Design, develop, and implement the strategic information system on health, dependence, and healthy aging: an analysis of the Mexican experience.

BACKGROUND: The Decade of Healthy Aging (2021-2030) emerges as a 10 years strategy to improve the lives of older adults, their families, and the communities in which they live. One of the actions defined in this framework is related to improving the measurement, monitoring, and understanding of characteristics, factors, and needs related to aging and health. The aim was to analyze and assess the process of construction and development of the Strategic Information System on Health, Funcional Dependence and Aging (SIESDE, for its acronym in Spanish). SIESDE will provide strategic information in Mexico at the municipal, state, and national levels that support the public policies on healthy aging. METHODS: The system processes and analyzes the data sources of the Health Information Systems and the National System of Statistical and Geographical Information. SIESDE comprises three components: (1) Design, construction, and evaluation of the indicators; (2) storage, management, and visualization, and (3) diffusion and translation of information. RESULTS: A total of 135 indicators were built on seven themes: (1) demographic, socioeconomic, and aging conditions, (2) health, (3) functional dependence, (4) healthy aging, (5) health services, (6) social and physical environments, and (7) complex indicators. CONCLUSIONS: SIESDE is an effective system for providing an overall view of health, aging, and functional dependence.

Common data quality elements for health information systems: a systematic review.

BACKGROUND: Data quality in health information systems has a complex structure and consists of several dimensions. This research conducted for identify Common data quality elements for health information systems. METHODS: A literature review was conducted and search strategies run in Web of Knowledge, Science Direct, Emerald, PubMed, Scopus and Google Scholar search engine as an additional source for tracing references. We found 760 papers, excluded 314 duplicates, 339 on abstract review and 167 on full-text review; leaving 58 papers for critical appraisal. RESULTS: Current review shown that 14 criteria are categorized as the main dimensions for data quality for health information system include: Accuracy, Consistency, Security, Timeliness, Completeness, Reliability, Accessibility, Objectivity, Relevancy, Understandability, Navigation, Reputation, Efficiency and Value- added. Accuracy, Completeness, and Timeliness, were the three most-used dimensions in literature. CONCLUSIONS: At present, there is a lack of uniformity and potential applicability in the dimensions employed to evaluate the data quality of health information system. Typically, different approaches (qualitative, quantitative and mixed methods) were utilized to evaluate data quality for health information system in the publications that were reviewed. Consequently, due to the inconsistency in defining dimensions and assessing methods, it became imperative to categorize the dimensions of data quality into a limited set of primary dimensions.

Manual de organización y funciones de la Dirección de Monitoreo Estratégico de Servicios de Salud / Manual of organization and functions of the Directorate of Strategic Monitoring of Health Services

Las funciones de monitoreo a los servicios de salud, se ven fortalecidas por los sistemas de información en salud, en ese sentido el exitoso avance y consolidación del Sistema Integrado de Salud, la conectividad y funcionalidad del 98% de los establecimientos de salud del Ministerio, permiten ahora continuar con las siguientes etapas del proceso buscando la edificación, expansión, mantenimiento y mejora con el objeto de consolidar la gestión de la información como pieza clave en los procesos de evaluación, monitoreo y toma de decisiones. La Dirección de Monitoreo Estratégico de Servicios de Salud, es partícipe directa en el proceso de planificación, implementación, monitoreo, evaluación y seguimiento del Sistema Integrado de Salud y apuesta por su fortalecimiento como una herramienta efectiva y ágil para la ejecución del monitoreo estratégico

The monitoring functions of health services are strengthened by health information systems, in that sense the successful advancement and consolidation of the Integrated Health System, the connectivity and functionality of 98% of the Ministry's health facilities, They now allow us to continue with the next stages of the process seeking construction, expansion, maintenance and improvement in order to consolidate information management as a key piece in the evaluation, monitoring and decision-making processes. The Directorate of Strategic Monitoring of Health Services is a direct participant in the process of planning, implementation, monitoring, evaluation and follow-up of the Integrated Health System and is committed to its strengthening as an effective and agile tool for the execution of strategic monitoring

A framework for health information governance: a scoping review.

BACKGROUND: As a newly emerged concept and a product of the twenty-first century, health information governance is expanding at a rapid rate. The necessity of information governance in the healthcare industry is evident, given the significance of health information and the current need to manage it. The objective of the present scoping review is to identify the dimensions and components of health information governance to discover how these factors impact the enhancement of healthcare systems and services. METHODS: PubMed, Scopus, Web of Science, ProQuest and the Google Scholar search engine were searched from inception to June 2024. Methodological study quality was assessed using CASP checklists for selected documents. Endnote 20 was utilized to select and review articles and manage references, and MAXQDA 2020 was used for content analysis. RESULTS: A total of 37 documents, including 18 review, 9 qualitative and 10 mixed-method studies, were identified by literature search. Based on the findings, six core categories (including health information governance goals, advantages and applications, principles, components or elements, roles and responsibilities and processes) and 48 subcategories were identified to form a unified general framework comprising all extracted dimensions and components. CONCLUSIONS: Based on the findings of this scoping review, health information governance should be regarded as a necessity in the health systems of various countries to improve and achieve their goals, particularly in developing and underdeveloped countries. Moreover, in light of the undesirable effects of the coronavirus disease 2019 (COVID-19) pandemic in various countries, the development and implementation of health information governance models at organizational, national and international levels are among the pressing concerns. Researchers can use the present findings as a comprehensive model for developing health information governance models. A possible limitation of this study is our limited access to some databases.

As Ransomware Attacks on Health Care Surge, Here's What Clinicians and Health Systems Can Do.

This Medical News story discusses the rise in ransomware cyberattacks on health care, as well as new cybersecurity initiatives.

The Role of Health Informatics Research: A Case of a Large-Scale Implementation in Norway.

Many see the role of health informatics research as informing the development and implementation of information technology in clinical practice. The aim of this study is to see if this role is realized in the ongoing implementation of a large-scale health information system in central Norway. By doing a document analysis of the planning documents for the implementation, we assess to what extend evidence from the scientific community is explicitly referenced and used in the implementation planning. We found that evidence available is not explicitly used, and that evidence required is not widely available.

Improving Health Information Systems Data Quality in Sub-Saharan Africa.

Data quality in health information systems (HIS) is essential for informed decision-making in the health sector, particularly in sub-Saharan Africa (SSA) where these systems face many challenges like resource limitations and weak infrastructure. This systematic review assessed the quality of HIS data in the region, focusing on the dimensions, and factors influencing this quality. It highlights the importance of systematic evaluation, ongoing training for data collectors in the analysis and use of data for decision-making, and the adoption of information and communication technologies in the healthcare system to improve data quality. These findings point the way to better use of health data and the need for a more integrated approach to digital health in SSA.

Opportunities and challenges of using a health information system in adolescent health management: A qualitative study of healthcare providers' perspectives in the West Bank, occupied Palestinian territory.

BACKGROUND: Adolescents are a critical demographic facing unique health challenges who are further impacted in humanitarian settings. This article focuses on the urgent need for a structured health information system (HIS) to address the gaps in data availability and evidence-based interventions for adolescent health. The study aims to identify opportunities and challenges in utilizing the HIS to enhance adolescent health in the West Bank by gathering insights from healthcare providers. METHODS: Semi-structured key informant interviews were conducted with participants involved in the HIS regarding adolescent health in the West Bank. They were selected by purposive sampling. Nineteen interviews were conducted between July and October 2022, and thematic analysis was carried out using MAXQDA software. RESULTS: The opportunities identified were the small-scale victories the participants described in building the HIS for adolescent health. These included institutional and individual capacity building, digitalizing parts of the HIS, connection fragmentation of adolescent health activities, multi-sectoral collaboration, reorienting services based on health information, working with limited resources, enhancing community engagement to encourage ownership and active participation, and taking strategic actions for adolescents for information. The challenges were the high workload of staff, lack of health information specialists, limited resources, lack of a unified system in data collection, lack of data on essential indicators, data quality, data sharing, and data sources and use. CONCLUSION: This study showed the potential of the HIS with capacity building, digitization, and collaborative initiatives; it also suffers from issues like staff shortages, non-standardized data collection, and insufficient data for essential indicators. To maximize the impact of the HIS, urgent attention to staff shortages through comprehensive training programs, standardization of data collection systems, and development of a unified core indicator list for adolescent health is recommended. Embracing these measures will allow the HIS to provide evidence-based adolescent health programs, even in resource-constrained and complex humanitarian settings.

Determinants of translating routine health information system data into action in Mozambique: a qualitative study.

INTRODUCTION: Routine health information systems (RHISs) are an essential source of data to inform decisions and actions around health facility performance, but RHIS data use is often limited in low and middle-income country contexts. Determinants that influence RHIS data-informed decisions and actions are not well understood, and few studies have explored the relationship between RHIS data-informed decisions and actions. METHODS: This qualitative thematic analysis study explored the determinants and characteristics of successful RHIS data-informed actions at the health facility level in Mozambique and which determinants were influenced by the Integrated District Evidence to Action (IDEAs) strategy. Two rounds of qualitative data were collected in 2019 and 2020 through 27 in-depth interviews and 7 focus group discussions with provincial, district and health facility-level managers and frontline health workers who participated in the IDEAs enhanced audit and feedback strategy. The Performance of Routine Information System Management-Act framework guided the development of the data collection tools and thematic analysis. RESULTS: Key behavioural determinants of translating RHIS data into action included health worker understanding and awareness of health facility performance indicators coupled with health worker sense of ownership and responsibility to improve health facility performance. Supervision, on-the-job support and availability of financial and human resources were highlighted as essential organisational determinants in the development and implementation of action plans. The forum to regularly meet as a group to review, discuss and monitor health facility performance was emphasised as a critical determinant by study participants. CONCLUSION: Future data-to-action interventions and research should consider contextually feasible ways to support health facility and district managers to hold regular meetings to review, discuss and monitor health facility performance as a way to promote translation of RHIS data to action.

[Managing routine health information system data during a security crisis in the health district of Timbuktu, Mali in 2023]. / La gestion des données du système d'information sanitaire de routine en période de crise sécuritaire dans le district sanitaire de Tombouctou, au Mali en 2023.

Introduction: an effective health information system (HIS) ensures the production, analysis, dissemination and use of reliable and up-to-date information on the determinants of health. However, it can encounter obstacles that hinder its functioning, such as armed conflicts, which limit access and quality of healthcare services. The purpose of our study was to help improve data management for routine health information system in the health district of Timbuktu during a security crisis. Methods: we conducted a descriptive cross-sectional study, among health information management professionals in the Timbuktu Health District from 15 April to 08 September 2023. Data obtained from a survey questionnaire were analyzed using Epi Info version 7.2.2. and processed using Microsoft Word and Excel 2016. Results: a total of 6 health facilities were surveyed. Data collection, analysis and feedback were very poor. Data quality was 100% complete, 92.40% prompt and 68.11% accurate. The major constraints were: low involvement of health workers in the SIS (22.22%), insufficient training on the SISR (29.63%), supervision (47.06%), internet inaccessibility (66.67%), feeling of insecurity (37.04%) and fear (61.76%) in health facilities. Conclusion: our results show low-level processes, poor network coverage, shortage of qualified health information management professionals and increasing insecurity. A broader mixed-methods research would provide a better understanding.

Health information systems with technology acceptance model approach: A systematic review.

In the rapidly evolving landscape of information technologies, individuals and organizations must adapt to the digital age. Given the diversity in users' knowledge and experience with technology, their acceptance levels also vary. Over the past 30 years, various theoretical models have been introduced to provide a framework for understanding user acceptance of technology. Among these, the Technology Acceptance Model (TAM) stands out as a key theoretical framework, offering insights into why new technologies are either accepted or rejected. Analyzing user acceptance of technology has thus become a critical area of study. Healthcare organizations aim to assess the perceived efficacy and user-friendliness of a given technology. This will help health organisations design and implement HIS that meet users' needs and preferences. In this context, how does the TAM clarify the acceptance and use of Health Information Systems (HIS)? To address this inquiry, a comprehensive literature review will be carried out. The systematic review involved 29 studies issued between 2018 and 2023 and searched the databases Pubmed, Scopus, Wos and Ulakbim TR Index. The PRISMA flowchart was used to identify the included studies. According to the results, some variables stand out in the acceptance and utilisation of HIS. Among the users of HIS, it can be said that the results relating to nurses stand out. In particular, there are studies which emphasise that 'gender' is a crucial factor in explaining the models. Another crucial finding of the current systematic review is the need to train users in the acceptance and use of HIS.

Improvements in data completeness in health information systems reveal racial inequalities: longitudinal national data from hospital admissions in Brazil 2010-2022.

BACKGROUND: Race and ethnicity are important drivers of health inequalities worldwide. However, the recording of race/ethnicity in data systems is frequently insufficient, particularly in low- and middle-income countries. The aim of this study is to descriptively analyse trends in data completeness in race/color records in hospital admissions and the rates of hospitalizations by various causes for Blacks and Whites individuals. METHODS: We conducted a longitudinal analysis, examining hospital admission data from Brazil's Hospital Information System (SIH) between 2010 and 2022, and analysed trends in reporting completeness and racial inequalities. These hospitalization records were examined based on year, quarter, cause of admission (using International Classification of Diseases (ICD-10) codes), and race/color (categorized as Black, White, or missing). We examined the patterns in hospitalization rates and the prevalence of missing data over a period of time. RESULTS: Over the study period, there was a notable improvement in data completeness regarding race/color in hospital admissions in Brazil. The proportion of missing values on race decreased from 34.7% in 2010 to 21.2% in 2020. As data completeness improved, racial inequalities in hospitalization rates became more evident - across several causes, including assaults, tuberculosis, hypertensive diseases, at-risk hospitalizations during pregnancy and motorcycle accidents. CONCLUSIONS: The study highlights the critical role of data quality in identifying and addressing racial health inequalities. Improved data completeness has revealed previously hidden inequalities in health records, emphasizing the need for comprehensive data collection to inform equitable health policies and interventions. Policymakers working in areas where socioeconomic data reporting (including on race and ethnicity) is suboptimal, should address data completeness to fully understand the scale of health inequalities.

MoCab: A framework for the deployment of machine learning models across health information systems.

BACKGROUND AND OBJECTIVE: Machine learning models are vital for enhancing healthcare services. However, integrating them into health information systems (HISs) introduces challenges beyond clinical decision making, such as interoperability and diverse electronic health records (EHR) formats. We proposed Model Cabinet Architecture (MoCab), a framework designed to leverage fast healthcare interoperability resources (FHIR) as the standard for data storage and retrieval when deploying machine learning models across various HISs, addressing the challenges highlighted by platforms such as EPOCH®, ePRISM®, KETOS, and others. METHODS: The MoCab architecture is designed to streamline predictive modeling in healthcare through a structured framework incorporating several specialized parts. The Data Service Center manages patient data retrieval from FHIR servers. These data are then processed by the Knowledge Model Center, where they are formatted and fed into predictive models. The Model Retraining Center is crucial in continuously updating these models to maintain accuracy in dynamic clinical environments. The framework further incorporates Clinical Decision Support (CDS) Hooks for issuing clinical alerts. It uses Substitutable Medical Apps Reusable Technologies (SMART) on FHIR to develop applications for displaying alerts, prediction results, and patient records. RESULTS: The MoCab framework was demonstrated using three types of predictive models: a scoring model (qCSI), a machine learning model (NSTI), and a deep learning model (SPC), applied to synthetic data that mimic a major EHR system. The implementations showed how MoCab integrates predictive models with health data for clinical decision support, utilizing CDS Hooks and SMART on FHIR for seamless HIS integration. The demonstration confirmed the practical utility of MoCab in supporting clinical decision making, validated by its application in various healthcare settings. CONCLUSIONS: We demonstrate MoCab's potential in promoting the interoperability of machine learning models and enhancing its utility across various EHRs. Despite facing challenges like FHIR adoption, MoCab addresses key challenges in adapting machine learning models within healthcare settings, paving the way for further enhancements and broader adoption.

Electronic oral health surveillance system for Egyptian preschoolers using District Health Information System (DHIS2): design description and time motion study.

BACKGROUND: Early childhood caries (ECC) is a major global health issue affecting millions of children. Mitigating this problem requires up-to-date information from reliable surveillance systems. This enables evidence-based decision-making to devise oral health policies. The World Health Organization (WHO) advocates the adoption of mobile technologies in oral disease surveillance because of their efficiency and ease of application. The study describes developing an electronic, oral health surveillance system (EOHSS) for preschoolers in Egypt, using the District Health Information System (DHIS2) open-source platform along with its Android App, and assesses its feasibility in data acquisition. METHODS: The DHIS2 Server was configured for the DHIS2 Tracker Android Capture App to allow individual-level data entry. The EOHSS indicators were selected in line with the WHO Action Plan 2030. Two modalities for the EOHSS were developed based on clinical data capture: face-to-face and tele/asynchronous. Eight dentists in the pilot team collected 214 events using modality-specific electronic devices. The pilot's team's feedback was obtained regarding the EOHSS's feasibility in collecting data, and a time-motion study was conducted to assess workflow over two weeks. Independent t-test and Statistical Process Control techniques were used for data analysis. RESULTS: The pilot team reported positive feedback on the structure of the EOHSS. Workflow adaptations were made to prioritize surveillance tasks by collecting data from caregivers before acquiring clinical data from children to improve work efficiency. A shorter data capture time was required during face-to-face modality (4.2 ± 0.7 min) compared to telemodality (5.1 ± 0.9 min), p < 0.001). The acquisition of clinical data accounted for 16.9% and 21.1% of the time needed for both modalities, respectively. The time required by the face-to-face modality showed random variation, and the tele-modality tasks showed a reduced time trend to perform tasks. CONCLUSIONS: The DHIS2 provides a feasible solution for developing electronic, oral health surveillance systems. The one-minute difference in data capture time in telemodality compared to face-to-face indicates that despite being slightly more time-consuming, telemodality still shows promise for remote oral health assessments that is particularly valuable in areas with limited access to dental professionals, potentially expanding the reach of oral health screening programs.

COVID-19 health information system assessments in eight European countries: identified gaps, best practices and recommendations.

BACKGROUND: Global threats, such as the coronavirus disease 2019 (COVID-19) pandemic, have highlighted the critical importance of robust and well-functioning health information systems (HIS) in effectively addressing public health emergencies. To enhance the understanding and the functioning of such systems, it is crucial to perform HIS assessments. This article explores key gaps and identifies best practices in the COVID-19 HIS of eight European countries. Furthermore, it provides recommendations to strengthen European systems for better pandemic preparedness. METHODS: Assessments were carried out in eight European countries using an adapted version of the WHO support tool to strengthen HIS and the Joint Action on Health Information assessment tool. The assessments took place between January 2022 and April 2023. RESULTS: Four main themes emerged regarding the gaps and best practices identified in the various HIS: organizational, technical, legal and resources. The results of these assessments show different approaches implemented by countries to improve their HIS and respond to the demands of the pandemic. CONCLUSIONS: It is imperative for countries to draw valuable insights from the COVID-19 pandemic and strengthen their HIS. This involves the adaptation or development of pandemic preparedness plans, strengthening legislative framework for data sharing and privacy protection, promotion of data standards and international definitions and implementation of a unique person identifier. Additionally, countries will have to act in this post-pandemic era and integrate the newly developed systems and innovations into existing structures, maintain and develop trust by citizens through transparent communication and engage in infodemic management and address resource gaps in the workforce.

Licensed Practical Nurses' Perceptions of the Benefits of Information Systems in Social and Healthcare Services.

Licensed practical nurses (LPNs) are the second largest occupational group and the largest group in the social and healthcare sector in Finland, and they have an extensive working environment. Like other health and social care professionals, LPNs also use health information systems (HIS) and client information systems (CIS) in their daily work. The aim of this study was to describe LPNs' perceptions of the benefits of information systems in daily patient care. The information systems include the main HIS or CIS that the respondents mainly use in their work. The data comprised 3 866 LPNs' responses were collected via an online survey in 2022. Most of the LPNs work in social care using the Lifecare system. ESKO is used in public health care and was rated as the most popular system that LPNs use regarding the benefits of information systems. Highly experienced LPNs seem to rate the benefits of information systems higher than LPNs who have just started working.

Mapa de Competencias sobre sistemas de información y salud digital para el personal de las instituciones de salud: Un marco de referencia basado en conocimientos, habilidades y experiencias necesarias para desarrollarse funcionalmente en la era de la interdependencia digital

En el entendido de que una competencia es la capacidad observable del conocimiento, la habilidad y los valores o las actitudes para el desarrollo de algo, un mapa de competencias es un instrumento a través del cual se puede observar qué conocimientos son los requeridos en el trabajo para lograr los resultados que el sector y la organización, finalmente, en su conjunto, se proponen. A los efectos del presente mapa, las competencias se agrupan en transversales y específicas, en cuyo caso las primeras son las que afectan a todo el personal de salud con independencia de su puesto de trabajo o categoría y las segundas, las que deben estar presentes en un individuo o grupo conforme a un puesto de trabajo o rol profesional concreto.

The role of governance in the digital transformation of healthcare: Results of a survey in the WHO Europe Region.

Optimal governance is among the key facilitators of the digital transformation of health systems intended to improve access to healthcare, quality, safety, and efficiency, and to attain universal health coverage. This paper highlights the findings of a survey assessing the status of governance of digital health in the WHO European Region. The 2022 survey is a continuation of the 2015 WHO Global Survey on eHealth. The survey focused on national digital health governance, monitoring and evaluation of digital health interventions, and funding and investment in digital health and was conducted through April to October 2022. All 53 Member States of the WHO European Region participated in the survey. The results showed that 83% of the Member States reported having a national digital health strategy in place, and 79% of the Member States reported having a health information system strategy. Most of the priorities of the national digital health strategies were devoted to increasing the accessibility, quality, safety, and efficiency of the health systems, strengthening health information systems, and improving information sharing and interoperability of data. Measures to ensure equity in access to digital healthcare services were directed towards improving broadband connectivity, information and communication technology, digital literacy, and digital health promotion. Oversight for the implementation and operation of the national digital health strategies are mostly delegated to government agencies. The prime source of funding for digital health programs was public funding, though a combination of funding sources was also noted. This analysis revealed increasing adoption of national digital health strategies for access to healthcare and creation of digital health agencies and funding programs for digital health.

Support tool to strengthen health information systems: guidance for health information system assessment and strategy development

It is essential for policy-makers to have a reliable and clear picture of how health is distributed in a given population, and what indicators contribute to or reduce opportunities to be healthy. Therefore, the surveillance of population health and well-being is the first of ten essential public health operations defined by WHO. WHO has a long tradition of providing support to Member States to strengthen their health information systems (HISs). Support tool to strengthen health information systems, is only one of WHO tools which provides guidance for HIS assessment and strategy development.The tool was first published in 2015, and an updated version was published in 2021. Current edition contains refined assessment methodology for the core module and four new add-on modules – Emergency response information management system, Geographic information system, Long-term care, and Migration health data - complementing the add-on modules included in the 2021 update (Health data governance, Health information for the Thirteenth General Programme of Work and the European Programme of Work 2020–2025, Human resources for health, Infectious disease surveillance, and Noncommunicable diseases monitoring).The tool has two main parts: guidance for performing an assessment of a full HIS and guidance for the subsequent development of an HIS strategy. The assessment methodology aims to achieve a good balance between data collection and actual data use and reflects the growing importance of electronic health records and other digital solutions. Add-on modules provide support for a more in-depth assessment of specific functions of HISs. Based on the outcomes of the assessment, the tool describes a stepwise and practical approach for HIS strategy development. The HIS assessment item sheets that are part of the assessment methodology are also available in the form of an excel sheet and published as a separate Web Annex.

Validating the Delone and Mclean's model in a developing country's infectious disease pandemic context.

BACKGROUND: This study aimed at validating the updated DeLone and McLean's information systems success model (D&MISS) in a developing country's infectious disease pandemic preparedness and response context. The findings from this study are relevant to inform policies and actions for enhancing developing countries' the Health Information System's (HIS) performance, and specifically to improve their future pandemic readiness and response. The study sought to respond to a key research question: to what extent can the D&MISS model provide evidence to enhance the HIS's infectious disease pandemic readiness and response in developing countries? METHOD: A cross-sectional study design that involved a multi-stage probability sampling approach to select eligible healthcare workers was applied. Conducted in Nigeria and Liberia, 576 primary healthcare workers, out of the proposed 600, participated, representing a response rate of 96%. The D&MISS model served as the theoretical underpinning for this study, and nine hypothesized relationships were stated before the study based on the interconnectedness of the model's six dimensions. Structural Equation Modelling (SEM) data analysis using the Partial Least Square approach was used to determine if hypothesized relationships were supported. RESULTS: 70% of the observed variance in the Net Benefit construct was explained by the predictive influence of the Use and User Satisfaction constructs. The Use construct had a slightly more substantial predictive influence than the User Satisfaction construct. Eight of the nine hypothesized relationships were supported, except for the relationship between Information Quality and Use. The relationships between System Quality and Use and User Satisfaction and Net Benefit had the highest beta coefficient, statistically significant at p < 0.05. CONCLUSION AND RELEVANCE: The D&MISS model demonstrated its relevance in providing evidence on the gaps of the HISs regarding future pandemic preparedness and response. However, from a future research opportunity, its enhancement and modifications with context-specific dimensions peculiar to developing countries will improve its ability to provide more context-specific evidence to improve pandemic preparedness and response for developing countries.