The healthcare industry is on the verge of a transformative era, driven by technological advancements like generative AI (Gen AI). These innovations are revolutionizing the way data is utilized, opening up new possibilities for healthcare delivery and efficiency. It comes as no surprise that the HIMSS Global Health Conference and Exhibition centered around the theme of “Creating Tomorrow’s Health.”
Last week, Milliman MedInsight had the privilege of participating in this highly anticipated event, where we immersed ourselves in insightful sessions and explored the latest technological investments to support healthcare’s workforce and delivery. This experience provided us with a comprehensive understanding of the latest trends and innovations shaping the industry. Here are the key discussion themes that captured our attention at HIMSS24.
The ongoing digital transformation journey
This year’s conference emphasized the continuous nature of digital transformation. What does digital transformation entail, and when can an organization consider it complete? While digital transformation can streamline processes, optimize resources, and enhance care experiences, one must keep in mind that it is not a destination, but rather an ongoing evolutionary process that delivers value incrementally.
The true power of digital transformation lies in its ability to liberate time and empower healthcare employees to actively contribute to addressing industry challenges. To achieve this, healthcare organizations must foster a collaborative, cross-functional approach to digital transformation. This approach involves not only migrating data to the cloud but also ensuring that all healthcare employees, including both IT and non-IT staff, are involved in finding solutions.
By breaking down the transformation process into manageable steps, healthcare organizations can maintain focus, adapt to challenges, and celebrate achievements along the way. This iterative approach allows for continuous improvement and ensures that the benefits of digital transformation are realized throughout the organization.
Advancing Gen AI in healthcare
The emergence of Gen AI in healthcare has brought about a revolutionary shift, offering transformative possibilities for patient care and operational efficiency. Our observations at HIMSS highlighted that many organizations have begun harnessing this technology to automate administrative tasks and allow healthcare analysts and professionals to focus on more critical aspects of their work. The potential of Gen AI to enhance efficiency, accuracy, and personalize patient experiences is significant.
However, it is crucial to address the challenges associated with implementing Gen AI in healthcare. Responsible application of this technology must be prioritized and take into consideration secure, trustworthy data. With the continuous creation of new models, there is an increased risk of potential harm or bias. Therefore, organizations utilizing Gen AI must recognize that while there is an abundance of data, its quality cannot always be assumed.
The importance of data governance
The successful implementation of new technologies can be hindered by complex organizational dynamics, including departmental silos. To maximize the value derived from these technologies, healthcare organizations must prioritize the establishment of data governance frameworks and policies.
By implementing data governance frameworks, organizations can ensure that data is collected, managed, and utilized in an ethical and responsible manner. This approach also helps to mitigate biases that may exist in the data and safeguards sensitive information. Moreover, data governance enables organizations to establish clear decision-makers, implement effective strategies, and empower teams to test, learn, and innovate.
Additionally, data governance supports standardization and consistency across different systems and applications, making it easier to access, analyze, and collaborate with confidence. By prioritizing data governance, healthcare organizations can extract higher quality outputs from their models, enabling them to gain deeper insights and unlock the full potential of their use cases.
How MedInsight can help you innovate with trusted data
The MedInsight AI application, the Data Science Portal (DSP), is a cloud-based platform that allows MedInsight customers to access their data mart and create a data lake. Supporting programming languages like Databricks SQL, Python, and R, the DSP aims to simplify the modeling process for analysts and data scientists by reducing the need for data formatting. By providing cloud-based access to the MedInsight data mart, the DSP enables clients to easily incorporate referential or non-referential data and perform advanced analysis. This helps clients be more efficient in identifying issues and improving data quality. MedInsight also assists clients in transitioning to the cloud and offers training and support. The DSP provides an intuitive interface for data exploration and analysis, allowing clients to gain insights more quickly. It has received positive feedback from early adopters who have benefited from automated report generation and enhanced analytics. Furthermore, MedInsight’s dedicated team of data scientists focuses on machine learning modeling and product development, continuously working on incorporating both machine learning and AI capabilities into MedInsight platforms and applications.
Harness the power of trustworthy data to unlock greater value from your analytic investments and uncover valuable insights for reducing risk and cost. Discover how Milliman MedInsight can provide your organizations with reliable data, advanced technology and expert analytics. Connect with a member of the MedInsight team today or request a demo to learn more.