Recently, Bisam Pharmaceuticals launched ‘QuickVitals’, claiming it as the world’s first health monitoring application powered by AI and Deep Learning Technologies. Harish Bisam, Founder & Managing Director, Bisam Pharmaceuticals, in an exclusive conversation with CXO News and APAC News Network, highlights the transformative role of AI and the QuickVitals app in India’s healthcare sector.
How would you describe the role of AI in transforming healthcare delivery in India?
The role of AI has been tremendous in transforming healthcare delivery in India, where addressing key challenges such as accessibility, affordability, and quality of care has been significant. Through AI, we have enhanced our diagnostics, the accuracy with which AI-driven tools have detected diseases at early stages, and reduced diagnostic errors is commendable. AI also increases operational efficiency, i.e., scheduling, billing and data entry.
Healthcare is an expensive industry. However, AI has made it possible to monitor patients remotely, reducing hospital stays. For those who may consider AI as a generalised way of treatment, be assured that AI has made it possible to orchestrate more personalised treatment than ever.
These are individual perks, but not all AI is being utilised for. On a global level, healthcare AI can also be used to predict disease outbreaks and health trends.
In your experience, what are the major areas in which AI is driving efficiency and quality in healthcare?
According to my experience and observations, there are a few major areas where AI is being applied globally to ensure efficiency and quality in healthcare:
Medical Imaging and Diagnostics
Radiology: Using imaging such as CT scans, MRIs and X-rays to diagnose and treat diseases and injuries has enhanced accuracy and speed in detecting anomalies like tumours, fractures and other conditions. Analyzing pathology slides and identifying disease markers in samples, speeding up diagnoses and reducing human error through AI have been proven to be efficient.
Early Disease Detection: Machine learning models can predict the onset of diseases like cancer, diabetic retinopathy, or cardiovascular issues much earlier than traditional methods
Predictive Analytics and Precision Medicine
AI analyzes more than just your symptoms. It gives you a holistic background of the patients even lifestyle factors to recommend tailor-made treatment options. It is crucial in a field like oncology where treatment is based on the molecular characteristics of a tumour. It also helps in preventive care by predicting the likelihood of diabetes, and heart diseases for early intervention. On the front of soft skill enhancement, AI tools also help enhance the decision-making process of doctors by suggesting treatment options.
Healthcare Operations and Workflow Automation
A Digital Revolution: AI is automating administrative tasks, freeing up healthcare staff to focus on what they do best: patient care. Imagine scheduling appointments, processing insurance claims, and managing patient records with a simple click. It’s like having a personal assistant for your healthcare practice.
Smart Resource Management: Think of AI as a healthcare traffic controller, predicting patient admissions, optimising bed allocations, and ensuring medical supplies are always where they need to be. It’s a game-changer for efficient hospital management.
Drug Discovery and Development
AI is making drug discovery more efficient by simulating molecular interactions, identifying potential drugs, and predicting their success. This cuts down on the time and cost of bringing new drugs to market. AI makes clinical trials more effective by analyzing patient data to select suitable participants, forecast trial outcomes, and monitor patient responses more accurately.
Telemedicine and Remote Patient Monitoring
Remote Diagnostics: By analyzing vital signs and health data, AI-powered apps and platforms like QuickVitals offer remote patient monitoring, improving access to healthcare for people living in underserved or rural locations.
Telehealth Platforms: Artificial intelligence chatbots and virtual assistants in telemedicine platforms assist with follow-up treatment, basic health question answering, and patient triage, freeing up doctors’ time to concentrate on more complex situations.
Robotic Surgery
Surgical Precision: Surgeons may execute intricate procedures with increased accuracy, minimally invasive methods, and reduced complications thanks to robotic equipment powered by artificial intelligence. Better patient outcomes and quicker recovery times are the effects of this.
Real-time Assistance: AI can assist surgeons in real-time during procedures, minimising human error and raising the standard of care overall.
Chronic Disease Management
AI-Driven Monitoring: Mobile apps and wearables with AI capabilities keep an eye on long-term ailments like asthma, diabetes, and high blood pressure. When a patient’s vital signs diverge from normal, these technologies send out alarms that allow for prompt intervention.
Personalised Care Plans: AI systems have the ability to design and modify care plans for individuals with chronic illnesses in response to changing health data, guaranteeing more flexible and timely treatment.
Mental Health Support
AI-driven mental health apps and chatbots can offer cognitive behavioural therapy (CBT), meditation instruction, and assistance for mental health issues such as depression and anxiety. For those who find it difficult to see a therapist, these resources are quite helpful.
Behavioural Insights: Artificial intelligence (AI) assists in identifying trends in voice, text, or behaviour that may be signs of mental health problems. This information allows for prompt intervention.
Security and Management of Health Data
Effective Data Management: Artificial intelligence (AI) makes it easier to store, retrieve, and analyze vast volumes of health data, guaranteeing the smooth integration of electronic health records (EHRs). This leads to more coordinated care and improved patient outcomes.
Data security: Artificial intelligence (AI) assists in identifying irregularities or breaches in healthcare data systems, guaranteeing that private patient information is safe from online attacks.
Public health and epidemiology
Predicting Disease Outbreaks: AI tracks and forecasts disease outbreaks (like COVID-19) by analyzing social media trends and public health data. This makes it possible for authorities to act quickly and effectively.
Population Health Management: AI is used to detect risk factors and create treatments to enhance public health generally by analyzing health patterns at the community or population level.
AI is revolutionizing healthcare in many ways, benefiting patients and healthcare professionals alike in the long run by lowering costs, raising operational efficiency, and improving the quality of service.
How is Quick Vitals impacting healthcare infrastructure in the country through the use of AI?
We have safely and mindfully curated QuickVitals to address the existing issues that our healthcare industry faces. We are revolutionizing healthcare in India by:
- Improving accessibility: Quick Vitals is dedicated to providing remote health monitoring in areas with limited healthcare infrastructure, allowing individuals to track their vital signs and consult with doctors virtually.
- Promoting preventive care: ‘Precaution is better than cure’. Quick Vitals detects early warning signs of diseases through continuous monitoring, enabling timely interventions and reducing the burden on hospitals.
- Leveraging data-driven insights: We analyze health data to identify trends, inform decision-making, and develop more effective public health strategies.
- Scaling health monitoring: Quick Vitals enables decentralised healthcare by empowering patients to manage their own health, reducing reliance on physical infrastructure and improving efficiency.
- Enhancing efficiency: It optimizes doctor-patient interactions through data-driven insights, reducing unnecessary consultations, and promoting preventive care.
- Strengthening public health surveillance: It collects and analyzes health data to detect and track disease outbreaks, enabling quicker and more effective responses.
- Addressing workforce shortages: It empowers non-specialist caregivers to monitor patient health, reducing the dependence on highly trained medical staff, and supporting primary healthcare.
- Promoting health awareness: ‘We only fear the unknown’. The more we understand something, the less intimidating it becomes. Through Quick Vitals we educate users about their health, providing personalised recommendations, and fostering a proactive approach to personal health management.
- Expanding telehealth: By integrating with telemedicine platforms to enable remote consultations, we reduce the strain on physical healthcare facilities.
According to you, what are the major challenges faced by the healthcare industry in deploying AI?
Despite its immense potential to revolutionise healthcare, AI faces significant challenges that must be addressed for its successful implementation which is what we all hope for future enhancements.
Data-related hurdles are a primary concern. Ensuring data privacy and security, particularly when dealing with sensitive patient information, is paramount. Additionally, the quality and availability of data can be a limiting factor. Inconsistent, incomplete, or siloed data can hinder AI’s effectiveness.
Integrating AI with existing healthcare systems can be complex due to interoperability issues and the presence of legacy systems. Ensuring seamless data exchange and compatibility with traditional infrastructure is crucial for successful AI deployment. Ethical and legal considerations are also paramount.
Addressing algorithmic bias, ensuring accountability, and establishing clear legal frameworks for AI-driven care are essential to mitigate risks and build trust. Overcoming resistance to change and addressing the “black box problem” are critical for gaining acceptance among healthcare professionals. Ensuring transparency and interpretability of AI models is essential for building trust and facilitating adoption.
Regulatory hurdles can be significant. Navigating lengthy approval processes, complying with evolving regulations, and ensuring AI systems meet rigorous standards are essential for safe and effective deployment.
The high costs of implementation and infrastructure requirements can be a barrier for many healthcare organisations, particularly in developing countries. Investing in advanced IT infrastructure and acquiring skilled expertise can be challenging.
Addressing skill gaps and training healthcare professionals is crucial for effective AI utilization. Ensuring that healthcare workers understand AI tools and can use them effectively is essential for maximising their benefits. Ensuring clinical validation and accuracy is another critical challenge. AI systems must undergo rigorous testing and validation to ensure they are safe, reliable, and effective in real-world settings.
Cultural and societal factors can also influence AI adoption. Building patient trust, addressing cultural concerns, and ensuring AI aligns with societal values are essential for successful implementation. Continuous learning and adaptation are crucial for AI systems to remain effective in a rapidly evolving healthcare landscape.
Ensuring AI systems can adapt to new medical knowledge, handle variability in real-world data, and remain relevant over time is essential for long-term success. Overcoming these challenges requires a collaborative effort involving technology providers, healthcare professionals, regulators, and policymakers. By addressing these issues, we can harness the full potential of AI to improve healthcare outcomes, reduce costs, and enhance patient experiences.
How do you envision the future of AI in the Indian healthcare industry in the coming 5-10 years?
I believe that the future of AI in Indian healthcare is incredibly promising! Over the next decade, we can expect AI to revolutionise the industry, improving access, affordability, and quality of care. One of the most significant impacts will be in diagnostics and imaging. AI-powered tools will become commonplace, analyzing medical images and providing quicker, more accurate diagnoses, especially in remote areas. This will enable early detection of diseases and more proactive treatment.
Telemedicine and remote monitoring will also see a major transformation. AI-powered tools will enhance telemedicine platforms, allowing patients to receive care from anywhere. Wearables and apps will enable real-time monitoring of chronic conditions, reducing hospital visits and improving patient outcomes. Personalised medicine will become a reality, thanks to AI. By analyzing genetic, lifestyle, and environmental data, AI can tailor treatment plans for individual patients, improving the effectiveness of care and reducing side effects.
Accessibility in rural areas will be significantly improved. AI-powered mobile health clinics can bring essential healthcare services to remote communities. Additionally, AI will strengthen primary healthcare, enabling community health workers and primary care providers to manage more patients effectively.
Public health surveillance and disease management will benefit greatly from AI. Artificial Intelligence can predict, track, and manage outbreaks, ensuring timely and effective responses. It can also analyze population-level data to identify health trends and implement targeted interventions. Surgical procedures will become more precise and efficient with AI-powered robotic systems and AI-assisted surgery. This will lead to quicker recovery times and better patient outcomes.
Affordable AI solutions will be developed to cater to the specific needs of India’s healthcare system. These solutions will be tailored to work in resource-constrained settings, ensuring accessibility for all. AI will also play a crucial role in drug discovery and clinical trials, accelerating the development of new treatments and improving the efficiency of clinical research. Mental health care will benefit from AI-powered apps and tools, offering mental health assessments, counselling, and support.
AI can also help identify early signs of mental health disorders, enabling early intervention. Regulatory frameworks and ethical guidelines will be developed to ensure the safe and responsible use of AI in healthcare. Collaboration between startups, hospitals, and government bodies will drive innovation and accelerate AI adoption.
How can AI be used to address the public health challenges like the pandemic?
I think that with AI, we have the potential to revolutionize how we respond to and manage public health crises like pandemics. By leveraging AI’s capabilities in data analysis, prediction, and automation, healthcare systems can enhance preparedness, response, and recovery. AI can play a crucial role in early detection and surveillance. By analyzing vast amounts of data, AI can detect early signs of outbreaks and track the spread of infections in real-time. This enables faster public health interventions and more effective containment strategies.
Contact tracing and containment can also be significantly improved with AI. AI-powered tools can automate contact tracing, identify hotspots, and optimise resource allocation. This helps prevent the further spread of diseases and ensures resources are deployed effectively. Data-driven decision-making is essential during public health crises. AI can analyze epidemiological data to predict the spread of diseases, optimise resource allocation, and inform policy decisions.
AI can also accelerate drug discovery and vaccine development. By analyzing existing drugs and simulating clinical trials, AI can help identify potential treatments and bring vaccines to market more quickly.
AI-driven diagnostics and testing can improve accuracy and speed, enabling faster identification and management of cases. Additionally, AI can enhance public health communication by providing accurate information and combating misinformation. Managing healthcare capacity during pandemics is crucial. It can help optimise hospital operations, allocate resources efficiently, and prioritize patients based on the severity of their symptoms.
Vaccine distribution and supply chain management can also benefit from AI. It can help optimise distribution plans and ensure the timely delivery of essential supplies. It can improve pandemic research and insights by analyzing vast amounts of data and facilitating global collaboration. This can lead to a better understanding of disease transmission and more effective public health interventions. Mental health support is also essential during pandemics. AI-driven mental health apps can provide crucial support to individuals coping with stress and isolation.
How is QuickVitals addressing the existing limitations of leveraging AI for Healthcare?
QuickVitals focuses on non-invasive, preventive health monitoring, which may be easier for patients to trust as it complements, rather than replaces, doctor-patient interactions. By providing transparent insights into their health metrics (e.g., heart rate, oxygen levels), QuickVitals can build patient confidence in AI by showing tangible, understandable results.
With user-friendly features and direct engagement with patients, QuickVitals can help demystify AI by allowing users to see immediate benefits from its use, making it more acceptable even among less tech-savvy populations.
Anannya Saraswat, APAC News Network
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