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

AI, as we all know, is already at work, increasing convenience and efficiency, reducing cost and errors, and generally making life easier for multiple industries. One of the world’s highest-growth industries, the AI sector was valued at about $600 million in 2014 and is projected to reach $150 billion by 2026, as mentioned in this AI in Healthcare Market Analysis by Accenture

AI is becoming prevalent specifically in the Healthcare and Life Sciences industry for a specific reason. AI in Healthcare increases the ability of HCP’s to better understand the day-to-day patterns and needs of patients through accurate and secure patient-centric data. With that understanding, they are able to provide better feedback, guidance, and support for improved patient outcomes and lower drug adherence.

To drive this transformation of the Healthcare and Life Sciences industry on the cloud, specific technologies need to be experimented with and for that, a joint effort is required. Both from the Healthcare Sector and the Technology Consulting Companies that drive growth on the cloud. 

AI in Healthcare 2020 Global Trends

AI in Healthcare is categorized into three fragments:

  • Patient-oriented AI

Today, the traditional one size fits all treatment care models are rapidly being replaced with more patient-centric models that drive focus towards the Patient Quality of Care, wellness, and Disease Management. The use of predictive AI techniques to improve the efficiency of patient operational flow while maintaining the patient/provider satisfaction are dominant. Platforms that can be customized to fit all clinical stakeholders’ needs achieving the end goal of providing personalized treatment to patients are coming up, specially customized solutions for better remote healthcare. 

  • Clinician-oriented AI

These include Predictive AI applications that are integrated with clinician workflows and medical record systems and require the highest level of regulatory compliance. To make a doctor’s life easier, such systems analyze counterintuitive patterns and sources of causality in medical records that result in a far more effective & personalized treatment process. AI in Healthcare is being used as a way to stop the data hemorrhaging. The technology breaks down data silos and connects in minutes, instantly providing the information that used to take years to process.

  • Administration-oriented AI

In the Healthcare and Life Sciences Industry, there exist multiple simple transactions like managing health informatics such as record keeping or making appointments. For such use cases, ML in Healthcare is becoming increasingly visible. From reliable identification of patient history across different databases to real-time patient monitoring and e-prescriptions, such applications take care of optimizing processes end-to-end. These applications are designed to automate the healthcare industry’s most repetitive tasks, thus freeing up administrators to work on higher-level ones.

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Here are a few global trends prevalent in the Healthcare and Life Sciences Cloud Services Domain today:  

  • 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.

Benefits of AI in Healthcare

Patient-Specific:

  • 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

Physician Specific:

  • 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

Administration Specific: 

  • Faster Appointment Booking
  • Faster Clinical Documentation
  • Faster Claims Processing and audits
  • Increased efficiency and reduced manual errors
  • Reduced operational costs
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SourceFuse’s Adaptation of Healthcare and Life Sciences Trends

SourceFuse, being a leading provider of cloud-based solutions, with a niche focus on Healthcare and Life Sciences cloud services, offers multiple solutions that leverage AI, ML, and NLP services for more efficient patient outcomes. 

AI for Healthcare and Life Sciences

Being AWS Healthcare Competency Partners, we are endorsed by AWS for our demonstrated technical expertise and proven customer success in building healthcare solutions on the AWS cloud. Our constant engagement with Healthcare organizations to build innovative, cost-effective, and secure solutions that improve operational and clinical effectiveness adds to our deep domain expertise. 

Patient-Centric Care: Developed for one of India’s leading Pharmaceutical Companies

Supporting the end goal of better patient lives, SourceFuse is redefining patient-centric care with a native iOS and Android Application and also a Web App supportive of all modern browsers, connecting the patients with the doctors from the comfort of their homes after hospital discharge. It’s a HIPAA Compliant, highly organized care-driven platform resolving the challenges that arise during the post-treatment recovery processes. 

SF Medic: AI-Enabled Telemedicine Product

SF Medic is an easy-to-use and HIPAA Compliant telemedicine application that can be adopted by hospitals, clinics, and even single-physician practices. It provides Real-time clinical decision support using AWS artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), real-time language translation, and Asynchronous text or voice messaging is the preferred mode of communication between patient and provider. SourceFuse offers SF Medic as a standalone SaaS (Software-as-a-Service) solution for hospitals and specialty clinics. It is also available as a plugin that integrates into existing hospital management systems and EHRs.

helloMD.online: Online Video Consultation with Appointment Scheduler

helloMD.online 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. 

RelayRIDE: Transforming Healthcare Transportation

The Patient is at the heart of all healthcare transportations. And to deliver the maximum benefit to the patient, a trusted solution, ensuring safety, reliability, and peace of mind is essential. RelayRIDE, built by SourceFuse, is one such solution that provides real-time monitoring and intervention for guaranteed drop off and pick-up of patients, be it for work-related injuries or long-term cases involving veterans. An Intuitive web and mobile application that effortlessly manages the patient’s journey and prevents any missed medical appointments.

E-Briefcase App: E-Detailing Solution for Medical Sales Reps

For Medical Sales Reps, we developed a One-Stop Platform with a compliant, tightly secured, and always accessible (even offline mode) Saas based iPad App. The App enables Medical Sales Reps with organized and efficient content & review management processes leveraging secure audit and traceability features. 

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Preparing for the Future of AI in healthcare

Think Big, Start Small, Scale Fast 

Based on our work with clients on applications of AI in healthcare and Life Sciences, we can offer certain best practices for better adoption of the technology. The spotlight must always be on the end user’s needs and preferences, which requires a clear understanding of their healthcare background. Along with that, when selecting the data used to “train” any AI/ML model, involving personnel with a combination of technology and healthcare expertise is essential to generate accurate predictions. And lastly, reduce cost and complexity by leveraging open-source technologies and enabling better customization. 

If you’re interested in applying AI to healthcare and Life Sciences, SourceFuse is here to help. 

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