Tag Archive for: AI and healthcare

How Machine Learning Can Help Improve Blood Pressure Treatment

New research shows how a machine-learning technique could provide insight into how to find the patients that would benefit the most from treatment for hypertension.

The study, which came out of UCLA, describes how a machine-learning technique known as “casual forest” could determine the hypertension patients that would benefit the most from treatment rather than assuming that the highest-risk patients require the most clinical attention.

According to the Centers for Disease Control and Prevention (CDC), over 670,000 deaths in the US can be attributed annually to hypertension. In addition, while about 47 percent of US adults have hypertension, only 24 percent of this population has the condition under control.

Traditionally, clinicians treating patients with high blood pressure focus on those with the highest risk of poor outcomes, as the assumption is that they will require the highest level of treatment. The researchers set out to see if they could leverage AI to treat patients based on benefit rather than risk for improved outcomes. They found their solution in a new ML technique, coined “casual forest.”

The study included data from 10,672 participants, all of whom were randomized to systolic blood pressure (SBP) targets of either less than 120 mmHg or less than 140 mmHg from two randomized controlled trials.

The researchers used the casual forest technique to create a prediction model of individualized treatment effects related to the control of SBP and its correlation with reductions in adverse cardiovascular outcomes after three years.

They found that 78.9 percent of individuals with an SBP greater than 130 mmHg achieved benefits from intensive SBP control.

“We found that a substantial number of individuals without hypertension benefited from lowering their blood pressure,” said lead author Kosuke Inoue, MD, Ph.D., who undertook the study while an epidemiology graduate student at the UCLA Fielding School of Public Health and is now an associate professor of social epidemiology at Kyoto University, in a press release. “By applying the causal forest method, we found that treating individuals with high estimated benefits provided better population health outcomes than the traditional high-risk approach.”

Further, the researchers noted that high-benefit approaches could increase the efficacy associated with treatment, potentially being more reliable compared to high-risk approaches.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

As the UCLA researchers have discovered, improving disease detection and making better decisions on the allocation of medical resources is an area where AI and machine learning are making a huge impact in healthcare.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve treatment and medical outcomes. In fact, it was my father’s own battle with and eventual death from lung disease that set me on my path to finding ways to use AI to provide earlier detection of serious medical conditions.

In fact, we have launched an AI Studio specifically for US-based Healthcare startups with AI centricity. Our mission is to help AI startups scale and gear up to stay one step ahead of the pack and emerge as winners in their respective domains.

AI Startups face numerous challenges when it comes to demonstrating their value proposition, particularly when it comes to advanced AI solutions for pharma and healthcare. We have taken an award-winning and unique approach to incubating and facilitating startups that allow the R&D team and stakeholders to efficiently collaborate and craft the process to best suit actual ongoing needs, which leads to a faster, more accurate output.

We provide:

  • Access to a top-level talent pool, including business executives, developers, data scientists, and data engineers.
  • Assistance in the development and testing of the MVP, Prototypes, and POCs.
  • Professional services for implementation and support of Pilot projects
  • Sales and Marketing support and potential client introductions.
  • Access to private capital sources.

BigRio excels in overcoming such initial hurdles, which present nearly insurmountable obstacles to a startup operation.

You can read much more about how AI is redefining healthcare delivery and drug discovery in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI and machine learning are being used to improve healthcare delivery at every touchpoint.

Rohit Mahajan is a Managing Partner with BigRio. He has particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

Canadian Lab is Using AI to Better Detect Breast Cancer!

AI has been improving healthcare in many areas, but perhaps one of the disciplines where it is making the largest difference is medical imaging. AI’s ability to detect anomalies in medical images such as x-rays and MRIs that are imperceptible to the human eye are vastly improving the diagnostic capabilities of such imaging technologies.

Now, a Canadian lab has announced that it is using AI to improve breast cancer screenings. A lab out of Waterloo, Ont., is taking breast cancer research to new heights by working to help patients get the most beneficial treatment with AI-enhanced imaging technology.

When patients get breast cancer, they typically undergo a type of imaging, like an MRI, to look for cancerous tumors. The Waterloo lab has created “a synthetic correlate diffusion” MRI that is tailored to capture details and properties of cancer in a way that previous MRI systems couldn’t.

“It could be a very helpful tool to help oncologists and medical doctors to be able to identify and personalize the type of treatment that a cancer patient gets,” Alexander Wong, professor and Canada Research Chair in Artificial Intelligence and Medical Imaging at the University of Waterloo told Canadian news outlet the Global News.

Using “synthetic correlate diffusion imagining data,” the new AI-driven technology predicts whether a patient is likely to benefit from neoadjuvant chemotherapy – or chemotherapy that occurs before surgery, according to Wong.

Though the hardware of the actual MRI machine hasn’t changed in this model, what has altered is the way the technology sends “pulses” through the patient’s body and how it collects data, Wong noted.

“The cancer itself just lights up and really shows the different nuances and characteristics around it, which makes it very much easier to identify not only where the cancer is, the size of the cancer, but also the actual tissue characteristics of the cancer to help doctors make better decisions,” he said.

The AI can then analyze the MRI data to help learn whether breast cancer patients could benefit from chemotherapy before surgery in their treatment process.

“It’s essentially the combination of two types of technologies. One is the new MRI imaging technology to really capture the right information. The other is the AI advancement in terms of a deep neural network.”

Deep neural networks are able to continue improving as more information is captured, said Wong.

“The more examples it sees, the better it gets at really identifying these subtle patterns that differentiate from one another. As we train it with more and more data, it’s able to have higher levels of predictive accuracy,” he said.

As to how accurate the AI algorithm is, in a study of nearly 300 patients, Wong said, “The AI, when using our new form of MRI, was able to identify and predict with over 87 percent accuracy which patients would benefit from chemotherapy.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

This new research into improved breast cancer screenings is just one of the many studies that are proving the powerful predictive power of AI and how it can be leveraged to better treat and even prevent injuries and disease.

In fact, improving disease detection and diagnostics is the area where AI is making one of the technology’s biggest impacts.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve diagnostics.

In fact, we have launched an AI Studio specifically for US-based Healthcare startups with AI centricity. Our mission is to help AI startups scale and gear up to stay one step ahead of the pack and emerge as winners in their respective domains.

AI Startups face numerous challenges when it comes to demonstrating their value proposition, particularly when it comes to advanced AI solutions for pharma and healthcare. We have taken an award-winning and unique approach to incubating and facilitating startups that allow the R&D team and stakeholders to efficiently collaborate and craft the process to best suit actual ongoing needs, which leads to a faster, more accurate output.

We provide:

  • Access to a top-level talent pool, including business executives, developers, data scientists, and data engineers.
  • Assistance in the development and testing of the MVP, Prototypes, and POCs.
  • Professional services for implementation and support of Pilot projects
  • Sales and Marketing support and potential client introductions.
  • Access to private capital sources.

BigRio excels in overcoming such initial hurdles, which present nearly insurmountable obstacles to a startup operation.

You can read much more about how AI is redefining healthcare delivery and drug discovery in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI and machine learning are being used to improve healthcare delivery at every touchpoint.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

Can AI Be Used to Predict Suicide Risk?

There has been no lack of news about how AI is redefining healthcare and improving patient outcomes for physical ailments. There has not been that much news, however, on how AI can help in the treatment of emotional or mental disorders.

Until now.

Researchers have just released the results of a study in which they used AI to better predict suicide risk.

The scientists from Worcester Polytechnic Institute (WPI) and Harvard Medical School-affiliated McLean Hospital in Belmont conducted a study assessing the use of AI to predict and gain a better understanding of suicide and the mechanisms and emotional states that drive self-injury.

This particular study targeted women because, according to the CDC, death by suicide is increasing at an alarming rate among women. The group of researchers developed an algorithm that was designed to predict suicide attempts among participants and identify subgroups of patients who were at the highest risk of entering a suicidal mindset.

They then used AI approaches to cluster data to expose any existing patterns. The patterns revealed a broad set of dissociative symptoms, such as the lack of connection between one’s sense of self and the environment. This was often due to trauma, the researchers said.

Following this step, researchers trained an algorithm to distinguish between patients with various dissociation levels and the 30 healthy controls. They found that this tool could zero in on specific dissociative symptoms, predicting previous suicide attempts with an accuracy of nearly 90% percent.

Aside from AI being able to predict thoughts of self-harm and previous suicide attempts accurately, researchers also noted that the study emphasized the need for clinicians to assess patients for dissociative disorder symptoms.

“We’re trying to say that among these hundreds of symptoms and indicators, our results suggest these two or three symptoms may be helpful to focus in on,” said Dmitry Korkin, Ph.D., the Harold L. Jurist ’61 and Heather E. Jurist Dean’s Professor of Computer Science at WPI, one of the lead researchers on the project.

The key takeaway from this study is that it is one of the first to show that AI-driven programs can give clinicians predictive and theoretically preventive tools for mental illnesses, just as they are already doing in practice for many physical disorders.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

The WPI research is one of the few studies that are now showing that AI has predictive value in mental health, just as it has already been put into practice in improving physical conditions. In fact, improving disease detection and diagnostics – whether that be physical, and now we see mental health — is the area where AI is making one of the technology’s biggest impacts.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve diagnostics.

In fact, we have launched an AI Studio specifically for US-based Healthcare startups with AI centricity. Our mission is to help AI startups scale and gear up to stay one step ahead of the pack and emerge as winners in their respective domains.

AI Startups face numerous challenges when it comes to demonstrating their value proposition, particularly when it comes to advanced AI solutions for pharma and healthcare. We have taken an award-winning and unique approach to incubating and facilitating startups that allow the R&D team and stakeholders to efficiently collaborate and craft the process to best suit actual ongoing needs, which leads to a faster, more accurate output.

We provide:

• Access to a top-level talent pool, including business executives, developers, data scientists, and data engineers.

• Assistance in the development and testing of the MVP, Prototypes, and POCs.

• Professional services for implementation and support of Pilot projects

• Sales and Marketing support and potential client introductions.

• Access to private capital sources.

BigRio excels in overcoming such initial hurdles, which present nearly insurmountable obstacles to a startup operation.

You can read much more about how AI is redefining healthcare delivery and drug discovery in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI and machine learning are being used to improve healthcare delivery at every touchpoint.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

Artificial Intelligence Could Save the Healthcare Industry Billions!

A report by Harvard University researchers has found that large-scale adoption of AI could save the American healthcare system nearly $400 billion annually.

The improvements that AI implementation in hospitals and other medical facilities can accomplish for patient care are becoming fairly well known. A little less obvious is the impact that AI can have on skyrocketing health costs.

Joint researchers with McKinsey & Company and Harvard University have found that widespread adoption of artificial intelligence in healthcare could save the US up to $360 billion annually.

For various reasons, the healthcare industry has a relatively low adoption of AI-based tools despite the benefits discovered by researchers and early adopters. In the new paper, researchers estimate that the broader adoption of AI in the healthcare industry could lead to savings in the range of 5% to 10% in healthcare spending, or between approximately $200 billion and $360 billion per year. Their estimates are based on AI use cases utilizing current technologies that are achievable within the next five years, without compromising quality or access.

The researchers say that hospitals could see cost savings mainly through improved clinical operations, quality, and safety – such as optimizing operating rooms or identifying adverse events. Physician groups can experience similar benefits by leveraging AI for continuity of care, such as referral management.

Similar savings could be experienced by health insurers as AI solutions can streamline their operations and work to reduce waste and fraud. The researchers concluded that insurance providers could experience savings from AI solutions that improve claims management, such as automating prior authorization, along with those that can enhance healthcare and provider relationship management, including preventing readmissions and provider directory management.

Based on AI-driven use cases, the researchers claim that private payers could save approximately 7% to 9% of their total costs, or between $80 billion and $110 billion annually, all within the next five years. Physician groups could save 3% to 8% of their costs, translating into savings of between $20 billion and $60 billion.

How BigRio Helps Facilitate Advancement in Healthcare AI

At BigRio, we understand how AI is changing the very nature of healthcare delivery in America, which is why our premier mission is to partner with startups to develop healthcare initiatives with AI at the core of their solutions.

In fact, we have launched an AI Studio specifically for US-based Healthcare startups with AI centricity. Our mission is to help AI startups scale and gear up to stay one step ahead of the pack and emerge as winners in their respective domains.

AI Startups face numerous challenges when it comes to demonstrating their value proposition, particularly when it comes to advanced AI solutions for pharma and healthcare. We have taken an award-winning and unique approach to incubating and facilitating startups that allow the R&D team and stakeholders to efficiently collaborate and craft the process to best suit actual ongoing needs, which leads to a faster, more accurate output.

We provide:

• Access to a top-level talent pool, including business executives, developers, data scientists, and data engineers.

• Assistance in the development and testing of the MVP, Prototypes, and POCs.

• Professional services for implementation and support of Pilot projects

• Sales and Marketing support and potential client introductions.

• Access to private capital sources.

BigRio excels in overcoming such initial hurdles, which present nearly insurmountable obstacles to a startup operation.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

Researchers Combine AI and the Internet of Things to Track Progression of Movement Disorders

Researchers have combined wearable “Fitbit”-type technology with AI to better track and monitor movement disorders.

In two ground-breaking studies, published in Nature Medicine, a cross-disciplinary team of AI and clinical researchers have shown that by combining human movement data gathered from wearable tech with a powerful new medical AI technology, they are able to identify clear movement patterns, predict future disease progression and significantly increase the efficiency of clinical trials in two very different rare disorders, Duchenne muscular dystrophy (DMD) and Friedreich’s ataxia (FA).

DMD and FA are rare, degenerative genetic diseases that affect movement and eventually lead to paralysis. There are currently no cures for either disease, but researchers hope that these results will significantly speed up the search for new treatments.

Scientists hope that, as well as using the technology to monitor patients in clinical trials; it could also one day be used to monitor or diagnose a range of common diseases that affect movement behavior, such as dementia, stroke, and orthopedic conditions.

Senior and corresponding author of both papers, Professor Aldo Faisal, from Imperial College London’s Departments of Bioengineering and Computing, who is also Director of the UKRI Center for Doctoral Training in AI for Healthcare, and the Chair for Digital Health at the University of Bayreuth (Germany), and a UKRI Turing AI Fellowship holder, said, “Our approach gathers huge amounts of data from a person’s full-body movement—more than any neurologist will have the precision or time to observe in a patient.

“Our AI technology builds a digital twin of the patient and allows us to make unprecedented, precise predictions of how an individual patient’s disease will progress.

“We believe that the same AI technology working in two very different diseases shows how promising it is to be applied to many diseases and help us to develop treatments for many more diseases even faster, cheaper, and more precisely.”

AI, Healthcare, and the Internet of Things

These two studies are just another example of how AI is being combined with the Internet of Things (IoT) for advanced diagnostics, earlier detection of disease, and better patient outcomes.

The Internet of Things (IoT), sometimes also referred to as The Internet of Everything (IoE), is a term used to describe the network of physical objects that we know as the “smart things” which are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet.

In terms of healthcare, it can readily be seen how IoT allows for the interactivity between bedside monitors, smartwatches, fitness trackers, implanted medical devices, and any other “thing” that transmits or receives a signal containing pertinent medical data that can then be accessed or stored from or to anywhere.

In broad terms, IoT is changing the very nature of data acquisition and data analytics as they are applied to healthcare, transforming both into something far deeper and more powerful.

Traditionally, healthcare organizations currently base most of their clinical and financial analytics on conventional data sources like EHRs, insurance claims data, and lab results. But now, thanks to the Internet of Things, they are starting to integrate behavioral data from clients’ credit cards or fitness data from health trackers and smartphone data, including searches for health topics and likes on social media.

Add to that all of the “things” such as remote monitoring from internet-connected prescription bottles, Bluetooth-connected scales, or wearable devices such as in Professor Faisal’s studies, – and it is easy to see how IoT is bringing a vastness and richness of data to healthcare that was never before possible and can improve patient care across the board.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

Like the muscle movement studies, leveraging IoT solutions for medical applications is an area where AI is making one of the technology’s biggest impacts in healthcare.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI and IoT tech to improve healthcare delivery and drug discovery. In fact, we have launched an AI Studio specifically for US-based Healthcare startups with AI centricity. Our mission is to help AI startups scale and gear up to stay one step ahead of the pack and emerge as winners in their respective domains.

AI Startups face numerous challenges when it comes to demonstrating their value proposition, particularly when it comes to advanced AI solutions for pharma and healthcare. We have taken an award-winning and unique approach to incubating and facilitating startups that allow the R&D team and stakeholders to efficiently collaborate and craft the process to best suit actual ongoing needs, which leads to a faster, more accurate output.

We provide:
• Access to a top-level talent pool, including business executives, developers, data scientists, and data engineers.
• Assistance in the development and testing of the MVP, Prototypes, and POCs.
• Professional services for implementation and support of Pilot projects
• Sales and Marketing support and potential client introductions.
• Access to private capital sources.

BigRio excels in overcoming such initial hurdles, which present nearly insurmountable obstacles to a startup operation.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

Microsoft Partners to Develop AI-Based Healthcare Services

Tech giant Microsoft is partnering with Vietnam-based AI conglomerate VinBrain to develop artificial intelligence-based healthcare services.

Under the collaboration, the two companies will work together to work on three areas of healthcare AI — data sharing, cross-product validation, and research and development, according to a recent press release from VinBrain.

VinBrain will also use Microsoft’s Azure Cognitive Services for computer vision to validate new deep-learning models.

The aim of the partnership is to accelerate the development of AI products in the health technology space. According to VinBrain, the AI platform runs on a dataset of over 2 million images sourced from multiple regions – the United States, Asia, and Europe. These data will be shared via Microsoft Azure, which will also ensure privacy and security, manage ever-changing compliance regulations, and improve data governance.

As part of the collaboration, VinBrain will also use Azure Cognitive Services for Computer Vision to validate new deep-learning models, including Microsoft’s latest computer vision model called Florence.

Accroding to the two companies the goal of the collaboration is to leverage AI to be applied to improve medical services in remote areas where there are limited medical facilities. “On the social aspect, this will help speed up the process of resolving [the] increasing number of healthcare issues with a lack of infrastructure, uneven doctor-to-patient ratio, and increased demand for healthcare services,” they said in a joint statement.

For VinBrain CEO Steven Truong, this partnership will deepen the company’s focus on and boost its development of AI products in the health technology space. “Using the latest foundation of AI technology and evaluation, this collaboration with Microsoft will directly impact billions of people through early [disease] detection and workflow productivity,” he added.

Perhaps equally important, the partnership, the first between Microsoft and a major player in the AI space from Vietnam is seen to open up opportunities for Microsoft to expand its presence in Southeast Asia’s healthcare scene.

 

How BigRio Helps Facilitate Investment in AI Startups

Much like the collaboration between Microsoft and VinBrain, BigRio is partnering with startups to develop healthcare initiatives with AI at the core of their solutions.

In fact, we have launched an AI Studio specifically for US-based Healthcare startups with AI centricity. Our mission is to help AI startups scale and gear up to stay one step ahead of the pack and emerge as winners in their respective domains.

AI Startups face numerous challenges when it comes to demonstrating their value proposition, particularly when it comes to advanced AI solutions for pharma and healthcare. We have taken an award-winning and unique approach to incubating and facilitating startups that allow the R&D team and stakeholders to efficiently collaborate and craft the process to best suit actual ongoing needs, which leads to a faster, more accurate output.

We provide:
• Access to a top-level talent pool, including business executives, developers, data scientists, and data engineers.
• Assistance in the development and testing of the MVP, Prototypes, and POCs.
• Professional services for implementation and support of Pilot projects
• Sales and Marketing support and potential client introductions.
• Access to private capital sources.

BigRio excels in overcoming such initial hurdles, which present nearly insurmountable obstacles to a startup operation.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

How Artificial Intelligence Is Improving Telemedicine

Telemedicine or telehealth services were already on the upswing before the arrival of the COVID-19 pandemic. Since the pandemic, as we were forced into quarantine, more patients and many more doctors and healthcare facilities became reliant on telehealth – pushing advancement in telehealth apps. Telemedicine apps needed to become broader, faster, more interactive, more intuitive, and more accurate — a need that was successfully fulfilled by AI.

AI is being increasingly used in telemedicine to allow doctors to make more data-driven, real-time decisions that may improve the patient experience and health outcomes.

According to a study from MIT, 75% of healthcare facilities that utilized AI reported improved capacity to manage illnesses, and 4/5 said that AI aided in reducing employee fatigue. AI in healthcare is a promising strategy for the future of telemedicine applications, given that COVID-19 continues to place a strain on both the volume of patient data analysis and the number of people who need medical attention.

In one example cited in the MIT study, an AI-integrated system was used to help a doctor in India manage his telehealth patient load. The system, which was designed by US-based company Welltok, was able to provide real-time analysis of the doctor’s interactions with patients and make recommendations on how he could improve his care. Telehealth solutions like these lower the burdens on health plans, providers, and employer benefit managers while providing an on-demand customized experience for patients.

According to Welltok, its AI “chatbot” has an accuracy rate of 98 percent and was found to save consumers time by over 60%.

Virtual nursing assistants are another way that AI is being used to deliver improved telehealth services. These assistants use natural language processing (NLP) to understand questions asked by patients and provide answers based on information from their electronic health records.

One example of a virtual nursing assistant is the app NurseWise, which was developed by the American Nurses Association. This app provides nursing advice and guidance to patients 24/hours a day, seven days a week.

Another progressive use of telehealth, also driven by the pandemic, was the increased use of RPM, which stands for remote patient monitoring. RPM is a way to gather and transmit patient health data to medical specialists outside of a doctor’s office or a clinical environment via linked technology. RPM leverages AI and Internet of Things technologies such as the Apple Watch, Google Fit, and other wearables to collect patient information and other vital signs like heart rates, sleep patterns, and physical activity levels.

Thanks to advances in AI, telehealth is becoming more widely available and affordable, making it easier for people to get the care they need without having to ever leave their homes!

How BigRio is Helping to Advance Telehealth

At BigRio, we like to feel that we are doing our part to improve telehealth by using our resources to help existing telemedicine providers and AI startups who are focused on leveraging AI for advanced telehealth applications.

For example, we recently had a client, a tech giant in the healthcare industry known for its telemedicine platform that connects providers, insurers, patients, and innovators to deliver greater access to more affordable, higher quality care. Due to the unprecedented times of the global COVID pandemic, this client needed to strengthen and expand their virtual care platform in order to stay ahead of their competition. We created a proprietary Accelerate Framework in order to meet aggressive deadlines and reduce the risk of market loss. Overall, upon implementation, the client saw three areas of improvement to make their application more competitive for their new market.

1. Improved access and documentation of Patient Care History
2. Migrating data and integrating old data from legacy systems
3. Increasing Security standards and SSO

What we did for them, we could do for you whether you have an existing telehealth application or are in the design and development phase; if you want to learn more about transforming your telehealth offerings, please contact us.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

How AI is Solving Healthcare Administrative Problems

In 2022 readers of these pages saw many reports on the incredible advances AI is creating in diagnostics and patient care. However, there is more to the delivery of healthcare in this country and to improving patient outcomes than direct treatment protocols. As it turns out, AI is tackling those issues as well, solving many of the bottlenecks and other burdens that are placed upon healthcare administration.

“Clinical burnout” is a very real problem among healthcare personnel. Mounds of paperwork and short staff have only increased these pressures in recent years. The more time doctors, nurses, and other clinical staff have to spend on administrative duties, the less time they can spend with patients – overall care at the facility or hospital suffers, and readmission rates increase.

According to the American Academy of Family Physicians, primary care physician appointments take an average of 18 minutes, of which 49% of the time is spent handling electronic health recording.

But a relatively new application of AI in healthcare, known as “computer-assisted physician documentation (CAPD),” can and is changing all of that, so more of the clinician’s time during a visit is spent on patient care and not on administrative tasks.

According to 3M when of the initial implementers of the solutions, “CAPD acts as a scribe and advisor, nudging clinicians with documentation suggestions to make record keeping as thorough as possible. These non-intrusive nudges decrease clinician stress and reinforce accurate billing and reimbursement.”

As AI assists with the capture-to-code process, integrated electronic health record (EHR) systems must work in tandem with cloud-based systems to pass and connect information across departments.

CAPD assistants not only save time but also lower the chances of errors and duplicative work. Information sharing across departments gives transparency to the revenue cycle and provides a complete picture of both the patient story and population health.

“The better the coding is, the better the outcome for the hospital, which enables the hospital to make decisions that will improve their services to patients,” explains Catalin Velescu, 3M area division director of the EMEA region.

How BigRio Helps Facilitate Advancement in Healthcare AI

Like the AI technology being developed and implemented by big IT players such as 3M, BigRio is also helping to foster innovation in AI for healthcare.

In fact, one of our most successful cases was using our resources to create a new cloud-based intuitive model for one of the top 10 EMR/HER providers in the US. The Client realized that their EHR platform needed UI/UX redesign and revision to take advantage of cloud-based integrations and applications. BigRio stepped in to create a modernization roadmap strategy, architecture, execution plan, and prototype to fit the Client’s needs.

We like to think of ourselves as a “Shark Tank for AI.”

If you are familiar with the TV series, then you know that, basically, what they do is hyper-accelerate the most important part of the incubation process – visibility. You can’t get better visibility than getting in front of celebrity investors and a TV audience of millions of viewers. Many entrepreneurs who have appeared on that program – even those who did not get picked up by the sharks – succeeded because others who were interested in their concepts saw them on the show.

At BigRio, we may not have a TV audience, but we can do the same. We have the contacts and the expertise to not only weed out the companies that are not ready, as the sharks on the TV show do but also mentor and get those that we feel are readily noticed by the right people in the biomedical community.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

AI Leverages Nursing Expertise to Improve Patient Outcomes

The know-how and experience of nurses are a critical body of knowledge and expertise about patients and patient care. Wouldn’t it be wonderful if there was a way to pool all of that knowledge into one place for hospitals and health organizations to make better decisions about patients?

There is, and as you might imagine, it involves AI.

Several health systems, led by the Columbia University Irving Medical Center (CUIMC), are testing an AI-driven predictive tool that is attempting to emulate nurses’ seemingly innate ability to pick up cues about patients’ health from subtle changes in behavior and appearance.

According to its developers, CONCERN (COmmunicating Narrative Concerns Entered by RNs) is a predictive tool that extracts nurses’ expert and knowledge-driven behaviors within patient health records and transforms them into observable data that support early prediction of organ failure or other critical conditions in hospitalized patients.

CUIMC is partnering with three hospital systems — Mass General Brigham (MA), Vanderbilt University Medical Center (TN), and Washington University School of Medicine/Barnes-Jewish Hospital (MO) — to test the effectiveness of the CONCERN implementation toolkit, developed to support large-scale adoption of the tool.

This initiative recently received funding from the American Nurses Foundation through the Reimagining Nursing Initiative.

“CONCERN shows what nurses already know: Our risk identification is not simply a subjective clinical hunch,” said Sarah Rossetti, assistant professor of biomedical informatics and nursing at Columbia, in a statement. “We’re demonstrating that nurses have objective, expert-based knowledge that drives their practice, and we’re positioning nurses as knowledge workers with tremendous value to the entire care team.”

Annually, more than 200,000 patients die in US hospitals from cardiac arrest, and over 130,000 patients’ deaths are attributed to sepsis. Many of these deaths could be preventable if patients who are at risk are detected earlier. Prior work from the CONCERN team found that nursing documentation within EHRs contains information that could contribute to early detection and treatment, but these data are not being analyzed and exposed by EHRs to clinicians to initiate interventions quickly enough to save patients.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

Like the CONCERN project, leveraging human expertise and adapting to the predictive power of AI algorithms is an area where AI and machine learning are making one of the technology’s biggest impacts in the healthcare field.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve patient outcomes. In fact, it was my father’s own battle with and eventual death from lung disease that set me on my path to finding ways to use AI to provide earlier detection of serious medical conditions for improved patient care.

Eventually, among our other success stories, we did collaborate with a researcher who is in the process of developing a cognitive digital twin of the human lung. Right now, that technology is being used specifically in the realm of testing inhalers for asthma patients, but like the CONCERN project, it has broader implications for better diagnostics and early interventions to save lives.

We like to think of ourselves as a “Shark Tank for AI.”

If you are familiar with the TV series, then you know that, basically, what they do is hyper-accelerate the most important part of the incubation process – visibility. You can’t get better visibility than getting in front of celebrity investors and a TV audience of millions of viewers. Many entrepreneurs who have appeared on that program – even those who did not get picked up by the sharks – succeeded because others who were interested in their concepts saw them on the show.

At BigRio, we may not have a TV audience, but we can do the same. We have the contacts and the expertise to not only weed out the companies that are not ready, as the sharks on the TV show do but also mentor and get those that we feel are readily noticed by the right people in the biomedical community.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

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