Category Archives: Wellness Solutions

AI in critical care

Role of AI in Chronic Care Management

Effectively managing chronic diseases such as asthma, diabetes, cancer, and several others have been one of the biggest challenges for healthcare providers worldwide. According to a study, chronic diseases are responsible for 70% of deaths and about 50% of the disease burden globally. Owing to this, we will discuss how AI in chronic care management can change these numbers.

As the pandemic unleashed a global health crisis, many countries faced a shortage of healthcare professionals and medical resources. This caused several hurdles for patients with chronic conditions to get treatment at the right time. Such conditions forced chronic patients to adapt to remote and digital treatment, which is the new normal in the current world.

For medical professionals to deliver quality remote healthcare, it has become essential to leverage fast-emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML).

Both AI and ML have already shown how they can significantly improve the efficiency of operations in various other industries like e-commerce, manufacturing, automotive, etc. In this article, we will take a look at the role of AI in Chronic Care Management (CCM).

Key Benefits of Chronic Care Management

Before we understand the importance of AI in Chronic Care Management, let us look at some key benefits of Chronic Care Management: 

  • Chronic Care Management or CCM offers an organized approach to dealing with chronic conditions, making the process more coordinated for patients as well as the healthcare provider.
  • Healthcare providers can build long-term relationships with patients through their CCM services, which can result in increased revenue.
  • It can prevent unnecessary visits to partitioners.
  • Researchers have proved that CCM can offer quality healthcare to patients at a lower cost.

What is the Role of AI in Critical Care Management?

Here is how AI in chronic care management can turn around the situation:

●     Medical Data Analysis

An extensive medical data set will be required to utilize AI in chronic care management at its full potential. In today’s digital world, it can be easily gathered throughout the patient life cycle via mobile applications, IoT devices, and patient portal software. An Al-based algorithm can analyze this pool of data and generate new insights and opportunities for both patients and medical professionals in CCM. This can streamline the overall chronic care management processes.

●     Prognosis and Prevention of the Disease

One aspect of CCM is to prevent diseases from happening. With the help of AI, practitioners can identify the choric disease to which the patient is susceptible. This allows the doctors to take the correct preventive measures and circumvent the chronic condition.

In a study published by Yannis Paschalidis in Harvard Business Review, healthcare professionals were able to forecast hospitalizations due to diabetes and heart disease a year in advance using machine learning and Electronic Health Records (EHRs) with an accuracy of 82%. 

●     Diagnosis of Diseases

Many recent studies have proved that AI can also be indispensable when it comes to the diagnosis of diseases. Al-algorithms can easily detect diseases based on data points like medical imagery, ECG data, patients’ demography, and their medical history. Such developments have led to time and cost-effective CCM service. It also has significantly improved remote diagnosis.

●     Treatment

The healthcare data can be used to create AI/ML models that can assist physicians in medication modeling and treatment suggestions. These models can be further applied to suggest appropriate dosage and treatment plans for the patient.

A personalized plan and treatment for individual patients can also be created by AI. The personalized treatment can enable clinicians to intervene before a patient’s condition becomes critical, making CCM more effective.

Recently, a company named IBM Watson has achieved some remarkable results by utilizing AI in the field of oncology. The organization performed genetic data analysis and was successfully able to identify the rare secondary leukemia caused by myelodysplastic syndromes.

●     Remote Patient Monitoring (RPM)

With an AI-powered CCM, healthcare professionals can constantly monitor a patient’s vitals like blood pressure, pulse rate, temperatures, etc., from the comfort of their home. The AI can also send an alert to health professionals if there is any sudden or critical change in the vitals of a patient.

●     Virtual Assistant

Chronic diseases generally last for a lifetime. As the patient gets older, it gets difficult for them to keep track of medication and appointments, which causes disturbance in their chronic care management. In such cases, an AI-powered virtual assistant can come in handy for the patient. It can assist them by ensuring drug adherence and also monitor their vital data.

For example, a Meditech company created AI-embed nurse avatars that send notifications to the patient each morning for a check-in routine, record their vitals, and sends alerts for timely intake of medicine.

Another aspect of chronic care management is measuring and managing the patient’s chronic pain. Here again, AI can assist in detecting chronic pain by monitoring the facial muscle movements of patients who are unable to self-report the pain to their physicians.

Conclusion

Artificial Intelligence can offer actionable insights to guide clinical decisions and allow physicians to diagnose, treat and handle chronic conditions remotely, thus making chronic care management more efficient, accessible, and affordable.

That’s why many healthcare organizations have begun to utilize AI in their chronic care management services. If you are also looking to leverage AI to improve your chronic care management, you will need to hire or work with people who have relevant expertise and skill set.

Mindfire Solutions is an IT-service provider that has worked with several healthcare organizations over the years to provide customized healthcare tech solutions that are highly cost-effective, secure, and scalable. Visit Mindfire Solutions to learn more about us.

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Vulnerabilities of IoMT

Top 6 Vulnerabilities of IoMT devices to look out for

The internet of medical things (IoMT) is an innovative solution transforming the healthcare industry. With IoMT, healthcare providers can gather data from various medical devices and create a comprehensive view of a patient’s health. The solution enables healthcare professionals to offer more proactive patient care and better treatment outcomes while reducing expenses.

That’s why many healthcare providers are keen on leveraging the internet of medical things. In 2020, as the pandemic caused global turmoil and remote solutions became a necessity, the global market capitalization for the internet of medical things (IoMT) reached a value of USD 41.7 billion.

By the time 2028 arrives, the global internet of medical things (IoMT) market size is projected to be worth USD 187.6 billion, growing at a CAGR of 29.5%.

While there are several benefits of utilizing the IoMT, there are also certain risks associated with the technology. In this blog, we will bring forward some of the vulnerabilities of IoMT.   

Vulnerabilities of IoMT

Here are some of the major vulnerabilities of IoMT:

Multiple Entry Points

The interconnectedness of medical devices makes IoMT a groundbreaking solution for healthcare; however, it also makes systems more vulnerable to cyberattacks. Medical devices are difficult to patch. As the number of devices and sensors increases, the possible entry points for attacks also increase. Even a single point of a breach can be catastrophic for the entire system.

That’s why it becomes essential to deploy anti-malware mechanisms to ensure that devices are not susceptible to attacks.

Privacy and Security Issues

IoMT systems gather large amounts of data from patients. This data is often sensitive, and if it falls into the wrong hands, it could be used for malicious purposes. For example,  passive attacks such as traffic analysis can allow attackers to gather confidential information on patients like their medical conditions, medications, and treatments.

Active attacks are also possible. For example, an attacker could use a denial-of-service (DoS) attack to disable a device or system, preventing it from being used. Such incidents can cause serious consequences for patients who rely on the device or system for care.

To protect patient privacy and security, healthcare organizations must implement strong security measures like encryption of stored data and data-in-transit.  

Poor Authentication

Most healthcare devices are not equipped with proper authentication mechanisms. Research that aimed to understand the vulnerabilities of IoMT devices observed that many healthcare organizations adhered to default passwords and settings, which were available on the manual online. 

This makes it easy for unauthorized individuals to access the network and tamper with it. In such cases, cybercriminals can remotely take control of devices and use them to carry out hostile activities.

Therefore, your organization should have security protocols such as Multi-Factor Authentication in place to improve the safety of IoMT devices.

Unsecured Internet Connection 

Usually, healthcare enterprises run IoMT systems on the same network which is used for managing their infrastructure. This not only poses a threat to your IoMT system but also to your entire organization’s infrastructure.

Hence, it is advisable to segment the company’s network. Operate IoMT devices on a separate network. This way, even if there is any breach, the damage will be limited to a small portion of your entire network, which can be countered quickly.

Lack of Visibility 

Another major issue with IoMT is the lack of visibility into the network. With so many devices and sensors collecting data, it becomes difficult to track all the activity occurring within the system. According to a study, about 80% of IoMT devices are used frequently in a month. Therefore, it is difficult for the IT team to identify anomalies and potential threats.

Outdated Systems

A study has shown that many healthcare organizations leveraging IoMT are still using outdated versions of operating systems that are not designed to deal with modern cybersecurity threats. This leaves systems vulnerable to sophisticated attacks that can easily bypass traditional security measures.

Even if the organization is up to date with its operating systems, it is equally important to update the devices in the IoMT system regularly. 

Conclusion

IoMT systems offer several transformational benefits to the healthcare organization. However, healthcare providers also need to be aware of these vulnerabilities and take steps to mitigate them.

One of the ways to secure your IoMT system is to conduct risk assessments, implement security measures, and keep up with the latest trends in cybersecurity. By doing so, you can ensure that your IoMT system is protected and can be used to improve patient care.

As testing any system can be an overwhelming task, you can also collaborate with an experienced IT service provider to reduce the workload.

Mindfire Solutions is one of the leading agencies in the IT sector that has assisted several world-renowned organizations with IoT Testing. With our team of industry experts, we offer solutions that are tailored to your organization. If you are also looking to test your IoT or IoMT system, visit Mindfire Solutions to learn more about our services.

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AI for healthcare

How Do AI Applications Improve Healthcare And Wellness?

The COVID-19 pandemic overwhelmed the existing healthcare infrastructure. It has been a rude reality check for clinical administrators worldwide. Now, as the contagion subsumes, the persisting rise in the global burden for non-communicable ailments like lifestyle disorders is likely to keep medical practitioners on their toes in the days ahead. With this, the demand for preventive measures is increasing. By using AI for healthcare, we may step ahead in this crisis.

A Looming Crisis In Healthcare

Today, the demand for preventative intervention is skyrocketing. But limited growth in clinical ranks indicates an ever-widening talent gap with cascading implications. WHO assessed a projected shortfall of 18 million healthcare workers by 2030. This gap is likely to be manifested primarily in low and lower-middle-income geographies. Medvocation, in one of its recent studies, found that nearly 44% of doctors worldwide are already breaking under the immense workload and are unable to live happy and healthy lives.

The existing state of affairs can portend a crippling impediment as the global population ages. Reactive healthcare becoming more costly adds to the worries of the patients and clinical professionals.

AI For Healthcare: Reimagining Wellbeing

Fortunately, advancements in data-driven technologies like AI and machine learning have brought preventive medicine much closer to high-risk and healthy individuals. It has improved the possibilities of self-care and wellness like never before. For instance, today, AI applications can monitor every heartbeat and predict congestive heart failure (CHF) with remarkable accuracy. It permits the prospective patient a significant head start in seeking expert advice long before ending up on a gurney in an ICU.

Due to this the global market for intelligent self-care medical devices ($13 billion in 2020) is expected to reach a valuation of more than $30 billion by 2027, with a CAGR of over 8%.  

AI in Medicine: A Comprehensive Approach

For some years, AI-powered applications have made significant inroads across various clinical procedures and treatments, from automating medical front desk services, drug repurposing, vaccine development, building Smart EHR systems, and improving pathology to successfully predicting drug reactions. Today, at least 90% of healthcare establishments have an AI strategy. Indeed the benefits are substantial as cognitive computing allows practitioners to delegate repetitive tasks like clinical data extraction, assimilation, and report creation to the machines. Effectively AI for healthcare professionals can help with better decisions and focus on what they do best: care for their patients. 

However, the role of AI on the demand side of the story is equally spectacular! Proper self-care, yet elusive, is now feasible as wearable devices embedded with machine intelligence enable individuals to listen to their vital signs better. As algorithms operating on the edge get more intelligent and more emphatic, they will only expand the chances of proactively and precisely diagnosing physiological parameters and assessing the likelihood of acute events for individuals with chronic conditions. It, in turn, will preempt health risks, transform clinical deliveries and ease the pressure on the existing medical infrastructure worldwide.

Factors Fueling The Influx Of AI For Healthcare

The trend is in no way isolated and wholly synced with the cognitive technology maturity curve. Several factors advocate making personal devices like Blood Glucose monitors, Insulin Pumps, Sleep Apnea Devices, Blood Pressure Monitors, and Smart Watches intelligent enough to improve self-care and wellness for their owners. None is more telling than the dichotomy that although there has been an explosive growth of health data collected institutionally in recent years, it may still fall short in enabling patient outcomes.

For instance, an asthma patient typically visits the physician every three months and spends over 2,100 hours in between when the symptoms are not actively monitored, undermining realistic assessment. Now, data continuously ingested through smart devices can bridge this gap. Other factors include:

– Advancement in cloud computing: 

The computational power available for training AI models and algorithms has grown exponentially in recent years with the GPU revolution. Today, with easy access to bare metal servers from cloud infrastructure providers, it is easy to configure systems for running high-performance healthcare workloads.

– Development of Deep Neural Networks: 

The development of Artificial Neural Networks today is supplementing ML capabilities, providing for much better and more precise modeling. ML procedures like Capsule Neural Networks and Transfer Learning can transform how ML models are built and deployed, leading to far more accurate predictions even when trained with limited datasets. It will indeed make self-care medical devices smarter and more cost-effective.

– Shift in the healthcare delivery philosophy: 

As AI systems become more readily available, institutions worldwide are unmistakably considering how care is delivered and how precious healthcare resources and infrastructure are utilized. For instance, the National Institute of Health in the United Kingdom has launched an initiative to encourage the use of AI for healthcare of individuals to self-diagnose the onset of chronic conditions. The broader objective is to eliminate unnecessary outpatient visits and save operating costs, optimizing the resources available to the frontline care workers.

AI In Self-care: Use Cases

This research paper published by Nature.com manifests the overall apprehensions of patients around the role of AI in healthcare. However, advancements in cognitive technologies can bring in early and reliable insights and even formulate an effective response to some of the most prevalent chronic health conditions worldwide. These includes: 

– Diabetes: 

While the retroactive insights on blood sugar levels are currently derived from lab tests like A1C and self-service glucometer readings, AI-enabled devices can completely upend the diabetes treatment pathway. Intelligent insulin pumps can monitor blood glucose levels and other health metrics in real-time and auto-administer appropriate insulin doses based on the patient’s health condition and symptoms.

– Hypertension: 

Collecting blood pressure readings periodically through cuff-based devices is only half the game, pending further diagnosis. However, with Smart wearable devices connected to the cloud, blood pressure data can be assimilated with multimodal data sets like genomics and behavioral to pinpoint anomalies and preempt acute instances.

– Asthma:  

Asthma patients must regularly visit clinics for pulmonary function tests. They are monitored for environmental variables like air quality and moisture profile that can adversely impact their health. AI algorithms can extrapolate heart rate and blood oxygen level data from pulse oxymeters. Utilizing other pointers like pathophysiological analysis, natural history, seasonality, phenotypes, genetics, environmental monitoring, disease biomarkers, etc., AI predicts the possibilities of an asthma attack.

– Congestive Heart Failure (CHF): 

Conventional detection for CHF is done through a clinical diagnosis like ECG and studying factors like hereditary prevalence and lifestyle choices. Nevertheless, AI algorithms can accurately predict heart health through raw electrocardiograms to predict the possibilities of CHF, almost with 100% accuracy.

– Depression: 

Screening for mental health conditions depends on subjective evaluations to detect the root cause and respond to symptoms. However, AI algorithms can eliminate this subjectivity and clinical bias from the equation by evaluating symptoms through facial expressions, voice patterns, and online habits. Moreover, they can objectively assess treatment progress by interpreting brainwave profiles unique to patients with depression.

Final Thoughts

Bringing AI to improve the state of self-care and wellness is an idea whose time has come. Cognitive technologies can play a pivotal role in preventing catastrophic health events and saving lives. However, considering the wide range of variables and the risks involved, expert implementation becomes as crucial as the technology to ensure the first-time-right outcomes. Therefore alongside investment in technology, it becomes a strategic necessity to find an experienced technology partner who can aptly demonstrate the viability of self-care through AI.

Mindfire Solutions is one such leader in AI/ML, well-acclaimed in the global health tech market. Get in touch with one of their AI consultants to discover how the company simplifies self-care and wellness for millions worldwide.

 

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wellness solutions

Wellness Industry Heading for a Digital Future

Introduction:

Digitization, the buzzword of the 21st century, is sweeping across sectors, the wellness industry is no different. Valued at USD 1.5 trillion in 2021, the industry is heading towards a digital future accelerated by a once-in-a-century pandemic. After the initial setback due to the pandemic, the wellness industry is slowly pivoting back to normalcy.

Emerging technologies and new apps coupled with changes in customer behavior have ensured that the wellness industry is well on its path to embracing digital solutions to meet the demands of new-age consumers.

Digital wellness solutions Making Inroads in the Wellness Industry

The last few years have seen digitization becoming a part of the industry, making its presence felt in multiple aspects of healthcare and wellness. Some of the most notable ones are:

1. A Rise in the Usage of Wearable Devices

A boom in fitness trends has accelerated the demand for wearable devices. Smartwatches, fitness trackers, and smart jewelry have become a part of an individual’s wardrobe and accessory.

A fitness-conscious population coupled with an increasing prevalence of chronic diseases has contributed to the surge of wearable devices. Providing real-time information on the user’s overall well-being, these devices have found an increased adoption among the masses.

No wonder the global wearable technology market pegged at USD 40.64 billion in 2020 is expected to grow at a CAGR of 13.8% from 2021 to 2028.

The growing popularity of IoT-connected devices, increase in smartphone penetration, and positive growth prospects of next-generation displays will further fuel the growth of wearable devices and make them an integral part of an individual’s lifestyle.

Leading fitness players are also leveraging advanced machine learning algorithms to harness data-mined insights that facilitate personalized workout and diet plans in line with the individual’s unique health profile and objectives. This has significantly improved the results for many users, driving them to stick to tech-led platforms.

2. Growing Preference for Telehealth

While telehealth always made a strong case, the Covid-19 pandemic accentuated its adoption by leaps and bounds. For instance, while telehealth accounted for less than 5% of India’s overall healthcare IT market before Covid-19, it rose to 47% during the pandemic. Also, earlier there were no proper guidelines on telehealth. The pandemic changed the situation drastically forcing the Government to come out with definitive guidelines.

Globally, there has been a marked increase in the downloads of different telehealth apps. For example, the patient companion app for Intouch health had around 2300 downloads in 2019 but over 22,300 in Q2, 2020 – an increase of around 870%. Similarly, Medispourt’s V2MD app increased from 50 in 2019 to around 4100 in Q2, 2020, an increase of 8270%.

Even otherwise, the multiple benefits that telehealth brings to the table are accelerating people towards adopting this mode of consultation with doctors and caregivers.

The fact that telehealth gives all individuals the opportunity to access quality healthcare irrespective of their background is catalyzing its growth. Also, by making digital solutions more inclusive, healthcare companies are reaching out to individuals at remote places with limited mobility. It helps to provide them the much-needed care they have been deprived of for years.

3. Rising Importance and Adoption of Digital Health Coaching

Delivering personalized, insight-driven programs and wellness solutions to help individuals better focus on their health and well-being, digital health coaching has come a long way. It’s not only individuals who are embracing digital health coaching.

Even companies are embracing health coaching. They are recognizing the strategic business advantage they have with a physically and emotionally healthy workforce. With employee health care costs skyrocketing, many employers are feeling the pinch. In addition to low productivity, many are experiencing higher rates of absenteeism and a decline in organizational morale.

To solve this problem, they are turning to health solutions like digital coaching. These not only improve the health of their employees but also positively affect their total business environment. Digital coaching helps to create personalized interactions with the use of intelligent technologies, behavioral science models and theories.

Through digital coaching, new-age players are allowing people to follow their own fitness and overall well-being regimes under the guidance of a virtual trainer. The fact that it is low cost and can be deployed across the population is further fuelling its adoption among organizations and individuals.

4. Digital Wellness Solutions for Holistic Healthcare

Today people realize the essence of mental, emotional, and psychological well-being. This goes beyond physical workouts. The definition of wellness has expanded manifold, more so since the pandemic. Today it includes healthy eating, good sleep, striking a balance between work and life, and being mindful, among others.

With an increasing number of people taking a holistic approach to wellness, there has been a surge in meditation and mindfulness apps. These apps provide an enjoyable experience with readily-available and potentially life-changing solutions which otherwise are difficult to access.

Also, more and more people are looking for online offerings of different workouts such as Zumba and yoga. This is driving players in the wellness segment to embrace digitization and offer these workout sessions in real-time.

Benefits of Digitization for the Industry:

For the industry, digitization entails multiple benefits such as:

  • Personalization: An overwhelming majority of people are willing to trade privacy for personalization particularly in Brazil and China. This has allowed enterprises to hyper target consumers with personalized products and offerings.
  • Faster service delivery and greater customer engagement: Due to COVID-19, the shift to digital channels has happened at a rapid pace. Some product categories like food, skincare may still be sold through traditional brick and mortar stores, wearable’s categories have moved to complete online models. Hence, companies are creating omni channel digital offerings for wellness solutions to engage with customers.
  • Blurring category lines: Consumers nowadays look for wellness solutions across multiple channels and categories. They don’t want a single brand for all wellness related needs. Companies are now building complementary solutions to their core business offerings.
  • Higher Operational efficiency

Final Thoughts:

Digital tech will play an important role in helping people stay fit and healthy not just today but also in a hybrid, post-pandemic future.

A tech-savvy population coupled with growing awareness for one’s well-being will further tilt the scales towards digitization for wellness players. It’s high time for them to be digital-ready to increase their clientele and enhance revenues.

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Like other businesses, if you too are looking for wellness solutions Mindfire Solutions can be your partner of choice. We have a team of highly skilled and certified software professionals, who have developed many custom solutions for our global clients over the years.

Here are a few interesting projects we have done. Click to know more:

App to assist Diet Management Planner and Weight Loss

Fitbit Integration with Healthcare Application

Platform for Wellness Influencers

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