Link2Outcome: Coordinating Social Care and Health Care using Semantic Web Technologies - overview


Link2Outcome is a semantic infrastructure to augment existing enterprise applications with context coming from external systems. We showcase our infrastructure using a use-case around Care Coordination, based on a set of IBM solutions. Navigate across different use-cases and components on the left.

Introduction

Healthcare and Social Care are unique domains in terms of cultural importance, economic magnitude and complexity. On a cultural level, the level of advancement of a society is often measured in terms of protection of the less able. In economic terms, for 2009, total expenditure on healthcare in the United States was 2.6 trillion USD or 17.4% of the GDP. Total expenditure on social care was 2.98 trillion USD or 19.90% of the GDP. In terms of US Federal government expenditure, social security, medicare and medicaid amount to 45% of total spending. In terms of complexity, organizations that are involved in providing social and medical care are numerous and span a very wide domain. For example, AHIP, the trade association of health insurers numbers some 1300 members; the number of hospitals registered with the American Hospital Association is 5724 and the number of homeless shelters surpasses 4000. In addition, medical information is vastly complex: Nuance reports that LinkBase contains more than 1 million concepts. Social care depends on information from a very broad domain, ranging from criminal records to housing.

Coordinating social care and health care has been identified both as a major pain point and a significant opportunity in modern health and social systems. Several studies have shown that costs can be contained and outcomes improved with a more holistic approach to care. As a simple motivating example, consider an individual quartered in inappropriate housing while suffering from a relatively minor health issue, aggravated by the housing condition. As a result, the given individual frequently resorts to visiting emergency rooms, resulting in significant cost to the healthcare system and a less effective treatment. By itself, the housing situation does not warrant state intervention. Nevertheless, resolving it would dramatically improve the health situation, resulting in a better quality-of-life for the individual and lower costs for the health system.

Even in this simple example, the challenges presented are significant:

  • How do we access information in disparate systems, storing vastly heterogeneous information on various infrastructures?
  • How do we cope with policy constraints disallowing replication or centralization of data?
  • How do we abstract from the information and representation complexity?

We propose a novel technical solution to augment applications with cross-domain context, in the domain of social care and health care based on business rules and contextual exploration. We claim that Semantic Technologies can uniquely address these problems because:

  • The distributed nature of RDF allows access to integrated information across silos.
  • Explicit and global semantics allow us to ground business rules across systems.
  • The distributed and incremental data integration paradigm advocated by linked data can help coping with the complexity of the data.

We present a demonstrator of a system that supports two key use-cases for this domain:

  • Displaying a view of the combined needs across several dimensions for a given person and people in their social context, based on a set of business rules. This allows a social/health worker to quickly assess the situation of an individual. From a knowledge management perspective, it requires grounding a set of business rules across several ontologies and instance data in several data sources.
  • Exploration of the context to surface information not directly covered by the business rules. Given the heterogeneity of the domain, the user will most likely need additional information around a given individual. Our demonstrator uses the business rules as a navigational aid to explore the semi-structured information.