Integrated Continuous Healthcare Team Computer System Architecture

Integrated Continuous Healthcare Team Computer System Architecture

José Jasnau Caeiro (Instituto Politécnico de Beja, Portugal), Henrique Oliveira (Instituto de Telecomunicações, Instituto Superior Técnico, Portugal), Margarida Goes (Universidade Católica Portuguesa, Portugal), Manuel José Lopes (Universidade de Évora, Portugal) and César Fonseca (Universidade de Évora, Portugal)
Copyright: © 2020 |Pages: 16
DOI: 10.4018/978-1-7998-1937-0.ch013

Abstract

A computer-based pattern recognition system architecture destined to collect and process geographically referenced data about integrated continuous healthcare teams (ECCI) is presented and discussed in the chapter. These teams are part of Portugal's National Network of Integrated Continuous Care (RNCCI). The system is designed to collect data about the displacement of each team during healthcare assistance. The pattern recognition system handles information about the costs related to the provided healthcare. The architecture is designed around open source software resources. Virtual machines and container-based technologies provide hardware independence. The Python programming language ecosystem is chosen for all the main components of the system.
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Introduction

The no. 101/2006 Decree-law of Portugal (Government, 2006), creates the National Integrated Continued Healthcare Network, constituted by continued healthcare teams and units, and/or social support, and/or palliative care and actions. ECCI’s (Integrated Continued Healthcare Teams) are defined as multidisciplinary teams that provide domiciled primary healthcare and social services to people with functional dependencies, terminal illness or are undergoing a convalescence process. These people are in situation that doesn’t require them to be admitted but are unable to move autonomously. The ECCI teams may be constituted by a set of medical doctors, nurses, social workers and psychologists. All over the country there in was in the year 2016 a set of 279 teams (Administração Central do Sistema de Saúde, 2017)þ, see Table 1. There are a number of factors that contribute to the heterogeneity in terms of these teams such as:

  • •

    The Area Covered by Each Team: There are regions that are very large and rural thus making the ECCI team displacement an important cost issue. This is the case with the Alentejo and Center regions.

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    The Population Density: There are densely populated areas such as the North and Lisboa and Tejo Valley whereas other areas in the country are sparsely populated such as Alentejo and the Center.

  • •

    The Constitution of Each Team: Each team has a varying number of doctors, nurses and other staff.

Table 1.
Distribution of ECCI teams for each region of continental Portugal
RegionArea (Km2)InhabitantsNumber of ECCI teams
North21 2783 689 17384
Center28 4622 327 02666
Lisboa and Tejo Valley11 9303 447 17360
Alentejo31 551758 73937
Algarve4 997451 00632
Total92 21810 673 117279

Key Terms in this Chapter

Container Technology: An operating system level virtualization to develop and deliver software.

Pattern Recognition: The automatic detection of regularities in data using algorithms and the corresponding use of these regularities to perform actions.

Machine Learning: The scientific area that studies algorithms and mathematical models that computer systems may use to perform tasks relying on pattern recognition and inference.

Geographical Information System: A system designed to capture store, manipulate, and analyze geographic data.

Virtual Machine: An emulation of a computer system. Virtual machines provide the functions of a physical machine. They may use special hardware or software to enhance their performance.

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