In this chapter we present an information system conceived for supporting managers of Public Health Care Agencies to decide the new health care services to propose. Our system is HL7-aware; in fact, it uses the HL7 (Health Level Seven) standard (Health Level Seven [HL7], 2007) to effectively handle the interoperability among different Public Health Care Agencies. HL7 provides several functionalities for the exchange, the management and the integration of data concerning both patients and health care services. Our system appears particularly suited for supporting a rigorous and scientific decision making activity, taking a large variety of factors and a great amount of heterogeneous information into account.
In the past years health care expenditure has significantly risen. As an example, a report of the Organization for Economic Cooperation and Development shows that, in the last years, US health expenditure grew 2.3 times faster than Gross Domestic Product (GDP), rising from 13% of GDP in 1997 to 14.6% of it in 2002 (Organisation for Economic Cooperation and Development [OECD], 2005); an analogous trend was observed in Western Europe, where health spending outpaced economic growth by 1.7 times on average.
Despite this large amount of funding, Public Health Care Agencies (hereafter PHCAs) have partially failed to keep pace with rapid changes in present societies. As an example, in the last decades, in many developed countries, both population size and the corresponding age distribution underwent to relevant changes due to low fertility rates and the continuous increase of life expectancy. Population ageing has deep both social and budgetary effects that compel PHCA managers to carefully plan resource and service allocation.
Disharmonious and unbalanced funding policies might imply redundancies/duplications of some services and lacks/deficiencies of other ones. As a consequence, patients might perceive a low quality in supplied services and unacceptable disparities in their delivery.
In this scenario, the real challenge consists of the efficient usage of available resources for providing patients with real benefits and for supporting health care managers to modernize PHCAs in such a way as to meet the expectations of a broad audience of users (e.g., patients, physicians). From a patient standpoint, this implies the possibility: (i) to access a comprehensive range of services through a friendly and uniform infrastructure; (ii) to access services tailored around his needs and preferences. From a PHCA manager point of view, this implies the possibility: (i) to successfully face severe financial constraints aiming at reducing the pressure of health care expenditure on public budget; (ii) to provide services for all in such a way as to avoid discrimination on the grounds of yearly income and social status.
A large body of evidence shows that, in order to effectively plan resource allocation in a PHCA, it is necessary to manage a large variety of socioeconomic and lifestyle data. This information is the core component of any decision support system operating at national, regional and local level (OECD, 2005).
A further problem to face concerns the representation and the storage of health-related data. Generally, medical information systems store their data in proprietary formats; this implies the lack of interoperability and coordination among independent PHCAs and, ultimately, undermines their effectiveness (Eichelberg, Aden, Riesmeier, Dogac, and Laleci 2005).
In the past, various approaches have been proposed for supporting PHCA managers in their decision making activities; many of them are agent-based. As an example:
Key Terms in this Chapter
E-Health: An emerging field in the intersection of medical informatics, public health and business, referring to health services and information delivered or enhanced through the Internet and related technologies. In a broader sense, the term characterizes not only a technical development, but also a state-of-mind, a way of thinking, an attitude, and a commitment for networked, global thinking, to improve health care locally, regionally, and worldwide by using information and communication technology.
Health Leven Seven (HL7): A standard series of predefined logical formats for packaging healthcare data in the form of messages to be transmitted among computers systems.
Clinical Document Architecture (CDA): An XML-based markup standard conceived to specify the encoding, structure and semantics of clinical documents in such a way as to make their exchange easy.
Logical Observation Identifiers Names and Codes (LOINC): A universal standard for allowing the electronic transmission of clinical data from medical laboratories to hospitals and surgeries. Each LOINC record has a code that can be used in HL7 messages. LOINC codes allow all sections of a CDA document to be codified; as a consequence, the usage of LOINC allows the production of CDA documents characterized by universally acknowledged codes..
Systematized Nomenclature of Medicine (SNOMED): The largest structured vocabulary used in medicine. All substantives, adjectives, eponyms, etc., concerning the medical language are stored in this vocabulary. SNOMED project was started in 1965 by the Committee on Nomenclature and Classification of Disease of the College of American Pathologysts. After various modifications, the current version of this vocabulary, called SNOMED CT (Clinical Terms), was produced.
Linear Programming Problem: Optimization problems in which the objective function and the constraints are all linear.
User Modeling: The process of gathering information specific to each user either explicitly or implicitly. This information is exploited to customize the content and the structure of a service to the user’s specific and individual needs.
User Profile: A model of a user representing both his preferences and his behaviour.
Extensible Markup Language (XML): The novel language, standardized by the World Wide Web Consortium, for representing, handling and exchanging information on the Web.