Abstract:INTRODUÇÃO: projeções mostram que em 2020, os idosos constituirão cerca de 13% da população brasileira. Esta transformação não é apenas demográfica, mas também epidemiológica. Há real necessidade de maior compreensão da prevalência de determinadas doenças na faixa etária geriátrica. OBJETIVO: avaliar queixas e diagnósticos em coloproctologia mais prevalentes na população acima de 60 anos, comparando-os com os de idade inferior. Avaliar o número de idosos encaminhados a procedimentos cirúrgicos, suas comorbidad… Show more
“…Because of the presented issues and the importance of DQ for the processes that use them, steps (2) and (3) resulted in the project of a prototype to manage data on coloproctological surgery. As a guide to properly build this prototype, the Electronic Health Records Certificate (Manual de Certificação para Sistemas de Registro Eletrônico em Saúde), approved by the resolution 1821/07 of the Federal Council of Medicine 24 , presents several guidelines for the development of the project.…”
Section: Discussionmentioning
confidence: 99%
“…According to this point of view, in the health field it is necessary to manage information on different aspects of a patients for the performance of a surgical procedure; more specifically, in coloproctology, this specialty comprises various diseases that can be treated with surgery, such as cancer, adenomatous polypo-sis, Chron's disease, among others [1][2][3][4][5][6] . Thus, an information system may significantly contribute with the management of data concerning surgery, that is, pre-, inter and postoperative periods, enabling the construction of a solid and organized database.…”
Section: Introductionmentioning
confidence: 99%
“…Nowadays, the Coloproctology service at the School of Medical Sciences (FCM) of Universidade Estadual de Campinas (UNICAMP) uses a system developed with Microsoft Acess (2) to register the surgeries performed in this service. However, this system, which was later called the legacy system, presents limitations and inconsistencies, thus not meeting all the users' needs, which impacts directly on the quality of the stored data.…”
Objective: To develop a prototype system to manage data on coloproctology surgery, aiming at Data Quality (DQ) and the adoption of a DQ monitoring process, which is nonexistent in most biomedical systems. Methods: The construction of the prototype was separated into five steps: analysis of an existing system (legacy), the analysis of requirements and specifications for the new prototype, the development of the model, definition of technologies and the development of a prototype. Results: The analysis of the legacy system revealed several limitations and inconsistencies, which can result in problems concerning the DQ. Therefore, actions to prevent these problems are already being executed at the step of developing the prototype, such as the creation of interactive and more elaborate interfaces, the use of validation mechanisms on data fields and the proposal of a process to monitor inconsistencies and incompleteness in patients' data. Conclusion: The adoption of DQ mechanisms on system development results in building a reliable and consistent database, to assist tasks such as management, scientific research and future intelligent data analysis methods. Future work includes subjective evaluations of DQ indicating the adequacy of the prototype for the users' needs.
“…Because of the presented issues and the importance of DQ for the processes that use them, steps (2) and (3) resulted in the project of a prototype to manage data on coloproctological surgery. As a guide to properly build this prototype, the Electronic Health Records Certificate (Manual de Certificação para Sistemas de Registro Eletrônico em Saúde), approved by the resolution 1821/07 of the Federal Council of Medicine 24 , presents several guidelines for the development of the project.…”
Section: Discussionmentioning
confidence: 99%
“…According to this point of view, in the health field it is necessary to manage information on different aspects of a patients for the performance of a surgical procedure; more specifically, in coloproctology, this specialty comprises various diseases that can be treated with surgery, such as cancer, adenomatous polypo-sis, Chron's disease, among others [1][2][3][4][5][6] . Thus, an information system may significantly contribute with the management of data concerning surgery, that is, pre-, inter and postoperative periods, enabling the construction of a solid and organized database.…”
Section: Introductionmentioning
confidence: 99%
“…Nowadays, the Coloproctology service at the School of Medical Sciences (FCM) of Universidade Estadual de Campinas (UNICAMP) uses a system developed with Microsoft Acess (2) to register the surgeries performed in this service. However, this system, which was later called the legacy system, presents limitations and inconsistencies, thus not meeting all the users' needs, which impacts directly on the quality of the stored data.…”
Objective: To develop a prototype system to manage data on coloproctology surgery, aiming at Data Quality (DQ) and the adoption of a DQ monitoring process, which is nonexistent in most biomedical systems. Methods: The construction of the prototype was separated into five steps: analysis of an existing system (legacy), the analysis of requirements and specifications for the new prototype, the development of the model, definition of technologies and the development of a prototype. Results: The analysis of the legacy system revealed several limitations and inconsistencies, which can result in problems concerning the DQ. Therefore, actions to prevent these problems are already being executed at the step of developing the prototype, such as the creation of interactive and more elaborate interfaces, the use of validation mechanisms on data fields and the proposal of a process to monitor inconsistencies and incompleteness in patients' data. Conclusion: The adoption of DQ mechanisms on system development results in building a reliable and consistent database, to assist tasks such as management, scientific research and future intelligent data analysis methods. Future work includes subjective evaluations of DQ indicating the adequacy of the prototype for the users' needs.
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