Apollo Hospitals Plans Increased Investment in AI to Alleviate Staff Workload
Apollo Hospitals, one of India’s largest hospital networks, is intensifying its use of artificial intelligence (AI) to alleviate the heavy workload faced by doctors and nurses. The company plans to automate routine tasks like medical documentation, aiming to free up valuable time for healthcare professionals.
With over 10,000 beds across its hospitals, Apollo is increasingly adopting AI to enhance diagnostic accuracy, predict patient risks, and streamline hospital operations. The use of AI is also helping improve precision in robotic surgeries and facilitating virtual medical care. Sangita Reddy, Apollo’s Joint Managing Director, shared that the company had allocated 3.5% of its digital spending to AI over the past two years and intends to further increase this investment in the coming year.
Apollo’s AI tools, which are still in the experimental phase, will analyze electronic medical records to suggest diagnoses, treatment plans, and tests. Additionally, AI will assist in transcribing doctors’ observations, generating discharge summaries, and creating nurses’ schedules from notes. The hospital chain is also developing an AI tool to recommend the most effective antibiotic treatments for patients’ conditions.
The company has set an ambitious goal of expanding its bed capacity by one-third over the next four years, with a portion of the revenue from these new additions being reinvested into AI tools without increasing overall costs. This initiative is part of a broader strategy to tackle the 25% nurse attrition rate, which is expected to rise to 30% by the end of fiscal 2025.
Despite the challenges of high technology costs, diverse data formats, and limited availability of electronic medical records, other major Indian hospital chains like Fortis Healthcare, Tata Memorial, and Max Healthcare are also incorporating AI tools to improve their services. However, according to Joydeep Ghosh, a partner at Deloitte India, accelerating AI adoption remains difficult due to concerns around profitability and operational hurdles.
