Article | October 21, 2020
Do you know a friend or loved one who suffers from fear, anxiety, and depression and do not know what to do?
It can be difficult to watch someone you know struggle with their mental health and not be able to do anything about it.
As a result, here are 8 important tips on how to help the person you care about in these kinds of situations.
1. Learn as much as you can in managing anxiety and depression: There are many books and information that will educate you on how to deal with fear and anxiety. Share this information with the person who is struggling with their mental health.
2. Be understanding and patient with the person struggling: Dealing with depression and anxiety can be difficult for the person so do not add more problems than what is already there. Do not get into arguments with the person who is having a difficult time with their mental health.
3. Talk to the person instead of talking at them: It is important not to lecture the person who is struggling with anxiety and depression. Talk to the person about their issues without getting upset. Most people will listen if you approach them in the right manner.
4. Remind the person the importance of getting help: One way to convince the person who is struggling with fear and depression is to tell them what may happen if they don't get some assistance. Anxiety and depression can be difficult to manage and usually these mental health issues won't go away by themselves.
5. Find out why the person won't seek assistance: Address the issues on why the person will not get the necessary help. Many people who are struggling are fearful and frustrated. Try to find out the reasons why he or she won't get the help they need and then try to find ways that will overcome their resistance of seeking treatment.
6. Join a local support group: There are many mental health support groups in your area that can help you. Many hospitals, churches, and counselors in your area will be able to provide you with a list of groups. These mental health organizations will be supportive of your situation and they can give you additional advice on how to help the person who is struggling.
7. Talk to someone who has been there: Find somebody who used to struggle with fear, anxiety, or depression and have them talk to the person who is struggling. He or she could use their past experiences to try to reason with the person that you care about, and they might be able to use their insights to convince the individual to seek treatment.
8. Talk to a counselor: Talk to a professional counselor on how you can help your friend or relative with their mental health struggles. A counselor can give you advice and ideas on how to help out your friend. Your main goal is to get the person who is struggling to seek help from a mental health specialist.
Article | April 2, 2020
The rapid advancement of technology has inspired hope in the healthcare industry, promising to employ artificial intelligence (AI) and cloud-based data platforms in life-altering ways. Surgery assisting robots and miraculously accurate AI-based cancer diagnosis methods are a few preliminary examples of what the industry can expect. With all these great technological strides being taken, however, compliance can easily be left in the dust. And with COVID-19 pushing the limits of healthcare systems worldwide, it’s too easy for cybersecurity to become a lesser priority.The situation is bleak, with nearly 17,000 patient records being breached every day, according to Entech. Healthcare democratization is essential to fully harnessing the power of AI and other tech advancements on the horizon, which require compliant data distribution and the application of insights gathered from it. Healthcare institutions are struggling to not only meet basic privacy and compliance laws but have difficulty leveraging the large amounts of data that they store in a meaningful way.
Article | December 15, 2020
As medical science has improved rapidly, life expectancy around the world also has risen. Still, as longevity increases, healthcare systems are facing a growing demand for advanced services, increased costs, and a struggling workforce to meet various requirements of patients. Demand is driven by many unstoppable forces: a shift in lifestyle choices, shifting patient expectations, population aging, and the never-ending cycle of innovation are a few among others.
Challenges Faced by the Healthcare Industry
According to Mckinsey, one in four people in North America and Europe will be over the age of 65 by 2050. This shows that, soon, the healthcare industry will have to deal with a larger number of patients with more complex requirements. Catering to these patients is expensive and requires health systems for providing long-term focused and proactive care. To remain sustainable, healthcare systems need major transformational and structural changes.
The industry also needs a larger workforce because according to the World Health Organization (WHO), globally there is a shortfall of approximately 9.9 million nurses, physicians, and midwives. Apart from attracting, training, and retaining these healthcare professionals, you also have to ensure that their time and effort add value to patient care. Utilizing the solutions powered by modern technologies, such as Artificial Intelligence (AI) in the healthcare industry, will add perfection and more value to human efforts.
AI in the healthcare industry has the potential required to transform and revolutionize healthcare by addressing the challenges in the industry mentioned earlier. AI can better the outcomes, improve efficiency, and augment productivity in healthcare delivery. This article takes an in-depth look at the impact of AI in healthcare.
Impact of AI in the Healthcare Industry
In the coming years, AI in the healthcare industry will improve the day-to-day life of healthcare practitioners, augment the patient experience, improve care delivery, and can even facilitate life-saving treatments and revolutionize the industry. Additionally, AI will improve population-health management, operations, and strengthen innovations.
According to Statista, the global AI healthcare market will increase to more than US$28 billion by 2025. Here is a detailed look into the areas where and how AI in the healthcare industry will be impactful.
Chronic Care Management
Chronic diseases, such as cancer, diabetes, kidney diseases, are the leading cause of disability and death in the US and the main drivers of the country’s annual health cost. Effectively managing various chronic diseases is an overarching and long-term process. But with the help of the right tool, healthcare providers can meet the needs of these patients without delay.
Artificial intelligence tools in the healthcare industry can help healthcare providers overcome the complexities of chronic disease management and make it more effective and provide quality treatment. AI in the healthcare industry is increasingly being leveraged by organizations to improve chronic disease management, enhance patient health, and drive down costs, which will also eventually result in data-driven and personalized care. AI in the healthcare industry is expected to move the industry toward proactive care delivery from a reactive one and lead the industry to provide more individualized treatments. This is just one of the ways AI in the medical industry is going to revolutionize chronic care management in hospitals.
Artificial intelligence in the healthcare industry is changing the way care is delivered; it is expected to make healthcare more efficient, accurate, and accessible. Reducing costs and improving health outcomes are the values health systems and hospitals are trying to deliver to patients every day. Hospitals are increasingly incorporating technologies, which are powered by the use of AI in healthcare to meet the challenge.
According to the American Hospital Association (AHA), AI in the healthcare industry has unlimited potential to solve most of the vexing challenges in the industry. They identify AI use cases in the healthcare industry in four broad areas, which are administrative, operational, financial, and clinical areas.
Administrative Use Cases for AI in the Healthcare Industry
• Admission procedures
• Appointment scheduling
• Customer service responses
• Discharge instructions
• Hiring and orientation protocols
• Licensure verification
• Patient check-in procedure
• Prior authorizations
• Quality measure reporting
Operational Use Cases of AI in the Healthcare Industry
• Inventory management
• Materials management
• Supply chain management
• Facilities management
Financial Use Cases for AI in the Healthcare Industry
• Billing and collections
• Claims management
• Insurance eligibility verification
• Revenue cycle management
Clinical Use Cases of AI in the Healthcare Industry
• Predictive technologies
• Interventional technologies
By incorporating and utilizing these scopes with AI in the healthcare industry, the industry can be transformed into a next-gen level in no time. It also allows healthcare practitioners to focus more on patients, which would eventually help in raising staff morale and improving retention.
Clinical Decision Support
Recent advancements in AI in the health industry are capable of enhancing the currently used clinical decision support (CDS) tools to have value-based imaging and to improve patient safety. According to the National Institute of Health (NIH), the synergy between CDS systems and AI in the healthcare industry will be able to:
• Reduce friction in radiology workflows
• Identify relevant imaging features easily
• Generate structured data to develop machine learning algorithms
• Enable an evolution toward decision support for a holistic patient perspective
• Suggest imaging examinations in complex clinical scenarios
• Assist in identifying appropriate imaging opportunities
• Suggest appropriate individualized screening
• Aid health practitioners to ensure continuity of care
AI in the healthcare industry is competent in making CDS a next-gen one, enhancing the experiences of radiologists and providers, and improving patient care.
Slowly but surely, AI is improving almost every aspect of human life with innovations and advancements. The latest is that AI in the healthcare industry is impending a revolution in medical diagnostics by providing accurate risk assessments, accelerating disease detection, and boosting hospital productivity. By automatically prioritizing urgent cases and accelerating reading time, image recognition AI enhances the workflow of radiologists. It even helps in the prevention of diseases by the early detection of diseases.
In medical images such as x-rays, MRIs, and CT scans, AI-driven software can efficiently be used to accurately spot signs of many diseases, especially in detecting many chronic diseases such as cancer. According to the NIH, AI will be widely applied in the healthcare industry especially for various tasks such as patient engagement and adherence, diagnosis, and treatment recommendations. So, there is no doubt that AI in healthcare will revolutionize the diagnostic process in the approaching years by detecting diseases, classifying diseases, and improving the decision-making process. The application of AI in the healthcare industry will make people live longer.
Triage and Diagnosis
AI can be effectively used to automatically triage cases. AI algorithms will analyze the cases and forward cases to pathologists after determining the priority based on the probability of cases according to the criteria set by labs. This makes the workflow of pathologists easier and efficient. Through the process the algorithm will be able to:
• Verify the digital images attached to the case belong to that case
• Validate the tests ordered and match the specimen type
• Identify cases marked as stat
• Determine the cases, which can be positive or are most likely to be negative
Moreover, AI technologies in the healthcare industry also can be effectively used to provide more accurate and faster diagnoses. This speeds up the entire process of triage and diagnosis and is expected to revolutionize the healthcare industry soon.
The Future Outlook for AI in the Healthcare Industry
Over the next few years, AI in the healthcare industry has the best opportunities in hybrid models to support clinicians in diagnosis, identifying risk factors, and in treatment planning. This scope will result in faster adoption of AI technology in healthcare, which will show measurable improvements in operational efficiency and patient outcomes.
With a plethora of issues to overcome, which are driven by documented factors such as growing rates of chronic diseases and the aging population, it is obvious that the healthcare industry needs new innovative solutions. AI-powered solutions in the healthcare industry will achieve a clear impact on the global healthcare industry in a short time.
Frequently Asked Questions
Which is the best application of AI in the healthcare sector?
Cognitive surgical robotics is the best application of AI in the healthcare sector as it helps practitioners collect data from real surgical processes, which would help in improving existing surgical approaches.
Why is artificial intelligence important in healthcare?
Artificial intelligence in healthcare is vital as it can help make decisions, analyze and manage data, and have conversations. So, AI will drastically change the everyday practices and roles of clinicians.
When was AI-first used in healthcare?
The term, Artificial intelligence (AI) was first described in 1950, but the limitations of the term prevented its acceptance. In the 2000s, these limitations were overcome and people started to accept the term.
Article | February 27, 2020
One off implementation services often take additional time to build, are more brittle and susceptible to failure, are less performant, and can impede realizing full value from your ERP investment. Productized integration means that there is ongoing coordination of the ERP application, the interface design, and the EHR, and that the interfaces are optimized for performance and tested prior to release. Productized integration delivers value faster and more reliably than one off implementations. For example, Infor Clinical Bridge is a product and subject to the exacting product design and testing process required for product release.