are no longer alive. This would allow individuals to learn about illnesses that they could carry the gene for so they are able to get the proper treatment before it becomes too late.

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