AI for Healthcare and Life Sciences: What’s trending?

  • Patient-oriented AI
  • Clinician-oriented AI
  • Administration-oriented AI
  • Patient Engagement and Adherence Applications: It is certain that the more patients proactively participate in their own well-being and care, the better the outcomes — utilization, financial outcomes, and member experience. Patient engagement and drug adherence have been seen as the final barrier between ineffective and good health outcomes. Such applications are increasingly addressing challenges related to patient outcomes by using Big Data and AI, evolving the healthcare system to a more patient-centric approach.
  • Rise of Telemedicine: Due to the pandemic overpowering the healthcare systems, Telemedicine showed its relevance at the right time. The use of NLP and ML-based applications for remote treatment and monitoring of patients reduces doctor in-person visits and keeps the personalized treatment factor persistent. Telemedicine is becoming immensely popular globally with millions of people being treated from different parts of the world eliminating the diversity and language barriers.
  • Faster and reliable Patient Transportation: Be it emergency / non-emergency, there are platforms available to support healthcare institutions easily schedule on-demand, recurring and multi-destination transportation for patients. This leads to streamlining the discharge process for hospitals and improved patient throughput. Supported by real-time language translation through machine learning, these platforms can scale globally.
  • Future of Pharma: On the Go technology for Medical sales reps: Medical sales reps are required to shift from the traditional representative detailing model to a new technology-driven sales model, that can enhance sales and improve operational efficiency. Starting with creating a robust digital sales pipeline, managing and analyzing customers through a non-clinical CRM, to seamless resource allocation, record-keeping & documentation, all processes can be automated to perform better.
  • Transformation of Clinical Trials: During the current COVID-19 era, AI and ML in Healthcare leverage huge potential to transform clinical trials. Once identified and recruited, the biggest challenge in clinical trials is keeping the volunteers engaged and optimized to treatment. And, Predictive AI can play a big role in understanding how patients are responding to a drug in real-time and their overall drug adherence and behavior.
  • Advancing Research of new products: To identify new indications in current medical products or research new ones, Life Sciences companies are exploring sophisticated AI algorithms. To further elaborate, with AI, useful data insights can be incurred that can lead to the identification of new mechanisms of disease, potential new line extensions, and design for preclinical experiments.
  • Better choice and convenience
  • Better transition from hospital to home recovery
  • Faster and easier appointment scheduling
  • Convenient Bill Payment
  • Less time spent filling medical form
  • More Accurate diagnosis and personalized treatment
  • Reduced wait times and errors
  • Increased Patient Satisfaction
  • Faster analysis and prediction of new diseases
  • Access to virtual treatment and payment options
  • Faster Appointment Booking
  • Faster Clinical Documentation
  • Faster Claims Processing and audits
  • Increased efficiency and reduced manual errors
  • Reduced operational costs Online Video Consultation with Appointment Scheduler leverages Secure, Easy, and Hassle-free Online Video Consultations for enabling better remote healthcare. It’s an end-to-end solution to empower patients and physicians for a stronger continuum of care from the comfort of their homes.

Preparing for the Future of AI in healthcare

Think Big, Start Small, Scale Fast



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