Question

How is Artificial Intelligence (AI) transform the future of EHR and Healthcare?

Answer 1

Artificial Intelligence is machine intelligence demonstrated by machines. It is the creation of computers that work and react like humans. It is the discovery of 20 the century. The main types are narrow or weak. Strong and superintelligence. It can recognize objects in images, translate languages, speak. navigate maps, predict crop yields, and many other fields in advanced technology.

EHR or Electronic health record is designed to prevent errors in the patient record. It should be kept in the system as data. It is the invention of advanced technology.

Nowadays, all health systems are connected. It is due to the progress of scientific technology. Other benefits of using this technology are cost-effectiveness, avoid mistakes, accuracy. Much medical software is developed to connect.

FUTURE OF EHR

Ehr is the technology used to preserve medical files. The main benefits are

*all health care system are connected

*preserve data in easy manner

*accuracy in data content

* helps to minimise work effort

*can be verify any time

The demerits of these systems are also there. Some of them are

* some time errors occurs in computer system

*variation in electric power

.

*

Answer 2

Ans) Life sciences researchers using artificial intelligence (AI) are under pressure to innovate faster than ever.

- Large, multilevel, and integrated data sets offer the promise of unlocking novel insights and accelerating breakthroughs. Although more data are available than ever, only a fraction is being curated, integrated, understood, and analyzed. AI focuses on how computers learn from data and mimic human thought processes. AI increases learning capacity and provides decision support system at scales that are transforming the future of health care. This article is a review of applications for machine learning in health care with a focus on clinical, translational, and public health applications with an overview of the important role of privacy, data sharing, and genetic information.

Answer 3

Artificial Intelligence(AI) improves learning ability, and it supports a decision system for transforming the future of health care. It helps providers identify risk patients, make diagnoses and plan treatment options, and emphasize responsibility for patient care. Artificial Intelligence in technology and computer science helps for learning and planning. AI is beneficial for payers and providers of care. Electronic Health Records (EHR) support data processing and make the workflow in health care organizations.

Answer 4

There are various capacities where AI is emerging as a game-changer for EHR healthcare industry. Below are a few examples in use today:

• Radiology - AI solutions are being developed to automate image analysis and diagnosis. This can help highlight areas of interest on a scan to a radiologist, to drive efficiency and reduce human error. There is also opportunity for fully automated solutions – to automatically read and interpret a scan without human oversight – which could help enable instant interpretation in under-served geographies or after hours. Recent demonstrations of improved tumour detection on MRIs and CTs are illustrating the progress towards new opportunities for cancer prevention. Meanwhile, a company in the USA has already received FDA clearance for an AI-powered platform to analyse and interpret Cardiac MRI images.
• Drug Discovery - AI solutions are being developed to identify new potential therapies from vast databases of information on existing medicines, which could be redesigned to target critical threats such as the Ebola virus. This could improve the efficiency and success rate of drug development, accelerating the process to bring new drugs to market in response to deadly disease threats.
• Patient Risk Identification - By analysing vast amounts of historic patient data, AI solutions can provide real-time support to clinicians to help identify at risk patients. A current focal point includes re-admission risks, and highlighting patients that have an increased chance of returning to hospital within 30 days of discharge. Multiple companies and health systems are developing solutions at present based on data in the patient’s electronic health record, driven in part by increasing push back from payers on covering hospitalisation costs associated with re-admission. Other recent work has demonstrated the ability to predict risk of cardiovascular disease based purely on a still image of a patient’s retina.
• Primary Care/Triage - Multiple organisations are working on direct to patient solutions to triage and give advice via a voice or chat-based interaction. This provides quick, scalable access for basic questions and medical issues. This could help avoid unnecessary trips to the GP, reducing rising demand on primary healthcare providers – plus, for a subset of conditions, provide basic guidance that otherwise wouldn’t be available for populations in remote or under-served areas. While the concept is clear, these solutions still need substantial independent validation to prove patient safety and efficacy.

The best opportunities for AI in healthcare over the next few years are hybrid models, where clinicians are supported in diagnosis, treatment planning, and identifying risk factors, but retain ultimate responsibility for the patient’s care. This will result in faster adoption by healthcare providers by mitigating perceived risk, and start to deliver measurable improvements in patient outcomes and operational efficiency at scale.  

With a plethora of issues to overcome, driven by well-documented factors like an aging population and growing rates of chronic disease, the need for new innovative solutions in healthcare is clear.

AI-powered solutions have made small steps towards addressing key issues, but still have yet to achieve a meaningful overall impact on the global healthcare industry, despite the substantial media attention surrounding it. If several key challenges can be addressed in the coming years, it could play a leading role in how healthcare systems of the future operate, augmenting clinical resources and ensuring optimal patient outcomes.