Integrating AI for Sustainable Technological Growth in Healthcare Start-ups
✍️ Opinions
This article has been contributed by Dr. Harshit Jain, Founder & Global CEO, Doceree.
In the continually evolving technological terrain, artificial intelligence (AI) and machine learning have stood out as the titans reshaping industries across the globe. In this revolution, healthcare emerges as a frontrunner, commanding a staggering 11% of the global GDP, and a hefty $9 trillion annually, according to WHO. Ranging from the creation of life-saving medications to improving diagnostic treatment to enabling precision in healthcare marketing practices, these technologies aren't just tinkering around the edges, they've taking the centre stage in elevating every facet of the healthcare industry.
As new-age solutions seamlessly integrate into every stage of the healthcare journey, they mark a remarkable opportunity, propelling the entire healthcare ecosystem forward into a future of sustainable growth and profound societal impact.
In this piece, we will try to delve into the critical AI-powered mechanisms that create a future shaped with sustainable healthcare achievements for enhanced patient outcomes and quality treatment delivery.
Fostering Disease Accuracy Through Timely Diagnosis
Enhanced Healthcare Delivery
Leveraging Explainable AI (XAI) For Transparency in Healthcare
Assisting Drug Development & Marketing
Harmonizing Digital with Eco-Friendly IoT
Fostering Disease Accuracy Through Timely Diagnosis
The notion of employing technology for medical diagnosis isn't novel. Yet, AI's prowess ushers in a realm of advanced analysis and swifter decision-making, surpassing conventional diagnostic approaches. According to a recent industry study, India's Artificial Intelligence (AI) diagnostics market is projected to grow from $0.02 billion in 2022 to $0.24 billion by 2030, registering a compound annual growth rate (CAGR) of 38% during the forecast period of 2022-2030. This growth is primarily due to AI systems capabilities in early detection of chronic diseases like Alzheimer's, diabetes, cardiovascular diseases, and several types of cancers including breast cancer and colon cancer, simultaneously reducing the financial burden and severity of the disease.
Additionally, with Government’s efforts towards fast tracking electronic health records (EHR) adoption in India, AI can again prove helpful in analysing patient data records for genetic testing results, lifestyle factors and more, thereby identifying patterns that may put individuals at risk for certain diseases. This will enable healthcare providers to intervene early with accurate preventative measures.
Enhanced Healthcare Delivery
The strategic application of AI triggers has demonstrated reliability in enabling compliant-friendly real-time mapping of patient data, enabling life sciences manufacturers to share relevant messages (as per the patient requirements) to healthcare providers (HCPs), empowering them to deliver quality treatment while tending to the patient. This fine-tunes treatment strategies by factoring in unique patient variables and forecasting outcomes, thus guaranteeing tailored care through intelligent analysis of patient data. Further, using machine learning algorithms and AI-driven chatbots, AI can swiftly analyse vast datasets that aid in furnishing immediate aid and reducing administrative pressures on healthcare providers (HCPs). In surgical settings, robotic support can improve precision, diminishing complications and recovery durations, particularly evident in cancer treatments.
Leveraging Explainable AI (XAI) For Transparency in Healthcare
While the accomplishments attained through the integration of AI in medicine are noteworthy, building trust and credibility around its accuracy among end-consumers, specifically patients, is paramount. Hence, the utilization of explainable AI (XAI) is crucial to uphold transparency and provide accurate knowledge about the technology to both healthcare providers (HCPs) implementing the technology and patients undergoing treatment facilitated by it. Amidst the complex ecosystem of medical decision-making, XAI clarifies the rationale behind AI-powered diagnosis and treatment suggestions to shed light on the process for the sake of transparency. Once HCPs understand how AI systems make decisions, they can leverage their expertise to fine-tune AI’s performance, ultimately bolstering confidence in the decisions made for both – HCPs and patients.
Subham Kumar
Assisting Drug Development & Marketing
According to a recent EY report, 48% of healthcare and pharma companies in India are set to integrate First-Gen AI solution within the next year. Through crafting tailored machine learning algorithms, governmental bodies and life sciences enterprises can streamline laborious tasks, preserving both time and research funds, thereby bringing more efficiency into R&D endeavours. For instance, intelligent use of algorithms can help AI decipher biological data, identify potential drug targets as well as assess their interactions with specific receptors. Even during clinical trials, AI can play a pivotal role in enhancing efficiency by identifying suitable candidates (during session with HCP), predicting potential outcomes, optimizing trial designs, leading to more successful and expedited drug discovery processes.
On drug marketing front, AI-driven marketing solutions potentially present a promising avenue for slashing exorbitant marketing budgets and amplifying sales conversion rates through precisely targeted relevant messaging aimed at HCPs. This strategic approach not only ensures HCPs remain abreast of emerging drug treatments/research but also empowers pharmaceutical brands to promote their offerings at minimal expense.
Harmonizing Digital with Eco-Friendly IoT
In India, conventional pharmaceutical marketing approaches predominantly involve face-to-face interactions between representatives and HCPs, leading to labour-intensive processes, carbon emissions, and energy depletion. Shifting towards AI-driven digital platforms can address these concerns, enabling streamlined engagement with millions of HCPs at the click, while concurrently reducing environmental impact and resource usage. Additionally, integrating AI with Green IoT emerges as the cornerstone of sustainable progress in healthcare, wherein Green-IoT-empowered medical equipment and wearables can collate health data for further analysis by AI algorithms to improve patient outcomes and make decision-making process for healthcare professionals (HCPs) much more efficient.
To sum up, as the future of healthcare highly depends on the technology and human expertise balance, it becomes crucial to dedicate considerable focus and resources to fostering responsible utilization and ethical deliberations throughout the stages of AI integration. This approach ensures sustainable technological advancement and guards against possible drawbacks, thereby ensuring that AI contributes positively to healthcare transformation. By aligning with societal values and priorities and optimizing its capabilities, AI can significantly enhance patient outcomes while upholding ethical standards and long-term sustainability.
Ashwini
