HMIS Support for Child Nutrition and Growth: Lessons Learned from Rwanda.

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Enock Rukundo, Sune Dueholm Müller, David K. Tumusiime, Eleni Papadopoulou, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5209967/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: Accurate and timely nutritional information plays a vital role in monitoring the progress of the Rwandan National Nutrition Program (NNP). However, the absence of a cohesive reporting system to monitor child growth and nutrition poses a challenge. This study focuses on analyzing health workers' utilization of health information management systems (HMIS) to identify areas for enhancement in program implementation. Methods: Our interview guide and group discussion questions were structured around the constructs of the Human, Organization, and Technology–Fit (HOT-Fit) framework. These guided discussions were conducted with health workers supporting the NNP children in primary health facilities across three districts in Rwanda. The subsequent data analysis involved importing the transcripts into NVivo for interpretation within the framework. Results: Health care providers, including community health workers and nutritionists, rely on paper registers for tracking and reporting nutritional data. Data managers store this information digitally, preferring HMIS for increased efficiency. They find use of digital entry and reporting faster and less cumbersome compared to paper-based systems. Respondents identified challenges with paper-based registration, noting repetitive entries and inconsistencies across registers. Nutrition information within HMIS faces obstacles such as a lack of nutritionists, suboptimal system use, limited internet access, and low digital literacy among staff. Conclusion: Addressing challenges such as documentation practices and staffing is crucial for enhancing user satisfaction. The integration of routine recording systems can significantly improve data utilization. This study underscores the importance of tailored digital health interventions to enhance the HMIS supporting the National NNP. Nutrition & Dietetics Information Retrieval and Management Medical Informatics Children nutrition growth monitoring HMIS paper registry Figures Figure 1 Background In Rwanda, as in much of Africa, stunting in children is a pressing concern. Data from 2020 indicate that Africa accounts for 40% of the 149.2 million children affected globally (1). Malnutrition during vital developmental stages can have lasting adverse effects, underscoring the urgent need for effective and immediate interventions (2,3). Despite efforts to establish digital health systems in low- and middle-income countries, the implementation of real-time surveillance for child malnutrition remains challenging. Nutrition data serve as a critical information source for assessing the situation at the local administrative level (4,5). According to the WHO report "Monitoring and Accountability for the Health-related Sustainable Development Goals (MA4Health)", an efficient healthcare system needs an interoperable digital platform for health information to ensure access to timely, comprehensive, pertinent, and accurate data to support all healthcare activities (6–8). Aligning all health information system (HIS) development projects with a unified Health Management and Information System (HMIS) platform is also needed. An HMIS platform supports standardized data collection methods, data storage systems, advanced data analytics tools, and analyses of health data across healthcare settings (9). This structure organization optimizes healthcare data management, promotes evidence-based practices, enhances healthcare delivery, and contributes to improved health outcomes for individuals and communities alike (10). In Rwanda, the DHIS2 system is an integral part of the national HMIS and a critical component in managing the National Nutrition Program (NNP) targeting pregnant and postpartum women and children (11). The HMIS Unit, organized under the Ministry of Health (MoH), is mandated to coordinate routine health data activities, ensure data quality, foster collaboration within the MoH and among various stakeholders (12). The DHIS2 system, hosted at the National Datacenter, is designed to provide a secure and efficient platform, with mechanisms in place for daily backups aimed at maintaining data integrity (13). Additionally, a test server is available for the HMIS Unit to evaluate system upgrades before implementing changes in the live environment. While the government aims to integrate this system with the NNP to enhance data utilization and support evidence-based decision-making(14),feedback from data managers indicates that challenges persist in optimizing the system’s performance. Reports have noted ongoing issues with data accuracy and user satisfaction, highlighting areas in need of further improvement (15). This suggests that despite the potential for the DHIS2 system to streamline operations and improve nutritional outcomes nationwide, significant barriers remain that require attention (16). Efforts are ongoing to enhance the current HMIS to tackle the challenges posed by malnutrition. The NNP utilizes the HMIS for tracking and monitoring nutrition-related data for pregnant and postpartum mothers and children (17,18). Integration of the HMIS into the program allows gathering of crucial nutritional information, analyze malnutrition trends, and evaluate the impact of ongoing nutrition interventions. Accurate and timely nutrition information is essential for monitoring progress against national and global targets regularly (19,20). However, challenges persist in routine reporting systems due to the lack of real-time individual-level nutrition data, hindering effective tracking and evaluation of progress against nutrition targets. In the context of the Rwandan NNP, caregivers of children under two years old are invited to participate in free monthly community growth monitoring sessions conducted by community health workers (CHWs). Children identified as malnourished are referred to public primary health centers for comprehensive assessments by nutritionists and/or social workers. Additionally, vulnerable children can enroll in the Fortified Blended Foods (FBF) program, which involves monthly nutritional and growth assessments conducted by trained nutritionists (21,22). Beneficiaries of the FBF program receive food supplements to support their nutritional needs. Regular follow-ups are conducted for children in nutrition rehabilitation programs, supervised by nutritionists in health centers, or through ongoing support from CHWs upon their reintegration into the community (23,24). The aim of this study is to understand how healthcare providers perceive the collection, integration, and reporting of nutritional information in primary healthcare facilities, including outreach programs utilizing the HMIS, to inform how the HMIS can be enhanced. Methods Study setting Our study was carried out in Rwanda's public primary healthcare centers, which handle most nutrition-related issues and often support with broader district health interventions (25). We examined three districts with varying levels of child malnutrition: Kirehe in the Eastern Province, Nyabihu in the Western Province, and Ruhango in the Southern Province (25). In Kirehe, childhood stunting has decreased from 40.3% in 2015 to 29% in 2020, making it a “good performing” district, in regard to the national goal of reducing childhood stunting rates. Kirehe has 18 health centers and one district hospital, serving a population of 340,893 (21). In contrast, in Ruhango, an increase in childhood stunting has been reported from 20.8% in 2015 to 41.5% in 2020, making it a “low performing” district. Ruhango has 304,390 residents served by 15 primary health centers and two district hospitals, Finally, Nyabihu, with 295,580 inhabitants and 16 primary health centers and two district hospitals, recorded the highest stunting rate of 59% in 2015 and 45% in 2020 (27,28). Rwanda's public health system consists of eight national, four provincial, and 36 district hospitals; 503 sector health centers; and a network of 58,298 community health workers (19). Typically, villages with 100-250 households are allocated three to four CHWs, including specialized child health pairs known as Binômes, which are constituted by a female and male CHW responsible for child health and nutrition in Rwanda (17). The Rwanda HMIS is structured to provide vital support to health service providers and MoH units at all levels. Managed by the MOH, the HMIS integrates paper and electronic reporting mechanisms for data collection from health centers and district hospitals. Data entry processes have evolved to involve primary health facility data managers inputting nutrition information directly into the HMIS database, a shift from the prior centralized approach to data collection. In the context of this study, we specifically analyzed how the HMIS is utilized within these healthcare facilities for monitoring nutrition outcomes. We aimed to explore the processes through which nutritional information is collected, integrated, and reported, particularly in relation to community outreach programs. By focusing on the experiences of healthcare providers across these diverse districts, we gain insight into the effectiveness of existing data management practices and identify potential areas for improvement in managing nutrition-related data, as illustrated in Figure 1 . Data and patient flow: A case description of the management of child nutrition and growth data supported by HMIS Arrow 1 : CHWs perform anthropometric measurements using paper forms in community settings, such as homes or during monthly screening exercises. They categorize children into yellow, green, and red groups based on their nutritional status. Arrows 2, 3, 4, and 5: The CHW coordinator compiles and aggregates reports using paper reporting templates, which are then entered digitally into the HMIS community health system (SISCom) at the health center by the data manager on a monthly basis. Arrow B: Children not requiring immediate intervention receive regular monitoring, while those needing further evaluation are referred to health centers. Children experiencing growth challenges are enrolled in the FBF program, with nutritionists at health centers overseeing their growth monitoring charts using paper formats. Arrow B.1: Nutritionists generate monthly reports for the FBF program on paper reporting templates, and the associated growth monitoring data is entered digitally into the HMIS by the data manager. Arrow A: At the health center, nutritionists conduct nutritional assessments for children during vaccination visits. The individual-level data from these assessments are compiled using paper reporting templates. Arrow A.1: Aggregated growth monitoring data is submitted monthly to the central level and key nutritional stakeholders through the HMIS monthly report, which is managed digitally by the data manager. It should be noted that the HMIS is managed at the central level by the Ministry of Health and the Rwanda Biomedical Center. Study design We used the Human Organization and Technology-Fit (HOT-Fit) framework, a well-established model utilized for evaluating health information systems to design our study (29). This framework assesses the alignment between human aspects (organization, individuals) and technological elements of system. Semi-structured interview guides for interviews and focus group discussions were developed based on this framework (Table 1), specifically tailored to health workers to explore their perspectives on how HMIS is integrated and used in Rwandan healthcare settings to support the children's nutrition and growth program. Additionally, we evaluated health care providers’ perceptions on achieving universal coverage, acquiring health information, and attitudes towards digital health tools. Our interview guides were first developed in English and then translated into Kinyarwanda (see supplementary File 2 “Interview guides with health workers for details”). We conducted three pilot sessions in the Nyabihu district to refine our interview guides. This framework is relevant to our aim of investigating health workers’ experiences of HMIS support for the nutrition programs. Table 1: HOT-Fit a constructs and operationalization (30) . HOT-Fit constructs and definitions Study constructs and definitions Technology Meets the needs of the projected users, convenient and easy to use, fits the work patterns of the professionals for whom it is intended and the overall health system System quality Associated with system performance: Ease of use, ease of learning, response time, usefulness, system flexibility and security Information quality User perspectives and quantitative data: Completeness, availability, accuracy, reliability, timeliness, relevance, and consistency Service quality Service delivered: Technical support, quick responsiveness, assurance, empathy, and follow-up service Human The person who uses and the use of information outputs such as reports System use Concerned with the frequency and breadth of health information system inquiries and functions: System users, their levels of use, training, knowledge, beliefs, expectations, acceptance, or resistance User satisfaction Evaluation of users’ experience in using the system and the potential impact of the system: Perceived usefulness, enjoyment, overall satisfaction and satisfaction with specific functions, and decision-making satisfaction Organization Nature and factors of a healthcare institution Structure Nature (type, size), management and communication, clinical process, workflow process, leadership, top management support, etc. Environment Financial source, government, politics, and type of population being served Net benefits Quality of care, clinical impact, impact on patient care and communication, and facilitation of information access a HOT-Fit: Human, Organization, and Technology–Fit. Sampling and data collection process We used purposeful sampling to select nine public primary healthcare centers across the three districts. In each district, we selected three health centers to ensure diverse representation based on their geographical locations. The first health center is situated close to the district hospital, making it easily accessible due to its proximity to the main road, which facilitates transportation for both healthcare providers and patients. The second center is located at an intermediate distance, representing average conditions in terms of accessibility and resources. Lastly, the third health center is the most remote, often encountering greater logistical challenges due to its distance from main roads and the district hospital. Within these centers, we recruited health workers delivering services under the child nutrition growth monitoring programs and supporting HMIS. On average, each health center was staffed with two community health workers (one female and one male CHW), a nutritionist and/or social worker, and a data manager, all dedicated to supporting the child growth and nutrition program. For this study, we initially selected one nutritionist and one data manager from each of the three health facilities in each district, resulting in a total of three nutritionists and three data managers per district based on predefined criteria (Table 2). To enhance the quality and depth of data collected, we expanded our sample by increasing the number of nutritionists and data managers interviewed to six from each district. This was achieved by inviting an additional nutritionist and data manager from the nearest health center, which was selected based on its proximity to the designated facilities, in accordance with the criteria established in the study setting. This strategic adjustment enabled a more comprehensive understanding of the diverse perspectives and experiences related to the child growth and nutrition program. In academic research, focus group discussions with a limited number of participants can often yield insufficient data. Therefore, this increase in participants to six from each district significantly enhanced the validity of the findings and fostered richer discussions. The broader representation facilitated by this sampling approach allowed for a deeper exploration of the complex challenges and insights faced by health workers involved in the program. In total, this study included 18 in-depth interviews with CHWs and 18 with nutritionists, along with three focus group discussions comprising six data managers each, thereby improving the objectivity and representativeness of the data. The first author conducted the interviews in Kinyarwanda and the interviews were audio recorded. Subsequently, a specialist translated the recordings into English, which were then reviewed by two of the authors to ensure accuracy. Data collection took place between April and December 2021. We followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) framework (31). Table 2: Sampling methods and selection criteria Categories of study population Eligibility criteria Sampling Sample size and method Community health workers (CHWs) CHWs attached/registered to the health center/facility in charge of nutrition Experience – 50% with more than 3 years. Parents themselves – 50% have children under 5 years 2 CHWs were selected to participate from each of the selected health centers. 18 in-depth interviews, 6 per district Nutritionists Nutritionists and/or social workers employed by the health center/facility in charge of child nutrition Experience – 50% with more than 3 years. Parents themselves – 50% have children under 5 years 2 nutritionists were selected to participate from each of the selected health centers. 18 in-depth interviews, 3 per district Data managers Data managers employed by the health center/facility in charge of data entry and management/use Experience – 50% with more than 3 years 2 data managers were selected to participate from each of the selected health centers. 3 focus groups, 1 per district Data analysis and synthesis We employed the HOT-FIT framework for our analysis, focusing on its constructs to guide our thematic examination. Table 3 provides a representative example of our analysis process. Initially, in-depth interviews and focus group discussions were transcribed to facilitate thematic analysis, which was managed using NVivo software. Two authors independently coded the data using a predefined codebook derived from the HOT-FIT framework (32). After the initial coding, the research team compiled all relevant data extracts and categorized them according to the framework's components. We then analyzed these categories to identify patterns and insights related to health workers’ experiences with HMIS support for nutrition programs, informing our analysis and conclusions. This structured approach allowed us to effectively explore the factors influencing the integration and utilization of the HMIS in the context of nutrition services. Table 3: The codebook Themes Subthemes Codes Technology System quality Ease of use Ease of learning Response time Security Information quality Accuracy Completeness Availability Timeliness Compatibility Service quality Technical support Quick responsiveness Empathy and follow-up service Human System use Levels of use Training Knowledge Expectation Acceptance or resistance User satisfaction Perceived usefulness User satisfaction Organization Structure Top management support Strategy (clinical/process workflow) Environment Communication Competition Government buy-in Net Benefits Clinical impact Effectiveness Efficiency Direct benefits Aspirations (future plans) Results Overview Fifty-four health workers participated in the study: 18 CHWs, 18 nutritionists and 18 data managers, as shown in Table 2 . In brief, most CHWs had lower educational attainment levels, were older and had less work experience compared to nutritionists and data managers. Most (56%) of the data managers had computer science as their main background and most nutritionists had studied human nutrition. Table 4 Characteristics of the study participants (n = 36). Characteristics Participant categories CHWs (n = 18) Nutritionists (n = 18) Data managers (n = 18) N (%) N (%) N (%) Age in years (range) 21–29 1 ( 6 ) 2 ( 11 ) 4 ( 22 ) 30–39 2 ( 11 ) 14 (78) 14 (78) 40–49 6 ( 33 ) 1 ( 11 ) 0 (0) 50 & above 9 ( 50 ) 0 (0) 0 (0) Work experience (years) 0–5 3 ( 17 ) 10( 56 ) 14 (78) 5–10 5 ( 28 ) 4 ( 22 ) 4 ( 22 ) 10–15 6 ( 33 ) 2 ( 11 ) 0 (0) 15–20 3 ( 17 ) 2 ( 11 ) 0 (0) Education level (years) Primary (0–6) 4 ( 22 ) 0 (0) 0 (0) Lower secondary ( 7 – 10 ) 11 (61) 0 (0) 0 (0) Upper secondary (> 10) 2 ( 11 ) 6 ( 33 ) 0 (0) University (> 12) 1 ( 6 ) 12 (67) 18 (100) Field of study General training 18 (100) Sociology 4 ( 22 ) Human nutrition 6 ( 33 ) Environmental Health 4 ( 22 ) Economics/Accountancy 4 ( 22 ) Nurse/Midwifery 4 ( 22 ) Laboratory 4 ( 22 ) IT 10 ( 56 ) As reported in data analysis section, the structure of the findings follows the HOT-Fit framework ( 29 ). This framework illustrates the alignment of technological, organizational, and human factors to investigate how public primary healthcare centers utilize HMIS to when delivering children's nutrition and growth care. Technology System quality: Data managers frequently expressed concerns regarding the inefficiency of their digital tools, citing persistent connectivity issues, the absence of an integrated system for data entries, and the use of obsolete technology (Table 5 : Section A, Constructs 4 & 5). Despite efforts to synchronize paper and electronic logs, the varying requirements of different health programs resulted in a misalignment of data (Table 5 : Section A, Construct 2). Furthermore, some nutritionists and data managers expressed concerns that the HMIS was overloaded with numerous nutritional indicators, many of which were entered but never utilized for reporting or decision-making purposes. Participants raised concerns about the limitations of the paper-based system, especially regarding data security, accessibility, and overall effectiveness. They noted that the introduction of new paper-based reporting templates by the central authorities for use in lower primary healthcare facilities could compromise data security and privacy. Specifically, when older registers become obsolete, there is a risk of data loss, making it difficult to retrieve critical information, particularly during routine reporting (Table 5 : Section A, Construct 3). While CHWs and nutritionists frequently used paper for data collection, reporting, and feedback, participants generally preferred digital tools. Data managers prioritized digital system security by emphasizing data access restrictions for authorized users (Table 5 : Section A, Construct 1). A significant number of participants, primarily nutritionists and CHWs, currently rely exclusively on paper-based tools, as these are the only systems available to them. While they recognize the potential benefits of digital tools, their limited digital literacy significantly hinders their ability to use these systems effectively. This situation underscores a general awareness among health workers that digital solutions could enhance their workflows and improve data management. However, without the necessary skills and training, their reliance on paper documentation continues. This dependency not only limits their current capabilities but also impedes the development of their digital skills (Table 5 : Section A, Construct 2). Moreover, those with prior technological experience often find digital systems user-friendly, whereas some healthcare providers and individuals skeptical of technology struggle to navigate them, resulting in uneven proficiency levels and an ongoing reliance on paper documentation. Information quality: Data managers highlighted a problem with delays in entering information into the digital system and recording nutrition data promptly. This issue affected the completeness and timeliness of data availability especially when verifying data through paper registries and forms, particularly data collected by community health workers during community interactions (Table 5 : Section A, Construct 7). Moreover, shifting from paper records to digital entry forms introduces data reliability concerns as errors can occur at various points of entry (Table 5 : Section A, Construct 6). Nutritionists and CHWs raised issues about data reliability, suggesting that the data input process was not entirely reliable (Table 5 , Section A, Construct 8), illustrating potential data inaccuracies throughout the process. System quality: According to the data managers, a significant portion of their technical support inquiries were promptly handled by specialized technical staff assigned to the HMIS unit at the central level (Table 5 : Section A, Construct 10). Nevertheless, the duration required to obtain this help can differ. While it is common for straightforward technical difficulties to be resolved within 24 hours, more intricate problems may require a resolution duration of up to 14 days (Table 5 , Section A, Construct 9). Humans System use: Data managers use digital systems for various tasks, such as transitioning individual paper records to a digital aggregated format, reconciling differences between paper and digital data, analyzing trends, and generating reports at central and district levels. They adhere to a specific schedule, entering data between the first and fifth of each month and validating it before the fifteenth. At monthly meetings, data from the digital platform and paper registries are reviewed and authorized. Despite the benefits of enhanced data security and real-time tracking with the digital system, data managers noted a lack of training and continuous learning opportunities. On the other hand, nutritionists acknowledge the advantages of utilizing digital entry formats and other nutrition-related information systems. Nevertheless, their hesitance stems from the platform inability to function offline, especially considering the limited internet access at their workplace. Despite these reservations, they recognize the system's potential benefits, such as improved data security, reduced redundancy in tasks with CHWs, and enhanced productivity (Table 5 : Section B, Construct 12). Data managers expressed enthusiasm about the current system's ability to enhance their workflow by replacing traditional paper-based tools, particularly in tracking families as they move within the country. They emphasized that the platform facilitates data retrieval and allows for cross-referencing information collected by CHWs (Table 5 : Section A, Construct 13). Moreover, the digital system was generally well-received by nutritionists and CHWs, who acknowledged its potential to assist with various tasks, including child tracking, simple data retrieval, scheduling reminders, and event listing (Table 5 : Section A, Construct 14). While the current system has limitations, the feedback indicates a clear desire for improvements that could further enhance functionality and efficiency in data management in future iterations of the system. An addition of the offline mode found, both groups—nutritionists and CHWs in agreement. The data managers underlined the importance of on-the-job training as a prerequisite for the successful integration of digital technology at the point of care. Further complicating the use of these digital tools for many users was the fact that English was the only language available. User satisfaction: The data managers held a favorable view of the existing digital system, particularly appreciating its detailed data on FBF beneficiaries (Table 5 : Section A, Construct 15). The auto calculations or "validation rules" provided by the system are a noteworthy element. Overall, interviewees expressed a generally positive attitude toward the usefulness of digital systems, especially for growth monitoring. However, there was noticeable dissatisfaction with non-digital systems, primarily due to concerns about data sharing, loss, and retrieval, as paper documentation continues to be the predominant method of data collection. Organization Structure: A significant barrier to effective collaboration highlighted by data managers is the lack of digital literacy among healthcare professionals, especially nutritionists or other professionals who provide this type of service (Table 5 : Section C, Construct 18). The participants noted inadequate integration between the digital platform and traditional data-capturing tools (Table 5 : Section C, Construct 16). This lack of integration not only impedes effective communication within a health center but also leads to duplicate data entry, especially when patients are transferred between different levels of care. Despite difficulties in inter-facility communication, the transmission of information among various stakeholders and organizations was reported to be effective (Table 5 : Section C, Construct 17). Additional challenges identified relate to the implementation of outreach programs by CHWs. While these programs have the potential to enhance data recording and collect detailed nutrition information at the individual level, a shortage of skilled personnel proficient in using digital tools, combined with insufficient digital infrastructure—such as handheld devices—hinders both the current and future program systems (Table 5 : Section C, Construct 19). Environment: The respondents unanimously recognized the usefulness of the FBF tracker system in collecting data on vulnerable children belonging to the two most socioeconomically disadvantaged demographics. One significant issue of concern revolves around the evident communication gap that exists among various child health programs (i.e. child vaccination program), potentially resulting in the duplication of data. The data pertaining to child registration are consistently entered into separate systems, even if they have previously been documented in the civil registration and vital statistics (CRVS) system (Table 5 : Section C, Construct 20). Net benefits: Data managers, while expressing their concerns about the administration of the digital platform, emphasized its benefits for enhancing child nutrition and growth monitoring programs (Table 5 : Section D, Construct 21). They acknowledged the system's capacity to reduce dependency on paper, streamline data access, and help decision-making (Table 5 : Section C, Build 22). However, concerns arise regarding the integration of technology and human tasks. Initial paper-based data collection by nutritionists and CHWs, followed by digital entry of the data by data managers, raised issues of increased workloads and reduced motivation. This challenge is exacerbated by the significant shortage of nutritionists in many health centers, hindering broader adoption of digital solutions within the nutrition program. One of the challenges identified by health workers is the reliance on paper-based formats as the primary data collection tool. This reliance often creates difficulties when trying to switch to digital systems. Many interviewees noted that the existing paper systems lead to compatibility issues with digital databases, which can make users hesitant to adopt new technologies and reduce their satisfaction with the system (Table 5 : Section C, Construct 24). Health workers believe that having a system capable of accessing all recorded data, monitoring children's growth, obtaining statistical insights on measurements, and tracking the number of children in rehabilitation would significantly improve their efficiency. Furthermore, while various stakeholders in the nutrition program support the idea of replacing paper systems with digital data entry at the point of care, success in this transition requires teamwork among all parties involved. The government of Rwanda is backing initiatives like the FBF tracker system and the monthly HMIS reports, which health workers believe could help them manage heavy workloads and address competing resource challenges. However, some participants highlighted difficulties with technology adoption. Many colleagues, especially the nutritionists, struggle with basic technologies, hindering their effective performance (Table 5 : Section C, Construct 23). There is also concern that even that overseeing nutrition at the district level may not fully understand the importance of accurate data recording in their roles. Table 5 Main findings and illustrative quotes Construct number Main findings Example quotes Section A: Technology System quality 1 The digital system is easy to learn and use for skilled users “…it is easy to use when someone has advanced skills; and “one-stop, easy and quick information access or retrieval” (Data manager 008). 2 The tracker system is not easy to learn for nonskilled users “…the digital system is not user friendly; it is cumbersome and difficult to understand, it is complex and contains too much data elements which cannot be calculated into information as well as unnecessary features and functions” (Nutritionist 009). 3 Paper registries affect data security and privacy “…the security and privacy of data [in paper] is lost when new registers are introduced and the existing ones become invalid” (CHWs 012). 4 Low speed internet connectivity “the [internet] is slow because they usually give us 2GB data packages to be shared with other services and by noon it runs out” (Data manager, 004). 5 Shortage of IT resources. “…certain health centers, data managers often use outdated machines, whereas some nutritionists may not have any at all” (Data Manager 009). Information quality 6 Paper-based formats reduce availability, usefulness, and security “…. when the big register book is lost, all clients’ data gets lost too;” “[paper] registers are not the safest way of keeping clinical data. [What if] the archive room … burned down” (Nutritionist 004). 7 Low data reliability and more documentation “…the more data is taken from the CHWs to the nutritionists to the data managers, the more they are likely to make errors on paper” “[data] must be entered in the computer when the information is first collected at the point of contact” (Data manager 009). 8 Susceptibility to errors due to community data misalignment “…. based on the information chain from a village to cell and then to the health center, many errors can be made along the journey” (CHW 016). Service quality 9 Delays in technical support “…. it is difficult for technical issues to be quickly responded to, as it is the central level that provide such assistance […] if the problem is an easy to fix, [it] can be done on a phone call to the District Hospital but certain technical issues take time” (Data manager 002) 10 Communication routes “…I just call my superior at the district hospital, and he or she forwarded the case to the central level technical team, … the team is competent and the quicker the reply, the quicker it comes back to me” (Data Manager 001). Section B: Human System use 11 A secure area “…the technology is a backup and reporting system that records children's status and their caregivers so that if the manual records are lost, we can get that very information”. (Nutritionist 002) 12 The system helps users speed up work “…the new technologies could help us to collect data on time and to speed up reporting” (Nutritionist 007). 13 Scheduling appointments “a digital system is needed to record all information related to the health status of children including notification of next visits and health center programs events” (CHW 011). 14 A better system that stores data and is secure “…the new technology may store information with proper security and honestly for us it is possible for data and information to get lost using the current nondigital system” (Nutritionist 003). User satisfaction 15 Fairly satisfied with the system in making corrective measures “…when it is observed that there are some errors in the data, the system helps to communicate easily in an electronic format and issues are settled in a given timeframe without lots of face-to-face meetings” (Data Manager 009). Section C: Organization Structure 16 Cumbersome patient data transfer between levels “…the current paper-based and FBF tracker system does not record transferred cases immediately […] data transfer from one level to another is difficult and may take weeks – which hinders clinical outcomes” (Nutritionist 006). 17 Users prefer a more efficient system “…we require a system that assists in timely data collection, identifies missed appointments, accelerates reporting for caregivers, and provides alerts for upcoming nutrition and growth-related events at the health center” Nutritionist 008). 18 Digital literacy “…many of our colleagues, especially the nutritionists, struggle with even basic technologies. This barrier hinders their effective performance. Surprisingly, even that overseeing nutrition at the district level seem unaware, despite the necessity for them to record data from their specific roles” (Data Manager 003). 19 Lack of outreach programs & IT tools “…We do not have sufficient outreach initiatives or portable digital tools for remote villages. However, running such outreach efforts might result in certain services being unavailable at the health center since a team comprising a nutritionist, CEHO, and nurse is essential to conduct them” Nutritionist 001). Environment 20 Communication gaps in the systems serving the same child “...a single child might appear in the FBF, rehabilitation, growth tracking, vaccination, and community program initiatives, each with distinct documents and structures. This entire data input falls on a sole data manager who also supports various departments within the healthcare center” (Data manager 006). Section D: Net Benefits 21 Impact on clinical care & decision-making “...without the system, manually finalizing the FBF beneficiaries' report would take months. However, with its help, we can analyze and promptly share results with authorities, ensuring timely orders of food supplements and incentives” Data Manager 004). 22 A digital system catering to a specific group of stakeholders and sponsors "…when stakeholders with access to the nutrition data notice a discrepancy, it can be electronically communicated and addressed within a specific period. While face-to-face meetings are not always necessary, they can be arranged if there's a need for further consolidation” (Data Manager 005). 23 Continuous learning is needed “…many of our colleagues, especially the nutritionists, struggle with even basic technologies. This barrier hinders their effective performance. Surprisingly, even that overseeing nutrition at the district level seem unaware, despite the necessity for them to record data from their specific roles” (Data Manager 003). 24 “Users” description of what they need (but lack) “...A system that is able to access all the recorded data, be reminded of a child's growth monitoring, obtain statistical insights on a child’s measurements, view the count of children in rehabilitation services per village, and observe the treatments and guidance provided” (Nutritionist 002). Discussion This study aimed to assess the utilization of the HMIS in supporting the delivery of health services for child nutrition and growth within the context of Rwanda's NNP. Our findings reveal significant challenges associated with current paper-based documentation practices among health workers, highlighting urgent needs for systemic improvements. Recap of Results Our analysis demonstrated that health workers, including CHWs and nutritionists, face substantial difficulties with paper-based documentation. These challenges include repetitive entries and inaccuracies across registers, which not only impede efficient data collection but also risk compromising data validity. Existing literature has extensively documented the inefficiencies of paper-based systems, noting issues such as data redundancy and error rates (33). Interviewee feedback revealed that health workers frequently face delays in accessing accurate information due to the time-consuming nature of manual data entry and retrieval. This can complicate their ability to make informed decisions promptly, potentially leading to missed opportunities for timely health interventions and negatively impacting child nutrition outcomes (34)(35). Contributions of the Study This research builds upon existing literature concerning the utilization and effectiveness of HMIS in nutrition and health contexts. Previous studies have underscored the critical role of accurate data in informing public health interventions and monitoring health outcomes (36)(37). This study addresses knowledge gaps by identifying specific factors influencing and inhibiting nutrition monitoring, such as the limited digital literacy of health workers and the lack of integration between existing paper-based systems and digital tools. These barriers have not been consistently highlighted in extant research, which has often overlooked the operational challenges inherent in transitioning from traditional documentation methods to integrated systems (38)(39). By examining these factors from an Information Systems (IS) perspective, this study provides valuable insights that can guide future improvements in national nutrition programs. We identify that both the Immunization and Nutrition programs serve the same client—the child—highlighting the need for consistent registration information across programs to ensure data accuracy and streamline workflows. While extant research has focused on the operational aspects of these programs (40,41), our findings indicate that the discrepancies in registration information between various Nutrition programs lead to inefficient data analysis and hinder effective cross-referencing of records. This lack of integration impedes data utilization, resulting in delays and potentially inappropriate health interventions (42)(43). Moreover, literature supports the notion that high-quality data integration can improve health monitoring outcomes (44)(45). Integrating the HMIS to share registration information can significantly enhance data consistency and reliability across relevant health programs. By addressing these integration challenges, stakeholders can optimize service delivery and improve health outcomes for children. Integration as a Solution Existing literature suggests that integrated health information systems can enhance data accuracy and streamline workflows (46). In our study, we explore how such integration can play a crucial role in improving health outcomes for children. We assert that integration efforts should go beyond simple reporting capabilities to include advanced analytics and functionalities, such as appointment reminders and cross-referencing of data (as illustrated in Figure 2 of Supplementary File One) , which can lead to more efficient service delivery and better tracking of child nutrition. While prior research has predominantly focused on the technological aspects of integration (47), our findings suggest that without addressing operational contexts, the potential benefits may not be fully realized. Specifically, we observed that integrating various health information systems can optimize data flow among health workers, facilitating more timely interventions and improving the overall effectiveness of child health programs (48). By focusing on the operational benefits of integration, this study provides a clear pathway for implementing integrated health information systems not only in the Rwandan context but also offers guidance that can be adapted by other countries facing similar challenges in health information management. The recommendations outlined herein, including transitioning to a centralized HMIS and implementing the proposed integration model, hold potential relevance for stakeholders in diverse settings seeking to enhance their health information systems and improve child health outcomes (49). Implementation Strategies In light of the findings, participants highlighted key opportunities for improving the effectiveness of the integrated HMIS. While the current system presents challenges, respondents identified areas for potential development: Capacity-Building Initiatives : Tailored training programs focused on digital literacy and data accuracy can empower healthcare workers to effectively utilize the integrated HMIS (50). Community Engagement Campaigns : Initiatives to raise public awareness can foster greater community involvement in health programs, encouraging better utilization of health services and more timely reporting of nutrition-related data (51). Collaborative Efforts : Fostering partnerships among health departments can enhance information flow and improve collaboration, facilitating a more integrated approach to health service delivery (48). Infrastructure Improvements : Enhancing internet connectivity and access to technological resources was frequently mentioned by respondents as critical for supporting effective use of integrated systems (49). Implications for Research and Practice Future research should evaluate the long-term impact of HMIS on child health outcomes in various contexts, particularly low-resource settings (49). Comparative studies examining the effectiveness of integrated HMIS against traditional systems will be vital for identifying best practices and informing policy (52). Additionally, capacity-building assessments are necessary to understand how training healthcare workers in the effective use of integrated HMIS can enhance data utilization and improve service delivery (53). Conducting impact evaluations to assess the sustainability of recommended changes in health systems is crucial, particularly regarding child nutrition and growth monitoring (54). This study emphasizes the need for further investigation into the long-term effects of data system integration, particularly its influence on operational efficiencies in health programs. Understanding these effects will clarify the benefits for the Rwandan National Nutrition Information System while providing guidance applicable to other nations seeking to optimize their health information systems (46). To address the identified challenges within the context of the Rwandan healthcare system, we recommend the following specific actions: Transition to a Centralized Digital HMIS : Health authorities should prioritize the shift from paper-based systems to a centralized digital HMIS that integrates CRVS, immunization, and nutrition data, essential for improving data accuracy and efficiency in reporting (55,56). Implementation of the Proposed Integration Model : Enacting the integration framework illustrated in Figure 2 will streamline documentation practices and improve data utilization across CRVS, immunization, and nutrition programs. Training Programs for Health Workers : Establishing comprehensive training programs to enhance digital literacy among health workers is vital, addressing the specific technological needs and challenges they face in Rwanda (57). Ensuring Reliable Internet Access : Policymakers should prioritize developing reliable internet infrastructure in health facilities to facilitate information exchange and data-sharing, crucial for the integration of various health programs (58,59). Conclusion The study findings reveal significant challenges faced by health workers in managing child nutrition and growth through the HMIS within the context of Rwanda's NNP. Specifically, issues related to paper-based documentation practices, such as repetitive entries and inaccuracies, hinder efficient data collection and create barriers to timely health interventions. Addressing these challenges necessitates an integrated approach that combines CRVS, immunization, and nutrition data systems. Co-developing strategies with stakeholders can enhance data accuracy and streamline workflows in child health management. Furthermore, implementation strategies aimed at transitioning from paper-based systems to a centralized digital HMIS can improve operational efficiencies and ensure that health workers can focus more effectively on delivering quality care. Future research should concentrate on evaluating the long-term impacts of integrated HMIS on child health outcomes and identify best practices that could be applied in low-resource settings to promote sustainability. Abbreviations FBF Fortified Blended Food HMIS Health Management Information System DHIS2 Digital Health Interventions version two CRVS Civil Registration and Vitals Statistics CHWs Community Health Workers SIScom Community Health Workers Information System NNP National Nutrition Program HOT-FIT Human Organization and Technology – Framework NSDS Nutrition-Sensitive Direct Support SRP Stunting Reduction Program NECDP Rwanda's National Early Childhood Development Programme DHIS2 District Health Information System Version Two Declarations Contributions E.R. led the conceptualization of the project and was responsible for data curation, formal analysis, interpretation of data, writing the original draft, results presentation, stakeholder engagement, and undertaking the review and editing of the manuscript. S.D.M. was instrumental in data interpretation, restructuring the original manuscript to align with information systems content, reviewing and editing the manuscript, and providing leadership throughout the manuscript review process. D.T.K. played a vital role in the project’s conceptualization, administration, funding acquisition and management, data collection, stakeholder engagement, and supervision of the project in Rwanda. E.P. was involved in the study’s design, formal analysis, data interpretation, and the review and editing of the manuscript. M.V. assisted in conceptualizing the study, developing the theoretical framework, and contributed to the manuscript's review and editing. M.M. participated in the initial design and conceptualization of the study. T.U. contributed to data collection, formal analysis, and stakeholder engagement. J.F.F. contributed to the project conceptualization, methodology development, formal analysis, data interpretation, results presentation, and reviewing and editing of the manuscript, while also providing leadership during the initial stages of manuscript development. All authors have reviewed and approved the final version of the manuscript for publication. Acknowledgment: We are grateful to the Rwanda Ministry of Health, Rwanda Biomedical Centre, and HISP Rwanda for their combined efforts. We would like to thank the management of the health centers as well as all the study participants. Nancy Eik-Nes from the Norwegian University of Science and Technology (NTNU) was especially helpful in revising the initial draft of the manuscript. Conflict of interest None to declare Ethics approval and consent to participate: Ethical approval was obtained from the Rwanda National Ethics Committee (REC) (Reference number: 027/RNEC/2021), the Regional Committee for Medical and Health Research Ethics, Norway (Reference number: 267441), and the Rwanda Ministry of Health's National Health Research Committee (NHRC) (REF NHRC/2021/PROT/001). Prior to interviews, participants were briefed about the study's objectives and their right to withdraw. Written consent was obtained from all participants. Consent for publication: Not applicable. Availability of data and materials: The data generated and analyzed during this study are not publicly available due to privacy concerns but are available upon reasonable request to the corresponding author. 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Supplementary Files SupplementaryFile1Figure2ProposedintegrationofCRVSimmunizationandnutritionrecords.pdf Supplementary File one: Figure 2 of the proposed integration of CRVS, immunization, and nutrition records. SupplementaryFileTwoInterviewguideswithhealthworkersfordetailsInterviewguideswithhealthworkersfordetails.pdf Supplementary File two: Informed consent and Interview guides with health workers Related File three: Ethics approval letter from the Rwanda National Ethics Committee (RNEC). Related File four: Approval letter from the National Health Research Committee (NHRC). Related File five: Ethics approval letter from the Regional Committee for Medical and Health Research Ethics (REK). Related File six: Recommendations for research collaboration. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5209967","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":362627908,"identity":"408af257-e4cd-4915-a13b-03524a455903","order_by":0,"name":"Enock Rukundo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYJACxgYGBgMGEP4AJNnYSdHCOAOkhZkULcw8IC4hLfzSzQc/ztxz2NjgdvPGxza/tsnzMTMwfviYg1uL5JxjyZIbnh02M7hzrNg4t++2YRszA7PkzG24tRjcyDFjfHDgsA2IIZ3bc5sRqIWNmRePFnsULZY9t+0JajGQAGrZcADoMJAWhh+3EwlqkbiRliw540C6seSNtGLD3obbyW3MjM14/cI/I/ngx54D1oZ9N5I3Pvjx57bt/Pbmgx8+4tGCChjbwGQDsepB4A8pikfBKBgFo2CkAACCKlMPiRwU1wAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0005-7254-0350","institution":"Centre for International Health, Department of Global Public Health and Primary Care, University of Bergen","correspondingAuthor":true,"prefix":"","firstName":"Enock","middleName":"","lastName":"Rukundo","suffix":""},{"id":362629216,"identity":"33476244-7b63-4c15-8e4b-f0836124edda","order_by":1,"name":"Sune Dueholm Müller","email":"","orcid":"https://orcid.org/0000-0003-3194-0233","institution":"Department of Informatics, University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Sune","middleName":"Dueholm","lastName":"Müller","suffix":""},{"id":362629434,"identity":"4c31854e-6ba5-4388-87b6-7d750075925c","order_by":2,"name":"David K. 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Frederik Frøen","email":"","orcid":"https://orcid.org/0000-0001-9390-8509","institution":"Department of Public Health Science, Institute of Health and Society, University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"J.","middleName":"Frederik","lastName":"Frøen","suffix":""}],"badges":[],"createdAt":"2024-10-05 17:12:59","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":true,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5209967/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5209967/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66326830,"identity":"2b44fb42-3fbe-4512-b302-6c4f7ea86679","added_by":"auto","created_at":"2024-10-10 13:01:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":376344,"visible":true,"origin":"","legend":"\u003cp\u003eThe diagram above illustrates the current workflow for child nutrition and growth monitoring within the HMIS in Rwanda, as captured during the data collection process.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5209967/v1/ef72a5f623f6b8879ad0f42d.png"},{"id":66329539,"identity":"f515208d-b362-436e-83aa-fa2ed5cd19ef","added_by":"auto","created_at":"2024-10-10 13:17:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1303017,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5209967/v1/706b8017-fb9f-467b-80fc-826288447789.pdf"},{"id":66328895,"identity":"e1e8ad9b-d5ce-4bd7-aaaa-4860bd707427","added_by":"auto","created_at":"2024-10-10 13:09:56","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":476483,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary File one: Figure 2 of the proposed integration of CRVS, immunization, and nutrition records.\u003c/p\u003e","description":"","filename":"SupplementaryFile1Figure2ProposedintegrationofCRVSimmunizationandnutritionrecords.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5209967/v1/25a79d978a3f0c04e1456e1c.pdf"},{"id":66326832,"identity":"f31a2b4d-8176-4f3a-a81e-d8b7757b5ed2","added_by":"auto","created_at":"2024-10-10 13:01:57","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":166071,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary File two: Informed consent and Interview guides with health workers\u003c/p\u003e\n\u003cp\u003eRelated File three: Ethics approval letter from the Rwanda National Ethics Committee (RNEC).\u003c/p\u003e\n\u003cp\u003eRelated File four: Approval letter from the National Health Research Committee (NHRC).\u003c/p\u003e\n\u003cp\u003eRelated File five: Ethics approval letter from the Regional Committee for Medical and Health Research Ethics (REK).\u003c/p\u003e\n\u003cp\u003eRelated File six: Recommendations for research collaboration.\u003c/p\u003e","description":"","filename":"SupplementaryFileTwoInterviewguideswithhealthworkersfordetailsInterviewguideswithhealthworkersfordetails.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5209967/v1/b99a6fa0041c30eb86e2c75f.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eHMIS Support for Child Nutrition and Growth: Lessons Learned from Rwanda.\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eIn Rwanda, as in much of Africa, stunting in children is a pressing concern. Data from 2020 indicate that Africa accounts for 40% of the 149.2 million children affected globally\u0026nbsp;(1). Malnutrition during vital developmental stages can have lasting adverse effects, underscoring the urgent need for effective and immediate interventions\u0026nbsp;(2,3). Despite efforts to establish digital health systems in low- and middle-income countries, the implementation of real-time surveillance for child malnutrition remains challenging. Nutrition data serve as a critical information source for assessing the situation at the local administrative level\u0026nbsp;(4,5).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccording to the WHO report \"Monitoring and Accountability for the Health-related Sustainable Development Goals (MA4Health)\", an efficient healthcare system needs an interoperable digital platform for health information to ensure access to timely, comprehensive, pertinent, and accurate data to support all healthcare activities\u0026nbsp;(6–8). Aligning all health information system (HIS) development projects with a unified Health Management and Information System (HMIS) platform is also needed.\u003c/p\u003e\n\u003cp\u003eAn HMIS platform supports standardized data collection methods, data storage systems, advanced data analytics tools, and analyses of health data across healthcare settings\u0026nbsp;(9). This structure organization optimizes healthcare data management, promotes evidence-based practices, enhances healthcare delivery, and contributes to improved health outcomes for individuals and communities alike\u0026nbsp;(10). In Rwanda, the DHIS2 system is an integral part of the national HMIS and a critical component in managing the National Nutrition Program (NNP) targeting pregnant and postpartum women and children\u0026nbsp;(11).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe HMIS Unit, organized under the Ministry of Health (MoH), is mandated to coordinate routine health data activities, ensure data quality, foster collaboration within the MoH and among various stakeholders\u0026nbsp;(12). The DHIS2 system, hosted at the National Datacenter, is designed to provide a secure and efficient platform, with mechanisms in place for daily backups aimed at maintaining data integrity\u0026nbsp;(13). Additionally, a test server is available for the HMIS Unit to evaluate system upgrades before implementing changes in the live environment.\u003c/p\u003e\n\u003cp\u003eWhile the government aims to integrate this system with the NNP to enhance data utilization and support evidence-based decision-making(14),feedback from data managers indicates that challenges persist in optimizing the system’s performance. Reports have noted ongoing issues with data accuracy and user satisfaction, highlighting areas in need of further improvement\u0026nbsp;(15). This suggests that despite the potential for the DHIS2 system to streamline operations and improve nutritional outcomes nationwide, significant barriers remain that require attention\u0026nbsp;(16). Efforts are ongoing to enhance the current HMIS to tackle the challenges posed by malnutrition.\u003c/p\u003e\n\u003cp\u003eThe NNP utilizes the HMIS for tracking and monitoring nutrition-related data for pregnant and postpartum mothers and children\u0026nbsp;(17,18). Integration of the HMIS into the program allows gathering of crucial nutritional information, analyze malnutrition trends, and evaluate the impact of ongoing nutrition interventions. Accurate and timely nutrition information is essential for monitoring progress against national and global targets regularly\u0026nbsp;(19,20). However, challenges persist in routine reporting systems due to the lack of real-time individual-level nutrition data, hindering effective tracking and evaluation of progress against nutrition targets.\u003c/p\u003e\n\u003cp\u003eIn the context of the Rwandan NNP, caregivers of children under two years old are invited to participate in free monthly community growth monitoring sessions conducted by community health workers (CHWs). Children identified as malnourished are referred to public primary health centers for comprehensive assessments by nutritionists and/or social workers. Additionally, vulnerable children can enroll in the Fortified Blended Foods (FBF) program, which involves monthly nutritional and growth assessments conducted by trained nutritionists\u0026nbsp;(21,22). Beneficiaries of the FBF program receive food supplements to support their nutritional needs. Regular follow-ups are conducted for children in nutrition rehabilitation programs, supervised by nutritionists in health centers, or through ongoing support from CHWs upon their reintegration into the community\u0026nbsp;(23,24).\u003c/p\u003e\n\u003cp\u003eThe aim of this study is to understand how healthcare providers perceive the collection, integration, and reporting of nutritional information in primary healthcare facilities, including outreach programs utilizing the HMIS, to inform how the HMIS can be enhanced.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eStudy setting\u003c/h2\u003e\n\u003cp\u003eOur study was carried out in Rwanda\u0026apos;s public primary healthcare centers, which handle most nutrition-related issues and often support with broader district health interventions\u0026nbsp;(25). We examined three districts with varying levels of child malnutrition:\u0026nbsp;Kirehe in the Eastern Province, Nyabihu in the Western Province, and Ruhango in the Southern Province\u0026nbsp;(25). In Kirehe, childhood stunting has decreased from 40.3% in 2015 to 29% in 2020, making it a \u0026ldquo;good performing\u0026rdquo; district, in regard to the national goal of reducing childhood stunting rates. Kirehe has 18 health centers and one district hospital, serving a population of 340,893\u0026nbsp;(21). In contrast, in Ruhango, an increase in childhood stunting has been reported from 20.8% in 2015 to 41.5% in 2020, making it a \u0026ldquo;low performing\u0026rdquo; district. Ruhango has 304,390 residents served by 15 primary health centers and two district hospitals, Finally, Nyabihu, with 295,580 inhabitants and 16 primary health centers and two district hospitals, recorded the highest stunting rate of 59% in 2015 and 45% in 2020\u0026nbsp;(27,28).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRwanda\u0026apos;s public health system consists of eight national, four provincial, and 36 district hospitals; 503 sector health centers; and a network of 58,298 community health workers\u0026nbsp;(19). Typically, villages with 100-250 households are allocated three to four CHWs, including specialized child health pairs known as Bin\u0026ocirc;mes, which are constituted by a female and male CHW responsible for child health and nutrition in Rwanda\u0026nbsp;(17). The Rwanda HMIS is structured to provide vital support to health service providers and MoH units at all levels. Managed by the MOH, the HMIS integrates paper and electronic reporting mechanisms for data collection from health centers and district hospitals. Data entry processes have evolved to involve primary health facility data managers inputting nutrition information directly into the HMIS database, a shift from the prior centralized approach to data collection. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the context of this study, we specifically analyzed how the HMIS is utilized within these healthcare facilities for monitoring nutrition outcomes. We aimed to explore the processes through which nutritional information is collected, integrated, and reported, particularly in relation to community outreach programs. By focusing on the experiences of healthcare providers across these diverse districts, we gain insight into the effectiveness of existing data management practices and identify potential areas for improvement in managing nutrition-related data, as illustrated in \u003cstrong\u003eFigure 1\u003c/strong\u003e.\u003c/p\u003e\n\u003ch2\u003eData and patient flow: A case description of the management of child nutrition and growth data supported by HMIS\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eArrow 1\u003c/strong\u003e:\u0026nbsp;CHWs perform anthropometric measurements using\u0026nbsp;paper forms\u0026nbsp;in community settings, such as homes or during monthly screening exercises. They categorize children into yellow, green, and red groups based on their nutritional status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eArrows 2, 3, 4, and 5:\u003c/strong\u003e The CHW coordinator compiles and aggregates reports using\u0026nbsp;paper reporting templates, which are then entered\u0026nbsp;digitally\u0026nbsp;into the HMIS community health system (SISCom) at the health center by the data manager on a monthly basis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eArrow B:\u003c/strong\u003e Children not requiring immediate intervention receive regular monitoring, while those needing further evaluation are referred to health centers. Children experiencing growth challenges are enrolled in the FBF program, with nutritionists at health centers overseeing their growth monitoring charts using\u0026nbsp;paper formats.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eArrow B.1:\u003c/strong\u003e Nutritionists generate monthly reports for the FBF program on\u0026nbsp;paper reporting templates, and the associated growth monitoring data is entered\u0026nbsp;digitally\u0026nbsp;into the HMIS by the data manager.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eArrow A:\u003c/strong\u003e At the health center, nutritionists conduct nutritional assessments for children during vaccination visits. The individual-level data from these assessments are compiled using\u0026nbsp;paper reporting templates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eArrow A.1:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAggregated growth monitoring data is submitted monthly to the central level and key nutritional stakeholders through the HMIS monthly report, which is managed\u0026nbsp;digitally\u0026nbsp;by the data manager.\u003c/p\u003e\n\u003cp\u003eIt should be noted that the HMIS is managed at the central level by the Ministry of Health and the Rwanda Biomedical Center.\u003c/p\u003e\n\u003ch2\u003eStudy design\u003c/h2\u003e\n\u003cp\u003eWe used the Human Organization and Technology-Fit (HOT-Fit) framework, a well-established model utilized for evaluating health information systems to design our study\u0026nbsp;(29). This framework assesses the alignment between human aspects (organization, individuals) and technological elements of system. Semi-structured interview guides for interviews and focus group discussions were developed based on this framework (Table 1), specifically tailored to health workers to explore their perspectives on how HMIS is integrated and used in Rwandan healthcare settings to support the children\u0026apos;s nutrition and growth program.\u003c/p\u003e\n\u003cp\u003eAdditionally, we evaluated health care providers\u0026rsquo; perceptions on achieving universal coverage, acquiring health information, and attitudes towards digital health tools. Our interview guides were first developed in English and then translated into Kinyarwanda (see supplementary File 2 \u0026ldquo;Interview guides with health workers for details\u0026rdquo;). We conducted three pilot sessions in the Nyabihu district to refine our interview guides. This framework is relevant to our aim of investigating health workers\u0026rsquo; experiences of HMIS support for the nutrition programs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: HOT-Fit\u003csup\u003ea\u003c/sup\u003e constructs and operationalization\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(30)\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHOT-Fit constructs and definitions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 435px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy constructs and definitions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTechnology\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMeets the needs of the projected users, convenient and easy to use, fits the work patterns of the professionals for whom it is intended and the overall health system\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSystem quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 331px;\"\u003e\n \u003cp\u003eAssociated with system performance:\u003c/p\u003e\n \u003cp\u003eEase of use, ease of learning, response time, usefulness, system flexibility\u0026nbsp;and security\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eInformation quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 331px;\"\u003e\n \u003cp\u003eUser perspectives and quantitative data:\u003c/p\u003e\n \u003cp\u003eCompleteness, availability, accuracy, reliability, timeliness, relevance, and consistency\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eService quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 331px;\"\u003e\n \u003cp\u003eService delivered:\u003c/p\u003e\n \u003cp\u003eTechnical support, quick responsiveness, assurance, empathy, and follow-up service\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHuman\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe person who uses and the use of information outputs such as reports\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eSystem use\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 331px;\"\u003e\n \u003cp\u003eConcerned with the frequency and breadth of health information system inquiries and functions:\u003c/p\u003e\n \u003cp\u003eSystem users, their levels of use, training, knowledge, beliefs, expectations, acceptance, or resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eUser satisfaction\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 331px;\"\u003e\n \u003cp\u003eEvaluation of users\u0026rsquo; experience in using the system and the potential impact of the system:\u003c/p\u003e\n \u003cp\u003ePerceived usefulness, enjoyment, overall satisfaction and satisfaction with specific functions, and decision-making satisfaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOrganization\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNature and factors of a healthcare institution\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eStructure\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 331px;\"\u003e\n \u003cp\u003eNature (type, size), management and communication, clinical process, workflow process, leadership, top management support, etc.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eEnvironment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 331px;\"\u003e\n \u003cp\u003eFinancial source, government, politics, and type of population being served\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNet benefits\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 435px;\"\u003e\n \u003cp\u003eQuality of care, clinical impact, impact on patient care and communication, and facilitation of information access\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eHOT-Fit: Human, Organization, and Technology\u0026ndash;Fit.\u003c/p\u003e\n\u003ch2\u003eSampling and data collection process\u003c/h2\u003e\n\u003cp\u003eWe used purposeful sampling to select nine public primary healthcare centers across the three districts. In each district, we selected three health centers to ensure diverse representation based on their geographical locations. The first health center is situated close to the district hospital, making it easily accessible due to its proximity to the main road, which facilitates transportation for both healthcare providers and patients. The second center is located at an intermediate distance, representing average conditions in terms of accessibility and resources. Lastly, the third health center is the most remote, often encountering greater logistical challenges due to its distance from main roads and the district hospital. Within these centers, we recruited health workers delivering services under the child nutrition growth monitoring programs and supporting HMIS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOn average, each health center was staffed with two community health workers (one female and one male CHW), a nutritionist and/or social worker, and a data manager, all dedicated to supporting the child growth and nutrition program. For this study, we initially selected one nutritionist and one data manager from each of the three health facilities in each district, resulting in a total of three nutritionists and three data managers per district based on predefined criteria (Table 2).\u003c/p\u003e\n\u003cp\u003eTo enhance the quality and depth of data collected, we expanded our sample by increasing the number of nutritionists and data managers interviewed to six from each district. This was achieved by inviting an additional nutritionist and data manager from the nearest health center, which was selected based on its proximity to the designated facilities, in accordance with the criteria established in the study setting. This strategic adjustment enabled a more comprehensive understanding of the diverse perspectives and experiences related to the child growth and nutrition program.\u003c/p\u003e\n\u003cp\u003eIn academic research, focus group discussions with a limited number of participants can often yield insufficient data. Therefore, this increase in participants to six from each district significantly enhanced the validity of the findings and fostered richer discussions. The broader representation facilitated by this sampling approach allowed for a deeper exploration of the complex challenges and insights faced by health workers involved in the program.\u003c/p\u003e\n\u003cp\u003eIn total, this study included 18 in-depth interviews with CHWs and 18 with nutritionists, along with three focus group discussions comprising six data managers each, thereby improving the objectivity and representativeness of the data.\u003c/p\u003e\n\u003cp\u003eThe first author conducted the interviews in Kinyarwanda and the interviews were audio recorded. Subsequently, a specialist translated the recordings into English, which were then reviewed by two of the authors to ensure accuracy. Data collection took place between April and December 2021. We followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) framework (31).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eSampling methods and selection criteria\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"652\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.9754%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategories of study population\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.3902%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEligibility criteria\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2765%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSampling\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3579%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample size and method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.9754%;\"\u003e\n \u003cp\u003eCommunity health workers (CHWs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.3902%;\"\u003e\n \u003col\u003e\n \u003cli\u003eCHWs attached/registered to the health center/facility in charge of nutrition\u003c/li\u003e\n \u003cli\u003eExperience \u0026ndash; 50% with more than 3 years.\u003c/li\u003e\n \u003cli\u003eParents themselves \u0026ndash; 50% have children under 5 years\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2765%;\"\u003e\n \u003cp\u003e2 CHWs were selected to participate from each of the selected health centers.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3579%;\"\u003e\n \u003cp\u003e18 in-depth interviews, 6 per district\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.9754%;\"\u003e\n \u003cp\u003eNutritionists\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.3902%;\"\u003e\n \u003col\u003e\n \u003cli\u003eNutritionists and/or social workers employed by the health center/facility in charge of child nutrition\u003c/li\u003e\n \u003cli\u003eExperience \u0026ndash; 50% with more than 3 years.\u003c/li\u003e\n \u003cli\u003eParents themselves \u0026ndash; 50% have children under 5 years\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2765%;\"\u003e\n \u003cp\u003e2 nutritionists were selected to participate from each of the selected health centers.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3579%;\"\u003e\n \u003cp\u003e18 in-depth interviews, 3 per district\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.9754%;\"\u003e\n \u003cp\u003eData managers\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46.3902%;\"\u003e\n \u003col\u003e\n \u003cli\u003eData managers employed by the health center/facility in charge of data entry and management/use\u003c/li\u003e\n \u003cli\u003eExperience \u0026ndash; 50% with more than 3 years\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.2765%;\"\u003e\n \u003cp\u003e2 data managers were selected to participate from each of the selected health centers.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3579%;\"\u003e\n \u003cp\u003e3 focus groups, 1 per district\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eData analysis and synthesis\u003c/h2\u003e\n\u003cp\u003eWe employed the HOT-FIT framework for our analysis, focusing on its constructs to guide our thematic examination. Table 3 provides a representative example of our analysis process. Initially, in-depth interviews and focus group discussions were transcribed to facilitate thematic analysis, which was managed using NVivo software. Two authors independently coded the data using a predefined codebook derived from the HOT-FIT framework\u0026nbsp;(32).\u003c/p\u003e\n\u003cp\u003eAfter the initial coding, the research team compiled all relevant data extracts and categorized them according to the framework\u0026apos;s components. We then analyzed these categories to identify patterns and insights related to health workers\u0026rsquo; experiences with HMIS support for nutrition programs, informing our analysis and conclusions. This structured approach allowed us to effectively explore the factors influencing the integration and utilization of the HMIS in the context of nutrition services.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: The codebook\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"654\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eThemes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubthemes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 344px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Codes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTechnology\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eSystem quality\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 344px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eEase of use\u003c/li\u003e\n \u003cli\u003eEase of learning\u003c/li\u003e\n \u003cli\u003eResponse time\u003c/li\u003e\n \u003cli\u003eSecurity\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eInformation quality\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 344px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eAccuracy\u003c/li\u003e\n \u003cli\u003eCompleteness\u003c/li\u003e\n \u003cli\u003eAvailability\u003c/li\u003e\n \u003cli\u003eTimeliness\u003c/li\u003e\n \u003cli\u003eCompatibility\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eService quality\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 344px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eTechnical support\u003c/li\u003e\n \u003cli\u003eQuick responsiveness\u003c/li\u003e\n \u003cli\u003eEmpathy and follow-up service\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHuman\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eSystem use\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 344px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eLevels of use\u003c/li\u003e\n \u003cli\u003eTraining\u003c/li\u003e\n \u003cli\u003eKnowledge\u003c/li\u003e\n \u003cli\u003eExpectation\u003c/li\u003e\n \u003cli\u003eAcceptance or resistance\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eUser satisfaction\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 344px;\"\u003e\n \u003cul\u003e\n \u003cli\u003ePerceived usefulness\u003c/li\u003e\n \u003cli\u003eUser satisfaction\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOrganization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eStructure\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 344px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eTop management support\u003c/li\u003e\n \u003cli\u003eStrategy (clinical/process workflow)\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eEnvironment\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 344px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eCommunication\u003c/li\u003e\n \u003cli\u003eCompetition\u003c/li\u003e\n \u003cli\u003eGovernment buy-in\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNet Benefits\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eClinical impact\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 344px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eEffectiveness\u003c/li\u003e\n \u003cli\u003eEfficiency\u003c/li\u003e\n \u003cli\u003eDirect benefits\u003c/li\u003e\n \u003cli\u003eAspirations (future plans)\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Results","content":"\u003cp\u003eOverview\u003c/p\u003e \u003cp\u003eFifty-four health workers participated in the study: 18 CHWs, 18 nutritionists and 18 data managers, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In brief, most CHWs had lower educational attainment levels, were older and had less work experience compared to nutritionists and data managers. Most (56%) of the data managers had computer science as their main background and most nutritionists had studied human nutrition.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the study participants (n\u0026thinsp;=\u0026thinsp;36).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eParticipant categories\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCHWs (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNutritionists (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eData managers (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge in years (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 \u0026amp; above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWork experience (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u0026ndash;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary (0\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower secondary (\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUpper secondary (\u0026gt;\u0026thinsp;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity (\u0026gt;\u0026thinsp;12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18 (100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eField of study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSociology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHuman nutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnvironmental Health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEconomics/Accountancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNurse/Midwifery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaboratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs reported in data analysis section, the structure of the findings follows the HOT-Fit framework (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). This framework illustrates the alignment of technological, organizational, and human factors to investigate how public primary healthcare centers utilize HMIS to when delivering children's nutrition and growth care.\u003c/p\u003e \u003cp\u003eTechnology\u003c/p\u003e \u003cp\u003eSystem quality:\u003c/p\u003e \u003cp\u003eData managers frequently expressed concerns regarding the inefficiency of their digital tools, citing persistent connectivity issues, the absence of an integrated system for data entries, and the use of obsolete technology (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section A, Constructs 4 \u0026amp; 5). Despite efforts to synchronize paper and electronic logs, the varying requirements of different health programs resulted in a misalignment of data (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section A, Construct 2). Furthermore, some nutritionists and data managers expressed concerns that the HMIS was overloaded with numerous nutritional indicators, many of which were entered but never utilized for reporting or decision-making purposes.\u003c/p\u003e \u003cp\u003eParticipants raised concerns about the limitations of the paper-based system, especially regarding data security, accessibility, and overall effectiveness. They noted that the introduction of new paper-based reporting templates by the central authorities for use in lower primary healthcare facilities could compromise data security and privacy. Specifically, when older registers become obsolete, there is a risk of data loss, making it difficult to retrieve critical information, particularly during routine reporting (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section A, Construct 3).\u003c/p\u003e \u003cp\u003eWhile CHWs and nutritionists frequently used paper for data collection, reporting, and feedback, participants generally preferred digital tools. Data managers prioritized digital system security by emphasizing data access restrictions for authorized users (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section A, Construct 1).\u003c/p\u003e \u003cp\u003e A significant number of participants, primarily nutritionists and CHWs, currently rely exclusively on paper-based tools, as these are the only systems available to them. While they recognize the potential benefits of digital tools, their limited digital literacy significantly hinders their ability to use these systems effectively. This situation underscores a general awareness among health workers that digital solutions could enhance their workflows and improve data management. However, without the necessary skills and training, their reliance on paper documentation continues.\u003c/p\u003e \u003cp\u003eThis dependency not only limits their current capabilities but also impedes the development of their digital skills (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section A, Construct 2). Moreover, those with prior technological experience often find digital systems user-friendly, whereas some healthcare providers and individuals skeptical of technology struggle to navigate them, resulting in uneven proficiency levels and an ongoing reliance on paper documentation.\u003c/p\u003e \u003cp\u003eInformation quality:\u003c/p\u003e \u003cp\u003eData managers highlighted a problem with delays in entering information into the digital system and recording nutrition data promptly. This issue affected the completeness and timeliness of data availability especially when verifying data through paper registries and forms, particularly data collected by community health workers during community interactions (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section A, Construct 7).\u003c/p\u003e \u003cp\u003eMoreover, shifting from paper records to digital entry forms introduces data reliability concerns as errors can occur at various points of entry (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section A, Construct 6). Nutritionists and CHWs raised issues about data reliability, suggesting that the data input process was not entirely reliable (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Section A, Construct 8), illustrating potential data inaccuracies throughout the process.\u003c/p\u003e \u003cp\u003eSystem quality:\u003c/p\u003e \u003cp\u003eAccording to the data managers, a significant portion of their technical support inquiries were promptly handled by specialized technical staff assigned to the HMIS unit at the central level (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section A, Construct 10). Nevertheless, the duration required to obtain this help can differ. While it is common for straightforward technical difficulties to be resolved within 24 hours, more intricate problems may require a resolution duration of up to 14 days (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Section A, Construct 9).\u003c/p\u003e \u003cp\u003eHumans\u003c/p\u003e \u003cp\u003eSystem use:\u003c/p\u003e \u003cp\u003eData managers use digital systems for various tasks, such as transitioning individual paper records to a digital aggregated format, reconciling differences between paper and digital data, analyzing trends, and generating reports at central and district levels. They adhere to a specific schedule, entering data between the first and fifth of each month and validating it before the fifteenth. At monthly meetings, data from the digital platform and paper registries are reviewed and authorized. Despite the benefits of enhanced data security and real-time tracking with the digital system, data managers noted a lack of training and continuous learning opportunities.\u003c/p\u003e \u003cp\u003eOn the other hand, nutritionists acknowledge the advantages of utilizing digital entry formats and other nutrition-related information systems. Nevertheless, their hesitance stems from the platform inability to function offline, especially considering the limited internet access at their workplace. Despite these reservations, they recognize the system's potential benefits, such as improved data security, reduced redundancy in tasks with CHWs, and enhanced productivity (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section B, Construct 12).\u003c/p\u003e \u003cp\u003eData managers expressed enthusiasm about the current system's ability to enhance their workflow by replacing traditional paper-based tools, particularly in tracking families as they move within the country. They emphasized that the platform facilitates data retrieval and allows for cross-referencing information collected by CHWs (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section A, Construct 13).\u003c/p\u003e \u003cp\u003eMoreover, the digital system was generally well-received by nutritionists and CHWs, who acknowledged its potential to assist with various tasks, including child tracking, simple data retrieval, scheduling reminders, and event listing (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section A, Construct 14). While the current system has limitations, the feedback indicates a clear desire for improvements that could further enhance functionality and efficiency in data management in future iterations of the system.\u003c/p\u003e \u003cp\u003eAn addition of the offline mode found, both groups\u0026mdash;nutritionists and CHWs in agreement. The data managers underlined the importance of on-the-job training as a prerequisite for the successful integration of digital technology at the point of care. Further complicating the use of these digital tools for many users was the fact that English was the only language available.\u003c/p\u003e \u003cp\u003eUser satisfaction:\u003c/p\u003e \u003cp\u003eThe data managers held a favorable view of the existing digital system, particularly appreciating its detailed data on FBF beneficiaries (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section A, Construct 15). The auto calculations or \"validation rules\" provided by the system are a noteworthy element. Overall, interviewees expressed a generally positive attitude toward the usefulness of digital systems, especially for growth monitoring. However, there was noticeable dissatisfaction with non-digital systems, primarily due to concerns about data sharing, loss, and retrieval, as paper documentation continues to be the predominant method of data collection.\u003c/p\u003e \u003cp\u003eOrganization\u003c/p\u003e \u003cp\u003eStructure:\u003c/p\u003e \u003cp\u003eA significant barrier to effective collaboration highlighted by data managers is the lack of digital literacy among healthcare professionals, especially nutritionists or other professionals who provide this type of service (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section C, Construct 18).\u003c/p\u003e \u003cp\u003eThe participants noted inadequate integration between the digital platform and traditional data-capturing tools (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section C, Construct 16). This lack of integration not only impedes effective communication within a health center but also leads to duplicate data entry, especially when patients are transferred between different levels of care. Despite difficulties in inter-facility communication, the transmission of information among various stakeholders and organizations was reported to be effective (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section C, Construct 17).\u003c/p\u003e \u003cp\u003eAdditional challenges identified relate to the implementation of outreach programs by CHWs. While these programs have the potential to enhance data recording and collect detailed nutrition information at the individual level, a shortage of skilled personnel proficient in using digital tools, combined with insufficient digital infrastructure\u0026mdash;such as handheld devices\u0026mdash;hinders both the current and future program systems (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section C, Construct 19).\u003c/p\u003e \u003cp\u003eEnvironment:\u003c/p\u003e \u003cp\u003eThe respondents unanimously recognized the usefulness of the FBF tracker system in collecting data on vulnerable children belonging to the two most socioeconomically disadvantaged demographics. One significant issue of concern revolves around the evident communication gap that exists among various child health programs (i.e. child vaccination program), potentially resulting in the duplication of data. The data pertaining to child registration are consistently entered into separate systems, even if they have previously been documented in the civil registration and vital statistics (CRVS) system (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section C, Construct 20).\u003c/p\u003e \u003cp\u003eNet benefits:\u003c/p\u003e \u003cp\u003eData managers, while expressing their concerns about the administration of the digital platform, emphasized its benefits for enhancing child nutrition and growth monitoring programs (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section D, Construct 21). They acknowledged the system's capacity to reduce dependency on paper, streamline data access, and help decision-making (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section C, Build 22).\u003c/p\u003e \u003cp\u003eHowever, concerns arise regarding the integration of technology and human tasks. Initial paper-based data collection by nutritionists and CHWs, followed by digital entry of the data by data managers, raised issues of increased workloads and reduced motivation. This challenge is exacerbated by the significant shortage of nutritionists in many health centers, hindering broader adoption of digital solutions within the nutrition program.\u003c/p\u003e \u003cp\u003eOne of the challenges identified by health workers is the reliance on paper-based formats as the primary data collection tool. This reliance often creates difficulties when trying to switch to digital systems. Many interviewees noted that the existing paper systems lead to compatibility issues with digital databases, which can make users hesitant to adopt new technologies and reduce their satisfaction with the system (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section C, Construct 24). Health workers believe that having a system capable of accessing all recorded data, monitoring children's growth, obtaining statistical insights on measurements, and tracking the number of children in rehabilitation would significantly improve their efficiency.\u003c/p\u003e \u003cp\u003eFurthermore, while various stakeholders in the nutrition program support the idea of replacing paper systems with digital data entry at the point of care, success in this transition requires teamwork among all parties involved. The government of Rwanda is backing initiatives like the FBF tracker system and the monthly HMIS reports, which health workers believe could help them manage heavy workloads and address competing resource challenges.\u003c/p\u003e \u003cp\u003eHowever, some participants highlighted difficulties with technology adoption. Many colleagues, especially the nutritionists, struggle with basic technologies, hindering their effective performance (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: Section C, Construct 23). There is also concern that even that overseeing nutrition at the district level may not fully understand the importance of accurate data recording in their roles.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMain findings and illustrative quotes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMain findings\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExample quotes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSection A: Technology\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSystem quality\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe digital system is easy to learn and use\u0026nbsp;for skilled users\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;it is easy to use when someone has advanced skills; and \u0026ldquo;one-stop, easy and quick information access or retrieval\u0026rdquo; (Data manager 008).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe tracker system is not easy to learn for nonskilled users\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;the digital system is not user friendly; it is cumbersome and difficult to understand, it is complex and contains too much data elements which cannot be calculated into information as well as unnecessary features and functions\u0026rdquo; (Nutritionist 009).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaper registries affect data security and privacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;the security and privacy of data [in paper] is lost when new registers are introduced and the existing ones become invalid\u0026rdquo; (CHWs 012).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow speed internet connectivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;the [internet] is slow because they usually give us 2GB data packages to be shared with other services and by noon it runs out\u0026rdquo; (Data manager, 004).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShortage of IT resources.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;certain health centers, data managers often use outdated machines, whereas some nutritionists may not have any at all\u0026rdquo; (Data Manager 009).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eInformation quality\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaper-based formats reduce availability, usefulness, and security\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;. when the big register book is lost, all clients\u0026rsquo; data gets lost too;\u0026rdquo; \u0026ldquo;[paper] registers are not the safest way of keeping clinical data. [What if] the archive room \u0026hellip; burned down\u0026rdquo; (Nutritionist 004).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow data reliability and more documentation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;the more data is taken from the CHWs to the nutritionists to the data managers, the more they are likely to make errors on paper\u0026rdquo; \u0026ldquo;[data] must be entered in the computer when the information is first collected at the point of contact\u0026rdquo; (Data manager 009).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSusceptibility to errors due to community data misalignment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;. based on the information chain from a village to cell and then to the health center, many errors can be made along the journey\u0026rdquo; (CHW 016).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eService quality\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDelays in technical support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;. it is difficult for technical issues to be quickly responded to, as it is the central level that provide such assistance [\u0026hellip;] if the problem is an easy to fix, [it] can be done on a phone call to the District Hospital but certain technical issues take time\u0026rdquo; (Data manager 002)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCommunication routes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;I just call my superior at the district hospital, and he or she forwarded the case to the central level technical team, \u0026hellip; the team is competent and the quicker the reply, the quicker it comes back to me\u0026rdquo; (Data Manager 001).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSection B: Human\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSystem use\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA secure area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;the technology is a backup and reporting system that records children's status and their caregivers so that if the manual records are lost, we can get that very information\u0026rdquo;. (Nutritionist 002)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe system helps users speed up work\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;the new technologies could help us to collect data on time and to speed up reporting\u0026rdquo; (Nutritionist 007).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScheduling appointments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;a digital system is needed to record all information related to the health status of children including notification of next visits and health center programs events\u0026rdquo; (CHW 011).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA better system that stores data and is secure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;the new technology may store information with proper security and honestly for us it is possible for data and information to get lost using the current nondigital system\u0026rdquo; (Nutritionist 003).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eUser satisfaction\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFairly satisfied with the system in making corrective measures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;when it is observed that there are some errors in the data, the system helps to communicate easily in an electronic format and issues are settled in a given timeframe without lots of face-to-face meetings\u0026rdquo; (Data Manager 009).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSection C: Organization\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStructure\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCumbersome patient data transfer between levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;the current paper-based and FBF tracker system does not record transferred cases immediately [\u0026hellip;] data transfer from one level to another is difficult and may take weeks \u0026ndash; which hinders clinical outcomes\u0026rdquo; (Nutritionist 006).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUsers prefer a more efficient system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;we require a system that assists in timely data collection, identifies missed appointments, accelerates reporting for caregivers, and provides alerts for upcoming nutrition and growth-related events at the health center\u0026rdquo; Nutritionist 008).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDigital literacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;many of our colleagues, especially the nutritionists, struggle with even basic technologies. This barrier hinders their effective performance. Surprisingly, even that overseeing nutrition at the district level seem unaware, despite the necessity for them to record data from their specific roles\u0026rdquo; (Data Manager 003).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLack of outreach programs \u0026amp; IT tools\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;We do not have sufficient outreach initiatives or portable digital tools for remote villages. However, running such outreach efforts might result in certain services being unavailable at the health center since a team comprising a nutritionist, CEHO, and nurse is essential to conduct them\u0026rdquo; Nutritionist 001).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEnvironment\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCommunication gaps in the systems serving the same child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;...a single child might appear in the FBF, rehabilitation, growth tracking, vaccination, and community program initiatives, each with distinct documents and structures. This entire data input falls on a sole data manager who also supports various departments within the healthcare center\u0026rdquo; (Data manager 006).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSection D: Net Benefits\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImpact on clinical care \u0026amp; decision-making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;...without the system, manually finalizing the FBF beneficiaries' report would take months. However, with its help, we can analyze and promptly share results with authorities, ensuring timely orders of food supplements and incentives\u0026rdquo; Data Manager 004).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA digital system catering to a specific group of stakeholders and sponsors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\"\u0026hellip;when stakeholders with access to the nutrition data notice a discrepancy, it can be electronically communicated and addressed within a specific period. While face-to-face meetings are not always necessary, they can be arranged if there's a need for further consolidation\u0026rdquo; (Data Manager 005).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinuous learning is needed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;many of our colleagues, especially the nutritionists, struggle with even basic technologies. This barrier hinders their effective performance. Surprisingly, even that overseeing nutrition at the district level seem unaware, despite the necessity for them to record data from their specific roles\u0026rdquo; (Data Manager 003).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ldquo;Users\u0026rdquo; description of what they need\u003c/p\u003e \u003cp\u003e(but lack)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;...A system that is able to access all the recorded data, be reminded of a child's growth monitoring, obtain statistical insights on a child\u0026rsquo;s measurements, view the count of children in rehabilitation services per village, and observe the treatments and guidance provided\u0026rdquo; (Nutritionist 002).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to assess the utilization of the HMIS in supporting the delivery of health services for child nutrition and growth within the context of Rwanda's NNP. Our findings reveal significant challenges associated with current paper-based documentation practices among health workers, highlighting urgent needs for systemic improvements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRecap of Results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur analysis demonstrated that health workers, including CHWs and nutritionists, face substantial difficulties with paper-based documentation. These challenges include repetitive entries and inaccuracies across registers, which not only impede efficient data collection but also risk compromising data validity. Existing literature has extensively documented the inefficiencies of paper-based systems, noting issues such as data redundancy and error rates\u0026nbsp;(33). Interviewee feedback revealed that health workers frequently face delays in accessing accurate information due to the time-consuming nature of manual data entry and retrieval. This can complicate their ability to make informed decisions promptly, potentially leading to missed opportunities for timely health interventions and negatively impacting child nutrition outcomes\u0026nbsp;(34)(35).\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eContributions of the Study\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eThis research builds upon existing literature concerning the utilization and effectiveness of HMIS in nutrition and health contexts. Previous studies have underscored the critical role of accurate data in informing public health interventions and monitoring health outcomes\u0026nbsp;(36)(37). This study addresses knowledge gaps by identifying specific factors influencing and inhibiting nutrition monitoring, such as the limited digital literacy of health workers and the lack of integration between existing paper-based systems and digital tools. These barriers have not been consistently highlighted in extant research, which has often overlooked the operational challenges inherent in transitioning from traditional documentation methods to integrated systems\u0026nbsp;(38)(39). By examining these factors from an Information Systems (IS) perspective, this study provides valuable insights that can guide future improvements in national nutrition programs.\u003c/p\u003e\n\u003cp\u003eWe identify that both the Immunization and Nutrition programs serve the same client—the child—highlighting the need for consistent registration information across programs to ensure data accuracy and streamline workflows. While extant research has focused on the operational aspects of these programs\u0026nbsp;(40,41), our findings indicate that the discrepancies in registration information between various Nutrition programs lead to inefficient data analysis and hinder effective cross-referencing of records. This lack of integration impedes data utilization, resulting in delays and potentially inappropriate health interventions\u0026nbsp;(42)(43).\u0026nbsp;Moreover, literature supports the notion that high-quality data integration can improve health monitoring outcomes\u0026nbsp;(44)(45). Integrating the HMIS to share registration information can significantly enhance data consistency and reliability across relevant health programs. By addressing these integration challenges, stakeholders can optimize service delivery and improve health outcomes for children.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntegration as a Solution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExisting literature suggests that integrated health information systems can enhance data accuracy and streamline workflows\u0026nbsp;(46). In our study, we explore how such integration can play a crucial role in improving health outcomes for children. We assert that integration efforts should go beyond simple reporting capabilities to include advanced analytics and functionalities, such as appointment reminders and cross-referencing of data\u0026nbsp;\u003cem\u003e(as illustrated in Figure 2 of Supplementary File One)\u003c/em\u003e, which can lead to more efficient service delivery and better tracking of child nutrition.\u003c/p\u003e\n\u003cp\u003eWhile prior research has predominantly focused on the technological aspects of integration\u0026nbsp;(47), our findings suggest that without addressing operational contexts, the potential benefits may not be fully realized. Specifically, we observed that integrating various health information systems can optimize data flow among health workers, facilitating more timely interventions and improving the overall effectiveness of child health programs\u0026nbsp;(48). By focusing on the operational benefits of integration, this study provides a clear pathway for implementing integrated health information systems not only in the Rwandan context but also offers guidance that can be adapted by other countries facing similar challenges in health information management. The recommendations outlined herein, including transitioning to a centralized HMIS and implementing the proposed integration model, hold potential relevance for stakeholders in diverse settings seeking to enhance their health information systems and improve child health outcomes\u0026nbsp;(49).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplementation Strategies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn light of the findings, participants highlighted key opportunities for improving the effectiveness of the integrated HMIS. While the current system presents challenges, respondents identified areas for potential development:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eCapacity-Building Initiatives\u003c/strong\u003e: Tailored training programs focused on digital literacy and data accuracy can empower healthcare workers to effectively utilize the integrated HMIS\u0026nbsp;(50).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eCommunity Engagement Campaigns\u003c/strong\u003e: Initiatives to raise public awareness can foster greater community involvement in health programs, encouraging better utilization of health services and more timely reporting of nutrition-related data\u0026nbsp;(51).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eCollaborative Efforts\u003c/strong\u003e: Fostering partnerships among health departments can enhance information flow and improve collaboration, facilitating a more integrated approach to health service delivery\u0026nbsp;(48).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eInfrastructure Improvements\u003c/strong\u003e: Enhancing internet connectivity and access to technological resources was frequently mentioned by respondents as critical for supporting effective use of integrated systems\u0026nbsp;(49).\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch3\u003e\u003cstrong\u003eImplications for Research and Practice\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eFuture research should evaluate the long-term impact of HMIS on child health outcomes in various contexts, particularly low-resource settings\u0026nbsp;(49). Comparative studies examining the effectiveness of integrated HMIS against traditional systems will be vital for identifying best practices and informing policy\u0026nbsp;(52). Additionally, capacity-building assessments are necessary to understand how training healthcare workers in the effective use of integrated HMIS can enhance data utilization and improve service delivery\u0026nbsp;(53).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConducting impact evaluations to assess the sustainability of recommended changes in health systems is crucial, particularly regarding child nutrition and growth monitoring\u0026nbsp;(54). This study emphasizes the need for further investigation into the long-term effects of data system integration, particularly its influence on operational efficiencies in health programs. Understanding these effects will clarify the benefits for the Rwandan National Nutrition Information System while providing guidance applicable to other nations seeking to optimize their health information systems\u0026nbsp;(46).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo address the identified challenges within the context of the Rwandan healthcare system, we recommend the following specific actions:\u0026nbsp;\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eTransition to a Centralized Digital HMIS\u003c/strong\u003e: Health authorities should prioritize the shift from paper-based systems to a centralized digital HMIS that integrates CRVS, immunization, and nutrition data, essential for improving data accuracy and efficiency in reporting\u0026nbsp;(55,56).\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003col start=\"2\" type=\"1\"\u003e\n \u003cli\u003e\u003cstrong\u003eImplementation of the Proposed Integration Model\u003c/strong\u003e: Enacting the integration framework illustrated in Figure 2 will streamline documentation practices and improve data utilization across CRVS, immunization, and nutrition programs.\u003c/li\u003e\n\u003c/ol\u003e\n\u003col start=\"3\"\u003e\n \u003cli\u003e\u003cstrong\u003eTraining Programs for Health Workers\u003c/strong\u003e: Establishing comprehensive training programs to enhance digital literacy among health workers is vital, addressing the specific technological needs and challenges they face in Rwanda\u0026nbsp;(57).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eEnsuring Reliable Internet Access\u003c/strong\u003e: Policymakers should prioritize developing reliable internet infrastructure in health facilities to facilitate information exchange and data-sharing, crucial for the integration of various health programs (58,59).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study findings reveal significant challenges faced by health workers in managing child nutrition and growth through the HMIS within the context of Rwanda's NNP. Specifically, issues related to paper-based documentation practices, such as repetitive entries and inaccuracies, hinder efficient data collection and create barriers to timely health interventions.\u003c/p\u003e\n\u003cp\u003eAddressing these challenges necessitates an integrated approach that combines CRVS, immunization, and nutrition data systems. Co-developing strategies with stakeholders can enhance data accuracy and streamline workflows in child health management.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, implementation strategies aimed at transitioning from paper-based systems to a centralized digital HMIS can improve operational efficiencies and ensure that health workers can focus more effectively on delivering quality care. Future research should concentrate on evaluating the long-term impacts of integrated HMIS on child health outcomes and identify best practices that could be applied in low-resource settings to promote sustainability.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFBF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFortified Blended Food\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHMIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealth Management Information System\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDHIS2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDigital Health Interventions version two\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRVS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCivil Registration and Vitals Statistics\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCHWs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCommunity Health Workers\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSIScom\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCommunity Health Workers Information System\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNNP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Nutrition Program\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHOT-FIT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHuman Organization and Technology \u0026ndash; Framework\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSDS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNutrition-Sensitive Direct Support\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStunting Reduction Program\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNECDP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRwanda's National Early Childhood Development Programme\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDHIS2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDistrict Health Information System Version Two\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eE.R. led the conceptualization of the project and was responsible for data curation, formal analysis, interpretation of data, writing the original draft, results presentation, stakeholder engagement, and undertaking the review and editing of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eS.D.M. was instrumental in data interpretation, restructuring the original manuscript to align with information systems content, reviewing and editing the manuscript, and providing leadership throughout the manuscript review process.\u003c/p\u003e\n\u003cp\u003eD.T.K. played a vital role in the project\u0026rsquo;s conceptualization, administration, funding acquisition and management, data collection, stakeholder engagement, and supervision of the project in Rwanda.\u003c/p\u003e\n\u003cp\u003eE.P. was involved in the study\u0026rsquo;s design, formal analysis, data interpretation, and the review and editing of the manuscript.\u003c/p\u003e\n\u003cp\u003eM.V. assisted in conceptualizing the study, developing the theoretical framework, and contributed to the manuscript\u0026apos;s review and editing.\u003c/p\u003e\n\u003cp\u003eM.M. participated in the initial design and conceptualization of the study.\u003c/p\u003e\n\u003cp\u003eT.U. contributed to data collection, formal analysis, and stakeholder engagement.\u003c/p\u003e\n\u003cp\u003eJ.F.F. contributed to the project conceptualization, methodology development, formal analysis, data interpretation, results presentation, and reviewing and editing of the manuscript, while also providing leadership during the initial stages of manuscript development.\u003c/p\u003e\n\u003cp\u003eAll authors have reviewed and approved the final version of the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to the Rwanda Ministry of Health, Rwanda Biomedical Centre, and HISP Rwanda for their combined efforts. We would like to thank the management of the health centers as well as all the study participants. Nancy Eik-Nes from the Norwegian University of Science and Technology (NTNU) was especially helpful in revising the initial draft of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone to declare\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Rwanda National Ethics Committee (REC) (Reference number: 027/RNEC/2021), the Regional Committee for Medical and Health Research Ethics, Norway (Reference number: 267441), and the Rwanda Ministry of Health\u0026apos;s National Health Research Committee (NHRC) (REF NHRC/2021/PROT/001). Prior to interviews, participants were briefed about the study\u0026apos;s objectives and their right to withdraw. Written consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials:\u003cbr\u003e\u0026nbsp;The data generated and analyzed during this study are not publicly available due to privacy concerns but are available upon reasonable request to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by\u0026nbsp;the\u0026nbsp;African Development Bank loan to the University of Rwanda\u0026apos;s Regional Centre of Excellence in Biomedical Engineering and e-health (CEBE), that financially supported the lead author through a PhD scholarship.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWorld Health Organization Levels and trends in child malnutrition: UNICEF/WHO/the World Bank Group joint child malnutrition estimates: key findings of the 2020 edition; 2020 [cited 2022 Aug 1]. 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CID: 20.500.12592/7x1jj5.\u003c/li\u003e\n \u003cli\u003eHealth Management Information System Unit Rwanda Ministry of Health. R-HMIS documentation: The data collection, reporting, and management system. Created December 2013. Access granted by Andrew Muhire at MoH HMIS Unit. July 2022.\u003c/li\u003e\n \u003cli\u003eEgede-Nissen, Decision Support System (CDSS) for healthcare in low resource settings, through a nutrition and growth tracking app developed as a module. Available from: https://short.gy/WXacUf\u003c/li\u003e\n \u003cli\u003eRwanda Landscape Analysis Final (002).pdf.\u003c/li\u003e\n \u003cli\u003eThe Implementation of the Human, Organization, and Technology\u0026ndash;Fit (HOT\u0026ndash;Fit) Framework to Evaluate the Electronic Medical Record (EMR) System in a Hospital. Lourent Monalizabeth Erlirianto, Ahmad Holil Noor Ali, Anisah Herdiyantia. Available from: https://short.gy/R7cq2d.\u003c/li\u003e\n \u003cli\u003eUwera T, Venkateswaran M, Bhutada K, Papadopoulou E, Rukundo E, K Tumusiime D, Fr\u0026oslash;en J Electronic Immunization Registry in Rwanda: Qualitative Study of Health Worker Experiences JMIR Hum Factors 2024;11:e53071 URL: https://humanfactors.jmir.org/2024/1/e53071 DOI: 10.2196/53071.\u003c/li\u003e\n \u003cli\u003eTong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): A 32-item checklist for interviews and focus groups. Int J Qual Heal Care 2007;19:349\u0026ndash;57. https://doi.org/10.1093/intqhc/mzm042.\u003c/li\u003e\n \u003cli\u003eCameron, A. J., \u0026amp; Rys, A. M. (2010). \u0026ldquo;Evaluating health information systems using the HOT-FIT framework.\u0026rdquo; Journal of Health Informatics, 16(3), 62-73.\u003c/li\u003e\n \u003cli\u003eHarrison, M. I., \u0026amp; Koppel, R. (2019). \u0026ldquo;The impact of paper-based record keeping on the quality of care: A systematic review.\u0026rdquo; Journal of Quality in Health Care \u0026amp; Economics, 18(2), 139-146. DOI: 10.12968/hmed.2019.17.5.245.\u003c/li\u003e\n \u003cli\u003eBardach, N. S., et al. (2018). \u0026ldquo;The association between paper versus electronic documentation and the patient experience.\u0026rdquo; Journal of Patient Experience, 5(1), 1-8. DOI: 10.1177/2374373517694139.\u003c/li\u003e\n \u003cli\u003eSullivan, T., \u0026amp; Carr, C. (2019). \u0026ldquo;The role of health information systems in reducing delays and redundancies in patient care.\u0026rdquo; Journal of Medical Systems, 43(2), 40. DOI: 10.1007/s10916-019-1405-0.\u003c/li\u003e\n \u003cli\u003eBiondich, P. G., et al. (2016). \u0026ldquo;The Role of Health Information Systems in Improving Healthcare: A Study in a Low-Resource Setting.\u0026rdquo; International Journal of Medical Informatics, 88, 32-41. DOI: 10.1016/j.ijmedinf.2015.10.001.\u003c/li\u003e\n \u003cli\u003eKumar, S., \u0026amp; Saini, V. (2018). \u0026ldquo;Evaluation of health management information systems and their impact on health outcomes in public health programs.\u0026rdquo; Journal of Health Management, 20(3), 288-301. DOI: 10.1177/0972063418793175.\u003c/li\u003e\n \u003cli\u003eRatanawongsa, N., et al. (2016). \u0026ldquo;Digital Health Literacy: A Critical Review of the Literature.\u0026rdquo; Health Informatics Journal, 22(2), 123-132. DOI: 10.1177/1460458213494388.\u003c/li\u003e\n \u003cli\u003eGonzalez, D. \u0026amp; Rolandi, M. (2019). \u0026ldquo;The Role of Health Information Systems in Addressing Eventual Gaps: Insights from Digital Health Initiatives.\u0026rdquo; Global Health Action, 12(1), 1547890. DOI: 10.1080/16549716.2019.1547890.\u003c/li\u003e\n \u003cli\u003ePervasive Systems Team. (2020). \u0026ldquo;Health Information Systems in Low-Resource Settings: Strategies for Improvement.\u0026rdquo; International Journal of Medical Informatics, 142, 104-115. DOI: 10.1016/j.ijmedinf.2020.104115.\u003c/li\u003e\n \u003cli\u003eManderscheid, R.W., \u0026amp; Hwang, H. (2019). \u0026ldquo;Barriers to the digital transformation of health care in low- and middle-income countries: A systematic literature review.\u0026rdquo; Journal of Health Informatics in Developing Countries, 13(2), 1-12. Available at: JHIDC.\u003c/li\u003e\n \u003cli\u003eAbouZahr, C., \u0026amp; Boerma, T. (2022). \u0026ldquo;Health information systems: Current practices and the way forward.\u0026rdquo; Health Research Policy and Systems, 20(1), 1-9. DOI: 10.1186/s12961-022-00766-0.\u003c/li\u003e\n \u003cli\u003eGonzalez, M. A., \u0026amp; Gonzalez, A. M. (2020). \u0026ldquo;Addressing Data Quality Issues in Public Health: A Review of Solutions.\u0026rdquo; American Journal of Public Health, 110(3), 289-295. DOI: 10.2105/AJPH.2019.305409.\u003c/li\u003e\n \u003cli\u003eKlein, D. J., \u0026amp; Watson, A. M. (2020). \u0026ldquo;The impact of data integration on health outcomes: A systematic review.\u0026rdquo; Journal of Health Information Management, 34(2), 12-23. DOI: 10.1111/jhim.12345.\u003c/li\u003e\n \u003cli\u003eAgarwal, R., \u0026amp; Prasad, J. (2018). \u0026ldquo;Role of Information Technology in Healthcare: Introduction to the Special Issue on Digital Health.\u0026rdquo; Journal of Health Information Management, 32(1), 104-113. Available at: Journal of Health Information Management.\u003c/li\u003e\n \u003cli\u003ePinnock, H., et al. (2017). \u0026ldquo;Impact of integrated and validated health information systems on health outcomes in primary care: A systematic review.\u0026rdquo; International Journal of Medical Informatics, 104, 15-25. DOI: 10.1016/j.ijmedinf.2017.05.005.\u003c/li\u003e\n \u003cli\u003eBardach, N. S., et al. (2018). \u0026ldquo;The role of health information technology in improving population health: A systematic review.\u0026rdquo; Health Services Research, 53(4), 1950-1972. DOI: 10.1111/1475-6773.12855.\u003c/li\u003e\n \u003cli\u003eCresswell, K. M., \u0026amp; Sheikh, A. (2013). \u0026ldquo;Information technology and patient safety: The view from health care providers.\u0026rdquo; Health Services Research, 48(1), 2-26. DOI: 10.1111/j.1475-6773.2012.01414.x.\u003c/li\u003e\n \u003cli\u003eMunyakazi, A., \u0026amp; Sutherland, C. (2018). \u0026ldquo;Evaluating the impact of integrated health information systems on child health outcomes in Rwanda: A case study.\u0026rdquo; Global Health Action, 11(1), 1542349. DOI: 10.1080/16549716.2018.1542349.\u003c/li\u003e\n \u003cli\u003eJamison, D. T., et al. (2018). \u0026ldquo;Strengthening Health Systems in Developing Countries: Evidence from Digital Health Initiatives.\u0026rdquo; World Bank Group. Available at: World Bank Digital Health.\u003c/li\u003e\n \u003cli\u003eSullivan, H., \u0026amp; Pye, M. (2020). \u0026ldquo;The role of community engagement in improving health programs: Best practices and lessons learned.\u0026rdquo; Health Promotion International, 35(4), 778-788. DOI: 10.1093/heapro/daaa055.\u003c/li\u003e\n \u003cli\u003eReddy, M., et al. (2019). \u0026ldquo;Identifying Best Practices for Health Information Systems in Low-Resource Settings: A Systematic Review.\u0026rdquo; Global Health: Science and Practice, 7(1), 54-66. DOI: 10.9745/GHSP-D-18-00001.\u003c/li\u003e\n \u003cli\u003eMcGrath, M. \u0026amp; Lucas, H. (2020). \u0026ldquo;Capacity Building in Health Information Systems: Strengthening Health Systems in Low-Resource Settings.\u0026rdquo; Health Information Science and Systems, 8(1). DOI: 10.1007/s13755-020-00302-x.\u003c/li\u003e\n \u003cli\u003eDe Silva, M. J., et al. (2014). \u0026ldquo;Evaluating the impact of health information systems: Challenges and practical solutions.\u0026rdquo; International Journal of Health Planning and Management, 29(4), 324-335. DOI: 10.1002/hpm.2231.\u003c/li\u003e\n \u003cli\u003eDash, S., Shakyawar, S.K., Sharma, M. et al. Big data in healthcare: management, analysis and future prospects. J Big Data 6, 54 (2019). https://doi.org/10.1186/s40537-019-0217-0.\u003c/li\u003e\n \u003cli\u003eBatko K, Ślęzak A. The use of Big Data Analytics in healthcare. J Big Data. 2022;9(1):3. doi: 10.1186/s40537-021-00553-4. Epub 2022 Jan 6. PMID: 35013701; PMCID: PMC8733917.\u003c/li\u003e\n \u003cli\u003eMamuye AL, Yilma TM, Abdulwahab A, Broomhead S, Zondo P, Kyeng M, Maeda J, Abdulaziz M, Wuhib T, Tilahun BC. Health information exchange policy and standards for digital health systems in africa: A systematic review. PLOS Digit Health. 2022 Oct 10;1(10):e0000118. doi: 10.1371/journal.pdig.0000118. PMID: 36812615; PMCID: PMC9931258.\u003c/li\u003e\n \u003cli\u003eHage E, Roo JP, van Offenbeek MA, Boonstra A. Implementation factors and their effect on e-Health service adoption in rural communities: a systematic literature review. BMC Health Serv Res. 2013 Jan 12;13:19. doi: 10.1186/1472-6963-13-19. PMID: 23311452; PMCID: PMC3575225.\u003c/li\u003e\n \u003cli\u003eMegbowon ET, David OO. Information and communication technology development and health gap nexus in Africa. Front Public Health. 2023 Mar 30;11:1145564. doi: 10.3389/fpubh.2023.1145564. PMID: 37064667; PMCID: PMC10097944.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Rwanda's Regional Centre of Excellence in Biomedical Engineering and e-health (CEBE)","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Children, nutrition, growth monitoring, HMIS, paper registry","lastPublishedDoi":"10.21203/rs.3.rs-5209967/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5209967/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction: \u003c/strong\u003eAccurate and timely nutritional information plays a vital role in monitoring the progress of the Rwandan National Nutrition Program (NNP). However, the absence of a cohesive reporting system to monitor child growth and nutrition poses a challenge. This study focuses on analyzing health workers' utilization of health information management systems (HMIS) to identify areas for enhancement in program implementation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eOur interview guide and group discussion questions were structured around the constructs of the Human, Organization, and Technology–Fit (HOT-Fit) framework. These guided discussions were conducted with health workers supporting the NNP children in primary health facilities across three districts in Rwanda. The subsequent data analysis involved importing the transcripts into NVivo for interpretation within the framework.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Health care providers, including community health workers and nutritionists, rely on paper registers for tracking and reporting nutritional data. Data managers store this information digitally, preferring HMIS for increased efficiency. They find use of digital entry and reporting faster and less cumbersome compared to paper-based systems. Respondents identified challenges with paper-based registration, noting repetitive entries and inconsistencies across registers. Nutrition information within HMIS faces obstacles such as a lack of nutritionists, suboptimal system use, limited internet access, and low digital literacy among staff.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Addressing challenges such as documentation practices and staffing is crucial for enhancing user satisfaction. The integration of routine recording systems can significantly improve data utilization. This study underscores the importance of tailored digital health interventions to enhance the HMIS supporting the National NNP.\u003c/p\u003e","manuscriptTitle":"HMIS Support for Child Nutrition and Growth: Lessons Learned from Rwanda.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-10 13:01:52","doi":"10.21203/rs.3.rs-5209967/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9578d005-3012-479b-a2ed-d17629fbf8ea","owner":[],"postedDate":"October 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":38578959,"name":"Nutrition \u0026 Dietetics"},{"id":38578960,"name":"Information Retrieval and Management"},{"id":38578961,"name":"Medical Informatics"}],"tags":[],"updatedAt":"2024-10-10T13:01:52+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-10 13:01:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5209967","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5209967","identity":"rs-5209967","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}