STUDYING SOCIAL INFORMATICS

Studying Social Informatics 'in the wild'

Studying Social Informatics 'in the wild'

Introduction

“Public health surveillance (PHS) is the ongoing and systematic collection, analysis, interpretation, and dissemination of data regarding health-related events to enable public health personnel to reduce morbidity and mortality and to promote public health.”1 PHS has attracted the attention of informaticians in recent years and important initiatives have been founded to create PHS standards, protocols, guidelines, and best practices. These include the U.S. Centers for Disease Control and Prevention's (CDC) Public Health Information Network (PHIN) initiative.

PHIN is intended to elevate and integrate the capabilities of information systems across various public health organizations and interrelated public health needs. To fulfill the vision of PHIN, PHS systems will need to interoperate with other systems that support disease surveillance, national health status indicator reporting, data analysis, public health decision support, knowledge management, alerting and notification, and assist in public health response management. Because PHIN focuses on introducing and prioritizing the functional requirements, capabilities, performance measures, and operational characteristics of public health systems, it leaves open the enabling approaches, methodologies, conceptualization of the IT infrastructures needed to implement its requirements. For instance, although the use of controlled vocabularies is frequently recommended throughout the PHIN documentation, there is no discussion of methods for representing, mapping and mediating, translating, or extending these vocabularies to support different local use cases, as they interoperate with federal and regional mandates(Zhang, 2002,, 42).

As public health systems rely on clinical data and reports from various health care providers as inputs (e.g., patient records from hospitals and outpatient clinics, clinical laboratory test results), PHIN calls for a tighter integration of PHS systems with electronic health record (EHR) systems to enable timely and reliable information exchange.8 This is also a call for informaticians to discuss the theoretical and practical implications of the construction, transport, transformation, integration, and interpretation of messages exchanged among disparate information systems, each of which having significant structural and semantic differences from the others.

For instance, the field should address questions such as “How can ICD9-CT codes recorded for billing purposes be integrated with SNOMED CT codes recorded for documentation of patients' health status?”, and “How data from clinical systems can be integrated with local health status indicators, surveys, and field reports that are not coded with any standard vocabulary?”, and “How this process can be validated and automated to scale for practical use?”.

Significance of Study

Frequently, the significance of the collected data may not be immediately clear, so public health officials use epidemiological investigation techniques to answer questions about the existence and nature of, causes of, and associations among observed patterns or aberrations in data. This allows them to develop hypotheses and rationale for disseminating public health alerts. Because each public health event is unique in nature, PHS systems face unique requirements concerning the type, complexity, and heterogeneity of data they must be prepared to process. However, the minimum set of data needed to support effective hypothesis building for a given PHS application has always been a ...