Annual Meeting of the European Regional Forum of the Public Health Emergency Operations Centre Network (EOC-NET) – World Health Organization (WHO)

Report on Knowledge Attributes of Health Management Information Systems for Emergency Preparedness

1.0 Introduction: Aligning Health Emergency Knowledge Management with Sustainable Development Goals

Effective knowledge management is fundamental to mitigating the impact of public health emergencies and is a critical component in achieving Sustainable Development Goal 3 (Good Health and Well-being), particularly Target 3.d concerning early warning and risk management. Historical analysis of outbreaks, including Ebola Virus Disease (EVD), SARS-CoV, MERS-CoV, and COVID-19, reveals persistent knowledge failures that have exacerbated morbidity and mortality rates. The COVID-19 pandemic, in particular, highlighted a crisis in scientific, social, and procedural knowledge, impeding the implementation of effective public health measures.

Conversely, instances where lessons from past emergencies were successfully applied demonstrate the value of robust knowledge systems. Nations that invested in health security and institutional memory following events like the 2014-2016 EVD outbreak or the SARS/MERS epidemics showed greater resilience during subsequent crises. This underscores the importance of systematic knowledge capture to prevent the cyclical “reinventing of the wheel” in emergency response.

A primary challenge is the loss of tacit knowledge—the unarticulated, experience-based wisdom of emergency personnel. This report evaluates the knowledge attributes of selected public Health Management Information Systems (HMIS) to inform the development of the World Health Organization’s ‘Nuggets of Knowledge’ (NoK) platform. The NoK platform aims to preserve this vital tacit knowledge, thereby strengthening global health security and supporting the interconnected goals of the 2030 Agenda for Sustainable Development, including SDG 16 (Peace, Justice, and Strong Institutions) by fostering more effective and accountable health governance.

2.0 Analysis of Health Management Information Systems (HMIS)

2.1 Methodological Approach

A scoping review was conducted to characterize 13 purposively selected HMIS used in health emergencies. The methodology was guided by established frameworks, including Arksey and O’Malley’s six-stage framework and the PRISMA-ScR approach. The central research question focused on identifying the knowledge attributes of HMIS that contain both tacit and explicit knowledge. Data was extracted from published articles, technical reports, and other literature sourced from Web of Science and Google Scholar, with no date restrictions.

2.2 Key Findings on HMIS Characteristics

2.2.1 Evolution and Knowledge Modes

• Systems containing explicit, documented knowledge (e.g., District Health Information System, Geographical Information System) generally predate those designed to incorporate tacit, experiential knowledge (e.g., OpenWHO, ProMED mail).
• A trend was observed towards the development of systems that capture tacit knowledge and integrate information from both formal and informal sources, reflecting a growing recognition of the value of diverse knowledge types in emergency response. This evolution supports SDG 9 (Industry, Innovation, and Infrastructure) by fostering innovation in health information technology.
• The number of publications on all HMIS has increased over time, indicating a growing field of research and development in health information technology to address emerging needs and leverage new technologies.

2.2.2 Distributional Disparities and SDG 10 (Reduced Inequalities)

• A significant disparity was identified in the global distribution of HMIS. Use was initially concentrated in high-income countries before gradually diffusing to lower-income settings.
• Crucially, HMIS containing tacit knowledge remain less accessible in low- and lower-middle-income countries. This digital divide represents a major barrier to achieving SDG 10 (Reduced Inequalities), as it limits the capacity of vulnerable nations to benefit from global knowledge and build resilient health systems.
• This inequity prevents the harnessing of invaluable, locally-generated tacit knowledge from responders in resource-limited settings, who often possess extensive experience in managing emergencies. Bridging this gap is essential for global health equity and fulfilling the SDG pledge to “leave no one behind.”

2.3 Analysis of Knowledge Attributes

The evaluation of HMIS across nine key attributes revealed distinct patterns, with significant implications for designing systems that support the SDGs.

1. Knowledge Mode: The majority of systems (7 of 13) incorporated tacit knowledge, which is critical for actionable, context-specific decision-making. However, systems based purely on explicit data (descriptive knowledge) were more frequently cited, indicating a need to elevate the role of reasoning and experiential knowledge.
2. Immediacy and Practicality: Attributes related to immediate usability (“immediacy”) and relevance (“practicality”) were the most frequently mentioned in the literature. This highlights a demand from emergency responders for knowledge that is directly and swiftly applicable to operational challenges, a key factor in strengthening institutional response under SDG 16.
3. Applicability and Accessibility: While most systems were designed for global applicability, supporting SDG 17 (Partnerships for the Goals), only about half were publicly accessible (open source). This limits cross-border learning and collaboration. Transforming locally relevant systems into globally accessible platforms is a key challenge.
4. Domain: The majority of systems (12 of 13) covered both animal and human health, reflecting a strong alignment with the “One Health” approach. This integrated perspective is vital for addressing zoonotic diseases and building comprehensive health security in line with SDG 3.
5. Source: Systems incorporating tacit knowledge were more likely to draw from both formal (e.g., official reports) and informal (e.g., media, expert opinion) sources. This hybrid approach enhances the richness and timeliness of information, enabling more agile responses.

3.0 Strategic Recommendations for an SDG-Aligned Knowledge Platform

Based on the findings, the following recommendations are proposed for the development of the NoK platform and other future HMIS to ensure they effectively contribute to the Sustainable Development Goals.

1. Promote Equity and Inclusivity (SDG 10): Employ low-cost, low-bandwidth, and interoperable technologies to ensure the platform is accessible in all income settings, thereby closing the digital divide in health knowledge.
2. Foster Innovation and Resilient Infrastructure (SDG 9): The platform should continuously evolve, integrating modern technologies to capture both articulated (explicit) and unarticulated (tacit) knowledge, complementing existing systems rather than duplicating them.
3. Enhance Global Health Security (SDG 3): Prioritize the capture of actionable, practical, and experiential knowledge that can be immediately applied by emergency personnel. The system should provide decision-support tools, not just descriptive data.
4. Strengthen Global Partnerships (SDG 17): Design the platform to be globally applicable and publicly accessible, facilitating cross-sectoral and cross-border learning. Mechanisms should be in place to share lessons learned and best practices while respecting data privacy.
5. Build Strong and Effective Institutions (SDG 16): Involve end-users throughout the development and lifecycle of the platform to ensure it remains user-friendly, relevant, and continuously aligned with the changing needs of emergency responders.

4.0 Conclusion

The analysis confirms that while progress has been made in developing sophisticated HMIS, significant gaps remain, particularly in the equitable distribution and capture of tacit knowledge. HMIS containing tacit knowledge exhibit more favorable attributes for emergency response, such as usability, applicability, and drawing from diverse sources. To advance the 2030 Agenda, future knowledge management platforms must be designed with the principles of the SDGs at their core. An ideal system will be equitable, innovative, actionable, and collaborative, transforming locally-held experiential knowledge into a global public good. By doing so, the global community can build more resilient health systems, reduce inequalities, and ensure better health outcomes for all.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

1. SDG 3: Good Health and Well-being
   • The article’s central theme is managing health emergencies like Ebola, SARS, MERS, and COVID-19. It discusses the high morbidity and mortality rates associated with these outbreaks and emphasizes the importance of strengthening health systems and preparedness to ensure healthy lives and promote well-being for all at all ages.
2. SDG 9: Industry, Innovation and Infrastructure
   • The article extensively evaluates various Health Management Information Systems (HMIS), which are a form of technological infrastructure. It discusses the development and use of innovative solutions like mHealth applications, telemedicine platforms, and online learning tools (OpenWHO) to manage health crises. The text also highlights the need for low-cost, interoperable, and low-bandwidth technologies, linking directly to fostering innovation and building resilient infrastructure.
3. SDG 17: Partnerships for the Goals
   • The article underscores the importance of global cooperation and knowledge sharing. It details the role of the World Health Organization (WHO) in developing global strategies and platforms (like the “Nuggets of Knowledge” platform) to facilitate the sharing of experiential knowledge across countries. The discussion on systems like the Global Early Warning System (GLEWS), which integrates mechanisms from multiple institutions, and the need for cross-border learning from health emergencies, directly relates to strengthening global partnerships.

2. What specific targets under those SDGs can be identified based on the article’s content?

1. Under SDG 3: Good Health and Well-being
   • Target 3.d: Strengthen the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risks.
     • The article directly supports this target by showing how countries that learned from past emergencies were better prepared for subsequent ones. For example, it states, “lessons learned from the disastrous MERS outbreak were used to develop International Health Regulations (2005) [IHR (2005)] capacities in the Republic of Korea’s preparedness system that enabled the country to successfully flatten the epidemic curve of COVID-19.” This demonstrates a strengthened capacity for managing global health risks.
2. Under SDG 9: Industry, Innovation and Infrastructure
   • Target 9.c: Significantly increase access to information and communications technology and strive to provide universal and affordable access to the Internet in least developed countries.
     • The article discusses the distribution of HMIS, noting that their use “was initially limited to higher-income settings but, with time, spread out to LIC and LMIC.” It also highlights the role of “the widespread availability of mobile technologies” in scaling up mHealth applications and the importance of “low-cost, interoperable, open-source, low-bandwidth technologies” for equitable knowledge distribution, which aligns with increasing ICT access.
3. Under SDG 17: Partnerships for the Goals
   • Target 17.6: Enhance North-South, South-South and triangular regional and international cooperation on and access to science, technology and innovation and enhance knowledge sharing on mutually agreed terms.
     • This target is addressed through the article’s focus on global knowledge management. The WHO’s strategy “recommends improving global access to health information and sharing experiential and applied knowledge.” The development of the “Nuggets of Knowledge (NoK) platform” is presented as a tool “to harness the contextual knowledge of emergency response personnel gained from health emergencies to facilitate continuity and preservation of tacit knowledge” across borders.
   • Target 17.8: Fully operationalize the technology bank and science, technology and innovation capacity-building mechanism for least developed countries… and enhance the use of enabling technology, in particular information and communications technology.
     • The article’s evaluation of 13 different HMIS, including telemedicine, mHealth, and GIS, is a direct examination of enabling ICT. The discussion on how systems like DHIS have become “the preferred information system for developing countries due to its open-source contextualized features” shows the practical application of this target.
   • Target 17.18: By 2020, enhance capacity-building support to developing countries… to increase significantly the availability of high-quality, timely and reliable data disaggregated by income, gender, age, race, ethnicity, migratory status, disability, geographic location and other characteristics relevant in national contexts.
     • The article defines HMIS as systems that “support the recording, storage, retrieval, and processing of health information to support decision-making.” The review of systems like the District Health Information System (DHIS) and the WHO Global Health Observatory (WHO GHO), which are designed to improve data collection and availability, directly relates to this target’s goal of increasing the availability of timely and reliable data.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

1. For Target 3.d
   • Indicator 3.d.1: International Health Regulations (IHR) capacity and health emergency preparedness.
     • This indicator is explicitly mentioned in the article: “Similarly, lessons learned from the disastrous MERS outbreak were used to develop International Health Regulations (2005) [IHR (2005)] capacities in the Republic of Korea’s preparedness system that enabled the country to successfully flatten the epidemic curve of COVID-19.” This provides a direct, measurable example of progress.
2. For Target 9.c
   • Implied Indicator: Adoption and use of ICT, such as mHealth applications and telemedicine, in low- and middle-income countries (LMICs).
     • The article implies this indicator by tracking the spread of HMIS to lower-income settings. It states, “The use of all HMIS… was initially limited to higher-income settings but, with time, spread out to LIC and LMIC.” The increased use of mHealth, attributed to “the widespread availability of mobile technologies,” serves as a proxy for measuring ICT access and use in the health sector.
3. For Target 17.6
   • Implied Indicator: Number and reach of global knowledge-sharing platforms for health emergencies.
     • The article provides examples that can be used to measure this, such as the development of the WHO’s “Nuggets of Knowledge (NoK) platform” and the analysis of OpenWHO, an online learning platform. The text notes OpenWHO’s “equivalent distribution across income settings” and its use in “diverse settings,” which are metrics of its reach and effectiveness in knowledge sharing.
4. For Target 17.18
   • Implied Indicator: Availability and use of Health Management Information Systems (HMIS) for decision-making in developing countries.
     • The article’s entire premise is the evaluation of HMIS to support decision-making. It specifically mentions that “DHIS is the preferred information system for developing countries.” The functionality and distribution of such systems serve as a clear indicator of a country’s capacity to produce and use timely, reliable health data.

4. Table of SDGs, Targets, and Indicators

Source: frontiersin.org