Digitization of the Healthcare Industry Part 2 - Data Integration Challenges and Approaches
In session 2 (learn more about session 1) we will look at the actual data and data standards that are impacted by electronic health records, and digitization of healthcare. These include administrative, demographic, clinical, and order data. There are numerous standards that attempt to describe various aspects of claims, coverage, costs, delivery, diagnoses, treatments and outcomes. Each of these classification structures and vocabularies plays a critical role in optimizing healthcare delivery, improving patient safety, understanding efficacy of treatments, improving quality of care and controlling overall costs. However, these languages and vocabularies have evolved over time to meet needs that were not originally considered and have been expanded by different groups for different purposes. The result is a “Babylonian confusion of languages” that make it difficult to achieve many of these goals.
We’ll discuss the role of these taxonomies and information science approaches in addressing:
- Clinical trial automation
- Post marketing drug surveillance
- Benefit-Risk analysis
- Comparative effectiveness of treatments
The session will summarize how diagnostic codes of ICD-9, MedDRA and SNOWMED compare in terms of coverage, semantic precision, concept independence and semantic breadth and how organizations need to adapt and map classification structures in order to address their challenges.