Healthtech Security
Article | August 31, 2023
Smoking has a lot of consequences to one’s health. It can lead to cancer, heart disease, and chronic obstructive pulmonary disease—all of which are chronic diseases. This is part of the reason why the Health and Human Services agency reports that 70% of adult smokers want to quit. As a medical provider, adults looking to stop smoking will come to you for advice and treatment. One alternative smoking product you might want to recommend is an e-cigarette, given their prevalence in recent years.
In this article, let’s take a deeper look at whether e-cigarettes’ should be recommended for smoking cessation and what other treatment options to endorse to patients.
Are e-cigarettes approved for smoking cessation?
Electronic cigarettes, more commonly known as e-cigarettes, are devices that vaporize nicotine-based liquid to be inhaled by its user. It almost replicates the experience of smoking a cigarette due to the device’s shape and the vapor it produces. However, the FDA has yet to approve e-cigarettes for smoking cessation because there is currently limited research on their effectiveness, benefits, and risks for the human body.
Additionally, scientists at the University of California found harmful metals in the vapor from tank-style e-cigarettes. These e-cigarettes are equipped with high-power batteries and atomizers to store more liquid. These result in high concentrations of metals like iron, lead, and nickel in the vapor. Exposure to and inhaling metallic particles may impair lung function and cause chronic respiratory diseases. As such, medical providers should not recommend e-cigarettes for smoking cessation.
What can medical providers recommend for smoking cessation?
Smoking cessation medication
Presently, two FDA-approved prescription medicines for smoking cessation are Bupropion and Varenicline. Bupropion is an antidepressant that decreases tobacco cravings and withdrawal symptoms. It does this by increasing the brain chemicals dopamine and noradrenaline. This comes in a pill and can be used alongside other smoking cessation aids.
Varenicline also reduces cravings and nicotine withdrawal symptoms. It blocks nicotine receptors in the brain, decreasing the amount of enjoyment one gets from smoking. One thing to note about this is that it will take several days for Varenicline's effects to take place. Therefore, it's best to prescribe these pills 1-2 weeks before the patient quits smoking. Like Bupropion, Varenicline may be used simultaneously with other quit-smoking products.
Nicotine Replacement Therapy
Nicotine replacement therapy (NRT) is a treatment involving nicotine consumption at gradually decreasing levels. This reduces the patient’s desire to smoke without them having to quit cold turkey. NRT involves using nicotine alternatives that don’t produce smoke, such as nicotine pouches and nicotine gum.
Nicotine pouches are oral products containing ingredients like nicotine, flavoring, and plant-based fibers. These are placed between the lip and gum, where nicotine is absorbed into the bloodstream. Different variations have different strengths. On! pouches come in different strengths: 2mg, 4mg, and 8mg. Patients may start from 8mg variants and gradually decrease this dosage as their NRT progresses. Pouches also come in a wide range of flavors—including citrus, mint, and berry—to entice users.
Meanwhile, nicotine gum is chewing gum that contains nicotine. It is chewed a few times before being parked between the gums and cheek for nicotine absorption. The nicotine gums by Lucy are a significantly better alternative for tobacco users. Like pouches, this gum comes in several flavors, such as cinnamon, mango, and wintergreen, and different strengths ranging from 2mg to 6mg.
Counseling
The recommendations mentioned above—medication and NRT—are more effective when coupled with counseling. A Primary Care Respiratory Medicine study revealed that successful smoking cessation is best attained through pharmacological treatment and counseling. Sessions typically involve a patient meeting with a counselor and they discuss their smoking habits, possible causes, and how to mitigate them. Medical providers should include counseling in addition to medication and NRT.
E-cigarettes have yet to be approved by the FDA as smoking cessation aids. For now, medical providers should provide medication, NRT, and counseling to patients who want to quit smoking.
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Health Technology, Digital Healthcare
Article | July 14, 2023
It’s no secret now that healthcare is an in-demand field. Today, business leaders need modern and intelligent decision-making solutions for their customers and clients. They must also focus on the right investment areas and learn the tricks for investing, spending, and setting goals for revenue generation to accelerate business.
With continuous developments in the healthcare sector, integrating AI into processes can help increase ROI. Therefore, if you, like any other business leader, are looking for solutions to empower your services and products in the healthcare domain, this article will help you through AI’s ultimate use cases and churn out a higher ROI.
What’s with AI in Healthcare at Present?
AI’s role in healthcare is evolving and enhancing traditional business operations, particularly marketing. According to a study by IBM, 71% of customers expect real-time communication. Thus, global demand is fueling the rising adoption of AI marketing solutions.
The effects of AI in healthcare are evident. Gartner reports increased marketing efficiency and effectiveness (86%), improved decision-making (71%), better data analysis and new insights (79%). Global AI spending will rise from $450 million in 2019 to over $28 billion by 2024 is not surprising.
Similar and further studies are ongoing on various use cases of AI in healthcare at scale. What are the efficient use cases of AI that will help healthcare businesses boost their ROI? Let’s find out.
How is AI Applied in Healthcare?
The promising applications of AI in healthcare to improve outcomes are very intriguing. While there is still much to achieve in the AI-dependent healthcare business, there is sufficient potential that tech companies are willing to invest in AI-powered tools and solutions.
Let’s examine the potential examples of AI in healthcare to prepare and support business strategies accordingly and foster higher ROI generation.
Predictive Analytics
AI-based predictive analytics impacts a business by automating administrative tasks, predicting sales outcomes for a year, customers’ behavior and making strategies accordingly. According to a Forbes study, AI-based predictive analytics can save businesses $18 billion in tasks, expenses, and pricing.
To understand this, one example of using AI to automate admin tasks is a collaboration between the Cleveland Clinic and IBM. Cleveland Clinic uses IBM’s Watson to mine big data and provides personalized services for customers and clients on marketing deeds.
Some of the practical applications of AI and predictive analytics in healthcare are:
Monitoring market trends to maximize marketing efforts
Organizing datasets
Creating marketing campaigns tailored to each demographic-based client
Mining collective data for future decision-making
Fraud Prevention
AmerisourceBergen Corp detects fraud and misleading business operations through AI. A sales account team conducts audits with AI to detect usual lea and queries to prevent hefty expenses for businesses.
The example explains that implementing AI in your process will help detect any significant fraud attempts inside your business operation. This will help your business save huge expenditures.
Boost Sales
By putting down false leads, AI helps in maximizing sales numbers, resulting in significant ROI generation. For example, AI transforms data into personalized data, which reduces the cost of operations.
Chatbots
Most healthcare businesses leverage chatbots on their websites to engage more and more customers and boost engagement. In this way, businesses tend to gain multiple leads and convert them into clients by providing the best marketing solutions.
Chatbots are fruitful for AI start-ups in healthcare—small businesses can deploy AI to their websites. By doing so, they can save millions in administrative costs and attract numerous leads.
The most prominent examples of AI in healthcare hail from giant tech titans such as IBM, Amazon, and Microsoft. They are assisting healthcare providers with AI to create and deploy digital-human employees.
Segmentation of Marketing Targets
Is your target audience not responding to your marketing campaigns (for example, by not clicking a link, subscribing or unsubscribing to a newsletter, or not registering for a medical event)? If that's the case, how should you go ahead?
Using AI-based tools allows your marketing to easily identify target behaviors and reactions based on the type of marketing actions to be carried out. Analyzing these actions can help segment targets based on your company's marketing objectives.
The most significant development took place in April 2022, when Amazon Alexa became fully HIPAA compliant. It works with health developers and service providers that manage protected information for customers.
AI Leads to Data Modernization
It’s all about the data—not any data!
There’s a precise association between AI and data management, resulting in data modernization. According to a Cognizant research study, healthcare leaders have made significant progress in modernizing their data. In contrast, most upcoming businesses are expecting to do so by 2024.
The maximum acceleration of AI in modernizing data will be seen in the manufacturing and marketing of healthcare products and services, respectively. It is because AI helps to churn data easily. The accessibility of data, in particular, becomes simpler with automation than doing it manually, which generates a massive amount of data. Such effects of AI in healthcare can be one of the prime reasons for the higher ROI of your business in the future.
“There has never been a greater need for skilled analytic talent in health care. Because AI is becoming more strategic, organizations must ensure access to this skill set, either by growing their analytic teams or seeking out experienced partners."
Steve Griffiths, CEO of Optum Enterprise Analytics
AI Expenditure is on the Rise
McKinsey says that by 2025, the use of AI in healthcare will be widespread, resulting in significant expenditure by global healthcare leaders.
AI is a significant concern for healthcare decision-makers, investors, and innovators as customers extensively engage and react to AI-powered services and solutions. AI is constantly bringing improvements to almost all processes, including cost savings, management of services and products, and monitoring of multiple operations. Even small businesses in the healthcare industry are proactively investing in AI applications to match steps with the current wave of innovation in healthcare services.
Accelerate ROI Using AI
AI in healthcare is becoming one of the prime responsible technologies for accelerating ROI. Technology can eradicate multiple business growth challenges. Let’s find out how.
Enhanced Performance
As previously stated, use cases of AI in healthcare can relieve stress on employees. This would allow them to devote their time to more value-added marketing activities to churn more ROI.
Emphasize Cost-Effectiveness
Most of the businesses associated with healthcare are concerned about the costs involved. With AI, they now develop policies to spend less on non-essential activities and necessitate profit-oriented actions.
"We believe in the potential of AI to deliver insights and operational efficiencies that unlock better health-care performance."
Robert Musslewhite, CEO at OptumInsight
Frequently Asked Questions
How is AI used in healthcare?
AI in healthcare automates and predicts processes by analyzing data throughout. It is used to predict potential customers, improve business management workflows, and manufacture medical products.
How does AI drive growth in the healthcare industry?
AI drives business growth by improving the ability to understand better day-to-day customer patterns and needs based on services and products.
How is AI changing the Healthcare industry?
AI applications in healthcare have demonstrated their potential to improve analytics and data management and assist service providers in making timely medical decisions.
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Health Technology, Digital Healthcare
Article | August 16, 2023
As consumers, we crave convenience and simplicity, and across an array of industries, technology has made it increasingly easy to search for and purchase products and services. From getting a pizza delivered to buying a car online, the process often involves entering a few pieces of information, hitting send, and waiting for a confirmation email.
A Changing Landscape
Unsurprisingly, people want this same level of convenience and simplicitywhen they're seeking care. This change in consumer demand for convenience is further compounded by fundamental shifts in the healthcare ecosystem. Among these shifts are cost-sharing models that have increased patient out-of-pocket expenses, healthcare systems that are increasingly shifting toward delivering value-based care, and innovations in digital health solutions.
While patients want to play an active role in managing their well-being, that is often easier said than done in a system that uses a combination of manual processes and non-integrated point solutions to try and meet consumer demand. Disparate and burdensome methods of managing patient engagement often lead to inefficiencies within provider organizations, resulting in missed appointments, increased registration and eligibility-based denials, incomplete payments, higher collections and write-offs, and low patient satisfaction.
Consumer Dissatisfaction
Healthcare consumers today feel like they're fighting an uphill battle. According to Change Healthcare's 2020 Harris Poll Consumer Experience Index, 67% of respondents agreed that it “feels like every step of the healthcare process is a chore.” A similar percentage, 62%, agreed that “the healthcare system feels like it is set up to be confusing.”
Furthermore, if consumers don’t receive the level of convenience and digitization they want from their current provider, they’re more than willing to seek it out elsewhere. In a recent Black Book survey, 80% of respondents indicated they would be willing to change providers for more convenience even if they were receiving good care from their current provider. An even higher percentage of patients,90%, do not think they have to continue seeing a provider if that provider does not “deliver an overall satisfactory digital experience.”
A Patient-Centric Approach
Improving the patient experiencestarts with humanizing revenue cycle management(RCM) —the administrative process that takes the patient from registration and appointment scheduling to the final payment of a balance. Simply making administrative touchpoints self-service and easy to understand throughout the patient’s financial journey can help humanize revenue cycle management for providers.
How is that possible? By thinking about the patients’ side of the administrative process and leveraging innovative technologies like artificial intelligence, robotic process automation (RPA), natural language processing (NLP), and machine learning. The more that providers’ staffs are able to automate repetitive tasks, the more time they're able to spend helping provide a seamless patient engagement journey that is focused on a patient’s specific needs. In other words, reducing human intervention throughout our technologies allows providers to infuse more human interaction with each patient as they navigate their healthcare journey.
According to Change Healthcare’s 2020 Harris Poll Consumer Experience Index, what patients really want is a retail-like shopping experience with modern, streamlined communication, as thevast majority (81%) agreed that “shopping for healthcare should be as easy as shopping for other common services” via a streamlined access point online. A clear majority (71%) also said they want their health insurance and healthcare providers (68%) to communicate with them using more-modern platforms.
Simplified Scheduling and Payment
The entire clinical-care journey is focused on the specific needs of the patient rather than the provider, so why shouldn’t the patient’s financial journey be handled the exact same way? From a patient-satisfaction perspective, patients are not separating their clinical journey from their financial journey, so providers should start viewing it the same way.
It should be easy to schedule an appointment and modify that appointment if needed. Patients should have to (securely) provide their personal and insurance information only once (digitally and in advance), then be squared away when they show up for their appointment with their provider. In addition, because of COVID-19 and the heightened awareness surrounding personal interaction, it’s important to provide patients with no-contact check-in and waiting room options.
By humanizing RCM, providers can achieve a cohesive end-to-end journey that allows patients to quickly and easily get the care they need complete with clear communication, price transparency , and a provider who truly takes the time to understand their unique situations. By putting the patient back at the center of their care journey, providers can improve care outcomes while also driving maximized business outcomes for their organizations.
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AI
Article | December 21, 2021
COVID-19 has been a catalyst for change, with the diagnostics industry taking centre stage and rising to the challenge of a global pandemic. One of the silver linings of this mammoth task has been the unprecedented time and focus dedicated to finding new technologies and solutions within the sector.
The lessons learned from the pandemic now need to be taken forward to improve breast and cervical cancer detection, prevention and treatment across the UK over the coming years.
In the more immediate term, the diagnostics industry, alongside public health leaders, faces a daunting backlog as screening programmes for breast and cervical cancer were put on pause for months. These two life-saving tests have been some of the most overlooked during the pandemic and getting back on track with screening is critical as we start to turn the corner. We believe innovation in diagnostics, particularly artificial intelligence guided imaging, is a key tool to tackle delays in breast and cervical cancer diagnosis.
The scale of the backlog in missed appointments is vast. In the UK, an estimated 600,000 cervical screening appointments were missed in April and May 2020. And an estimated 986,000 women missed their mammograms, of which an estimated 10,700 could be living with undiagnosed breast cancer. It is clear that hundreds of thousands of women have been affected as COVID-19 resulted in the reprioritisation of healthcare systems and resource allocation.
Both cervical and breast cancer screening are well suited for digital technologies and the application of AI, given both require highly trained medical professionals to identify rare, subtle changes visually –a process that can be tedious, time-consuming and error prone. Artificial intelligence and computer vision are technologies which could help to significantly improve this.
What does AI mean in this context?
Before examining the three specific areas where digitisation and AI can help, it is important to define what we mean by AI. It is the application of AI to medical imaging to help accelerate detection and diagnosis. Digitisation is the vital first step in implementing an AI-driven solution – high quality images demand advanced cloud storage solutions and high resolution. The better the quality of the input, the more effectively trained an AI system will be.
The first area where AI-guided imaging can play a role is workflow prioritisation. AI, along with increased screening units and mammographers, has the potential to increase breast cancer screening capacity, by removing the need for review by two radiologists. When used as part of a screening programme, AI could effectively and efficiently highlight the areas that are of particular interest for the reader, in the case of breast screening, or cytotechnologist when considering cervical screening.
Based on a comparison with the average time taken to read a breast screening image, with AI 13% less time is needed to read mammogram images, improving the efficiency with which images are reviewed. This time saving could mean that radiologists could read more cases a day and potentially clear the backlog more quickly.
For digital cytology for cervical cancer screening, the system is able to evaluate tens of thousands of cells from a single patient in a matter of seconds and present the most relevant diagnostic material to a trained medical professional for the final diagnosis. The job of a cytotechnologist is to build a case based on the cells they see. Utilising these tools, we are finding that cytotechnologists and pathologists are significantly increasing their efficiency without sacrificing accuracy to help alleviate the backlog of cervical screening we are seeing in many countries.
Prioritising the most vulnerable patients
Another key opportunity is applying AI to risk stratification, as it could help to identify women who are particularly at risk and push them further up the queue for regular screening. Conversely, it would also allow the screening interval for those women at lower risk to be extended, creating a more efficient and targeted breast screening programme.
For example, women with dense breast tissue have a greater risk factor than having two immediate family members who have suffered from breast cancer. What’s more, dense breasts make it more difficult to identify cancerous cells in standard mammograms. This means that in some cases cancers will be missed, and in others, women will be unnecessarily recalled for further investigation.
A simple way to ensure that those most at risk of developing breast cancer are prioritised for screening and seen more regularly would be to analyse all women on the waiting list with AI-guided breast density software. This would allow clinicians to retrospectively identify those women most at risk and move them to the top of the waiting list for mammograms.
In the short term, to help tackle the screening backlog, prior mammograms of women on the waiting list could be analysed using the breast density software, so that women at highest risk could be seen first.
Finding new workforce models
Being able to pool resources will allow resource to be matched to demand beyond borders. Globally, more than half a million women are diagnosed with cervical cancer each year and the majority of these occur where there is a lack of guidance to conduct the screening programme. The digital transformation of cervical screening can connect populations that desperately need screening to resources where that expertise exists. For example, developing countries in Africa could collect samples from patients and image these locally, but rely on resources in the UK to support the interpretation of the images and diagnoses. Digital diagnostics brings the promise of a ‘taxi-hailing’ type model to cervical cancer screening – connecting groups with resources (drivers with cars) to those who are in need (passengers): this is an efficient way of connecting laboratory professionals to doctors and patients around the world.
It’s going to take many months to get cancer screening programmes up and running at normal levels again, with continued social distancing measures and additional infection control impacting turnaround times. But diagnostic innovation is on a trajectory that we cannot ignore. It will be key to getting cancer screening programmes get back on track. AI is a fundamental piece of the innovation puzzle and we are proud to be at the forefront of AI solutions for our customers and partners.
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