Health Technology, Digital Healthcare
Article | September 8, 2023
Do you know a friend or loved one who suffers from fear, anxiety, and depression and do not know what to do to help them?
It can be frustrating to watch someone you know struggle with their mental health and not be able to do anything to relieve their suffering.
With this in mind, here are seven ways to help the person cope 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 successfully overcome fear and anxiety. Share this information with the individual who is struggling with their fears. The key is to get your friend to understand how important it is to seek some guidance when it comes to their mental health.
2. Be understanding and patient with the person struggling with their fears: Maintaining depression and anxiety can be difficult for the individual so do not add more problems than what is already there. Do not get into arguments with your friend who may be having a difficult time with their anxieties. Make an effort to listen to the person rather than making judgements.
3. Talk to the person instead of talking at them: It is important not to lecture the individual who’s having a hard time with anxiety and depression. Talk to the person about their issues without being rude. Most people will listen if you approach them in a proper manner. Remember to treat others the way you would want to be treated if you were the one who was struggling.
4. Ask for some ideas: Seek advice from a professional who can assist the person you know with their mental health issues. A counsellor can give you some ideas on how to overcome anxiety, fear, and depression. Getting help from a therapist is the number one priority in getting the individual to do something about their problems.
5. Find out why the person won’t get assistance: Address the issues on why he or she will not seek treatment. Many people who are struggling are fearful and frustrated. Try to find out the reasons why your friend won’t get the help they need and then try to find the ways that will overcome their resistance of seeking some guidance.
6. Remind the person on the consequences of not getting help: Another way to convince the individual who is struggling with fear and depression is to tell them what may happen if they don’t get some counselling. Anxiety and depression can make things worse and usually won’t go away by themselves.
7. You can’t manage your mental health all by yourself: A person’s fears and anxieties can be difficult to manage and more than likely he or she will need some help. Many people think that they can overcome their mental health problems on their own. This is a mistake. The individual should admit they have a problem and then seek treatment to get their life back on track.
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Health Technology
Article | September 12, 2023
Across the spectrum of healthcare delivery – payor, provider, vendor, consumer, there is a land rush underway to embrace consumer-centric care. With tools like value-based care, chronic disease management, retail services, analytics, and remote patient monitoring, healthcare organizations are pivoting towards capabilities that provide a deeper understanding of patient behaviors and address the whole patient and not just the condition.
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Health Technology, Digital Healthcare
Article | August 21, 2023
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.
Care Delivery
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.
Diagnostics
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.
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Digital Healthcare
Article | February 19, 2022
As competition for patients intensifies, more hospitals and health systems are embracing a consolidated, single-bill approach for services rendered. Creating a single bill for the patient’s portion of inpatient or outpatient services can help eliminate confusion and reduce the ill will that frequently results when patients receive multiple invoices for a single care event. Yet incorporating anesthesia charges into a consolidated invoice is often problematic due to the unique nature of the anesthesia billing compliance.
Anesthesia Billing Service Hurdles
A few weeks ago, I met with the CEO of a 300-bed hospital. We discussed anesthesia billing, and he explained that his hospital traditionally outsourced this portion of its billing due to the more complex nature of anesthesia coding and the need to collect anesthesia minutes for billing. Unlike most inpatient services, anesthesia charges are not directly derived from CPT codes but instead utilize minutes and modifiers unique to the specialty.
That means coders must use a CPT crosswalk to account for ASA codes, base and time units, emergency- and physical-status monitors, split anesthesia units reflecting CRNA involvement, and other specialty-specific nuances. Most coders and hospital billing staff are not trained in these complexities, and hiring and retaining capable staff in today’s competitive market can be difficult. Moreover, many billing platforms are simply not equipped to incorporate all the variables necessary to produce an accurate anesthesia bill.
As a result, producing a consolidated patient bill that includes anesthesia is tricky. Yet leaving anesthesia off a single bill can undercut its value since, after facility and surgical charges, anesthesia often is one of the largest cost items patients incur. Fortunately, we at Change Healthcare know how to roll anesthesia charges into existing hospital billing systems to produce an accurate and timely single patient bill.
Helping to Reduce Costs
The benefits of consolidated billing extend beyond an improved patient experience. Producing just one bill reduces costs and repetition at both the front and back end of the revenue cycle management process. It can also ease staff burden when collecting on self-pay accounts, since there’s only one bill per patient. Finally, consolidated bills can help increase revenue by simplifying collections when patients present for follow-up care.
Here’s an example: When the patient comes back for post-surgery physical therapy, a hospital employee at the registration desk can remind them that they still owe $150 for anesthesia and ask if they’d like to take care of that now. In my experience, patients usually hand over their credit card and settle their bill on the spot when asked at the time of care about a balance due.
System-Agnostic Billing Across Hospital Platforms
Change Healthcare has a long history of providing full-service, outsourced anesthesia-billing services to hospital and health-system clients. Unlike most other billing vendors, we’ve developed what we call a system-agnostic approach. That means we’ll provide billing services on our proprietary system or on the hospital’s existing billing platform, regardless of type, to generate accurate anesthesia-billing results.
In practical terms, we’ll function as part of your billing team and use the same system your coders and billing staff rely on to generate anesthesia charges that can be included in a single patient bill.
System-agnostic billing also allows us to provide clients with custom anesthesia reporting that wouldn’t otherwise be available with an outsourced billing solution. This helps clients gain far greater visibility and insight into anesthesia-billing charges. And by incorporating our anesthesia coding and billing capabilities into your existing billing system, you’ll be spreading the platform’s fixed costs across a greater number of departments.
The bottom line? It’s not a heavy lift for us to virtually embed our trained anesthesia coders and billing professionals into your system. Our specialists will review your existing platform and provide, at no obligation, a return-on-investment analysis that can help you determine whether outsourcing anesthesia billing to capture claims on a single hospital bill makes sense for you.
We expect the answer will be yes. Not only will you enjoy greater system efficiencies, but you’ll be in a position to produce a single bill that truly reflects the entire episode of care.
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