AMIA Lunch and Learn Events are fully catered events hosted by organizations looking to engage directly with leaders in the field.
Participation is open to all attendees.
Tuesday, March 24 12:15 p.m. – 1:15 p.m.
Cyril Magnin III
(not eligible for CME/CE)
Capture of Structured Clinical Data at the Point of Care to Support Translational Medicine: The IMO 2.x Platform
Eric Rose, MD, FAAFP, Director of Clinical Terminology, and Regis Charlot, MS, Chief Technology Officer and President, IMO
Complex analysis of clinical data for purposes of process or outcomes measurement, population health management, and knowledge discovery (e.g. genome-wide association studies) requires that clinical information be faithfully captured at the point of care. Standardized clinical terminologies are an absolute necessity for performing such activities on a large scale, particularly when aggregating data across multiple systems. However, there are numerous challenges to their successful use for clinical data capture.
While such terminologies can often represent clinical information at a fine level of granularity, they often also provide very coarse-grained representation of such information, and in everyday usage, clinicians may not avail themselves of the available granularity, limiting secondary use of such data.
Furthermore, standardized terminologies often have limited conceptual coverage in various areas. Lastly, for many semantic domains, there are multiple standardized terminologies in use. The introduction of ICD-10-CM has complicated the situation by forcing granularity in often non-intuitive ways and this will have a potentially distorting impact on structured data.
This presentation will describe a clinical interface terminology solution that addresses these issues.
- By providing clinician-friendly terms mapped to standardized terminologies, the semantic limitations of those terminologies can be overcome, and codes from multiple standardized terminologies can be retrieved for a single term.
- By providing frequent updates, IMO terminology and technology can keep up with rapid developments in clinical science, emerging diseases, and changes in clinical nomenclature.
- In addition, the solution links different terms in a semantic hierarchy, allowing end-users to be prompted, when they select a coarsely-granular term, with potential additional specificity, increasing the likelihood of capturing data at a fine level of specificity. This will initially be used to provide point-of-care decision support to assist with ICD-10-CM coding while maintaining clinical relevance.
The second portion of this presentation will describe the technical platform that supports this terminology solution, which allows organizations to deploy and update rapidly and seamlessly across multiple systems and environments, to monitor its use, and to understand the implications of any update of content.
Thursday, March 26 12:15 p.m. – 1:15 p.m.
Cyril Magnin III
The Convergence of Delivery and Discovery to Enhance Quality, Performance, and Cost in a Value-based Era
Fred Lee MD, MPH, VP Healthcare Analytics, ConvergeHEALTH by Deloitte
Providers who can effectively leverage their organization’s discovery capabilities towards improving care delivery will likely realize significant competitive advantages in a value-based environment. Predictive models, simulations, and AI methods can be used to enhance care for at-risk populations, help improve operational performance, and forecast financial impacts of assuming risk. Yet enabling learning healthcare loops at the enterprise level requires an integration of (1) statistically founded analytic technologies, (2) professional services, (3) data science, and (4) a collaborative network of peers and partners that can share content, insights, and experience.
In this session, attendees will be presented with how industry approaches centered on these four factors are accelerating the convergence of the discovery and delivery missions within AMCs, children’s hospitals, and other providers to enable evidence-based practice and practice-based evidence to operate in a self-reinforcing cycle.