The Ethiopian Health Information System: Where are we? And where are we going?

Health Information System (HIS) is a system that integrates data collection, management, and interpretation, including the use of the information to improve the quality of service and care through better management at all levels of health services (1). Early on, efforts to restructuring HIS to systematically collect, analyze, and report data for improved management in developing countries were undertaken by national program managers of vertically structured programs. In recent years, however, HIS in developing countries, including Ethiopia, has gained more and more attention as more effort by governments, international agencies, non-governmental organizations, donors, and other development partners seek to improve health care to reverse disease trends in these countries. The expansion of the health system, diagnostic capacity with the rapid transition of diseases epidemiology, and information technology played a crucial role in the increment of health data demand and information use in the health sector over the years (2). HIS encompasses a number of issues: data use, data quality, quality of care, e-Health and other relevant topics. This editorial provides a highlight of each of these topics and associated challenges. Because these entities are very much linked, it is not possible to expect successful progression in the use and quality of health information systems unless they are treated holistically

LITERATURE REVIEW: FAKTOR KEBERHASILAN IMPLEMENTASI SISTEM INFORMASI MANAJEMEN RUMAH SAKIT (SIMRS)

Sistem Informasi Manajemen Rumah Sakit (SIMRS) merupakan suatu sistem teknologi informasi komunikasi yang memproses dan mengintegrasikan seluruh alur proses pelayanan rumah sakit dalam bentuk jaringan koordinasi, pelaporan dan prosedur administrasi untuk memperoleh informasi secara tepat dan akurat dan merupakan bagian dari Sistem Informasi Kesehatan. Penelitian ini bertujuan untuk mengetahui faktor keberhasilan implementasi SIMRS dengan metode HOT-Fit. Penelitian ini menggunakan metode literature review. Pengumpulan data menggunakan data sekunder dan dianalisis secara deskriptif yang dilakukan dengan mendeskripsikan fakta yang ada, analisa data dilakukan dengan mencari kesamaan, ketidaksamaan, pandangan, ringkasan terhadap beberapa penelitian. Jurnal yang dianalisis sebanyak 14 jurnal dari tahun 2020-2022. Hasil penelitian ada 3 faktor yang mempengaruhi implementasi SIMRS yaitu faktor manusia adalah kepuasan pengguna dan penggunaan sistem. Faktor organisasi adalah struktur organisasi, lingkungan organisasi, dukungan pimpinan, manajemen proyek, dan kondisi fasilitas. Faktor teknologi adalah kualitas sistem, kualitas informasi, kualitas layanan dan vendor support. Perlu adanya peningkatan hubungan antara teknologi dan penggunaan SIMRS dapat harus ditingkatkan guna mendukung pelayanan yang prima dengan memberi pelatihan penggunaan sistem

'The false reporter will get a praise and the one who reported truth will be discouraged': a qualitative study on intentional data falsification by frontline maternal and newborn healthcare workers in two regions in Ethiopia

INTRODUCTION: Health Management Information Systems (HMIS) are vital to ensure accountability and for making decisions including for tracking the Sustainable Development Goals. The Ethiopia Health Sector Transformation Plan II includes preventing data falsification as a major strategic initiative and our study aimed to explore the reasons why healthcare providers intentionally falsify maternal and newborn health (MNH) data in two regions of Ethiopia. METHODS: We conducted a qualitative study in two hospitals, four health centres and their associated health posts in Oromia and Amhara regions. We conducted 45 in-depth interviews with health facility managers, quality improvement (QI) focal persons, health information technicians, MNH care providers, Health Extension Workers and QI mentors. Data were collected in local languages and transcribed in English. During analysis we repeatedly read the transcripts, coded them inductively using NVivo V.12, and categorised the codes into themes. RESULTS: Participants were hesitant to report personal data falsification but many reported that falsification is common and that they had experienced it in other facilities or had been told about it by other health workers. Falsification was mostly inflating the number of services provided (such as deliveries). Decreasing the number of deaths or reclassifying neonatal death into stillbirths was also reported. An overarching theme was that the health system focuses on, and rewards, the number of services provided over any other metric. This focus led to both system and individual level incentives for falsification and disincentives for accurate reporting. CONCLUSION: Our finding suggests that to reduce facility level data falsification policy makers might consider disentangling reward and punishments from the performance reports based on the routine HMIS data. Further studies examining the high-level drivers of falsification at regional, national and global levels and effective interventions to address the drivers of data falsification are needed

Assessment of immunization data management practices, facilitators, and barriers to immunization data quality in the health facilities of Tach Gayint district, Northwest Ethiopia

AbstractIntroduction: Although data quality mainly depends upon the proper management of its primary sources, limited studies examined immunization data management practice in Ethiopia.Aim: To explore data management practices, facilitators, and barriers to immunization data quality among front-line immunization experts in the Tach Gayint district of Northwest Ethiopia.Methods: A mixed method study design was applied using document review and key-informant interviews. Quantitative data was collected through document review from 18 health facilities and 26 key-informant interviews, were conducted on experts of immunization for qualitative data. A STATA version 14.1 was used for quantitative data analysis. Qualitative data was transcribed verbatim and translated back into English. Data was coded, reduced, and searched for salient patterns. Thematic analysis was done using open-code version 4.02.Results: The Health Management Information System data recording tools were often lacking. The significant number (83.3%) of health facilities practiced immunization information display, while dissemination at the local level was low. The key informants mentioned that they were responsible for conducting regular Performance Monitoring Team (PMT) and Lots Quality Assurance Sampling (LQAS) as facilitators. Furthermore, a shortage of recording tools, limited supportive supervision, vertical reporting, impracticality of Lots of Quality Assurance Sampling (LQAS) at the health posts, poor implementation of Community Health Information System (CHIS), and mass vaccination were barriers identified to immunization data quality.Conclusion: We found that majority of health workers use locally developed tools instead of using the standard data recording and reporting tools. Regular Performance Monitoring Team meetings and Lots Quality Assurance Sampling assessment were found to be facilitators. Furthermore, limited supportive supervision, vertical reporting and poor implementation of Community Health Information System were barriers. Therefore, strengthening the use of standard recording and reporting tools, conducting regular supportive supervision, and implementing routine vaccination services are recommended to improve the data management practice. [Ethiop. J. Health Dev. 2021; 35(SI-3):28-38]Key words: Immunization, Data management practice, Data quality, Information us

The Health Management Information System and HIV and AIDS monitoring: Insights from Ethiopia

Background: A well-performing health information system (HIS) provides timely, complete, accurate and easily retrievable data. However, HIS in low- and middle-income countries (LMICs), including Ethiopia, is highly complex and influenced by pressures from donors, politics and technical factors. Hence, these countries experience persistent challenges in producing quality data and difficulties using health management information system (HMIS) data from their HISs. Objectives: This study aimed to evaluate how HMIS was perceived and utilised in HIV and AIDS monitoring in Ethiopia, and views regarding the influence of determinants on the use of HMIS. Method: A qualitative evaluative case study using focus group discussions with data producers and users was conducted in selected health facility in Addis Ababa. A purposive critical case sampling was used to recruit participants. Results: Key findings revealed that HIV and AIDS-specific indicators, information and communication technology (ICT) and other related resources were critical barriers to the successful use of the HMIS. Participants believed these technical issues impacted the quality of data adversely and, subsequently, the conversion of that data to information and using it to monitor the HIV and AIDS programme’s performance. Conclusion: Technical factors affected all strategic decisions taken by the organisation. The health facilities did not process information as expected. However, staff performed the HMIS tasks with the tools available as they tried to make sense of data. Contribution: This study contributed to the body of knowledge by identifying the technical factors on data quality and use of HMIS for HIV and AIDS monitoring

Calidad de gestión y atención por teleconsulta en el Centro de Salud Tuman, Chiclayo

La actual indagación presentó como propósito determinar la relación entre la calidad de gestión y atención por teleconsulta en el Centro de Salud Tuman, Chiclayo, el estudio es de tipo básica. La investigación es de diseño no experimental descriptivo y correlacional con una población conformada por 90 personas, debemos indicar que la muestra es igual a la población por ello se refiere a una muestra censal la cual está conformada por 45 trabajadores del Centro de Salud Tuman y 45 pacientes, logrando una totalidad de 90 personas en el Centro de Salud Tuman, Chiclayo entre el período julio hasta agosto con un muestreo no probabilístico. En consecuencia, se obtuvo como resultados que según la prueba estadística Rho de Spearman indica que ambas variables tienen un coeficiente de correlación de 0,720 según la escala es correlación alta con una significancia p=0.000. Esta implementación selectiva es el medio de calidad de la atención indicando que la gestión de la información es uno de los componentes básicos de un sistema de salud. La conclusión evidencia que la calidad de gestión si se relaciona con la atención por teleconsulta en el Centro de Salud Tuman, Chiclayo

On people, data and systems : perspectives on routine health data processing and its digitalization in Tanzania

Background: Facility-based routine health information is captured in health management information systems by health care providers and is the main data source for health system planning and outcome monitoring in Tanzania and other low- and middle-income countries. While this system is fully digitalized in high-income countries, it is still partly paper-based in others. These use i) facility registers, ii) daily tally sheets and iii) monthly summary forms, which are later entered into the District Health Information System-2 software. These hybrid systems are prone to errors related to i) data entry, ii) calculation and iii) data transfer, with negative implications for data completeness and availability. The unavailability of data and lack of trust in its quality may lead to low data use for resource forecasting and planning, especially at subnational and facility levels. Through automatization of data processing, digital technology may be able to address these challenges, making it especially attractive in settings with high disease burdens and few resources. One example of a promising digital solution for low-resource settings is Smart Paper Technology, which produces automated electronic registers and summary reports by scanning bar-coded forms from individual service encounters. Implementation research, however, suggests a complex interplay between the implementation environment and the introduction and sustained institutionalization of technology. The aim of this thesis was to understand the social practices involved in generating and processing routine maternal and newborn health data, using paper-based and digital tools within the health management information system in Tanzania. Smart Paper Technology and the current health management information system with its different digital components are used for evaluation. Study I had the objective of understanding health care providers’ and facility/district managers’ perceptions of Smart Paper Technology and to assess time spent on documentation with the new system. A time-motion study, before and after the introduction of the technology, was applied together with eight focus group discussions with 18 health care providers from three health facilities and 11 in-depth interviews with healthcare managers from one district authority. Quantitative data was analyzed using descriptive statistics and bivariable modelling. Reflexive thematic analysis was used to analyze qualitative data. Findings illustrate challenges to Smart Paper Technology implementation related to pre-existing health system bottlenecks, e.g. lack of human resources, supervision and transport, but also a difference in values assigned to the new system by health care providers and their managers. Health care providers found Smart Paper Technology useful and applicable to their context with perceived benefits for documentation and clinical care. These experiences were confirmed by quantitative data, showing no significant difference between time spent on overall documentation pre- and post-introduction of Smart Paper Technology (27 vs 26 %, adjusted p 0.763) but an increase in time spent on clinical tasks (26.9 vs 37.1%, adjusted p 0.001). Health care managers, in contrast, found it difficult to identify benefits from the new technology for their own work related to national reporting, due to access problems with the digital dashboard and questionable quality of Smart Paper Technology data. They therefore continued to focus managerial efforts on the existing health management information system. Study II’s objective was to assess the quality of Smart Paper Technology data for maternal care services related to i) completeness and timeliness and ii) internal consistency. A cross-sectional survey over 12 months was performed in 13 health facilities using data from the Smart Paper Technology system and District Health Information System-2. Descriptive statistics were produced based on indicators derived from the World Health Organization’s Data Quality Review Toolkit. Results show that data quality of the Smart Paper Technology system was not superior to that of the pre-existing health management information system overall. This may be linked to the effects of duplicate data entry on health care provider performance and consequently on data completeness. Smart Paper Technology performed slightly better in some aspects of internal consistency: Fewer health facilities produced only one or two outliers with Smart Paper Technology in each month of the study period (antenatal care=4, care during labour = 6, postnatal care =4) than with the District Health Information System-2 (antenatal care= 7, care during labour= 9, postnatal care= 6). Smart Paper Technology also yielded higher consistency for the documented postpartum use of oxytocin in relation to the number of documented deliveries with 62% of facilities showing a less than 10% difference between these indicators as opposed to 38% for the District Health Information System-2. However, the pre-existing system demonstrated better data quality in all other quality dimensions, i.e. data completeness, timeliness and consistency of data trends over the study period. Study III: The objective was to improve understanding about the processes involved in health care providers’ data use; which type of information is used together with health management information system data and for what purposes. A constructivist grounded theory-based ethnographic approach was applied, consisting of i) 14 in-depth interviews with health care providers from maternity wards in two hospitals, as well as ii) 48 hours of observation in the maternity wards and ii) two focus group discussions with 11 health care providers from the same hospitals. Findings illustrate how health care providers appropriated numeric data from the official health management information system and narrative data that they had produced for clinical documentation to safeguard social relationships with superiors, patients and the community they served. While they identified themselves as data collectors and not users of the health management information system, they applied narrative clinical documentation systems to service improvement and to protect themselves against litigation or managerial reprimands. Study IV’s objective was to generate knowledge on experiences and perceptions of health care policymakers in Tanzania related to data, data systems and the implementation of digital technology to support health information management. 16 in-depth interviews with healthcare managers from national and subnational levels were conducted and analyzed using reflexive thematic analysis. Results suggest that the health management information system in Tanzania is governed using institutional and discretionary power. Institutional power was mainly used at the national level to conceptualize data collection and processing systems and the scale-up of digitalization. Discretionary power was mainly used for implementation at subnational level. The use of different power practices was influenced by available funding and health care managers’ perception that health care providers, the primary data collectors, lack motivation to perform and are unpredictable in their actions regarding the continuous production of good data quality. Conclusions: Acceptance or rejection of digital technology was influenced to a considerable extent by social practices at all levels of the health system. These included actors’ perceived benefits of maintaining existing social practices. These practices, which are part of an organization’s culture related to data and data processes, require attention during the conceptualization and implementation of health information systems. Numeric and contextual information is used concomitantly at various levels of Tanzania’s health management information system. The health management information system in Tanzania forms a complex adaptive system with inherently high levels of unpredictability, non-linearity, self-organization and adaptation over time. Health care managers’ power practices in the conceptualization and implementation of policies reflect this complexity. Contextual factors affect digital technology integration and have consequences for data quality and use of digital AND paper-based health management information systems. Context may therefore be even more important than the format and technology of data collection and processing

Evaluating performance of routine health information system for reproductive health in Tshwane

The Routine Health Information System (RHIS) in South Africa utilises the District Health Information System (DHIS) to manage reproductive health programme data. The reproductive health programme requires an RHIS that is capable of generating quality data that will be used for decision-making. The study intended to evaluate the performance of the RHIS using DHIS in generating quality reproductive health information in the Tshwane district. The study was conducted in 13 facilities in the City of Tshwane. A sequential explanatory mixed-method design was employed to evaluate the performance of the RHIS in generating quality reproductive health information. A Delphi technique was then used to develop strategies to improve the management of reproductive health data. The stratified random, purposive critical case and purposive sampling were used to select health care providers (HCPs), facility managers and experts, respectively. Data were collected from HCPs, facility managers and experts through questionnaires, in-depth interviews, and the modified Delphi technique, respectively. Quantitative data were analysed using the Statistical Package for Social Sciences (SPSS) program for Windows, and thematic analysis was employed for the qualitative data. The majority of HCPs were not trained on the RHIS. Data generated from the system was therefore of poor quality. Managers played a critical role in managing reproductive health information by ensuring the generation of high-quality data. Reproductive health information was used in managing the facility and improving the service, however the culture of information use was suboptimal. Several challenges related to behavioural (HCPs’ competence, confidence, interest and commitment), technical (complex design of data collection tool), and organisational (training, resources, supportive supervision and information culture) factors affected data quality and the use of information negatively. The reproductive health programme was not performing well due to a lack of skills for inserting intrauterine contraceptive devices, patients’ preference for short-acting reversable contraceptive (SARC) methods, and the use of private practitioners who failed to report reproductive services on the RHIS. The performance of the RHIS was below expectation because of the suboptimal level of data quality and use of information. Strategies were developed to address the factors affecting the data management process, with the aim of improving the performance of the RHIS in managing reproductive health information.Health StudiesPh. D. (Public Health