SMART: a service-oriented architecture for monitoring and assessing Brazil’s Telehealth outcomes

Paiva, Jailton Carlos de; Carvalho, Túlio de Paiva Marques; Vilela, Allyson Bruno Campos Barros; Nóbrega, Giovani Ângelo Silva da; Souza, Beatriz Soares de; Valentim, Ricardo Alexsandro de Medeiros

doi:10.1590/2446-4740.18004

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Research on Biomedical Engineering

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Original Article • Res. Biomed. Eng. 34 (4) • Oct 2018 • https://doi.org/10.1590/2446-4740.18004 copy

SMART: a service-oriented architecture for monitoring and assessing Brazil’s Telehealth outcomes

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Introduction

Brazilian Telehealth Program was instituted by the Ministry of Health in 2007. Its initial structure was composed by nine telehealth centers administered by public higher education institutions. No standards, processes, applications or quality indicators had been defined since its creation. All this, combined with the decentralization of the centers, led each one of them to develop their own system, with different programming languages and architectures. The lack of regulation and integration of the information with the Ministry of Health made it difficult to evaluate the program. In this context, this paper describes the specification, implementation and validation of an architecture, entitled SMART, to integrate the various telehealth platforms developed by the centers. Such architecture aims to standardize information so that the Ministry of Health can monitor and evaluate the results of Telehealth actions.

Methods

SMART’s architecture consists of four main components: a web tool for data manipulation; a web service to receive the center’s production data; a component responsible for converting the received data into decision support data; and a component that collects data from external sources to compose the data warehouse.

Results

The architecture was validated with performance tests, which were executed under extreme workloads. The results of the experiments were summarized in order to attest SMART’s effectiveness.

Conclusion

The analysis of the results obtained on real data shows that the project’s performance remained stable under the workloads and its high quality was proven due to the absence of errors during the experiments.

Keywords
Telehealth; Evaluation; Standardization; SOA; Integration; Interoperability

Database	Used terminology
CNES ¹ 1 National Registries of Health Services (CNES) updated by the Department of Health Informatics (DATASUS), whose function is to available information on the current conditions of the physical infrastructure and the functioning of the health services in the country.	CNES code for identification of the health establishment;
	(CPF of the health professional, CNES code and CBO code) to identify the health professional's affiliation;
	INE code to identify the health team;
IBGE ² 2 Brazilian Institute of Geography and Statistics (IBGE) is the agency responsible for the official collection of statistical, geographic, cartographic, geodetic and environmental information in Brazil.	IBGE Code to identify cities, federal units and regions of Brazil;
CBO ³ 3 Brazilian Classification of Occupations (CBO), identifier code of occupations in the job market for classificatory purpose to the administrative and domiciliary registries, available by the Ministry of Labor.	CBO code for identification of health professionals’ occupation and 4 first digits identify the occupation’s category;
ICD 10 ⁴ 4 International Statistical Classification of Diseases and Related Health Problems (ICD -10) is published by the World Health Organization (WHO) and aims to standardize the diseases codes and other problems related to health.	ICD Code 10 for classification of teleconsulting diseases;
ICPC 2 ⁵ 5 International Classification of Primary Care (ICPC 2). Its main objective is to classify issues related to people, not diseases. It allows the classification of both the problems diagnosed by health professionals and the reasons for the consultation and the answers.	ICPC 2 code for classification of teleconsulting diseases;
DeCS ⁶ 6 The trilingual and structured vocabulary DeCS - Health Sciences Descriptors - was created by the Latin American and Caribbean Center on Health Sciences Information (BIREME) for use in indexing articles from scientific, journals, books, congress proceedings, technical reports, and other types of materials, as well as for searching and retrieving subjects from the scientific literature in LILACS, MEDLINE and other data bases. of Bireme	DeCS Code to identify the themes of tele-education activities;
SIA/SIH ⁷ 7 Hospital and Outpatient Information System (SIH/SIA) updated by DATASUS. The SIA/SUS comprises data on the number of outpatient procedures that were performed under SUS coverage, either at the public or at the private network.	SIA/SIH code to classify the type of exam of the telediagnosis.

Type of activity	Average data volume		Maximum data volume
Type of activity	Number of records	Data size (MB)	Number of records	Data size (MB)
Teleconsulting	247	0.07	3812	1.04
Telediagnosis	11627	3.69	53195	14.25
Tele-education	295	0.04	3798	0.46

Type	User	RT (seconds)				PT (seconds)				TT (seconds)
Type	User	Min	Max	AVG	SD	Min	Max	AVG	SD	Min	Max	AVG	SD
TC	18	7.72	14.27	9.79	0.82	7.44	11.30	9.21	0.61	0.12	4.90	0.58	0.55
TC	36	11.94	27.59	20.43	2.22	7.54	11.66	9.47	0.59	2.06	18.19	10.96	2.19
TD	18	14.90	24.18	17.18	1.06	14.71	21.44	16.77	0.92	0.12	4.91	0.61	0.53
TD	36	19.26	36.25	28.03	2.35	15.23	21.44	17.12	0.91	1.52	18.23	10.91	2.16
TE	18	1.54	6.72	2.34	0.59	1.37	2.48	1.79	0.19	0.10	4.89	0.56	0.54
TE	36	5.93	19.61	12.77	2.15	1.43	2.82	1.85	0.17	4.13	17.63	10.92	2.14

Sociedade Brasileira de Engenharia Biomédica Centro de Tecnologia, bloco H, sala 327 - Cidade Universitária, 21941-914 Rio de Janeiro RJ Brasil, Tel./Fax: (55 21)2562-8591 - Rio de Janeiro - RJ - Brazil
E-mail: rbe@rbejournal.org

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[1] *Corresponding author: R. Dr. Nilo Bezerra Ramalho, 1692, Tirol, CEP 59015-300 Natal, RN, Brazil. E-mail: jailton.paiva@ifrn.edu.br