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Dehnavieh, Reza, AliAkbar Haghdoost, Ardeshir Khosravi, et al. "The District Health Information System (DHIS2): A literature review and meta-synthesis of its strengths and operational challenges based on the experiences of 11 countries." Health Information Management Journal 48, no. 2 (2018): 62–75. http://dx.doi.org/10.1177/1833358318777713.
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Background: Health information systems offer many potential benefits for healthcare, including financial benefits and for improving the quality of patient care. The purpose of District Health Information Systems (DHIS) is to document data that are routinely collected in all public health facilities in a country using the system. Objective: The aim of this study was to examine the strengths and operational challenges of DHIS2, with a goal to enable decision makers in different counties to more accurately evaluate the outcomes of introducing DHIS2 into their particular country. Method: A review of the literature combined with the method of meta-synthesis was used to source information and interpret results relating to the strengths and operational challenges of DHIS2. Databases (Embase, PubMed, Scopus and Google Scholar) were searched for documents related to strengths and operational challenges of DHIS2, with no time limit up to 8 April 2017. The review and evaluation of selected studies was conducted in three stages: title, abstract and full text. Each of the selected studies was reviewed carefully and key concepts extracted. These key concepts were divided into two categories of strengths and operational challenges of DHIS2. Then, each category was grouped based on conceptual similarity to achieve the main themes and sub-themes. Content analysis was used to analyse extracted data. Results: Of 766 identified citations, 20 studies from 11 countries were included and analysed in this study. Identified strengths in the DHIS were represented in seven themes (with 21 categories): technical features of software, proper management of data, application flexibility, networking and increasing the satisfaction of stakeholders, development of data management, increasing access to information and economic benefits. Operational challenges were identified and captured in 11 themes (with 18 categories): funds; appropriate communication infrastructure; the need for the existence of appropriate data; political, cultural, social and structural infrastructure; manpower; senior managers; training; using academic potentials; definition and standardising the deployment processes; neglect to application of criteria and clinical guidelines in the use of system; data security; stakeholder communications challenges and the necessity to establish a pilot system. Conclusion: This study highlighted specific strengths in the technical and functional aspects of DHIS2 and also drew attention to particular challenges and concerns. These results provide a sound evidence base for decision makers and policymakers to enable them to make more accurate decisions about whether or not to use the DHIS2 in the health system of their country.
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Bhatt, Prakash Raj, Rabindra Bhandari, Shiksha Adhikari, and Nand Ram Gahatraj. "Health professionals’ experience on District Health Information System (DHIS2) and its utilization at local levels in Gandaki province, Nepal: A qualitative study." PLOS Global Public Health 4, no. 3 (2024): e0002890. http://dx.doi.org/10.1371/journal.pgph.0002890.
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DHIS2 is a web-based platform primarily used in developing countries, ensuring reliable data and aiding decentralized decision-making. The Ministry of Health and Population has greatly emphasized using DHIS2 for data entry and reporting. However, studies regarding health workers’ experiences on DHIS2 and the utilization of data at the local level remain limited. Therefore, this study aims to investigate the usage and practical experience of DHIS2 at the local levels of Gandaki province, Nepal. An exploratory qualitative study was conducted in the Gandaki province from February to August 2023. We conducted twenty in-depth interviews among the DHIS2 users at local levels, health posts, and provincial health directorate using in-depth interview guidelines. The study participants were selected purposively. Thematic analysis was conducted to analyze the data, and NVivo was used to facilitate data analysis. Health professionals demonstrated dedication and commitment to use DHIS2 for reporting. DHIS2 has facilitated timely reporting, data storage, data analysis and visualization, feedback and communication mechanisms, and service delivery. Users’ self-motivation and support from the local and provincial levels and regular review and program-specific review meetings were major facilitators for DHIS2 use. Similarly, technical issues, poor internet connectivity, power outages, and inexperienced health professionals were the significant challenges to using DHIS2. The basic and refresher training needed improvement at all levels, and learning materials were unavailable in health facilities. In addition, the data utilization at the local level in various actions was unsatisfactory despite sufficient data. Health professionals have been facilitated by DHIS2 in various actions. Capacity building of health professionals on data analysis and interpretations, continued onsite coaching, reliable internet connectivity, availability of learning materials, and improved server capacity are needed to enhance the performance of DHIS2 at the local level.
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Usifoh, Nnamdi, Toby Yak, Ivy Dooga, et al. "Measles Data Reporting in the District Health Information System: A Case Study of Gombe State." Global Journal of Health Science 11, no. 11 (2019): 109. http://dx.doi.org/10.5539/gjhs.v11n11p109.
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BACKGROUND: The District Health Information System (DHIS2) is a modular, cloud-based data management system designed for use in integrated health information systems. In Nigeria, it serves as the repository for routine health data, including measles. A first dose of measles is given routinely in most countries, however, for a country to include a second dose of measles in the routine immunization schedule, it must meet certain criteria set by the World Health Organization (WHO). Unfortunately, Nigeria falls into the category of countries that haven’t met the criteria. Despite this, MCV2 data can be seen on the DHIS2 platform. Data from DHIS2 also shows that Gombe State has the highest number of health facilities that reported MCV2 data at least once from 2015 to 2017.
 
 The aim of the study was to determine the reasons for the MCV2 reporting on DHIS2 platform for Gombe State. 
 
 METHOD: We conducted a cross-sectional study among health workers in selected health facilities and LGA RI Officers at the LGA level in Gombe State. Health facility registers were reviewed, and data consistency was ascertained. We reviewed and conducted secondary data analysis of MCV2 data for Gombe State from January 2015 to December 2017.
 
 RESULTS: Of the 22 health facilities assessed, 14 health facilities (12 public and 2 private) reported offering MCV2 during the health facility-level interviews. At the LGA level, 5 LGAs out of the 11 LGAs reported during the LGA-level interviews that a second dose of measles is part of the RI schedule in their respective LGAs. For the 6 LGAs that reported not offering a second dose of measles as part of the RI schedule, 3 LGAs identified data entry error as the possible reason for having MCV2 data in the DHSI2 platform while the remaining 3 LGAs reported that the MCV2 data in the DHIS2 platform can be attributed to recording children who didn’t receive a first dose of measles at 9 months but received at 18–23 months as second dose of measles.
 
 CONCLUSION: Data entry error and knowledge gap on how to record measles data were identified factors responsible for MCV2 data on the DHIS2 platform. There is a need for targeted interventions towards improving the quality of RI data in Nigeria.
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Ihekweazu, Chikwe, Paulinus Ossai, Robinson Nnaji, Ugochukwu Osigwe, and Mba Ngozi. "Interoperability of Surveillance Data Collection Tools (District Health Information System 2 and District Vaccine Data Management Tools) in Enugu State, Nigeria, From 2015-2018." Iproceedings 5, no. 1 (2019): e15235. http://dx.doi.org/10.2196/15235.
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Background Over the years, Nigeria has used District Vaccine Data Management Tool (DVDMT) for surveillance data collection including routine immunization. In 2012, Nigeria adopted District Health Information Software (DHIS2), a Java driving online real-time tool for data collection. In 2015, Enugu State commenced the use of DHIS2 alongside the traditional DVDMT as surveillance data capturing tools. Objective The objective was to carry out an evaluation of the two surveillance data tools to assess surveillance attributes, interoperability, effect in decision making, and preference of use. Methods We quantitatively and qualitatively assessed surveillance attributes of Enugu State’s DHIS2 and DVDMT from 2015 to 2018 using adapted CDC guidelines (2001). We administered semi-structured questionnaires to all 17 local immunization officers from the 17 local government areas (districts) to assess surveillance attributes. We carried out desk review at all levels, key informants done with 6 purposefully selected stakeholders, and focused group discussion carried out with 6 randomly selected heads of surveillance at local governments areas. We recorded proportions, interoperability, effect in decision making, and preference of use. Results Average completeness of data is 100% in both DHIS2 and DVDMT systems (target 90%). Eligibility is 100% in DHIS2 and 85% in DVDMT (target 80%). Timeliness of reporting is 100% and 80% in DHIS2 and DVDMT, respectively (target 80%). All stakeholders accepted both tools and agreed that they are simple and flexible. In addition to collection of all data recorded by DVDMT, DHIS2 captures vaccine utilization. Data collection and transmission of DVDMT and DHIS2 are carried out by the same surveillance personnel at health facility and local government area levels. Apart from vaccine utilization both tools can complement each other in case of missed data as they record the same thing. All key informants opined that it is double work managing the two tools and also agreed that DHIS2 is better than DVDMT in decision making because it has features for data visualization and real-time reporting. The focused group discussion agreed that both tools are good, although DVDMT is easier to work with as DHIS2 requires computer proficiency of current users alongside hardware management of the Java-enabled phones used in data capture and transmission. However, they also agreed that DHIS2 usage is less time consuming and opined they will prefer to use DHIS2 as the only data capturing tool in Enugu State if proper capacity building is done. Conclusions The DHIS2 and DVDMT surveillance data tools in Enugu State is meeting all its targets based on surveillance attributes, though DHIS2 provides better quality data. There is a good understanding and synergy in operation of the two systems in all levels and intermittently data from both tools can be compared. DHIS2 can enable prompt decision making than DVDMT as data can be assessed and visualized in real time. Surveillance officers prefer the use of DHIS2 as the only surveillance tool in Enugu State, although proficiency is a challenge. We recommended a gradual phase out of DVDMT for data capturing in Enugu State, while capacity building of users for DHIS2 should be addressed.
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Hanifah, Ni'mah, Guardian Yoki Sanjaya, Nuryati Nuryati, Aprisa Chrysantina, Niko Tesni Saputro, and Mardiansyah Mardiansyah. "Using District Health Information System (DHIS2) for Health Data Integration in Special Region of Yogyakarta." Jurnal Pengabdian kepada Masyarakat (Indonesian Journal of Community Engagement) 8, no. 1 (2022): 48. http://dx.doi.org/10.22146/jpkm.40379.
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A number of applications have been used for managing health data and information and tend to be fragmented between health programs in health offices. In consequence, the analysis and interpretation process becomes difficult since the data is scattered in separate sources. One of the solutions offered as an effort to synchronize and integrate health data in Indonesia is through implementing District Health Information Software (DHIS2). DHIS2 is an application that emphasizes data integration at the health office level. Faculty of Medicine, Public Health and Nursing UGM has been partnered with the Special Region of Yogyakarta Health Office to carry out community service activities in the context of utilizing DHIS2 for health data integration in the province. The implementation of DHIS2 was divided into 4 stages, namely workshop on data availability, socialization, and training of DHIS2; data mapping and customizing DHIS2; implementing health data integration; and dissemination, supervision, and evaluation. Six health offices were the target of community service activities in the province. DHIS2 has facilitated health office staff to analyse and visualize health information that is used for decision making and advocacy. This community service activity supports the government’s efforts to provide one-stop data and contributes to strengthening health information systems both nationally and regionally.
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Kanfe, Shuma G., Berhanu F. Endehabtu, Mohammedjud H. Ahmed, Nebyu D. Mengestie, and Binyam Tilahun. "Commitment Levels of Health Care Providers in Using the District Health Information System and the Associated Factors for Decision Making in Resource-Limited Settings: Cross-sectional Survey Study." JMIR Medical Informatics 9, no. 3 (2021): e23951. http://dx.doi.org/10.2196/23951.
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Background Changing the culture of information use, which is one of the transformation agendas of the Ministry of Health of Ethiopia, cannot become real unless health care providers are committed to using locally collected data for evidence-based decision making. The commitment of health care providers has paramount influence on district health information system 2 (DHIS2) data utilization for decision making. Evidence is limited on health care providers’ level of commitment to using DHIS2 data in Ethiopia. Therefore, this study aims to fill this evidence gap. Objective This study aimed to assess the levels of commitment of health care providers and the factors influencing their commitment levels in using DHIS2 data for decision making at public health care facilities in the Ilu Aba Bora zone of the Oromia national regional state, Ethiopia in 2020. Methods The cross-sectional quantitative study supplemented by qualitative methods was conducted from February 26, 2020 to April 17, 2020. A total of 264 participants were approached. SPSS version 20 software was used for data entry and analysis. Descriptive and analytical statistics, including bivariable and multivariable analyses, were performed. Thematic analysis was conducted for the qualitative data. Results Of the 264 respondents, 121 (45.8%, 95% CI 40.0%-52.8%) respondents showed high commitment levels to use DHIS2 data. The variables associated with the level of commitment to use DHIS2 data were found to be provision of feedback for DHIS2 data use (adjusted odds ratio [AOR] 1.85, 95% CI 1.02-3.33), regular supervision and managerial support (AOR 2.84, 95% CI 1.50-5.37), information use culture (AOR 1.92, 95% CI 1.03-3.59), motivation to use DHIS2 data (AOR 1.80, 95% CI 1.00-3.25), health needs (AOR 3.96, 95% CI 2.11-7.41), and competency in DHIS2 tasks (AOR 2.41, 95% CI 1.27-4.55). Conclusions In general, less than half of the study participants showed high commitment levels to use DHIS2 data for decision making in health care. Providing regular supportive supervision and feedback and increasing the motivation and competency of the health care providers in performing DHIS2 data tasks will help in promoting their levels of commitment that can result in the cultural transformation of data use for evidence-based decision making in health care.
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Yilma, Tesfahun Melese, Asefa Taddese, Adane Mamuye, et al. "Maturity Assessment of District Health Information System Version 2 Implementation in Ethiopia: Current Status and Improvement Pathways." JMIR Medical Informatics 12 (July 26, 2024): e50375. http://dx.doi.org/10.2196/50375.
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Background Although Ethiopia has made remarkable progress in the uptake of the District Health Information System version 2 (DHIS2) for national aggregate data reporting, there has been no comprehensive assessment of the maturity level of the system. Objective This study aims to assess the maturity level of DHIS2 implementation in Ethiopia and propose a road map that could guide the progress toward a higher level of maturity. We also aim to assess the current maturity status, implementation gaps, and future directions of DHIS2 implementation in Ethiopia. The assessment focused on digital health system governance, skilled human resources, information and communication technology (ICT) infrastructure, interoperability, and data quality and use. Methods A collaborative assessment was conducted with the engagement of key stakeholders through consultative workshops using the Stages of Continuous Improvement tool to measure maturity levels in 5 core domains, 13 components, and 39 subcomponents. A 5-point scale (1=emerging, 2=repeatable, 3=defined, 4=managed, and 5=optimized) was used to measure the DHIS2 implementation maturity level. Results The national DHIS2 implementation’s maturity level is currently at the defined stage (score=2.81) and planned to move to the manageable stage (score=4.09) by 2025. The domain-wise maturity score indicated that except for ICT infrastructure, which is at the repeatable stage (score=2.14), the remaining 4 domains are at the defined stage (score=3). The development of a standardized and basic DHIS2 process at the national level, the development of a 10-year strategic plan to guide the implementation of digital health systems including DHIS2, and the presence of the required competencies at the facility level to accomplish specific DHIS2-related tasks are the major strength of the Ministry of Health of Ethiopia so far. The lack of workforce competency guidelines to support the implementation of DHIS2; the unavailability of core competencies (knowledge, skills, and abilities) required to accomplish DHIS2 tasks at all levels of the health system; and ICT infrastructures such as communication network and internet connectivity at the district, zonal, and regional levels are the major hindrances to effective DHIS2 implementation in the country. Conclusions On the basis of the Stages of Continuous Improvement maturity model toolkit, the implementation status of DHIS2 in Ethiopia is at the defined stage, with the ICT infrastructure domain being at the lowest stage as compared to the other 4 domains. By 2025, the maturity status is planned to move from the defined stage to the managed stage by improving the identified gaps. Various action points are suggested to address the identified gaps and reach the stated maturity level. The responsible body, necessary resources, and methods of verification required to reach the specified maturity level are also listed.
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Zerfu, Taddese Alemu, Moges Asressie, Zenebu Begna, et al. "Unveiling the role of DHIS2 in enhancing data quality and accessibility in primary healthcare facilities: Evidence from Ethiopia." PLOS ONE 19, no. 12 (2024): e0314505. https://doi.org/10.1371/journal.pone.0314505.
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Background The implementation of DHIS2 in healthcare systems has transformed data management practices worldwide. However, its specific impact on data quality, availability, and performance in Primary Health Unit (PHU) facilities in Ethiopia remains underexplored. Therefore, we investigated the contribution of DHIS2 to enhancing data quality, availability, and performance within PHU facilities in Ethiopia. Methods We employed qualitative methods, specifically Key Informant Interviews (KIIs) and Focus Group Discussions (FGDs), to gather insights from stakeholders, including healthcare providers and administrators at PHCUs across Ethiopia. Convenience sampling was used for FGDs, while purposive sampling targeted key informants with relevant expertise. Data were systematically analysed thematically, identifying patterns and themes related to DHIS2’s impact on data management within PHUs. This approach offered a comprehensive understanding of the system’s effectiveness and the factors influencing its implementation, highlighting both successes and challenges in integrating DHIS2 into healthcare practices. Findings Participants from various regions reported significant enhancements in the timeliness, completeness, accuracy, and accessibility of health data following the implementation of DHIS2. While some concerns were raised regarding variations in reporting intervals, the consensus indicated marked improvements in data management processes. DHIS2 standardized data collection methods, enabling healthcare providers to input and access data in real-time. This advancement fostered greater accountability and transparency within the healthcare system. Additionally, unexpected benefits arose, including increased digital literacy among staff, equipping them with necessary skills for effective data management, and the creation of job opportunities, particularly for youth. Ultimately, DHIS2 emerged as a pivotal tool for enhancing data quality and promoting health service equity across Ethiopia. Conclusion DHIS2 has significantly improved data quality and accessibility in Ethiopia, enhancing healthcare management and accountability across facilities. Healthcare providers should continue to leverage its robust features and prioritize ongoing staff training to improve digital literacy and data management skills. Establishing consistent reporting practices and regular audits will further maintain data integrity and foster a culture of accountability within the healthcare system.
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Saputro, Niko Tesni. "Integrasi data berbasis program kesehatan di dinas kesehatan daerah istimewa yogyakarta." Journal of Information Systems for Public Health 6, no. 2 (2021): 9. http://dx.doi.org/10.22146/jisph.44495.
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Latar Belakang: Disintegrasi data kesehatan masih terjadi tidak hanya di tingkat pusat, melainkan juga di tingkat provinsi hingga kabupaten/kota, termasuk di dinas kesehatan di Daerah Istimewa Yogyakarta. Disintegrasi data bisa berdampak terhadap kualitas kebijakan kesehatan yang dihasilkan, maka perlu dilakukan integrasi data. WHO menyerukan penggunaan data repository untuk integrasi data. DHIS2 hadir sebagai data repository yang dapat memenuhi kebutuhan daerah dan pusat. Belum pernah dilakukan penelitian terkait integrasi data berbasis program kesehatan di dinas kesehatan di Daerah Istimewa Yogyakarta, khususnya menggunakan aplikasi DHIS2.Tujuan: Mengeksplorasi proses integrasi data berbasis program kesehatan di dinas kesehatan tingkat provinsi maupun kabupaten/kota di Daerah Istimewa Yogyakarta.Metode : Jenis penelitian yang digunakan adalah penelitian action research. Penelitian ini dilakukan di Dinas Kesehatan Daerah Istimewa Yogyakarta, juga termasuk dinas kesehatan kabupaten/kota di Daerah Istimewa Yogyakarta. Penelitian ini dilakukan pada bulan Juli 2018 - Februari 2019.Hasil: Rangkaian kegiatan integrasi data menggunakan aplikasi DHIS2 dilaksanakan dengan melibatkan pengelola program kesehatan di masing-masing dinas kesehatan dalam tiga tahapan kegiatan, meliputi: tahapan sosialisasi, pelatihan dan analisis kebutuhan, tahapan pengembangan dan tahapan diseminasi dan evaluasi. Sumber data yang terkumpulkan pada tahapan analisis kebutuhan, sosialisasi dan pelatihan meliputi KIA, Gizi, Surveilans, SDMK, Promkes, Keswa, LB1 dan LB4, Imunisasi, Diare, ISPA dan DBD. Masih ada kendala teknis yang apabila tidak diatasi, maka akan menambah waktu yang diperlukan untuk integrasi data menggunakan aplikasi DHIS2, yakni tata desain formulir pelaporan rutin belum terstandar. Kendala non-teknis yang utama yakni terkait standarisasi dan regulasi tertulis yang mengatur tentang integrasi data.Kesimpulan: Integrasi data berbasis program kesehatan di Dinas Kesehatan Daerah Istimewa Yogyakarta dilaksanakan melalui strategi berupa pelaksanaan pertemuanpertemuan dalam rangkaian kegiatan integrasi data menggunakan aplikasi DHIS2. Terdapat kendala-kendala pada pelaksanaan kegiatan integrasi data menggunakan aplikasi DHIS2 yang dapat dikelompokkan menjadi kendala teknis dan kendala non-teknis. Solusi untuk masing-masing kendala pada pelaksanaan kegiatan integrasi data menggunakan aplikasi DHIS2 perlu dilakukan. Diperlukan peningkatan atau perbaruan strategi integrasi data yang dapat dilakukan pada siklus selanjutnya. Kata Kunci: Integrasi, Program Kesehatan, DHIS2
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Ndlovu, Kagiso, Kabelo Leonard Mauco, Mpho Keetile, et al. "Acceptance of the District Health Information System Version 2 Platform for Malaria Case-Based Surveillance By Health Care Workers in Botswana: Web-Based Survey." JMIR Formative Research 6, no. 3 (2022): e32722. http://dx.doi.org/10.2196/32722.
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Background Similar to many low- and middle-income countries, Botswana has identified eHealth as a means of improving health care service provision and delivery. The National Malaria Programme (NMP) in Botswana has implemented the District Health Information System version 2 (DHIS2) to support timely malaria case reporting across its 27 health districts; however, the implementation of an eHealth system is never without challenges. Barriers to the implementation of eHealth innovations within health care settings may arise at the individual or organizational levels. As such, the evaluation of user perceptions of the technology is an important step that can inform its sustainable implementation. The DHIS2 was implemented without evaluating user perceptions beforehand; therefore, the Botswana Ministry of Health and Wellness was uncertain about the likelihood of acceptance and use of the platform. Objective We aimed to determine the acceptance of the DHIS2 platform by the NMP in Botswana to gauge whether adoption would be successful. Methods The study’s design was informed by constructs of the technology acceptance model. A survey, with items assessed using a 7-point Likert scale, and focus group discussions were undertaken with DHIS2 core users from 27 health districts and NMP personnel at the Ministry of Health and Wellness. The web-based survey was administered from August 3, 2020 to September 30, 2020. Results Survey participants were core users (n=27). Focus group participants were NMP personnel (n=5). Overall, participants’ survey responses (frequently occurring scores of 7) showed their confidence in the DHIS2 platform for case-based surveillance of malaria; however, participants also noted some organizational issues that could compromise user acceptance of the DHIS2 platform. Conclusions Participants’ responses indicated their acceptance of the DHIS2 platform; however, the consideration of factors related to organizational readiness could further enhance successful acceptance, and consequently, successful adoption of the platform by the malaria program in Botswana.
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Aboubacar Sidiki, Magassouba. "Qualitative Analysis of Factors Influencing the Use of DHIS2 for Tuberculosis Surveillance: A Case Study in Guinea." TEXILA INTERNATIONAL JOURNAL OF PUBLIC HEALTH 11, no. 3 (2023): 170–77. http://dx.doi.org/10.21522/tijph.2013.11.03.art014.
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Tuberculosis (TB) is a major public health problem in Guinea, where many cases are undetected and untreated. A robust health information system is needed to improve TB case detection and treatment outcomes. DHIS2 (District Health Information Software 2) is a web-based system that collects, analyses and reports data on TB indicators. However, its use and use in Guinea is affected by various factors. We explored these factors using a qualitative survey with health workers and managers who use DHIS2 for TB surveillance. We collected data through a survey with open-ended questions and analysed them using classical content analysis. We conducted a qualitative survey with 35 health workers and managers who use DHIS2 for TB surveillance at different levels of the health system in Guinea. We collected data through an online survey with open-ended questions and analysed them using classical content analysis with NVivo software. We identified four main themes: technical issues (such as internet connection, data synchronisation, and validation rules), data quality issues (such as data validation, data aberrations, and data completeness), training and support issues (such as data analysis techniques, online training, orientation on DHIS2), and organisational issues (such as integration of community data, standardisation of data elements, meetings for data validation). We discussed how these findings could inform the improvement of DHIS2 for TB surveillance in Guinea and other similar settings. Keywords: DHIS2, Health information system, Surveillance, Tuberculosis, Qualitative study.
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Refat, Md Nazmul Hassan, Baizid Khoorshid Riaz, ANM Shamsul Islam, Taufique Joarder, Mahmuda Khandaker, and Md Mainul Hassan. "Limitations of District Health Information Software 2 (DHIS2) as a Decision Support Tool for Upazila Health Service Management in Bangladesh." Journal of Preventive and Social Medicine 42, no. 2 (2025): 43–50. https://doi.org/10.3329/jopsom.v42i2.77163.
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Background: District Health Information Software 2 (DHIS2) is an open source, web-based, health management information system (HMIS) recognized as world's largest HMIS platform, customized for health information system of Bangladesh for decentralized data entry since 2011. Health care managers and employees should be well informed about the health information system for accurate, appropriate, precise, timely, valid information and also interpretation of information which are the basis for policy planning and decision-making at various levels of the organization. The study aimed at exploring the limitations of DHIS2 in decision making process for health service management among the Upazila (Sub district) level health managers of Bangladesh. Methods: The cross sectional study was conducted among the Upazila Health and Family Planning Officers (UH&FPOs) of Bangladesh during the period of January to December 2018. All (482) UH&FPOs of Bangladesh posted as regular, current charge or in-charge were included for the study. Data were collected by a pre-tested semi-structured email-based questionnaire. Results: Response rate was 88.8% (428 out of 482). The mean age of the respondents was 47.08 (±6.33 SD). Mean duration of job experiences as UH&FPO was 1.9 years (±1.635 SD). Regarding limitation, the study revealed that 76.2% (of 424) UH&FPOs think that lack of rrealizing the Importance of DHIS2 by Doctors, Nurses and other Staffs is the most important “Facility Centered Barriers” for using DHIS2 as a decision support tool of Upazila health service management. Beside this 71.2% UH&FPOs think that lack of effective training of the staffs concerned with DHIS2 operation are the second most important barrier. The study also revealed that 59.7% (of 402) UH&FPOs think that absence of the option for automatically displaying the summary reports of various datasets in the respective Upazila dashboard is the most important “Software Centered Barriers” for using DHIS2 as a decision support tool of Upazila health service management beside this 58.5% UH&FPOs think difficulties in identifying the management related data elements from various data sets of DHIS2. Conclusion: So, this study recommends scaling up DHIS2 by redesigning training programs with more focus on the ways of its’ application in the decision making process, create awareness among all categories of health staffs, customization of its contents and more research on this ground. These initiatives will explore several innovative approaches to monitor health indicators by DHIS2, measure and plan health interventions to ensure quality health service and will lead towards achieving Sustainable Development Goal 3 (SDG-3). JOPSOM 2023; 42(2): 43-50
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Etamesor, Sulaiman, Chibuzo Ottih, Ismail Ndalami Salihu, and Arnold Ikedichi Okpani. "Data for decision making: using a dashboard to strengthen routine immunisation in Nigeria." BMJ Global Health 3, no. 5 (2018): e000807. http://dx.doi.org/10.1136/bmjgh-2018-000807.
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Availability of reliable data has for a long time been a challenge for health programmes in Nigeria. Routine immunisation (RI) data have always been characterised by conflicting coverage figures for the same vaccine across different routine data reporting platforms.Following the adoption of District Health Information System version 2 (DHIS2) as a national electronic data management platform, the DHIS2 RI Dashboard Project was initiated to address the absence of some RI-specific indicators on DHIS2. The project was also intended to improve visibility and monitoring of RI indicators as well as strengthen the broader national health management information system by promoting the use of routine data for decision making at all governance levels. This paper documents the process, challenges and lessons learnt in implementing the project in Nigeria.A multistakeholder technical working group developed an implementation framework with clear preimplementation; implementation and postimplementation activities. Beginning with a pilot in Kano state in 2014, the project has been scaled up countrywide.Nearly 34 000 health workers at all administrative levels were trained on RI data tools and DHIS2 use. The project contributed to the improvement in completeness of reports on DHIS2 from 53 % in first quarter 2014 to 81 % in second quarter 2017.The project faced challenges relating to primary healthcare governance structures at the subnational level, infrastructure and human resource capacity. Our experience highlights the need for early and sustained advocacy to stakeholders in a decentralised health system to promote ownership and sustainability of a centrally coordinated systems strengthening initiative.
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Hagel, Christiane, Chris Paton, George Mbevi, and Mike English. "Data for tracking SDGs: challenges in capturing neonatal data from hospitals in Kenya." BMJ Global Health 5, no. 3 (2020): e002108. http://dx.doi.org/10.1136/bmjgh-2019-002108.
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BackgroundTarget 3.2 of the United Nations Sustainable Development Goals (SDGs) is to reduce neonatal mortality. In low-income and middle-income countries (LMICs), the District Health Information Software, V.2 (DHIS2) is widely used to help improve indicator data reporting. There are few reports on its use for collecting neonatal hospital data that are of increasing importance as births within facilities increase. To address this gap, we investigated implementation experiences of DHIS2 in LMICs and mapped the information flow relevant for neonatal data reporting in Kenyan hospitals.MethodsA narrative review of published literature and policy documents from LMICs was conducted. Information gathered was used to identify the challenges around DHIS2 and to map information flows from healthcare facilities to the national level. Two use cases explore how newborn data collection and reporting happens in hospitals. The results were validated, adjusted and system challenges identified.ResultsLiterature and policy documents report that DHIS2 is a useful tool with strong technical capabilities, but significant challenges can emerge with the implementation. Visualisations of information flows highlight how a complex, people-based and paper-based subsystem for inpatient information capture precedes digitisation. Use cases point to major challenges in these subsystems in accurately identifying newborn deaths and appropriate data for the calculation of mortality even in hospitals.ConclusionsDHIS2 is a tool with potential to improve availability of health information that is key to health systems, but it critically depends on people-based and paper-based subsystems. In hospitals, the subsystems are subject to multiple micro level challenges. Work is needed to design and implement better standardised information processes, recording and reporting tools, and to strengthen the information system workforce. If the challenges are addressed and data quality improved, DHIS2 can support countries to track progress towards the SDG target of improving neonatal mortality.
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Paddo, Atika Rahman, Snigdha Kodela, Lava Timsina, Shomita S. Mathew-Steiner, Saptarshi Purkayastha, and Chandan K. Sen. "Development and validation of the DHIS2 platform for integrating sociomedical data to study wound care outcomes." PLOS ONE 19, no. 12 (2024): e0308553. https://doi.org/10.1371/journal.pone.0308553.
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Wound trajectory and outcomes research has applications in different aspects of wound healing: forecasting wound healing time, access and utilization of wound care services, factors associated with disparities in wound care services, and its quality and outcomes. Wound care research benefits from a well-maintained record management system. In this article, we demonstrate the customization of the District Health Information Software (DHIS2) platform to integrate wound care clinical data with social determinants of health from several Comprehensive Wound Centers (CWC) in Indiana. We describe the modules and features of our platform, such as tracker capture, visualization, and maps. DHIS2 is used in more than 60 countries to monitor and evaluate health programs. However, to the best of our knowledge, this is the first attempt to use DHIS2 as a wound care data warehouse, a platform to perform wound care research for academic researchers and clinical practitioners. Clinicians can use the platform as one of the key tools to make an informed decision in determining the treatment for favorable healing trajectory and wound outcomes. We conducted a usability and acceptance survey among researchers at the Indiana Center for Regenerative Medicine and Engineering and found that DHIS2 can be a suitable infrastructure to manage metadata to import and analyze combined data from disparate sources, including Electronic Medical Records, WoundExpert, and clinical trials management software like REDCap.
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Woldeyohannes, Birkinesh, Mark Gaynor, and Temtim Assefa. "Inclusive Entrepreneurship in Handling Competing Institutional Logics for DHIS2 Adoption in Ethiopian Public Health Care Context." International Journal of Managing Information Technology 14, no. 4 (2022): 1–17. http://dx.doi.org/10.5121/ijmit.2022.14401.
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Information System (IS) research advocates employing collaborative and loose coupling strategies to address contradictory issues to address diversified actors’ interests than the prescriptive and unilateral Information Technology (IT) governance mechanisms’, yet it is rarely depicting how managers employ these strategies in Health Information System (HIS) implementation, particularly in a resource-constrained setting where IS implementation activities have highly relied on multiple international organizations resources. This study explored how managers in resource-constrained settings employ collaborative IT governance mechanisms in the case of District Health Information System 2 (DHIS2) adoption with an interpretative case study approach and the institutional logic concept. The institutional logic concept was used to identify the major actors’ logics underpinning the DHIS2 adoption. The study depicted the importance of high-level officials' distance from the dominant systemic logic to consider new alternative, and to employ inclusive IT governance mechanisms which separated resource from the system that facilitated stakeholders’ collaboration in DHIS2 adoption based on their capacity and interest.
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Godage, Prabhadini, Sapumal Dhanapala, and Achala Jayatilleke. "Usability evaluation of a DHIS2-based electronic information management system for environmental, occupational health and food safety in Sri Lanka." BMJ Health & Care Informatics 32, no. 1 (2025): e101357. https://doi.org/10.1136/bmjhci-2024-101357.
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ObjectivesThe Public Health Inspector (PHI) Monthly Report is a critical document that provides insights into environmental, occupational health and food safety aspects within each Medical Officer of Health area in Sri Lanka. Currently, PHIs use a paper format to track these key health indicators, resulting in incomplete and inaccurate national data. This study evaluates the usability of a DHIS2 (District Health Information Software 2) based digital solution to improve PHI reporting.MethodsThe DHIS2 system was customised to address the gaps in the current reporting process, and its usability was evaluated using the System Usability Scale (SUS) with 50 stakeholders who tested the system.ResultsThe DHIS2 platform was flexible enough to be customised to meet the requirements of the new electronic Environmental, Occupational Health and Food Safety Information Management System (eEOHFSIMS). The system achieved an average SUS score of 72.25, exceeding the accepted benchmark of 68, with a high SD of 13.37. However, a 92% knowledge gap remained.DiscussionDigitising the PHI monthly report using DHIS2 addresses the challenges of traditional paper-based reporting, enabling timely monitoring of public health indicators. The favourable SUS score confirms the system’s high usability, yet the knowledge gap underscores the need for ongoing user training to ensure data quality.ConclusionsThe eEOHFSIMS demonstrated its capacity to deliver accurate, complete and timely data, greatly benefiting Sri Lanka’s primary healthcare services. This system enhancement supports better-informed decision-making, aligns with national health policies and enables continuous monitoring and evaluation of public health services.
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Okeyo, Seth, Raymond Omollo, Robert Kimutai, Michael Ochieng, and Thaddaeus Egondi. "PILOTING DHIS2 SYSTEM IN VISCERAL LEISHMANIASIS SURVEILLANCE." BMJ Global Health 2, Suppl 2 (2017): A64.3—A65. http://dx.doi.org/10.1136/bmjgh-2016-000260.173.
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Bahati, Felix, Jacob Mcknight, Fatihiya Swaleh, et al. "Reporting of diagnostic and laboratory tests by general hospitals as an indication of access to diagnostic laboratory services in Kenya." PLOS ONE 17, no. 4 (2022): e0266667. http://dx.doi.org/10.1371/journal.pone.0266667.
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Introduction Information on laboratory test availability and current testing scope among general hospitals in Kenya is not readily available. We sought to explore the reporting trends and test availability within clinical laboratories in Kenya over a 24-months period through analysis of the laboratory data reported in the District Health Information System (DHIS2). Methods Monthly hospital laboratory testing data were extracted from the Kenyan DHIS2 between January 2018 and December 2019. We used the national laboratory testing summary tool (MoH 706) to identify the tests of interest among 204 general hospitals in Kenya. A local practitioner panel consisting of individuals with laboratory expertise was used to classify the tests as common and uncommon. We compared the tests on the MoH 706 template with the Essential Diagnostic List (EDL) of the World Health Organisation and further reclassified them into test categories based on the EDL for generalisability of our findings. Evaluation of the number of monthly test types reported in each facility and the largest number of tests ever reported in any of the 24 months were used to assess test availability and testing scope, respectively. Results Out of the 204 general hospitals assessed, 179 (179/204) reported at least one of the 80 tests of interest in any of the 24 months. Only 41% (74/179) of the reporting hospitals submitted all their monthly DHIS2 laboratory reports for the entire 24 months. The median testing capacity across the hospitals was 40% with a wide variation in testing scope from one hospital laboratory to another (% IQR: 33.8–51.9). Testing scope was inconsistent within facilities as indicated by often large monthly fluctuations in the total number of recommended and EDL tests reported. Tests of anatomical pathology and cancer were the least reported with 4 counties’ hospitals not reporting any cancer or anatomical pathology tests for the entire 24 months. Conclusion The current reporting of laboratory testing information in DHIS2 is poor. Monitoring access and utilisation of laboratory testing across the country would require significant improvements in consistency and coverage of routine laboratory test reporting in DHIS2. Nonetheless, the available data suggest unequal and intermittent population access to laboratory testing provided by general hospitals in Kenya.
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Setiawan, Mohammad Yusuf. "Pemanfaatan Register Leptospirosis melalui Implementasi DHIS2 di Indonesia." Journal of Information Systems for Public Health 7, no. 2 (2022): 1. http://dx.doi.org/10.22146/jisph.70727.
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Latar belakang: Profil Kesehatan Indonesia tahun 2019 menunjukkan adanya peningkatan jumlah kasus pada beberapa penyakit zoonosis dibandingkan tahun 2018. Salah satu program surveilans zoonosis yang dilakukan di Indonesia adalah Sistem Informasi eZoonosis yang menggunakan platform DHIS2. Platform Sistem Informasi DHIS2 dapat dikustomisasi untuk kasus khusus, salah satunya adalah kasus leptospirosis. Dalam rangka penerapan Sistem Informasi eZoonosis, perlu diadakan beberapa kegiatan pendahuluan seperti sosialisasi dan pelatihan. Dilakukan pengembangan register leptosipirosis dalam Sistem Informasi eZoonosis yang nantinya akan diimplementasikan melalui sosialisasi dan pelatihan. Kegiatan sosialisasi dan pelatihan akan ditujukan kepada pengguna di tingkat dinas kesehatan kabupaten dan puskesmas. Metode: Penelitian ini adalah action research dengan pendekatan mixed-method. Data kualitatif diambil melalui diskusi, wawancara dan observasi sedangkan data kuantitatif diambil melalui kuesioner dan kuis pada platform khusus saat pelatihan secara daring. Data kemudian dianalisis secara deskriptif untuk memberikan gambaran proses dan implementasi sistem informasi eZoonosis.Hasil: Tingkat literasi digital, penerimaan sistem dan evaluasi pelatihan daring menunjukkan hasil yang positif. Pengembangan sistem informasi eZoonosis mencakup 7 register, termasuk register leptospirosis. Sistem eZoonosis mencakup pelaporan data individu dan agregrat tentang leptospirosis yang dapat dimonitor secara real time dan didiseminasikan secara deskriptif guna membantu proses pengambilan kebijakan. Evaluasi implementasi menunjukkan masih terdapat kendala penggunaan sistem karena masalah jaringan, kesalahan server dan keterampilan pengguna yang belum maksimal.Kesimpulan: DHIS2 dapat digunakan sebagai pengembangan sistem informasi surveilans. Tantangan dan kendala yang ditemui selama pengembangan dan evaluasi sistem informasi eZoonosis membutuhkan pengembangan lebih lanjut.
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Ashoranga, I. K. R., N. V. J. Thenuwara, P. U. Chulasiri, and K. D. N. P. Ranaweera. "A digital health solution for parasitological surveillance at Anti-Malaria Campaign, Sri Lanka." Sri Lanka Journal of Health Research 2, no. 1 (2022): 125–29. http://dx.doi.org/10.4038/sljhr.v2i1.38.
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The Anti Malaria Campaign in Sri Lanka is a public health initiative aimed at preventing and controlling the spread of malaria in the country. The outcome of the malaria control program is improved by effective surveillance. The National Malaria Strategic Plan highlights the lack of a web-based surveillance system for malaria as a weakness in the central-level availability of malaria parasitological surveillance data. DHIS2 (District Health Information Software 2) is a global-good, health management information system recommended by WHO. Creating a malaria information system based on DHIS2 and incorporating an interactive dashboard are employed to enhance the prompt accessibility of data at the national level.
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Sanjel, Keshab, Shiv Lal Sharma, Swadesh Gurung, Man Bahadur Oli, Samikshya Singh, and Tuk Prasad Pokhrel. "Quality of routine health facility data for monitoring maternal, newborn and child health indicators: A desk review of DHIS2 data in Lumbini Province, Nepal." PLOS ONE 19, no. 4 (2024): e0298101. http://dx.doi.org/10.1371/journal.pone.0298101.
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Introduction Health-facility data serves as a primary source for monitoring service provision and guiding the attainment of health targets. District Health Information Software (DHIS2) is a free open software predominantly used in low and middle-income countries to manage the facility-based data and monitor program wise service delivery. Evidence suggests the lack of quality in the routine maternal and child health information, however there is no robust analysis to evaluate the extent of its inaccuracy. We aim to bridge this gap by accessing the quality of DHIS2 data reported by health facilities to monitor priority maternal, newborn and child health indicators in Lumbini Province, Nepal. Methods A facility-based descriptive study design involving desk review of Maternal, Neonatal and Child Health (MNCH) data was used. In 2021/22, DHIS2 contained a total of 12873 reports in safe motherhood, 12182 reports in immunization, 12673 reports in nutrition and 12568 reports in IMNCI program in Lumbini Province. Of those, monthly aggregated DHIS2 data were downloaded at one time and included 23 priority maternal and child health related data items. Of these 23 items, nine were chosen to assess consistency over time and identify outliers in reference years. Twelve items were selected to examine consistency between related data, while five items were chosen to assess the external consistency of coverage rates. We reviewed the completeness, timeliness and consistency of these data items and considered the prospects for improvement. Results The overall completeness of facility reporting was found within 98% to 100% while timeliness of facility reporting ranged from 94% to 96% in each Maternal, Newborn and Child Health (MNCH) datasets. DHIS2 reported data for all 9 MNCH data items are consistent over time in 4 of 12 districts as all the selected data items are within ±33% difference from the provincial ratio. Of the eight MNCH data items assessed, four districts reported ≥5% monthly values that were moderate outliers in a reference year with no extreme outliers in any districts. Consistency between six-pairs of data items that are expected to show similar patterns are compared and found that three pairs are within ±10% of each other in all 12 districts. Comparison between the coverage rates of selected tracer indicators fall within ±33% of the DHS survey result. Conclusion Given the WHO data quality guidance and national benchmark, facilities in the Lumbini province well maintained the completeness and timeliness of MNCH datasets. Nevertheless, there is room for improvement in maintaining consistency over time, plausibility and predicted relationship of reported data. Encouraging the promotion of data review through the data management committee, strengthening the system inbuilt data validation mechanism in DHIS2, and promoting routine data quality assessment systems should be greatly encouraged.
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Tesfaye, Latera, Tom Forzy, Fentabil Getnet, et al. "Estimating immunization coverage at the district level: A case study of measles and diphtheria-pertussis-tetanus-Hib-HepB vaccines in Ethiopia." PLOS Global Public Health 4, no. 7 (2024): e0003404. http://dx.doi.org/10.1371/journal.pgph.0003404.
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Ethiopia has made significant progress in the last two decades in improving the availability and coverage of essential maternal and child health services including childhood immunizations. As Ethiopia keeps momentum towards achieving national immunization goals, methods must be developed to analyze routinely collected health facility data and generate localized coverage estimates. This study leverages the District Health Information Software (DHIS2) platform to estimate immunization coverage for the first dose of measles vaccine (MCV1) and the third dose of diphtheria-pertussis-tetanus-Hib-HepB vaccine (Penta3) across Ethiopian districts (“woredas”). Monthly reported numbers of administered MCV1 and Penta3 immunizations were extracted from public facilities from DHIS2 for 2017/2018-2021/2022 and corrected for quality based on completeness and consistency across time and districts. We then utilized three sources for the target population (infants) to compute administrative coverage estimates: Central Statistical Agency, DHIS2, and WorldPop. The Ethiopian Demographic and Health Surveys were used as benchmarks to which administrative estimates were adjusted at the regional level. Administrative vaccine coverage was estimated for all woredas, and, after adjustments, was bounded within 0–100%. In regions with the highest immunization coverage, MCV1 coverage would range from 83 to 100% and Penta3 coverage from 88 to 100% (Addis Ababa, 2021/2022); MCV1 from 8 to 100% and Penta3 from 4 to 100% (Tigray, 2019/2020). Nationally, the Gini index for MCV1 was 0.37, from 0.13 (Harari) to 0.37 (Somali); for Penta3, it was 0.36, from 0.16 (Harari) to 0.36 (Somali). The use of routine health information systems, such as DHIS2, combined with household surveys permits the generation of local health services coverage estimates. This enables the design of tailored health policies with the capacity to measure progress towards achieving national targets, especially in terms of inequality reductions.
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Timothy, Kiyemba, Makabayi-Mugabe Rita, Kirirabwa Nicholas Sebuliba, et al. "A comparative analysis of two national tuberculosis reporting systems and their impact on tuberculosis case notification in Uganda." African Health Sciences 23, no. 4 (2023): 13–20. http://dx.doi.org/10.4314/ahs.v23i4.3.
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AbstractBackground: Before 2018, the use of parallel tuberculosis (TB) reporting systems was resource intensive with duplication of efforts and hence the need to select one that contributed to better TB case notification at the National TB and Leprosy Program (NLTP) in Uganda. We sought to analyse the difference in reporting rates between the two systems in order to improve NTLP TB case notification rates, logistics management, and planning for better health service delivery initiatives.
 Methods: We conducted a comparative study to assess TB case notification between the web-based DHIS2 and the district TB supervisor-led health management information system between January 2016 to December 2017. We used Poisson regression analysis to assess the statistical differences in reporting rates between the two reporting systems.
 Results: The association between TB case notification and the type of reporting system was statistically significant (Prob > chi2 = 0.0000). The Incident Rate Ratio (IRR) for the web-enabled DHIS2 system versus the district TB supervisor-led health management information system was 1.106625.Conclusion: The web-based integrated DHIS2 system was more effective in reporting missing TB cases. It presents an opportunity for better planning and allocation of resources for improved service delivery in a low-income setting.
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Amare, Samson Yohannes, Getu Tadele Taye, Tesfit Gebremeskel Gebreslassie, Ruduan Plug, and Mirjam van Reisen. "Realizing health data interoperability in low connectivity settings: The case of VODAN-Africa." FAIR Connect 1, no. 1 (2023): 55–61. http://dx.doi.org/10.3233/fc-221510.
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VODAN Africa has produced FAIR data in low resource settings. Federated machine actionable data is available in a triple store for visiting. Interoperability facets (I1–I3) were followed to achieve semantic interoperability. Vertical interoperability was also realized with DHIS2.
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Eggers, Carrie, Lise Martel, Amber Dismer, et al. "Implementing a DHIS2 Ebola virus disease module during the 2021 Guinea Ebola outbreak." BMJ Global Health 7, no. 5 (2022): e009240. http://dx.doi.org/10.1136/bmjgh-2022-009240.
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In 2017, the national agency for health security (L’Agence Nationale de Sécurité Sanitaire—ANSS) in Guinea implemented the District Health Information Software (DHIS2) as the Ministry of Health national surveillance system to capture and report aggregate disease data. During 2019, the ANSS started using DHIS2 Tracker to collect case-based (individual-level) data for epidemic-prone diseases. In 2020, the capability was expanded, and it was used during the COVID-19 pandemic to capture data relevant to the COVID-19 response. When an Ebola virus disease (EVD) outbreak was announced in February 2021, the Tracker module was updated, and enhanced functionalities were developed to meet the needs for the emerging epidemic. This novel EVD module has components to capture information on cases, contacts, alerts, laboratory and vaccinations and provides a centralised site for all EVD outbreak data. It has since been expanded for use with future viral haemorrhagic fever outbreaks.
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Bobokhojaev, O. I., S. R. Sayfuddinov, S. G. Shukurov, and F. R. Khakimov. "Evaluative analysis of collection, storage, and transmission of statistical data on tuberculosis at district and central levels of health care in the Republic of Tajikistan." Health care of Tajikistan, no. 2 (August 20, 2024): 13–17. http://dx.doi.org/10.52888/0514-2515-2024-361-2-13-17.
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Aim. To assess the effectiveness of collection, storage and transfer of statistical information on tuberculosis in the districts of Rasht region.Material and methods. The material for the planned study was data on registered cases of tuberculosis for 2022 according to the National Tuberculosis Register “OpenMRS”, the Unified Health Management Information Network “DHIS2” and the initial data of primary documentation of the anti-tuberculosis service in five districts of the Rasht region (Rasht, Tajikabad, Sangvor, Nurabad, Lakhsh).Results. The studies conducted revealed a significant discrepancy in the official statistical information on tuberculosis in the unified health management information system “DHIS2”, in the national tuberculosis data register “OpenMRS” and in the primary documentation of the anti-tuberculosis service: Form No. 036, Reporting Form 8, Patient Registration Journal - TB-03 and TB-03U, Quarterly Report Form - TB-07 and TB-07U in all five districts of Rasht region.Conclusion. Frequent criticism of the specialists responsible for providing official statistics on tuberculosis for their inconsistency with WHO data, data from the unified health management information system “DHIS2”, data from the national registry “OpenMRS” and data from the primary documentation of the anti-tuberculosis service is justified. One of the ways to bring official statistical data into line with the real epidemiological situation of tuberculosis is to carry out systematic routine monitoring and evaluation of the quality of collection, storage and transmission of statistical information on tuberculosis from the district level to the central level, to organise continuous training of specialists responsible for this component, to minimise paperwork and to prioritise the digitalisation of this process.
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Mercy, Kyeng, Stephanie J. Salyer, Comfort Mankga, Calle Hedberg, Phumzile Zondo, and Yenew Kebede. "Establishing an early warning event management system at Africa CDC." PLOS Digital Health 3, no. 7 (2024): e0000546. http://dx.doi.org/10.1371/journal.pdig.0000546.
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Africa is home to hotspots of disease emergence and re-emergence. To adequately detect and respond to these health threats, early warning systems inclusive of event-based surveillance (EBS) are needed. However, data systems to manage these events are not readily available. In 2020, Africa Centres for Disease Control and Prevention developed an event management system (EMS) to meet this need. The district health information software (DHIS2), which is free and open-source software was identified as the platform for the EMS because it can support data capture and analysis and monitor and report events. The EMS was created through a collaborative and iterative prototyping process that included modifying key DHIS2 applications like Tracker Capture. Africa CDC started piloting the EMS with both signal and event data entry in June 2020. By December 2022, 416 events were captured and over 140 weekly reports, including 19 COVID-19 specific reports, were generated and distributed to inform continental awareness and response efforts. Most events detected directly impacted humans (69%), were considered moderate (50%) to high (29%) risk level and reflected both emerging and endemic infectious disease outbreaks. Highly pathogenic avian influenza, specifically H5N1, was the most frequently detected animal event and storms and flooding were most frequently detected environmental events. Both data completeness and timeliness improved over time. Country-level interest and utility resulted in four African countries adapting the EMS in 2022 and two more in 2023. This system demonstrates how integrating digital technology into health systems and utilising existing digital platforms like DHIS2 can improve early warning at the continental and country level by improving EBS workflow.
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Prihantoro, Budi. "Evaluasi penerapan konsep integrasi data menggunakan dhis2 di kementerian kesehatan." Journal of Information Systems for Public Health 5, no. 1 (2021): 43. http://dx.doi.org/10.22146/jisph.33959.
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Shuaib, Faisal, Abdullahi Bulama Garba, Emmanuel Meribole, et al. "Implementing the routine immunisation data module and dashboard of DHIS2 in Nigeria, 2014–2019." BMJ Global Health 5, no. 7 (2020): e002203. http://dx.doi.org/10.1136/bmjgh-2019-002203.
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In 2010, Nigeria adopted the use of web-based software District Health Information System, V.2 (DHIS2) as the platform for the National Health Management Information System. The platform supports real-time data reporting and promotes government ownership and accountability. To strengthen its routine immunisation (RI) component, the US Centers for Disease Control and Prevention (CDC) through its implementing partner, the African Field Epidemiology Network-National Stop Transmission of Polio, in collaboration with the Government of Nigeria, developed the RI module and dashboard and piloted it in Kano state in 2014. The module was scaled up nationally over the next 4 years with funding from the Bill & Melinda Gates Foundation and CDC. One implementation officer was deployed per state for 2 years to support operations. Over 60 000 RI healthcare workers were trained on data collection, entry and interpretation and each local immunisation officer in the 774 local government areas (LGAs) received a laptop and stock of RI paper data tools. Templates for national-level and state-level RI bulletins and LGA quarterly performance tools were developed to promote real-time data use for feedback and decision making, and enhance the performance of RI services. By December 2017, the DHIS2 RI module had been rolled out in all 36 states and the Federal Capital Territory, and all states now report their RI data through the RI Module. All states identified at least one government DHIS2 focal person for oversight of the system’s reporting and management operations. Government officials routinely collect RI data and use them to improve RI vaccination coverage. This article describes the implementation process—including planning and implementation activities, achievements, lessons learnt, challenges and innovative solutions—and reports the achievements in improving timeliness and completeness rates.
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Youssef, Dalal, S. Hemedeh, G. Allouch, et al. "Laboratory Based Surveillance Using District Health Information System(DHIS2): Lebanon 2017." Iproceedings 4, no. 1 (2018): e10546. http://dx.doi.org/10.2196/10546.
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Manoj, Subodha, Arjuna Wijekoon, Manjula Dharmawardhana, et al. "Implementation of District Health Information Software 2 (DHIS2) in Sri Lanka." Sri Lanka Journal of Bio-Medical Informatics 3, no. 4 (2013): 109. http://dx.doi.org/10.4038/sljbmi.v3i4.5431.
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Achmad, Lia. "Penerimaan DHIS2 oleh Sumber Daya Manusia Kesehatan di Kabupaten Kulon Progo." Journal of Information Systems for Public Health 6, no. 3 (2021): 62. http://dx.doi.org/10.22146/jisph.71284.
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Sitompul, Taufiq Hamzah, Popy Meilani, Syefira Salsabila, and Lalu Lian Hariwangi. "SILACAK: Bagaimana Penggunaan Aplikasi Pelacakan Kasus Kontak Erat COVID-19 di Indonesia." Indonesian of Health Information Management Journal (INOHIM) 9, no. 2 (2021): 127–37. http://dx.doi.org/10.47007/inohim.v9i2.357.
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AbstractCOVID-19started outbreaks in Indonesia from March 2020, with a large spread rate making not only Indonesia, but all exposed countries in the world find the difficulties to deal with it. The advance of technology has been used to overcome the COVID-19 cases. The Ministry of Health supported by Health Information System Programme (HISP) Indonesia adopted the DHIS2 platform in the development of a contact tracing application called SILACAK. In this study, we will discuss the development of the SILACAK application which is used as a COVID-19contact tracing application in Indonesia. The method in this study is a qualitative method with an action research approach. The use of SILACAK starts from the primary healthcare level by utilizing health workers and collaboration with volunteers and The Indonesian National Military and The Indonesia National Police. The use of SILACAK was used in stages and in July 2020 it was used by 34 provinces. Currently SILACAK is used as a tool for tracking and monitoring close contact, in which close contact tracing (at least 80%) and the ratio of close contact to confirmation cases are used as a national reference (1:15). However, for some regions there are those that cannot exceed this provision because tacthe number of close contacts does not exceed the specified limit. So that, another assessment was also carried out to see the performance of contact tracing, which consisted of: close contacts who conducted entry and exit tests, close contacts who were monitored and completed the monitoring.Keyword: SILACAK, DHIS2, COVID-19, contact tracing applicationAbstrakCOVID-19 memasuki Indonesia di bulan Maret 2020, dengan laju penyebaran yang besar membuat tidak hanya Indonesia tapi seluruh negara yang terpapar di dunia merasa kesulitan dalam menghadapinya. Kecanggihan teknologi dimanfaatkan untuk menanggulangi COVID-19. Kementerian Kesehatan didukung oleh Health Information System Programme (HISP) Indonesia mengadopsi platform DHIS2 dalam pengembangan aplikasi Pelacakan Kasus Kontak COVID-19 yang disebut SILACAK. Dalam penelitian ini akan membahas perkembangan aplikasi SILACAK yang digunakan sebagai aplikasi pelacakan kontak COVID-19 di Indonesia. Metode dalam penelitian ini dengan metode kualitatif dengan pendekatan action research. Pemanfaatan SILACAK dimulai dari level puskesmas dengan memanfaatkan tenaga Kesehatan dan berkolaborasi dengan relawan serta TNI dan POLRI. Penggunaan SILACAK digunakan secara bertahap dan di bulan Juli 2020 dimanfaatkan oleh 34 provinsi. Saat ini SILACAK dijadikan sebagai alat untuk pelacakan dan pemantauan kontak erat, yang mana pelacakan kontak erat (minimal 80%) dan rasio kontak erat dengan kasus konfirmasi yang dijadikan sebagai acuan Nasional (1:15). Namun beberapa daerah belum bisa memenuhi angka tersebut di karena kan angka dari jumlah kontak eratnya tidak memenuhi sampai angka tersebut. Sehingga dalam menilai suatu kinerja dari keberhasilan pelacakan kontak suatu daerah juga dapat mempertimbangkan dari kontak erat yang dilakukan entry tes dan exit tes, kontak erat yang dilakukan pemantauan dan menyelesaikan pemantauannya.Kata Kunci: SILACAK, DHIS2, COVID-19, aplikasi pelacakan kontak
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Prauseová, Jana, Oluwatosin Nkereuwem, Uduak Okomo, et al. "Toward an Electronic Pregnancy Registry in The Gambia: Linking up Maternal and Newborn Health Data Using the Smart Paper Technology." Pediatric Infectious Disease Journal 44, no. 2S (2025): S119—S122. https://doi.org/10.1097/inf.0000000000004677.
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Smart Paper Technology, an innovative paper-to-digital system implemented at Bundung Maternal and Child Health Hospital in The Gambia links maternal and newborn health information with immunization records. In 9 months, Smart Paper Technology facilitated over 3500 mother–child connections, replacing traditional paper-based registers and ensuring DHIS2 interoperability. This pilot enhances reporting and data availability, advancing maternal vaccine safety surveillance in resource-limited settings.
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Lyatuu, Isaac, Georg Loss, Andrea Farnham, Goodluck W. Lyatuu, Günther Fink, and Mirko S. Winkler. "Associations between Natural Resource Extraction and Incidence of Acute and Chronic Health Conditions: Evidence from Tanzania." International Journal of Environmental Research and Public Health 18, no. 11 (2021): 6052. http://dx.doi.org/10.3390/ijerph18116052.
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Natural resource extraction projects are often accompanied by complex environmental and social-ecological changes. In this paper, we evaluated the association between commodity extraction and the incidence of diseases. We retrieved council (district)-level outpatient data from all public and private health facilities from the District Health Information System (DHIS2). We combined this information with population data from the 2012 national population census and a geocoded list of resource extraction projects from the Geological Survey of Tanzania (GST). We used Poisson regression with random effects and cluster-robust standard errors to estimate the district-level associations between the presence of three types of commodity extraction (metals, gemstone, and construction materials) and the total number of patients in each disease category in each year. Metal extraction was associated with reduced incidence of several diseases, including chronic diseases (IRR = 0.61, CI: 0.47–0.80), mental health disorders (IRR = 0.66, CI: 0.47–0.92), and undernutrition (IRR = 0.69, CI: 0.55–0.88). Extraction of construction materials was associated with an increased incidence of chronic diseases (IRR = 1.47, CI: 1.15–1.87). This study found that the presence of natural resources commodity extraction is significantly associated with changes in disease-specific patient volumes reported in Tanzania’s DHIS2. These associations differed substantially between commodities, with the most protective effects shown from metal extraction.
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Dascalov, Alexandr. "DIGITAL TOOLS FOR THE RESPONSE AGAINST COVID-19." Arta Medica 91, no. 2 (2024): 22–31. https://doi.org/10.5281/zenodo.13328381.
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<strong>Objectives.</strong><strong> </strong>This study aimed to describe and compare various digital tools used in response to COVID-19, with a focus on digitalized epidemiological surveillance. Our objective was to assess the specific functions, implementation, and effectiveness of these tools in managing the pandemic. <strong>Methods.</strong><strong> </strong>We conducted a literature review and analyzed available data on various digital tools used in response to COVID-19. We examined platforms such as District Health Information Software (DHIS2), Surveillance, Outbreak Response Management and Analysis System (SORMAS), Go.Data, Open Data Kit (ODK), Epi Info, CommCare, and others. <strong>Results.</strong><strong> </strong>We found that each digital tool has specific functions tailored to local needs and requirements. Digitalized epidemiological surveillance platforms, such as DHIS2 and SORMAS, have been widely used for data collection, analysis, and reporting on COVID-19 cases. Mobile applications, such as Go.Data and ODK, have facilitated contact tracing and symptom monitoring, while education and training platforms, such as CommCare, have been essential in providing information and instructions to healthcare workers and the public. <strong>Conclusions. </strong>Digital tools have been an essential element in the global response to the COVID-19 pandemic, facilitating efficient data collection and management, public education, and case management.
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Manoj, M. Subodha. "Customising DHIS2 for Maternal and Child Health Information Management in Sri Lanka." Sri Lanka Journal of Bio-Medical Informatics 3, no. 2 (2013): 47. http://dx.doi.org/10.4038/sljbmi.v3i2.2496.
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Raharjo, Untoro Dwi. "Implementasi DHIS2 untuk Program Surveilans Kasus Gigitan Hewan Penyebab Rabies di Indonesia." Journal of Information Systems for Public Health 7, no. 1 (2022): 11. http://dx.doi.org/10.22146/jisph.71311.
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Djadi, Ni Ketut Hesti Widiastuti. "Implementasi dhis2 untuk pengelolaan data kia di puskesmas ampana timur, sulawesi tengah." Journal of Information Systems for Public Health 5, no. 1 (2021): 9. http://dx.doi.org/10.22146/jisph.27696.
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Orjingene, Obinna, Ojo Olumuyiwa, Clara Oguji, et al. "Full childhood immunization coverage and incidence of vaccine preventable disease in Nigeria: a regression analysis." International Journal Of Community Medicine And Public Health 8, no. 12 (2021): 5757. http://dx.doi.org/10.18203/2394-6040.ijcmph20214563.
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Background: Childhood immunization contributes significantly in the reduction of cases of vaccine preventable diseases in children. DHIS2 data showed that only 60.59% of children under one were fully immunized in 2020. This implies that 39.41% did not receive all recommended vaccinations therefore at risk of contracting vaccine preventable diseases. This study therefore examined the effect of full immunization coverage on incidence of vaccine preventable diseases.Methods: Full childhood immunization coverage and incidence of vaccine preventable disease was examined using simple linear regression model at 5% level of significance and 95% confidence interval. Measles new case for children under five was the dependent variable while children under one fully immunized was the independent variable. Data was retrieved from DHIS2 for the period 2017-2020.Results: The study showed a negative relationship between full immunization coverage and incidence of under-five measles new cases. The study found that any unit increase in full immunization coverage would lead to decrease in measles cases by 6%.Conclusions: Full immunization coverage is still low (below WHO target of 80%) despite effort by government and partners. This implies that a lot of children are at risk of contracting vaccine preventable diseases. In order to avert this risk, health authorities and partners should devise appropriate means of educating the populace on the importance of childhood immunization.
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Tadesse, Girmaw Abebe, Laura Ferguson, Caleb Robinson, et al. "Forecasting acute childhood malnutrition in Kenya using machine learning and diverse sets of indicators." PLOS One 20, no. 5 (2025): e0322959. https://doi.org/10.1371/journal.pone.0322959.
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Objectives Malnutrition is a leading cause of morbidity and mortality for children under-5 globally. Low- and middle-income countries, such as Kenya, bear the greatest burden of malnutrition. The Kenyan government has been collecting clinical indicators, including on malnutrition, using District Health Information Software-2 (DHIS2) for over a decade. We aim to address the existing gap in decision-makers’ ability to develop and utilize malnutrition forecasting capabilities for timely interventions. Specifically, our objectives include: develop a spatio-temporal machine learning model to forecast acute malnutrition among children in Kenya using DHIS2 data, enhance forecasting capability by integrating external complementary indicators, such as publicly available satellite imagery-driven signals, and forecast acute malnutrition at various stages and time horizons, including moderate, severe, and aggregated cases. Methods We propose a framework to forecast malnutrition risk for each sub-county in Kenya based on clinical indicators and remote sensory data. To achieve this, we first aggregate clinical indicators and remotely sensed satellite data, specifically gross primary productivity measurements, to the sub-county level. We then label the rate of children diagnosed with acute malnutrition at the sub-county level using the standard Integrated Food Security Phase Classification for Acute Malnutrition. We then apply and compare several methods for forecasting malnutrition risk in Kenya using data collected from January 2019 to February 2024. As a baseline, we used a Window Average model, which captures the current practice at the Kenyan Ministry of Health. We also trained machine learning models, such as Logistic Regression and Gradient Boosting, to forecast acute malnutrition risk based on observed indicators from prior months. Different metrics, mainly Area Under Receiver Operating Characteristic Curve (AUC), were used to evaluate the forecasting performance by comparing their forecast values to known values on a hold-out test set. Results We found that machine learning based models consistently outperform the Window Average baselines on forecasting sub-county malnutrition rates in Kenya. For example, the Gradient Boosting model achieves a mean AUC of 0.86 when forecasting with a 6-month time horizon, compared to an AUC of 0.73 achieved by the Window Average model. The Window Average method particularly fails to correctly forecast malnutrition in parts of West and Central Kenya where the acute malnutrition rate is variable over time and typically less than 15%. We further found that machine learning models with satellite-based features alone also outperform Window Averaging baselines, while not needing clinical data at inference time. Finally, we found that recently observed outcomes and the remotely sensed data are key indicators. Our results demonstrate the ability of machine learning models to accurately forecast malnutrition in Kenya at a sub-county level from a variety of indicators. Conclusions To the best of the authors’ knowledge, this work is the first to use clinical indicators collected via DHIS2 to forecast acute malnutrition in childhood at the sub-county level in Kenya. This work represents a foundational step in developing a broader childhood malnutrition forecasting framework, capable of monitoring malnutrition trends and identifying impending malnutrition peaks across more than 80 low- and middle-income countries collecting similar DHIS2 datasets.
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Soltany, Razia, Mir Salamuddin Hakim, Khwaja Mir Islam Saeed, and Shoaib Naeemi. "COVID-19 reinfection in Afghanistan: A descriptive analysis of data from DHIS2, 2022." Afghanistan Journal of Infectious Diseases 2, no. 1 (2024): 25–32. http://dx.doi.org/10.60141/ajid/v.2.i.1.4.
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Background: Despite millions of COVID-19 infections worldwide since the beginning of the pandemic, relatively few confirmed cases of COVID-19 reinfection have been reported. In Afghanistan, COVID-19 undetected cases are more than detected cases. This study aims to describe the burden of COVID-19 reinfection cases in Afghanistan, along with the epidemiological and demographical patterns. Methods: A descriptive study of national-wide secondary data on COVID-19 reinfection cases was carried out from January to June 2022. Data were extracted from the District Health Information Software 2 (DHIS2) and managed and analyzed using Microsoft Excel and Epi Info V.7.2.1. Results: In 2022, 79 reinfection cases of COVID-19 were reported, with males being more affected than females. The mean age of re-infected patients was 39, with most from Wardak province. Most cases occurred within six months after the primary infection. Cough was more prevalent among reinfected cases. Only 26 patients had taken two doses of the vaccine, while 44 (55.70%) had not received it. Out of all cases, 44 (55.70%) were recovered and 5 (6.85%) died. Conclusion: The COVID-19 reinfection rate is very low in Afghanistan, which was common in males since other cases might be unreported. Coughing was more common among reinfection patients. Relying on the results, vaccination and awareness-raising may play a protective role in reinfection; hence, enhancement of vaccination and taking preventive measures are recommended to prevent further reinfection.
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Ario, Alex Riolexus, Dativa M. Aliddeki, Daniel Kadobera, et al. "Uganda’s experience in establishing an electronic compendium for public health emergencies." PLOS Global Public Health 3, no. 2 (2023): e0001402. http://dx.doi.org/10.1371/journal.pgph.0001402.
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Uganda has implemented several interventions that have contributed to prevention, early detection, and effective response to Public Health Emergencies (PHEs). However, there are gaps in collecting and documenting data on the overall response to these PHEs. We set out to establish a comprehensive electronic database of PHEs that occurred in Uganda since 2000. We constituted a core development team, developed a data dictionary, and worked with Health Information Systems Program (HISP)-Uganda to develop and customize a compendium of PHEs using the electronic Integrated Disease Surveillance and Response (eIDSR) module on the District Health Information Software version 2 (DHIS2) platform. We reviewed literature for retrospective data on PHEs for the compendium. Working with the Uganda Public Health Emergency Operations Center (PHEOC), we prospectively updated the compendium with real-time data on reported PHEs. We developed a user’s guide to support future data entry teams. An operational compendium was developed within the eIDSR module of the DHIS2 platform. The variables for PHEs data collection include those that identify the type, location, nature and time to response of each PHE. The compendium has been updated with retrospective PHE data and real-time prospective data collection is ongoing. Data within this compendium is being used to generate information that can guide future outbreak response and management. The compendium development highlights the importance of documenting outbreak detection and response data in a central location for future reference. This data provides an opportunity to evaluate and inform improvements in PHEs response.
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Ugwu, GO, A. Odii, A. Bisi-Onyemaechi, et al. "Digital Technology Tool for Routine Immunization: Lessons Learned from Open Data Kit Intervention and Way Forward." Nigerian Journal of Clinical Practice 26, Suppl 1 (2023): S65—S70. http://dx.doi.org/10.4103/njcp.njcp_561_22.
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ABSTRACT Background: Digital technology tools like open data kit (ODK) can improve the quality of routine immunization (RI) data, yet we know very little about how well it performs. Aim: This study evaluated the implementation of ODK for RI data capture and transmission. We also discussed the way forward for the uptake of ODK for RI data capture and transmission. Methods: Sixty focal persons were recruited from 60 PHCs and trained for two days on the use of ODK. The DHIS2 tools that include daily immunization register, daily vaccine utilization summary, and daily TT immunization register were loaded into ODK. The participants collected RI data and transmitted same via ODK to a secure server for 3 months. At the end of the exercise, we conducted six (ten per group) focus group discussions with them. They were interviewed to share their experiences. The implementation was evaluated using Proctor’s outcomes with a specific focus on acceptability, adoption, and appropriateness. Results: Findings show that users were satisfied with the use of ODK for RI data capture and transmission. It was reported that ODK removed the need to transport data from the facilities to the local government headquarters for entry into the DHIS2 platform. It was also learned that it reduced errors and inconsistencies commonly reported in RI data. Conclusion: Digital technologies like ODK can improve the quality of RI data in Nigeria. Policymakers and implementers must, however, consider contextual issues relating to the incentivization of staff.
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Wulandari, Pradea. "Platform WEB Based District Health Information System Versi 2 (DHIS2) dalam Pembuatan Disease Registry." Journal of Information Systems for Public Health 7, no. 3 (2022): 1. http://dx.doi.org/10.22146/jisph.71322.
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Matin, Hamidullah, Khwaja Mir Islam Saeed, Mir Salamuddin Hakim, and Shoaib Naeemi. "COVID-19 Vaccines Coverage in Afghanistan: a descriptive analysis of secondary data from DHIS2." Razi International Medical Journal 3, no. 2 (2023): 62–69. http://dx.doi.org/10.56101/rimj.v3i2.95.
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Background: Mass immunization is an economical and effective way to control the pandemic of COVID-19. Afghanistan started its first COVID-19 vaccination campaign at the national level in February 2021. Upon initiation, 10 target groups have been given priority to get vaccinated. This study focuses on a descriptive analysis of COVID-19 vaccination coverage at the national level. Methods: This is a descriptive secondary data analysis of COVID-19 vaccination coverage from all 34 provinces of Afghanistan from February 2021 to June 2022. All data analyzed in this study were extracted from the District Health Information System 2 (DHIS2), National EPI’s database for tracking EPI indicators, and analyzed using Epi Info V.7.2.1. Results: Since the launch of the COVID-19 vaccination, 33% of the population in Afghanistan has received at least one dose of the COVID-19 vaccine, among which 26% are fully immunized. The coverage accounts for 13% of the total population in the country. Among the immunized population, 48% are female and 52% are male. At the provincial level, Kabul is the top-performing province with 54% of the target population, followed by Kandahar with 43%. Zabul and Nuristan had the lowest vaccination coverage of the target population, with only 5% vaccinated. Among administered vaccines, Johnson & Johnson are administered widely (67%), followed by Sinopharm (18%) and AstraZeneca (15%). Conclusion: Vaccine coverage for all categories is lower than expected, with a higher interest in one-dose regimen vaccines. The low coverage shows a low demand for vaccine uptake. Provinces with lower coverage could undertake extended campaigns to maintain and enhance the coverage of vaccination. There is a demand for interventions to improve public awareness about COVID-19 as well. Furthermore, advocacy for full vaccination is required.
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Aila, Mohamed Asafa, and Peter Kithuka. "Use of routine health information for decision making among health care workers in Marsabit county, Kenya." International Journal Of Community Medicine And Public Health 8, no. 10 (2021): 4726. http://dx.doi.org/10.18203/2394-6040.ijcmph20213768.
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Background: In Kenya today, public health facilities at different levels collect a large amount of routine health (RH) data. However, with the introduction of district health information software (DHIS2), recent evidence has shown low levels of data are used by the targeted stockholders in Kenya. The therefore study aims to examine the association of human resource and information technology factors associated with the frequent use of RH data in decision-making among health-workers in Marsabit county.Methods: The study employed a cross-sectional design. Researchers purposively stratified 201 health workers by cadre, then probability proportionate sampling was applied to get the required number from every cadre. Both qualitative and quantitative data were collected and entered into the SPSS software, descriptive measurement and Chi square test were used to analyze the dataResults: The majority (74%) of respondents had basic computer skills but 80% of respondent lacked training in health information management. The study found that training increases the likelihoods of healthcare workers utilizing RH data. The type of software (DHIS2 and MedBoss) in use had a significant association with the frequent use of RH data at a p (0.047<0.05).Conclusions: The study revealed that the health facilities lacked ample IT accessories even though internet and electricity connectivity was not limited, however, RHI use was not optimal in health facilities. The study found that the majority of respondents lacked training in RH data implying that training may influence the overall use of the routine data. The study also observed that RH data were used for decision-making frequently for a range of management functions.
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Chrysantina, Aprisa, Guardian Sanjaya, Matthieu Pinard, and Ni’mah Hanifah. "Improving Health Information Management Capacity with Digital Learning Platform: The Case of DHIS2 Online Academy." Procedia Computer Science 161 (2019): 195–203. http://dx.doi.org/10.1016/j.procs.2019.11.115.
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Jayatilleke, Achala Upendra, Roshan Hewapathirana, and Achini Silva. "43 District health information system 2 (DHIS2) for injury surveillance in a resource constrained context." Injury Prevention 21, Suppl 2 (2015): A15.3—A16. http://dx.doi.org/10.1136/injuryprev-2015-041654.43.
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