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August, 2023

Digital Healthcare Ecosystem in the USA

August, 2023

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Table of Contents
01  The HealthTech Monthly Roundup

02  Digital Healthcare Ecosystem in USA

03  Will AI Take Over Everything?

04  Applications of Generative AI in Healthcare

05  State of Digital Healthcare in India

News & Events

The Mantra Podcast Season 2

Tune in to the 1st episode of Mantra Podcast Season 2 with Sumit Bhatnagar, CEO of GreenBrilliance, and Shawn Williams, Director of Business Development in the U.S., Mantra Labs.

Watch the full video!

The HealthTech Monthly Roundup

A quick roundup of the month’s latest health tech activity, both in India and globally.

  • What’s Up Wellness, a Gurugram-based firm secured Rs 14 crore in funding. The added capital will be leveraged to expand its team, drive growth and scalability, and facilitate the development of new product offerings.
  • CK Birla Hospital teamed up with Intuitive India to unveil a surgical robot for advanced medical treatment that will support surgery, enabling precision and reducing post-operative complications.
  • Health-tech startup Vital Bio garnered US$48 million in its recent funding round. The additional capital will be infused to further accelerate the development of the VitalOne technology and introduce clinical studies. 
  • Neurowyzr raised additional funding of $2.1 million. The capital acquired will be utilized to expedite product development and to facilitate the company’s expansion in Southeast Asia and India.

Most Innovative Insurtechs of 2023

Read the blog, here. 


Digital Healthcare Ecosystem in the USA

The U.S. has witnessed an incredible transformation in the healthcare landscape in the last few years. From telemedicine and wearable devices to electronic health records and health monitoring apps, digital health solutions are creating a new era of personalized, efficient, and patient-centered care moving towards a value-based experience.

The current scenario: Healthcare Challenges

The latest report released by the Peter G. Foundation states that U.S. per capita healthcare spending is 2 times higher than the average of other wealthy countries. 

However, when it comes to standard health metrics like life expectancy, infant mortality, and unmanaged diabetes, the USA is still way behind. There may be several reasons behind this: 

Fragmented Healthcare System: The US healthcare system is highly fragmented, with multiple private insurers, providers, and government programs. This fragmentation can lead to inefficiencies, lack of coordination in care, and challenges in accessing healthcare services, especially for vulnerable populations.

Lack of Universal Healthcare Coverage: Unlike many other developed countries, the US still needs a universal healthcare system. While efforts have been made to expand access to healthcare through programs like Medicaid and the Affordable Care Act (ACA), millions of Americans remain uninsured or underinsured, leading to delayed or foregone medical care and poorer health outcomes.

Lifestyle and Behavioral Factors: Unhealthy lifestyle choices, such as poor diet, lack of physical activity, smoking, and substance abuse, are prevalent in the US population. These lifestyle factors contribute to chronic health conditions like diabetes, cardiovascular disease, and obesity, impacting life expectancy and overall health.

Overemphasis on Treatment over Prevention: The US healthcare system has historically focused more on acute care and treatment rather than preventive care and public health initiatives. A shift towards a greater emphasis on preventive measures could potentially improve health outcomes and reduce healthcare costs in the long run.

In order to address the above challenges and bridge the existing gap in the ecosystem, technology could give much-needed support to improve customer and provider experience.

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Will AI Takeover Everything?

The term Artificial Intelligence (AI) often sends a ripple of excitement mixed with a dash of fear through society. While some envision a utopian future aided by intelligent machines, others predict an Orwellian nightmare. To unravel this complex web of emotions and demystify the concepts of AI, we must journey into the heart of its two main facets: Artificial Narrow Intelligence (ANI) and Artificial General Intelligence (AGI).

Artificial Narrow Intelligence (ANI)

Artificial Narrow Intelligence refers to AI systems that are designed to perform a specific task. Unlike human intelligence, ANI lacks the ability to understand, learn, or apply knowledge beyond that particular function.

According to a report by Gartner, by 2022, 40% of customer interactions were expected to be handled by AI-driven automation.

Artificial General Intelligence

AGI, on the other hand, refers to machines that possess the ability to understand, learn, and apply knowledge across various domains, much like a human being. AGI is a theoretical concept and doesn’t exist in practice yet.

ANI vs AGI: A Comparative Insight

Feature ANI AGI
Learning Capability Task-Specific Cross-Domain
Existence Present and Functional Theoretical Concept
Usage in Industries Widespread (e.g., Healthcare, Finance) N/A
Potential Risk Limited to Task Failure Hypothetical Existential Risks


In deciphering the complex world of AI, one must appreciate the nuanced differences between ANI and AGI. ANI, with its specificity, has already embedded itself into our daily lives, enriching and optimizing various sectors. It’s a tool, not a threat, serving humanity in ways previously unimaginable.

AGI, though intriguing, remains a conceptual framework without practical implementation. The fear of machines taking over is a narrative woven more from the threads of fiction than the fabric of reality. What we should focus on is the tangible benefits and ethical considerations of the AI technologies currently at our disposal.

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Applications of Generative AI in Healthcare

Artificial intelligence (AI) is transforming the healthcare industry in various ways, from improving diagnosis and treatment to enhancing patient experience and reducing costs. One of the most promising and innovative branches of AI is generative AI. 

Generative AI uses deep learning models, such as generative adversarial networks (GANs) or large language models (LLMs), to learn from extensive data and produce realistic and diverse outputs.

Generative AI has many potential applications in healthcare, such as:

  • Data augmentation: Firms can create synthetic data that can augment the existing data and improve the performance and accuracy of other AI models. For example, creating synthetic medical images that can help train diagnostic or predictive models with more data and diversity. 

American healthcare company, CloudMedX is a computing platform that improves patient outcomes using predictive analytics. It uses AI to collect data and build holistic pictures of individuals and communities. Its single, unified data platform has operational, clinical, and financial functions, meaning healthcare providers can find everything they need in one place. 

The company’s predictive healthcare models can predict disease progression and determine the likelihood that patients may have complications by processing medical data and providing risk assessment scores. 

  • Data privacy: Using generative AI, healthcare companies can create anonymized data to protect patients’ and providers’ privacy and security. For example, synthetic patient records can be used for research or analysis without revealing actual patients’ identities or sensitive information.
  • Data generation: We can create new data or content that can provide insights or solutions for healthcare problems. For example, USA-based startup Persado uses generative AI to create personalized and persuasive content for healthcare communication and engagement. Their digital solutions, Persad PerScribed and Persado Motivation AI Platform have helped healthcare companies, insurers, and retail clinics conduct effective campaigns. 
  • Data enhancement: Generative AI can enhance the existing data or content by adding more details or quality. For example, the tech can help respond to patient queries better. Google DeepMind has developed MedPaLM, a large language model (LLM) trained on medical datasets that can respond to healthcare queries. 

Nuance Communications, a technology provider of advanced conversational AI for ambient clinical documentation and decision support through voice biometrics; and specialized ambient sensing hardware, leverages Open AI’s Chat GPT to enhance customer responses and manage administrative tasks. 

  • Data synthesis: Generative AI can synthesize different data or content types to create a comprehensive and coherent output. AI-based firm Zebra Medical Vision has developed more than 11 algorithms to help medical professionals detect diseases better. Their HealthMammo tool is trained on over 350,000 mammogram reports and detects cancer with a 92% success rate compared to 87% among radiologists.

Read More

State of Digital Healthcare in India

The onset of the COVID-19 pandemic served as a catalyst in the acceleration of digital healthcare adoption.

This significant progress reflects India’s commitment to leveraging digital means to enhance healthcare services, bringing a promising future for the digitization of healthcare.

Challenges and the Road Ahead

While the journey so far has been significant, the Digitization of Healthcare in India still faces certain hurdles.

  • Digital Divide: India’s digital divide, especially between urban and rural areas, remains a concern. Ensuring equal access to digital healthcare services is a challenge.
  • Cybersecurity: With increased digitization, data privacy and security become paramount. Robust data protection mechanisms need to be in place.
  • Digital Literacy: Ensuring digital literacy among all users, especially among the older generation, is critical for the success of digital healthcare.

Despite these challenges, the potential for digital healthcare in India is immense. With government initiatives, and innovative solutions like Connect2Clinic, the future of healthcare in India appears increasingly digital. The digital transformation holds promise for improved healthcare access, affordability, and quality, catering to India’s vast population.

Read More.

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