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This book focuses on a range of geospatial applications for environmental health research, including environmental justice issues, environmental health disparities, air and water contamination, and infectious diseases. Environmental health research is at an exciting point in its use of geotechnologies, and many researchers are working on innovative approaches. This book is a timely scholarly contribution in updating the key concepts and applications of using GIS and other geospatial methods for environmental health research. Each chapter contains original research which utilizes a geotechnical tool (Geographic Information Systems (GIS), remote sensing, GPS, etc.) to address an environmental health problem. The book is divided into three sections organized around the following themes: issues in GIS and environmental health research; using GIS to assess environmental health impacts; and, geospatial methods for environmental health. Representing diverse case studies and geospatial methods, the book is likely to be of interest to researchers, practitioners and students across the geographic and environmental health sciences.

A routine health information system is one of the essential components of a health system. Interventions to improve routine health information system data quality and use for decision-making in low- and middle-income countries differ in design, methods, and scope. There have been limited efforts to synthesise the knowledge across the currently available intervention studies. Thus, this scoping review synthesised published results from interventions that aimed at improving data quality and use in routine health information systems in low- and middle-income countries. We included articles on intervention studies that aimed to improve data quality and use within routine health information systems in low- and middle-income countries, published in English from January 2008 to February 2020. We searched the literature in the databases Medline/PubMed, Web of Science, Embase, and Global Health. After a meticulous screening, we identified 20 articles on data quality and 16 on data use. We prepared and presented the results as a narrative. Most of the studies were from Sub-Saharan Africa and designed as case studies. Interventions enhancing the quality of data targeted health facilities and staff within districts, and district health managers for improved data use. Combinations of technology enhancement along with capacity building activities, and data quality assessment and feedback system were found useful in improving data quality. Interventions facilitating data availability combined with technology enhancement increased the use of data for planning. The studies in this scoping review showed that a combination of interventions, addressing both behavioural and technical factors, improved data quality and use. Interventions addressing organisational factors were non-existent, but these factors were reported to pose challenges to the implementation and performance of reported interventions.

Background The Health Information System (HIS) in public healthcare services in Serbia was introduced in 2008, with the first comprehensive evaluation of its maturity conducted in 2021. Since then, several improvement initiatives have been implemented. This study aimed to assess the extent of HIS advancement between 2021 and 2024 and to identify both the desirable and realistic future maturity status. Methods The maturity assessment of the Serbian HIS in 2024 was conducted using the same tool as in 2021: The Health Information Systems Stages of Continuous Improvement (SOCI), enabling direct comparison between the two periods. Progress was measured across five domains: Leadership and Governance, Management and Workforce, Information and Communication Technologies (ICT), Standards and Interoperability, and Data Quality and Use. These domains covered 13 components and 39 single subcomponents, with their maturity stages being assessed on a 5-point Likert scale on the basis of the opinions of key informants and documented through a desk review. Higher scores indicate a higher level of development. Along with a current assessment of maturity, key informants identified desired maturity levels for the future, using the same scale. Data were presented as comparisons in total scores per domain in 2024 versus 2021, for both current and projected statuses. Results Between 2021 and 2024, the overall maturity of the Serbian HIS improved by nearly 1 point (from 1.6/5 to 2.5/5). The same difference of 0.9 was observed between the current 2024 status and the future desired status (2.5 versus 3.4). The most notable improvements were observed in the HIS Strategic Plan under Leadership and Governance (2.5-point increase) and Business Continuity under ICT Infrastructure (2-point increase). The primary driver of progress over the past 3 years was the adoption of the national Program for Digitalization in the Health System of Serbia (eHealth Strategy) and its corresponding Action Plan, which served as a development blueprint. Conclusions Substantial progress in HIS maturity was achieved between 2021 and 2024, driven by strong governmental commitment, international donor support, and the engagement of dedicated national professionals. If current momentum and resourcing are sustained, the projected maturity levels are likely to be attainable in the near future.

Background Health Information System is the key to making evidence-based decisions. Ethiopia has been implementing the Health Management Information System (HMIS) since 2008 to collect routine health data and revised it in 2017. However, the evidence is meager on the use of routine health information for decision making among department heads in the health facilities. The study aimed to assess the proportion of routine health information systems utilization for evidence-based decisions and factors associated with it. Method A cross-sectional study was carried out among 386 department heads from 83 health facilities in ten selected districts in the Amhara region Northwest of Ethiopia from April to May 2019. The single population proportion formula was applied to estimate the sample size taking into account the proportion of data use 0.69, margin of error 0.05, and the critical value 1.96 at the 95% CI. The final sample size was estimated at 394 by considering 1.5 as a design effect and 5% non-response. The study participants were selected using a simple random sampling technique. Descriptive statistics mean and percentage were calculated. The study employed a generalized linear mixed-effect model. Adjusted Odds Ratio (AOR) and the 95% CI were calculated. Variables with p value < 0.05 were considered as predictors of routine health information system use. Result Proportion of information use among department heads for decision making was estimated at 46%. Displaying demographic (AOR = 12.42, 95% CI [5.52, 27.98]) and performance (AOR = 1.68; 95% CI [1.33, 2.11]) data for monitoring, and providing feedback to HMIS unit (AOR = 2.29; 95% CI [1.05, 5.00]) were individual (level-1) predictors. Maintaining performance monitoring team minute (AOR = 3.53; 95% CI [1.61, 7.75]), receiving senior management directives (AOR = 3.56; 95% CI [1.76, 7.19]), supervision (AOR = 2.84; 95% CI [1.33, 6.07]), using HMIS data for target setting (AOR = 3.43; 95% CI [1.66, 7.09]), and work location (AOR = 0.16; 95% CI [0.07, 0.39]) were organizational (level-2) explanatory variables. Conclusion The proportion of routine health information utilization for decision making was low. Displaying demographic and performance data, providing feedback to HMIS unit, maintaining performance monitoring team minute, conducting supervision, using HMIS data for target setting, and work location were factors associated with the use of routine health information for decision making. Therefore, strengthening the capacity of department heads on data displaying, supervision, feedback mechanisms, and engagement of senior management are highly recommended.

To raise awareness about health inequalities, a well-functioning health inequality monitoring system (HIMS) is crucial. Drawing on work conducted under the Joint Action Health Equity Europe, the aim of this paper is to illustrate the strengths and weaknesses in current health inequality monitoring based on lessons learned from 12 European countries and to discuss what can be done to strengthen their capacities. Fifty-five statements were used to collect information about the status of the capacities at different steps of the monitoring process. The results indicate that the preconditions for monitoring vary greatly between countries. The availability and quality of data are generally regarded as strong, as is the ability to disaggregate data by age and gender. Regarded as poorer is the ability to disaggregate data by socioeconomic factors, such as education and income, or by other measures of social position, such as ethnicity. Few countries have a proper health inequality monitoring strategy in place and, where in place, it is often regarded as poorly up to date with policymakers’ needs. These findings suggest that non-data-related issues might be overlooked aspects of health inequality monitoring. Structures for stakeholder involvement and communication that attracts attention from policymakers are examples of aspects that deserve more effort.

Background Assessing the maturity level of digital solutions and the ability of digital systems to meet the changing needs and demands related to their purposes is essential. Despite Ethiopia’s significant efforts in expanding the electronic Community Health Information System (eCHIS), the results have been below expectations, varying by location and hindered by several issues. This research aimed to evaluate the current maturity status, identify implementation gaps and propose future directions for improving eCHIS in Ethiopia. Methods Through a consultative workshop, a collaborative assessment was carried out with the participation of key stakeholders and experts. The Stages of Continuous Improvement (SOCI) tool was used to measure maturity levels in 39 subcomponents, 13 components and 5 core domains. The evaluation focussed on the leadership and governance of the digital health system, human resources, information and communication technology (ICT) infrastructure, interoperability and data quality and use. The measurement scales used were Emerging, Repeatable, Defined, Managed and Optimized. Results The current maturity status of eCHIS is rated as repeatable (2.24/5) and aims to improve to the defined state (3.75/5) by 2025. Comparatively, the leadership and governance domain had the highest level of maturity (2.67/5), followed by the standards and interoperability domain (2.47/5) and the data quality and use domain (2.28/5). The ICT infrastructure (1.67/5) and management and workforce (2.09/5) domains have the lowest level of maturity. Strengths include the presence of a comprehensive HIS strategic plan, updated standard guidelines and operational manuals, a defined organizational structure and processes for eCHIS, defined data management, reporting and use procedures, monitoring and evaluation (M&E) mechanisms for eCHIS and central eCHIS infrastructure capacity. Areas of improvement in the digital solution included the absence of certain aspects such as a standard eCHIS training curriculum (both pre-service and in-service), reliable power supply and connectivity at health facilities, robust business continuity plans, a multiyear budget and a skilled workforce. Furthermore, weaknesses were also found in the enforcement of existing laws, regulations and policies, as well as leadership and coordination within the eCHIS program at lower levels. Conclusions The implementation status of eCHIS in Ethiopia was at the repeatable stage, with the ICT infrastructure domain having the lowest level of maturity compared with the other four domains. By 2025, the current maturity status was planned to advance to the defined stage by addressing the identified gaps. To achieve this maturity level, various action points are suggested.