Development of Health Information System in TB Control Decision Support: Territoriality-Based Approach

Setyowati, Maryani; Setiyadi, Noor Alis; Suharyo, Suharyo; Febiyanto, Dwi Feri; Sudaryanto, Slamet

doi:10.4108/eai.22-7-2020.2300294

Cited by 4 publications

(3 citation statements)

References 4 publications

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“…55,56 A reporting system need to be established to identify import cases from neighboring villages or areas. 57,58 There are several same environmental factors between Jambi and Sumba, i.e., the existence of shrubs and puddles/ stagnant water surrounding the household area and the presence of livestock near the house area. Studies have found that bushes are a risk factor in a densely forested area and can encourage mosquitoes to breed.…”

Section: Discussionmentioning

confidence: 99%

Risk factors and housing effect on malaria infection: A case-control study

Setiyadi

Handayani²,

Sayono

et al. 2022

F1000Res

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Background: This study aims to demonstrate the different risk factors between low and high endemicity area and housing effect on malaria infection. Methods: This study is a case-control study with a ratio of 1:2 comparing low (Jambi) and high (Sumba) endemicity areas. Initial screening of malaria was done to assign cases and controls following inclusion criteria. The selected cases and controls were then assessed with a structured questionnaire in relation to risk factors of malaria infection. Additionally, to discover the impact of house type on malaria infection, a total of 72 houses was observed in a series of six weeks (between 28 June and 12 August 2018) human landing catch (HLC) observations that includes three types of houses; malaria, non-malaria, and permanent dwellings. The HLC was done indoors and outdoors for each house type each night. A weekly screening was taken to monitor the malaria infection rate of each house type. Results: Jambi and Sumba shared several similar individual and environmental risk factors. However, agricultural activity or visiting forestry areas is a protective factor for malaria infection in Jambi but is a risk factor in Sumba. The general linear mixed univariate model result indicates the difference in risk factor variables between Jambi and Sumba. The entomological survey found that only malaria houses significantly differed in the number of means collected mosquitoes compared with the other type of houses. Weekly screening found that the incidence rate of malaria houses is highest among others. Conclusion: The risk factors are inevitably crucial for malaria prevention strategy. Risk factor management needs to consider the location where the endemicity level may differ for each risk factor, and housing improvement is not a proper strategy before controlling other environmental factors.

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Section: Discussionmentioning

confidence: 99%

Risk factors and housing effect on malaria infection: A case-control study

Setiyadi

Handayani²,

Sayono

et al. 2022

F1000Res

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“…However, these systems remain disease-specific, fragmented, and unconsolidated. For example, the HIV and AIDS information system was implemented to integrate a HIV and AIDS recording and reporting system [5], the integrated TB information system [6], and registers for maternal and child health [7].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Integrated Information Systems in Community-based and School-based Public Health Surveillance

Hargono

Artanti²,

Syahrul³

et al. 2022

Open Access Maced J Med Sci

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BACKGROUND: The involvement of the community in supporting health programs requires an integrated information system. Public health registers obtained by the community means some data is collected repeatedly in different formats or leads to data redundancy. AIM: This research aims to analyze and design an integrated information system model of current community-based and school-based public health surveillance based on a system development life cycle approach. METHODS: Data analysis is carried out using content analysis. RESULTS: The results show that entities involved in the system include health cadres in Posyandu (an integrated health post for maternal and child health), Posbindu (an integrated development post of noncommunicable disease), and school health services. The necessary data include data on vital characteristics, maternal and child health, the risk factors of both communicable and noncommunicable diseases, students’ illness complaints, clean and healthy living behavior, mortality, and environmental health. Information obtained includes the health status of an individual, planning on pregnancy and labor, antenatal care visits, stunting data, immunization status, students’ illness complaints, the number of accidents, larva-free rate, and mortality rate. Information from the system is reported to public health centers, the district health office, and district education office. CONCLUSION: The output of the system is useful to complement the recording and reporting of data from health facilities.

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“…Masyarakat yang belum diperiksa dan diobati akan menjadi sumber penularan bagi orang di sekitarnya, sehingga dapat menyebabkan masalah TB tidak kunjung selesai. Besaran dan luasnya permasalahan akibat TB ini mengharuskan semua pihak untuk dapat berkomitmen dan bekerjasama dalam melakukan pencegahan dan pengendalian TB karena kerugian yang diakibatkannya sangat besar bukan hanya dari aspek kesehatan saja tetapi meliputi juga aspek sosial maupun ekonomi, sehingga TB masih menjadi ancaman terhadap cita-cita pembangunan untuk meningkatkan kesejahteraan rakyat secara menyeluruh sehingga perang terhadap TB berarti perang terhadap kemiskinan, ketidakproduktifan dan kelemahan akibat TB (K. Kesehatan & Indonesia, 2018) (Setyowati et al, 2020).…”

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Pelatihan Tenaga Kesehatan Tentang Digitalisasi Aplikasi Sensor Tb Untuk Pemantauan Pasien Tuberkulosis

Setyowati,

Kurniadi,

Manglapay

et al. 2023

JMM

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Abstrak: Kasus Tuberkulosis atau TB saat ini masih ditemukan terutama di Indonesia padahal target WHO untuk menurunkan insidens sebesar 80% pada tahun 2030. Sensor-TB merupakan nama untuk alat menggunakan aplikasi sensor dari tanda-tanda vital yang dimiliki oleh seseorang khususnya pada penderita TB positif. Tujuan kegiatan ini untuk meningkatkan pengetahuan tenaga kesehatan tentang penggunaan aplikasi sensor TB. Metode yang digunakan untuk kegiatan ini adalah sosialisasi dan pelatihan penggunaan Aplikasi Sensor TB untuk pemantauan Pasien Tuberkulosis. Adapun mitra yang terlibat adalah Pengelola Program TB Dinas Kesehatan Kabupaten Sukoharjo, Kepala Puskesmas, Programmer TB dan kader kesehatan Puskesmas Kartasura dan Puskesmas Bulu, Kabupaten Sukoharjo, Jawa Tengah sebanyak 13 Orang. Hasil yang dicapai menunjukkan bahwa Aplikasi Sensor-TB yang dibuat berupa bentuk gelang tangan telah dilakukan uji coba dengan menggunakan data pasien TB yang sesuai Puskesmas yang hadir, dan terjadi peningkatan pengetahuan tenaga kesehatan sebesar 100% dari sebelum dan sesudah pelatihan.Abstract: Cases of Tuberculosis or TB cases are currently still found mainly in Indonesia even though the WHO target is to reduce the incidence by 80% by 2030. The TB-Sensor is a tool that uses sensor applications of vital signs owned by a person, especially in people with positive TB. The purposethis activity is to improve the health workers knowledge about the use TB-sensor applications. . The method used for this activity is socialization and training on using Sensor TB Application for monitoring Tuberculosis Patients. The partners involved were the TB Program Manager of the Sukoharjo District Health Office, the Head of Puskesmas, the TB Programmer, and 13 health cadres of Puskesmas Kartasura and Puskesmas Bulu, Sukoharjo District, Central Java. The results show that the TB-Sensor Application made in the form of a hand bracelet has been tested using TB patient data according to the attending Puskesmas, and there is an increase in health workers' knowledge by 100% from before after training.

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Development of Health Information System in TB Control Decision Support: Territoriality-Based Approach

Cited by 4 publications

References 4 publications

Risk factors and housing effect on malaria infection: A case-control study

Risk factors and housing effect on malaria infection: A case-control study

Analysis of Integrated Information Systems in Community-based and School-based Public Health Surveillance

Pelatihan Tenaga Kesehatan Tentang Digitalisasi Aplikasi Sensor Tb Untuk Pemantauan Pasien Tuberkulosis

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