We are back with a new article in The AI Chronicles Series. Do check out the previous 3 episodes of our series:
- The AI Chronicles #1 – What’s hot in the pharma world with Generative AI, how to build robust patient data privacy, and what’s up with Apple’s AI-powered health coach.
- The AI Chronicles #2 – McKinsey’s 5-step digital transformation for Pharma companies, Sanofi’s AI approach to employee productivity, and more on digitization of medical data.
- The AI Chronicles #3 – Find content in images and videos with Microsoft’s Vector, Washington’s new health privacy law, and the importance of personalization in healthcare.
Now, coming back to this edition, the healthcare landscape is rapidly evolving, driven by innovative technologies that promise to revolutionize patient care and operational efficiency.
Hots of this Edition
In a groundbreaking move, Amazon Web Services (AWS) has introduced AWS HealthScribe, a generative AI-powered service that has the potential to reshape clinical documentation.
A Roche-sponsored report provides food for thought on digital technologies and the importance of data integration and management.
Pytrial – a Generative AI tool that offers AI support for various clinical trial tasks.
In this blog post, we delve into the implications and significance of these latest tech advancements for the healthcare industry, and their resonance within the larger context of data-driven healthcare innovations.
Amazon, Generative AI, and HealthScribe – What is it About?
Amazon Web Services (AWS) has announced a new generative AI-powered service called AWS HealthScribe that automatically creates clinical documentation. The service uses speech recognition and generative AI to transcribe and summarize clinical notes, saving healthcare providers time and effort in creating medical notes. The service is HIPAA-eligible and supports generative AI clinical documentation capabilities for general medicine and orthopedics specialties.
What Does it Mean?
The AWS HealthScribe service can help healthcare providers save time and effort in creating medical notes, allowing them to focus more on patient care. This service can also help improve the accuracy and completeness of clinical documentation, which is critical for patient care and safety. Leaders in the healthcare industry can use this information to stay up to date with the latest trends in healthcare technology and make informed decisions based on data-driven insights.
Looking to explore the latest in Generative AI trends? Watch our on-demand webinar on the applications of Gen AI in Pharma.
Innovation in Data-Driven Health Care – An HBR Report by Roche
A report sponsored by Roche provided interesting insights into how digital technologies can transform patient care and improve operational efficiency in healthcare. The report highlights that data integration and managing data across settings have been a challenge, but digital technologies have made data integration easier.
- More than half of the respondents say their organization prefers evidence-backed and medically certified digital solutions. Leaders are more likely to say that it is an organizational requirement for digital solutions to be medically certified.
- The report also highlights that the COVID-19 pandemic has accelerated the adoption of digital tools in healthcare. Fifty-seven percent of respondents say their organization adopted new digital tools during the pandemic for managing data, of which 31% say their organization significantly improved its operational insights.
- 43% of respondents say one of the greatest inhibitors of becoming more data-driven is disconnected or incompatible systems/data.
What Does it Mean?
In the pharmaceutical industry, like in many other sectors, data integration and system compatibility have historically been challenges. Pharma companies deal with large volumes of data from various sources, including research and development, clinical trials, manufacturing, distribution, and sales. These data come from a wide array of systems and may be stored in disparate formats, making it challenging to seamlessly integrate and analyze them.
By leveraging advanced analytics and AI technologies, pharma companies can gain insights from their data and identify patterns, trends, and correlations. These insights can help optimize processes, improve decision-making, and drive innovation
Finally, for pharma/medical device companies that develop digital health tools, it is going to be important to ensure that their solutions are validated for clinical and regulatory compliance and backed by scientific evidence. This can help build trust among healthcare providers and regulators and increase the adoption of these solutions.
PyTrial – What is it About?
This paper about PyTrial provides interesting insights from using a Python package that offers various clinical trial tasks supported by AI algorithms, including patient outcome prediction, trial site selection, and trial outcome prediction. The package provides pre-processed datasets for quick adoption of AI algorithms and allows for easy customization and integration with other tools.
What Does it Mean?
Generative AI tools, such as PyTrial, have promised to offer tools for reducing costs and accelerating the drug development process. There is a lot of excitement for the development and use of such tools to improve the efficiency and success rates of clinical trials. With PyTrial, the researchers demonstrated that it can easily load data, define models, train models, and evaluate models with just a few lines of code, and customize and integrate the platform with other tools as needed.
The Gramener Take
At Gramener, we work with Pharmaceutical and Healthcare organizations around the world with a single focus on using data analytics and AI to accelerate and enhance processes with better outcomes, while reducing implementation costs.
We understand the pivotal role that data integration plays in building confidence in analytics and AI among internal and external stakeholders. We also recognize that in the dynamic landscape of this industry and the immense potential that generative AI holds in transforming healthcare.
Generative AI has the ability to create new content, whether it’s text, images, or other forms of data, based on patterns and knowledge it has learned from existing data. In the context of healthcare, this technology could be applied in several ground-breaking ways from clinical documentation to drug discovery, to personalized treatment plans, and more.
