AI & ML-based technology is leading innovation breakthroughs in the ever-evolving healthcare industry. The interest and inclusion of artificial intelligence and machine learning (AI&ML) have grown rapidly over the last decade. The healthcare ecosystem works on in-depth knowledge and application of research-based customized output aligning people to prognosis.
The use of AI & ML is evolving in the healthcare industry. Historically, healthcare and clinical research were undertaken manually. Clinical research is a highly complex, people-intensive, multi-trial sector. It is also susceptible to unexpected errors in outcomes and biases due to large, heterogeneous data. Technology, advanced computing, data accessibility, and technical talent have expedited the amalgamation of AI and ML in the healthcare domain, giving better or at par output.
Clinical research can benefit tremendously using AI and ML to read data which would have a larger success rate at generalizing, segregating, identifying perplexing data patterns, and predicting results thereof. The areas of machine learning contributing largely to clinical research are the efficiency of pre-trials, enhancing translational research, interpretation, and integration of results. Adding AI capability also has a crucial role in EHR data management, identifying and streamlining patient selection, data simulation to control participants' study burden.
AI & ML use cases beyond clinical research have expansive potential in diagnosis and treatment applications. The core idea of AI was the predictive and accurate diagnosis and treatment analysis, which however was restrictive owing to the prior non-digitization of clinician methodologies and health records. However, smart machine-led predictive tech can offer varied advantages over human analytics and clinical decision-making methods. Integrating data digitization and training data algorithms opens avenues to streamlining processes, newer diagnostics, treatment possibilities, post-operative care methods, and their results.
The healthcare sector can count on the AI & ML benefits by combining narrative, diagnostic data, and clinical findings to analyse patient/people data to swiftly identify, minimise and reduce risks by tapping into early actionable points to prevent the onset of disease and promote a holistic approach to wellness and cure. Clinical decision-making can be leveraged by applying AI & ML algorithms to minimise delays due to traditional processes, diagnostic inefficiencies and offer better options and outcomes on a real-time basis. AI-enabled robotics-assisted surgeries can be a solution to mitigate the risks of complex surgical procedures and any complications with precision surgeries. Machine learning offers an array of real-time insights helping healthcare professionals take immediate actions during and post-procedural care to reach the best actionable solutions.
Artificial intelligence and machine learning are a boon to tap into for providing accessible healthcare on a digitised infrastructure through faster diagnosis by quicker interpretations of diagnosis and marginalised errors. It also helps manage the shortage of qualified healthcare professionals in certain diagnostic areas.
AI & ML can also enhance efficiency in healthcare administration by streamlining processes, medical records, documentation, claims to process, and managing revenue cycles. Within the healthcare ecosystem, a robust AI-enabled system can optimise asset utilization, improve procedures and processes, prioritise need-based services and automate routine work to optimise people's utility.
As a leader of a digital health organization, I am convinced about the huge potential that AI & ML-enabled technology can garner to provide cutting-edge healthcare solutions. The impact of this predictive technology on healthcare delivery efficiency, disease management, and clinical research is bound to revolutionise healthcare in India.
Anurag Khosla, CEO, Aetna India
Anurag Khosla has been spearheading the operations of Aetna India since November 2020 as the CEO. In this role, he is responsible for accelerating business growth and capturing the huge pace of change around digital healthcare in India.
In his previous role at Optum Global solutions, Anurag was instrumental in scaling the company's business and making it a leading global healthcare technology and IT services company. His business acumen and leadership helped OGS become a global market force and expand its reach in North & South American markets, Europe and the Asia Pacific. Anurag has also served Wipro BPO at various positions of significance and was responsible for the launch and growth of its three verticals in the Healthcare and Technology Industry. Under Anurag's leadership, the business has continued to perform well and serve almost 3.4 million customers across India with an ecosystem of primary healthcare services, all pivoting around vHealth at its core.
A post-graduate from the Indian School of Business and Kellogg's School of Management, Chicago, Anurag also holds a Corporate Development & Competitive Marketing Strategies Certification from Wharton School of Business, University of Pennsylvania.
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