About

OCL's vision is to lower barriers to adopting standardized terminology, focusing on priority health issues in low-resource settings, to facilitate monitoring, evaluation, and performance improvement across the healthcare and public health systems. OCL will do this through a community-supported, standards-based approach.

Our idea is to create an open-source, cloud-based toolset for open and collaborative terminology, indicator, and core dataset management and development to accelerate convergence on best practices for data and data dictionary harmonization, information exchange, and reuse of analytics tools and approaches. This toolset will include (1) a web application to search, export, subscribe, and map to standardized terminology and indicators; (2) pre-populated terminology dictionaries and indicator registries, including a curated health terminology dataset from our primary academic partner and international standards such as ICD-10, SNOMED, WHO Indicator Registry, and US Meaningful Use Clinical Quality Indicators; (3) functionality to collaboratively create, export, and subscribe to subsets of terms and indicators that represent particular specialty areas (e.g. PEPFAR reporting requirements, mobile data collection form, or antenatal care core dataset); (4) design of an open API and interfaces with key community (e.g. CommCare and Magpi), facility (OpenMRS), district and national-level (DHIS2) platforms and terminology management systems (Apelon); and (5) support for communities of practice to advance terminology, indicator and tools development for specific domains, such as maternal-child health.

Standardized terminology is the fundamental enabler of interoperability- it gives meaning to data regardless of where, when, how, or by whom it was collected. Yet, barriers to leveraging standardized terminology to achieve meaningful information exchange remain prohibitively high, especially in low-resource settings where capacity is limited and vertical information siloes are common. This means that despite unprecedented amounts of data being available, we still cannot meaningfully track what services are being provided, at what level of quality, and what are the patient outcomes. The aim of this solution is to increase liquidity of data across organizational and technical boundaries by dramatically improving the usability and relevance of curated terminology resources. What is unique about our approach is: