Health Informatics and the Role of Standards and Interoperability - OpenConceptLab/ocl_user_wiki GitHub Wiki

Health informatics is the field of....(ask Jon for favorite definition).

#####Standards and Interoperability Overview

A key enabler of quality health informatics is a commitment to using data that maps to standards and is interoperable with multiple systems, data sets, and quality measurement reporting mechanisms.

Standardized terminology is a fundamental enabler of interoperability, which is a prerequisite to a connected and coordinated health system. This is especially important in maternal-child health in which continuity of care and longitudinal tracking of health information are critical to ensure proper care. There is no one right way to use terminology to represent a particular procedure, diagnosis, or other health concept, although there are best practices to follow to ensure that terminology is accurate, sufficiently precise, and interoperable.

Example of semantic conflation (please tell me there is a better term for this For example, blood pressure can correctly be captured in the following ways (and many others):

  1. Two integers, one each for systolic and diastolic blood pressure;
  2. High blood pressure during pregnancy: Yes / No / Unknown; or
  3. A clinical diagnosis of pregnancy-associated hypertension added to the client’s problems list.

To achieve interoperability, it is necessary, although not sufficient, to use correct terminology; one must also use the correct set of terms to represent a domain of care. For example, a minimum dataset for pregnancy might include the client’s age, estimated date of last menstrual period, and a basic medical history including potential risk factors and previous birth statistics. The set of terms used to represent a domain of care can be packaged into a core dataset. This core dataset is usually defined by and linked to relevant quality measures, indicators, and reports.

The Open Concept Lab will lower barriers to adopting standardized terminology, focusing on priority health issues in low-resource settings. OCL will foster participation and engagement of a community-supported approach and in the population of an open-source, cloud-based toolset. The resultant standards-linked dictionary will facilitate stronger M&E, enabling targeted quality improvement initiatives and performance improvement that will lead to a better quality of care across healthcare and public health systems, resulting in better health outcomes, a better experience of care and reduced costs.

####Why is that so important?

Standardized terminology is the fundamental enabler of interoperability- it gives meaning to data regardless of where, when, how, or by whom it is collected. The adoption and utilization of standardized terminology allows disparate health data reporting systems to benchmark their data in a more meaningful way, which will accelerate dissemination and implementation of best practices, resulting in better health outcomes, a better experience of care and reduced costs.

For more about standardized terminology and interoperability, view this video.

####What’s standing in the way of using standardized terminology?

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 silos 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. Moreover, the ability to compare outcomes and the efficacy of interventions in different settings is limited, stymieing the adoption of best practices.

####Where does OCL come into play?

The aim of the Open Concept Lab solution is to increase liquidity of data across organizational and technical boundaries by dramatically improving the usability and relevance of curated terminology resources.

#####OCL: Enabling and Promoting Interoperability OCL addresses the multiple levels of interconnectedness required for meaningful interoperability:

  • Technical and semantic interoperability: The solution supports the capability to interoperate through access to terminology resources geared for the developing world and an open API providing access to all terminological resources;

  • Process and institutional interoperability: The solution supports the actual interoperability (process) through real-time data dictionary translations and guidelines for utilization, and minimizes institutional barriers through communities of practice that foster shared learning and guide terminology development and evolution, tool reuse and deployment.

Users can deploy OCL to facilitate data and data dictionary harmonization, information exchange, and reuse of analytics tools and approaches. By managing and sharing this information, communities of practice can to accelerate convergence on best practices for data and data dictionary harmonization, information exchange, and reuse of analytics tools and approaches. This toolset include innovative features that provide essential benefits to users at the facility and government level.