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      Towards evidence-based, GIS-driven national spatial health information infrastructure and surveillance services in the United Kingdom

      review-article
      1 ,
      International Journal of Health Geographics
      BioMed Central

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          Abstract

          The term "Geographic Information Systems" (GIS) has been added to MeSH in 2003, a step reflecting the importance and growing use of GIS in health and healthcare research and practices. GIS have much more to offer than the obvious digital cartography (map) functions. From a community health perspective, GIS could potentially act as powerful evidence-based practice tools for early problem detection and solving. When properly used, GIS can: inform and educate (professionals and the public); empower decision-making at all levels; help in planning and tweaking clinically and cost-effective actions, in predicting outcomes before making any financial commitments and ascribing priorities in a climate of finite resources; change practices; and continually monitor and analyse changes, as well as sentinel events. Yet despite all these potentials for GIS, they remain under-utilised in the UK National Health Service (NHS). This paper has the following objectives: (1) to illustrate with practical, real-world scenarios and examples from the literature the different GIS methods and uses to improve community health and healthcare practices, e.g., for improving hospital bed availability, in community health and bioterrorism surveillance services, and in the latest SARS outbreak; (2) to discuss challenges and problems currently hindering the wide-scale adoption of GIS across the NHS; and (3) to identify the most important requirements and ingredients for addressing these challenges, and realising GIS potential within the NHS, guided by related initiatives worldwide. The ultimate goal is to illuminate the road towards implementing a comprehensive national, multi-agency spatio-temporal health information infrastructure functioning proactively in real time. The concepts and principles presented in this paper can be also applied in other countries, and on regional (e.g., European Union) and global levels.

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          Most cited references117

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          Geographically masking health data to preserve confidentiality.

          The conventional approach to preserving the confidentiality of health records aggregates all records within a geographical area that has a population large enough to ensure prevention of disclosure. Though this approach normally protects the privacy of individuals, the use of such aggregated data limits the types of research one can conduct and makes it impossible to address many important health problems. In this paper we discuss the design and implementation of geographical masks that not only preserve the security of individual health records, but also support the investigation of questions that can be answered only with some knowledge about the location of health events. We describe several alternative methods of masking individual-level data, evaluate their performance, and discuss both the degree to which we can analyse masked data validly as well as the relative security of each approach, should anyone attempt to recover the identity of an individual from the masked data. We conclude that the geographical masks we describe, when appropriately used, protect the confidentiality of health records while permitting many important geographically-based analyses, but that further research is needed to determine how the power of tests for clustering or the strength of other associative relationships are adversely affected by the characteristics of different masks.
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            Primary care service areas: a new tool for the evaluation of primary care services.

            To develop and characterize utilization-based service areas for the United States which reflect the travel of Medicare beneficiaries to primary care clinicians. The 1996-1997 Part B and 1996 Outpatient File primary care claims for fee-for-service Medicare beneficiaries aged 65 and older. The 1995 Medicaid claims from six states (1995) and commercial claims from Blue Cross Blue Shield of Michigan (1996). A patient origin study was conducted to assign 1999 U.S. zip codes to Primary Care Service Areas on the basis of the plurality of beneficiaries' preference for primary care clinicians. Adjustments were made to establish geographic contiguity and minimum population and service localization. Generality of areas to younger populations was tested with Medicaid and commercial claims. Part B primary care claims were selected on the basis of provider specialty, place of service, and CPT code. Selection of Outpatient File claims used provider number, type of facility/service, and revenue center codes. The study delineated 6,102 Primary Care Service Areas with a median population of 17,276 (range 1,005-1,253,240). Overall, 63 percent of the Medicare beneficiaries sought the plurality of their primary care from within area clinicians. Service localization compared to Medicaid (six states) and commercial primary care utilization (Michigan) was comparable but not identical. Primary Care Service Areas are a new tool for the measurement of primary care resources, utilization, and associated outcomes. Policymakers at all jurisdictional levels as well as researchers will have a standardized system of geographical units through which to assess access to, supply, use, organization, and financing of primary care services.
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              Technical Description of RODS: A Real-time Public Health Surveillance System

              This report describes the design and implementation of the Real-time Outbreak and Disease Surveillance (RODS) system, a computer-based public health surveillance system for early detection of disease outbreaks. Hospitals send RODS data from clinical encounters over virtual private networks and leased lines using the Health Level 7 (HL7) message protocol. The data are sent in real time. RODS automatically classifies the registration chief complaint from the visit into one of seven syndrome categories using Bayesian classifiers. It stores the data in a relational database, aggregates the data for analysis using data warehousing techniques, applies univariate and multivariate statistical detection algorithms to the data, and alerts users of when the algorithms identify anomalous patterns in the syndrome counts. RODS also has a Web-based user interface that supports temporal and spatial analyses. RODS processes sales of over-the-counter health care products in a similar manner but receives such data in batch mode on a daily basis. RODS was used during the 2002 Winter Olympics and currently operates in two states—Pennsylvania and Utah. It has been and continues to be a resource for implementing, evaluating, and applying new methods of public health surveillance.
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                Author and article information

                Journal
                Int J Health Geogr
                International Journal of Health Geographics
                BioMed Central (London )
                1476-072X
                2004
                28 January 2004
                : 3
                : 1
                Affiliations
                [1 ]School for Health, University of Bath, Claverton Down, Bath BA2 7AY, UK
                Article
                1476-072X-3-1
                10.1186/1476-072X-3-1
                343292
                14748927
                275334ed-ad0d-4701-834f-2074877b9b8c
                Copyright © 2004 Boulos; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.
                History
                : 18 December 2003
                : 28 January 2004
                Categories
                Review

                Public health
                Public health

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