Utilization of Health Management Information System and its Determinants Among Health Professionals Working at Public Health Facilities in Banadir Region, Somalia. A cross-sectional study

Utilization of Health Management Information System and its Determinants Among Health Professionals Working at Public Health Facilities in Banadir Region, Somalia. A cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Utilization of Health Management Information System and its Determinants Among Health Professionals Working at Public Health Facilities in Banadir Region, Somalia. A cross-sectional study Nor Haji Osman, Abdiweli Mohamed Abdi, Mohamed Abdelrahman Mohamed, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5071178/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 Background Health Information Management System (HMIS) is a system that permits for the gathering, storing, compiling, transmission, analysis, and usage of health data that support decision- makers and stakeholders in managing and planning resources at every level of health service. This study aimed to assess the utilization of health information management system and its determinants amongst healthcare professionals employed at public health facilities in Banadir Region, Somalia. Methods A cross-sectional research was carried out from March to June 2024 at public health care facilities in eight randomly selected districts of Banadir region. A total of 405 public healthcare professionals were chosen by using simple random sampling. The data was analyzed by using the Statistical Package for Social Sciences version 27. Results The present study indicated a good level of health information utilization at 68.1%. In a multivariate logistic regression analysis, the type of facility (AOR = 3.18, 95% CI: 1.169–8.657), attending training on Health Information System (AOR = 0.31, 95% CI: 0.007–0.126), use of standard indicators (AOR = 0.188, 95% CI: 0.047–0.745), utilization of health information for decision-making (AOR = 14.954, 95% CI: 2.886–77.475), and health information analysis (AOR = 0.165, 95% CI: 0.029–0.926) were significantly associated with good health information utilization. Conclusion This study revealed that more than one-third of health care workers had poor health information utilization, therefore, providing health information system training for the staff, strengthening facility support, and empowering the healthcare system's decision-making ability in the Banadir region should be a priority. Information utilization healthcare professionals Banadir Region Somalia Background The Health Management Information System (HMIS) constitutes one of the six building blocks of a health system that integrates data collection, processing, reporting, and use. 1 HMIS is a system that permits for the gathering, storing, compiling, transmission, analysis, and usage of health data that support decision- makers and stakeholders in managing and planning resources at every level of health services. 2 The health information system's main purpose is to generate health-quality information or information that users of the health system can utilize to make reasonable choices. 3 The utilization of data serves as the fundamental aspect within the agenda of the information revolution. 2 A well-designed health information utilization policy can assist policymakers and planners in developing appropriate health regulations that enhance the health outcomes of the population. 4 Health professionals can benefit from using health information that is produced by care delivery institutions. This information can help them to understand the specific situations of their patients and to choose the best course of action. 2 , 4 The enhancement of the efficiency and efficacy of healthcare services is contingent on the establishment of efficient health management information systems across all tiers of the healthcare delivery system. 5 The classification of HMIS is twofold- It falls into the categories of conventional health information system and population-centered health information system. Consequently, regular health information system is one that makes it easier to capture, store, retrieve, and process medical data to optimize health-related decision-making processes. 6 A Health Information System is a system that has been intended to facilitate the gathering and processing of data, data utilization, and report dissemination of health and health-related information to elevate healthcare outcomes. 7 The World Health Organization (WHO) offers a definition of Health Information System as a comprehensive system which assimilates the data collecting, data processing, data reporting, and utilization of essential data to enhance efficiency and effectiveness of healthcare services using optimal managing across entire levels of the healthcare system. 3 Regular health data is essential for the smooth operation of the healthcare system, allowing for strategic planning and informed decision-making to strengthen overall care. 8 Information utilization across all levels of the healthcare system through efficient data interpretation, analysis, and application possesses significant importance. Nevertheless, the predominant concerns lie in the inadequate quality of data (incompleteness and incorrectness) and limited utilization. 3 , 9 Routine health information systems in developing countries are failing to offer the crucial data support required for making informed decisions due to multiple reasons. 10 Insufficient documentation procedures result in to inaccurate, Low quality and insufficient documentation has an impact on patient care continuity and management. 11 The reasons include, the weak information culture, inadequate data analysis, inadequately skilled healthcare professionals, and the excessive workloads associated with HMIS tasks, particularly in the health sector. 12 Although HMIS is acknowledged and accepted as a source of regular health data in SubSaharan African countries, health programs usually do not use it effectively enough to advise decision-makers. 13 District health information system (DHIS) is used in more than sixty nations and the majority of global programs are more focused on using DHIS to track health outcomes. 14 In many developing countries, routine health data is not used effectively by health care providers. They just report the data without getting enough feedback or seeing the benefits of information. This is especially true for healthcare workers and data managers at district and facility levels of the healthcare systems. Studies from Africa show that the level of routine health information utilization is low 7 , 60% in Tanzania 15 , 59% in Uganda 16 and 22% in Kenya. 17 Also, studies conducted in Jimma, southwest Ethiopia 32.9% 18 and Gojjam, northern Ethiopia 45.8%. 19 The usage is not very high.subsequent research conducted in this area revealed that health professionals typically utilize little of the data from the HMIS system and spend 40% or more of their time filling out forms. 20 The percentage of facility reporting in Tanzania Mainland was high, reaching 98% in the period of 2018–2020. The proportion of births that took place in health institutions also increased significantly, from 71.2% in 2016 to 81.7% in 2020, indicating improved access and quality of maternal health services. 21 The existing literature, mostly based on quantitative methods, shows that the data quality and use are low. The factors that affect the data quality in the country's HMIS include individual factors, such as insufficient knowledge, and organizational factors, such as inadequate training. 21 In Kenya Completeness was 61.1%, consistency was 80%. 21 Research shows that using routine health information depends on three main things: the availability of technical factors, how willing and comfortable people are to use it (behavioral factors), and the support provided by the organization. 14 The Department of Policy and Planning in the Ministry of Health of Somalia established a dedicated Health Management Information System (HMIS) Section in 2012. However, the effective functioning of the HMIS Section has been hindered by the challenges of limited resources, particularly in the area of data collection from various health facilities across different regions, districts, and villages within the country. In 2017, DHIS2 became the main health information management system for collecting service utilization and basic epidemiology data in public health facility in Somalia. 14 The successful execution of the HMIS Section's responsibilities and the fulfillment of its mandate to manage the health information system mainly depend on availability of adequate resources. 22 To address these resource limitations, the HMIS Section receives support from the Global Fund through UNICEF. This assistance has a vital role in enhancing the capacity and capabilities of the HMIS Section to overcome the challenges related to data collection. Additionally, the Government of Somalia contributes by providing the necessary funding for the salaries of the central staff involved in the operation of the HMIS Section. 22 This strategy presents an opportunity to address the challenges we have experienced, where HISs in the health sector is fragmented, technical, and financial efforts are misaligned, duplicative and wasteful, and decision-making processes at district, region, state and federal level do not have capacity to exploit available data for strategic insights. We are confident that a systematic and coordinated implementation of this strategy will help foster an environment, infrastructure, people and organizational capabilities required to meet the challenges found in our health sector. 14 The utilization of routine health information is a critical component of effective healthcare management and decision-making within the health system on every stage. In Somalia, public health institutions rely on routine health data to monitor and evaluate the performance of health programs and to inform policy decisions. However, there is limited information on the utilization of health data, and its determinants amongst healthcare workers in public health care facilities in Banadir Region, Somalia. The current study aimed to investigate the utilization of HMIS and its determinants among healthcare employees at public health care facilities in Banadir region Somalia. Methods and Materials Study Design and Area A cross-sectional study design was conducted from March to June 2024 to assess the utilization of health management information and its determinants among health care professionals working at public health facilities in Banadir Region, Somalia. Study Population The study included all health professionals who are employed at public health facilities, with at least six months experience prior to the data collection period. However, health professionals who are on leave or absent, and those who were unwilling to participate for any reason were excluded. Sample Size Determination The determination of sample size was conducted utilizing the single population proportion formula, with the assumption of 50% as P, A 95% level of confidence, with a 5% margin of error, a design effect of 2, and a 10% non-response rate. Based on the above assumptions, the sample size is n = Z 2 x p (1-p) / d 2 + nonresponse rate; (n = 1.96 2 x 0.50 (1–0.50) / 0.05 2 = 384 + non response rate (10%) = 405 Sampling procedure The study employed a stage of simple random sampling procedure. Banadir region consisted of 17 districts, administratively grouped into four geographic divisions considered as clusters. The West part comprising four districts: Dharkenley, Wadajir, Kahda, and Daynile. The East section consisting of four districts: Kaaraan, Heliwaa, Yaaqshid, and Shibis. The Central with five districts: Shangani, Abdiaziz, Hamarweyne, Boondheere, and Wardhiigley, and the Waliyow Cadde part consisting of four districts: Hodan, Howlwadaag, Waabari, and Hamarjajab. Two districts were randomly selected from each part, using simple random sampling, and a total of eight districts (Dayniile, Wadajir, Yaaqshid,, Hamarweyne, Shangani, Hodan, and Hamarjajab, Karan) were included in the study. There was a total of 32 public health facilities (6 hospitals, and 26 health centers) in Banadir region and we considered these public health facilities located within these randomly selected eight districts. As a result, non-equal proportion sampling was used to allocate the participants. We included a total of 6 hospitals and 26 health centers, and we reached out to a total of 405 healthcare professionals who worked permanently in the chosen public health facilities. Data Collection instrument and procedure The study data was gathered using a self-administrated questionnaire that was adopted as of the PRISM conceptual. 7 , 23 , 24 The questionnaire consisted of six main sections. Section 1 asked questions about sociodemographic characteristics (6 questions), section 2 focused on technical characteristics (17 questions), section 3 looked at organizational factors (9 questions), section 4 asked about behavioral characteristics (11 questions), and Section 5 measured the use of health information (13 questions). A standardized questionnaire that had been pretested was used to collect the data. Utilization of health management information of the respondents was evaluated with questions on a 5-point Likert scale, ranging from ‘1 = strongly disagree’ to ‘5 = strongly agree’. The definition of routine health information utilization encompasses various activities such as treating the patients, prioritizing diseases, drug procurement, ensuring data quality, allocating the resources, for planning, for evaluating department performance, evaluating staff performance, selecting the experience among the health facility, sharing health information, making decisions, and the mobilization in the community and discussion. The data gathering tool included the Likert scale for all these components, ranging from "strongly disagree" to "strongly agree." Finally, we used the mean scores of health workers to categorize their routine health information utilization as "good" when their score was higher than the mean value, or "poor" when it was the same as or lower. Healthcare workers were defined as any medical staff who gathered health data with the intention of using it to improve the overall health status. To ensure the correctness and the consistency of the data collection, a total of four data collectors in the districts and a supervisor received a one-day training session for data gathering before the data collection period. After that the study participants of the healthcare professionals were informed about the objectives of the study. Data Analysis The data were cleaned and coded in excel and moved into SPSS version 27 for the data analysis, whereby frequency, percentage, means and standard deviation were used to summarize the results of the dependent and the independent variables. To ascertain whether there is a substantial degree of relationship between the variables and the overall association between the adoption of Health Management Information System and the independent variables, an odds ratio (OR) was employed. To account for confounders, variables with a p-value of less than 0.25 in the bivariate analysis were included in a multivariate logistic regression data analysis. To ascertain which independent variables significantly affect the dependent variable, a binary logistic regression analysis was used. Explanatory variables with a p-value of < 0.05 was deemed to have a significant relationship with the outcome variable, and their adjusted odds ratio, along with their 95% confidence intervals were presented. Results Socio-demographic characteristics of the health care professionals A total of 405 health care professionals working at public health facilities in Banadir Region participated in this study, with a 100% response rate. 186 (45.9%) of the respondents were male, while 219 (54.1%) were female, with the mean ± SD age of the study participants being 29.42 ± 6.10 years. In terms of the level of education, the study revealed that the majority 291 (72.1%) of the study participants had a bachelor's degree. The rest, 65 (16.0%) and 47 (11.6%) were diploma and master’s degree holders, respectively. Most of the participants were 187 (46.2%), 67 (16.5%) were nurses and midwives respectively (see Table 1 for details). Table 1 Socio-demographic characteristics of health care professionals working at public health facilities in Banadir Region, Somalia, 2024 Variables Frequency (n = 405) Percentage (%) Sex Male 186 45.9 Female 219 54.1 Age in years 30 142 35.1 Level of education Diploma 65 16.0 BSc 292 72.1 Master 47 11.6 Profession Medical Doctor 60 14.8 Nursing 187 46.2 Midwife 67 16.5 Nutrition 30 7.4 Lab 30 7.4 Pharmacy 16 4.0 Other 15 3.7 Districts Deynile 52 12.8 Hamarweyne 78 19.3 Hamarjajab 17 4.2 Hodan 15 3.7 Karan 51 12.6 Shingani 17 4.2 Wadajir 155 38.3 Yaqshid 20 4.9 Type of Health Facility Health Center 150 37.0 Hospital 255 63.0 Please insert Table 1 here. Technical characteristics of health care professionals Of the total participants, 304 (75.1%) did not attend training on HMIS for the last 12 months prior to the data collection. The study also revealed that 169 (41.7%) did not set the standard for indicators. Regarding the on-the-job training, the majority (68.1%, 276) received on job training on the ground, while 31.9% (129) did not. In terms of HMIS utilization orientation, 62.7% (254) received orientation, while 37.3% (151) did not (see Table 2 for details). Table 2 Technical characteristics of health care professionals working at public health facilities in Banadir Region-Somalia, 2024 Variables Frequency (n = 405) Percentage (%) Did you attend training on HMIS in the last 12 Months? Yes 101 24.9 No 304 75.1 On job training program Yes 276 68.1 No 129 31.9 Orientation on Utilization of HMIS Yes 254 62.7 No 151 37.3 HMIS tools recording for daily activities Yes 333 82.2 No 72 17.8 Electronic devices in routine health information utilization Yes 215 53.1 No 190 46.9 Understand set of indicators Yes 279 68.9 No 126 31.1 Standardized set of indicators Yes 236 58.3 No 169 41.7 Displayed health indicator targets Yes 184 45 No 221 55 Discussed the monthly performance progress using the standard indicators Yes 281 69.4 No 124 30.6 Correctly and completely filled by the health professionals Yes 342 84.4 No 63 15.6 Changed the collected data into information Yes 304 75.1 No 101 24.9 Reported the collected data in the last three months Yes 343 84.7 No 62 15.3 Please insert Table 2 here. The types of HMIS training received in the last 12 months The type of HMIS (Health Management Information System) training that the 405 healthcare workers in Banadir Region have received over the last 12 months. 46 healthcare workers (11.4%) received training in health information collection, while 359 (88.6%) did not receive any training. 25 (6.2%) received training in health information analysis, while 380 (93.8%) did not receive any training. 22 (5.4%) received training in health information presentation, while 383 (94.6%) did not receive any training. Finally, only 9 (2.2%) received training in health information use, while 396 (97.8%) received no training. Organizational characteristics of the health care professionals Most respondents, 333 (82.2%), reported using routine health information for decision-making, while 72 individuals (17.8%) indicated they did not use routine health information for decision-making. In terms of staff awareness of their responsibilities, a significant proportion of participants, 352 (86.9%), reported being aware of their responsibilities, while 53 (13.1%) stated that they were not aware. 189 (46.7%) reported the presence of awards in the health facility as a motivation for good work, while 216 (53.3%) indicated the absence of such awards. The study also indicated whether the facility has a data quality check system. Most respondents, 330 (81.5%), reported that their facility has a data quality check system, while 75 (18.5%) reported the absence of such a system. Please insert Table 3 here. Table 3 Organizational characteristics of health care professionals working at public health facilities in Banadir Region, Somalia, 2024 Variables Frequency (n = 405) Percentage (%) Routine health information for decision-making Yes 333 82.2 No 72 17.8 Staff are aware of responsibilities Yes 352 86.9 No 53 13.1 Award in the health facility as a motivation for good work Yes 189 46.7 No 216 53.3 Accountability for poor performance Yes 291 71.9 No 114 28.1 Are there factors influencing the information use? Yes 291 71.9 No 114 28.1 Facility has a data quality check system Yes 330 81.5 No 75 18.5 Regular monitoring and evaluation supervision for the health information system Yes 328 81.0 No 77 19.0 What interval do you receive feedback? For every report 369 91.1 Quarterly 33 8.1 Annual 3 .7 Routine health information utilization of the health care professionals The current study found that most of the respondents (77.5%) utilized routine health information for patient treatment, 76.5% used for prioritizing diseases, 70.4% as drug procurement, 75.1% in monitoring daily activities related to health services, 76.8% for verification of data quality, 68.9% for allocation of resources, 77.5% for planning, 77.3% for the assessment of departmental performance, 81.5% for the assessment of employee performance, 77% for selecting the experience in the facility, 76.8% for sharing health information, 76.3% for making decisions, and 78.8% for discussions and mobilizations among the community. Please insert Table 4 here. Table 4 Routine health information utilization characteristics of health care professionals working at public health facilities in Banadir Region, Somalia, 2024 Activities employed for the utilization of the routine health information (n= %405) Yes No Information for treating patients 314(77.5%) 91(22.5%) Information for disease prioritization 310(76.5%) 95(23.5%) Information for drug procurement 285(70.4%) 120(29.6%) For monitoring day to day health service activities 304(75.1%) 101(24.9%) Information use for data quality 311(76.8%) 94(23.2%) For resource allocation 279(68.9%) 126(31.1%) For departments performance evaluation 313(77.3%) 92(22.7%) For planning 311(77.5%) 94(23.2%) For monitoring the performance of staff 330(81.5%) 75(18.5%) For selecting good experience within the facility 312(77.0%) 93(23.0%) For sharing of best experience for health facilities and stakeholders 311(76.8%) 94(23.2%) For decision making 309(76.3%) 96(23.7%) Information use for community mobilization and discussion 319(78.8%) 86(21.2%) Behavioral characteristics of the health care professionals Most healthcare providers (56.5%) didn’t demand health information. 29.9% of healthcare providers exhibited a poor attitude towards data collection. Only 22.2% considered the routine health information system to be useless. 15.6% feel that collecting information adds no value to their activities. Eighty-one percent (81.2%) hold the opinion that the data they gather lacks customization for patient treatment. According to 30.9% of respondents, routine health information is useful for monitoring facility performance. 47.9% of health facility staff properly documented their activities and kept records. 61.2% do not feel committed to using routine health information outputs to improve the target community's health status. 46.4% of respondents understand and appreciate their roles and responsibilities in managing routine health information. 51.4% do not frequently use routine health information, and data collection benefits both patients and health facilities. 62.7% of respondents do not believe that decisions based on evidence improve service delivery quality. Please insert Table 5 here. Table 5 Behavioral characteristics of health care professionals working at public health facilities in Banadir Region-Somalia, 2024 Items (n= %405) Yes No Healthcare providers demand information 176(43.5%) 229(56.5%) Health professionals have a poor attitude toward data collection 121(29.9%) 284(70.1%) The routine health information system is useless 90(22.2%) 315(77.8%) Collecting information adds no value for my activity 63(15.6%) 342(84.4%) The collected data is not customized to patients' treatment 76(18.8%) 329(81.2%) Routine health information is useful for monitoring facility performance 125(30.9%) 280(69.1%) Health facilities’ staff document their activities and keep records 194(47.9%) 211(52.1%) Routine health information outputs give feel committed in improving health status of the target community 157(38.8%) 248(61.2%) Understand and appreciate my role and responsibilities regarding to managed routine health information 188(46.4%) 217(53.6%) Frequent use of routine health information and data collection had benefit of patients as well as health facilities 197(48.6%) 208(51.4%) Decisions based on evidence improve services delivery 151(37.3%) 254(62.7%) Factors influencing Health Management Information Utilization of the health care professionals The bivariable logistic regression data analysis revealed that variables such as sex, education, profession, type of health facility, ever-trained status, information collection, analysis, presentation, on-the-job training, orientation, HMIS tool recording, standard indicator, supervision, staff responsibilities, accountability, demand information, and customization were associated with good routine health information utilization. The above variables were further used to a multivariate logistic regression data analysis, finding that the type of facility, standard indicators, ever-trained HMIS, information collection, information for decision-making, awareness of staff responsibilities, information output, and appropriate roles and responsibilities were significantly associated with the utilization routine health data at a p-value of < 0.05. The study found that health centers were significantly more likely to utilize health management information than hospitals (AOR = 3.181, 95% CI: 1.169 to 8.657, p = 0.024). Not attending training on the Health data within the last 12 months was associated with a significantly lower utilization rate (AOR = 0.31, 95% CI: 0.007 to 0.126, p < 0.001), suggesting a potential negative impact of recent training on utilization. Similarly, the absence of health information analysis training significantly reduced utilization (AOR = 0.165, 95% CI: 0.029 to 0.926, p = 0.041). On the other hand, using electronic devices (AOR = 4.192, 95% CI: 1.422 to 12.359, p = 0.009) and employing a standardized set of indicators (AOR = 0.188, 95% CI: 0.047 to 0.745, p = 0.017) were both significantly associated with increased utilization. Moreover, using regular data for decision-making had a significant positive impact (AOR = 14.954, 95% CI: 2.886 to 77.475, p = 0.001), emphasizing the importance of incorporating health data into decision-making processes. Attitude, output, and role were also influential factors, with good attitude (AOR = 0.095, 95% CI: 0.013 to 0.706, p = 0.021), good output (AOR = 0.025, 95% CI: 0.002 to 0.407, p = 0.009), and good role (AOR = 0.012, 95% CI: 0.01 to 0.230, p = 0.003) being significantly linked with increased utilization. These findings highlight the importance of training, technology adoption, standardized indicators, and positive attitudes and behaviors in promoting effective health management information utilization. (Table 7). Please insert Table 6 here. Table 6 Factors associated with routine health information utilization among health care professionals at public health facilities in Banadir Region, Somalia, 2024 Variables Health management information utilization COR (95% CI) AOR (95% CI) p-value Poor Good Type of the health facility Health Center 42 (28%) 109 (72%) 0.751 (0.483 to 1.167) 3.181 (1.169 to 8.657) 0.024 Hospital 87 (34.1%) 168 (65.9%) 1 1 1 Did you attend any training on Health Information System in the last 12 month? No 58 (19.1%) 246(80.9%) 1 1 1 Yes 71 (70.3%) 30 (29.7%) 10.08 (6.005 to 16.780) 0.31 (0.007 to 0.126) < 0.001 Health information analysis Trained 14(56%) 11(44%) 1 1 1 Un-Trained 115(30.3%) 265(69.7%) 0.341(0.150 to 0.774) 0.165(0.029 to 0.926) 0.041 Do you use electronic device in routine health information utilization? No 88 (46.3%)1 102 (53.7%) 1 1 1 Yes 41 (19.1%) 174 (80.9%) 0.273 (0.175 to 0.426) 4.192 (1.422 to 12.359) 0.009 Standardized set of indicators No 65(38.5%) 104(61.5%) 1 Yes 64(27.1%) 172(72.9%) 0.595(0.390 to 0.908) 0.188 (0.047 to 0.745) 0.017 Routine health information for decision-making No 42(58.3%) 30(41.7%) 1 1 1 Yes 87(26.1%) 246(73.9%) 0.253(0.149 to 0.429) 14.954 (2.886 to 77.475) 0.001 Health professionals have a poor attitude toward data collection Poor 111(39.1%) 173 (60.9%) 1 1 1 Good 18 (14.9%) 103 (85.1%) 3.671 (2.109 to 6.393) 0.095 (0.013 to 0.706) 0.021 Routine health information outputs give feel committed Poor 101(40.7%) 147 (59.3%) 1 1 1 Good 28 (17.8%) 129(82.2%) 3.165 (1.957 to 5.120) 0.025 (0.002 to 0.407) 0.009 Understand and appreciate the role and responsibilities Poor 105(48.4%) 112(51.6%) 1 1 1 Good 24(12.8%) 164(87.2%) 6.406(3.869 to 10.608) 0.012 (0.01 to 0.230) 0.003 Discussion The objective of this study was to examine the utilization of the Health Management Information System and its influencing factors among healthcare workers employed in public health facilities in Banadir Region, Somalia, employing tools from the PRISM framework. The outcomes of the current study suggested that the level of health management information utilization was good in (68.1%). This finding is consistent with studies conducted in Malawi 25 with 68.8% and Ethiopia with 65.8% and 69.3%, respectively. 24 , 26 However, the present finding is lower than other research in Ghana 77% 27 and Ethiopia 78.5%. 7 This finding is higher than other studies carried out in Tanzania 60 15 , Kenya 48.1% 28 and Uganda 59%. 29 Study area, sample size, the emphasis on HMIS training to build staff capacity on health information usage, countries' health information system (HIS) structures, and healthcare workers' motivation to use the HMIS may explain variations between different study findings. Health center participants used the health management system three times better than hospital participants.Similar results were seen in Ethiopian research. 7 , 19 The reason could be that governments may pay less attention to hospitals compared to health centers. 30 Not attending health information systems training within the previous 12 months was strongly negatively associated with good utilization. Similar findings were reported elsewhere. 23 This underscores the significance of HMIS-specific training in enhancing the information utilization skills of healthcare workers. A statistically significant association was observed between HMIS (Health Management Information System) utilization and predictors, including supervision and standard indicators. Another study reported similar results. 7 Supervision and setting standard indicators might enhance employee performance and motivation. This is the first study of its kind in Somalia, providing valuable baseline data for future research and public health data initiatives. However, it's essential to highlight that the study was limited to public health facilities in Banadir region, so the findings may not be representative of the entire country. Conclusion The findings of this study indicate that more than one-third of healthcare practitioners in public health care facilities poorly utilize routine health information systems. The findings indicates that the use of health information falls short of the national Health Management Information System (HMIS) expectations. The study identified several key factors that significantly impact the health information system's utilization rate. These factors include a lack of training on the HMIS system, inadequate use of electronic devices for routine health data collection. Staff responsibilities and the role for health information utilization remain unclear, data quality checks and facility supervision are inadequate, and the demand for health information within the facilities is limited. Therefore, providing of health information system training for all staff in the facility, strengthening facility encourage and empower healthcare providers' ability to make decisions in Banadir region public health care facilities should be essential. The study is highly recommended regularly monitoring and ensuring the availability of the above factors in health facilities. The finding also recommended conducting further research into the culture and attitudes of healthcare workers towards routine data generation. Declarations Ethics consideration This study involved human participants, and the researchers obtained ethical clearance from the ethical review board of the Somali National Institute of Health (NIH/IRB/07/MAR/2024). Additionally, the researchers obtained a supporting letter from the Jamhuriya University for Science and Technology. Informed consent was obtained from each study participant after they were informed of the study's objectives and potential benefits. To maintain the confidentiality of the information provided by the study subjects, the data collection procedure was conducted anonymously. Declaration of conflicting interests The authors have no competing interests to disclose Consent for publication: All authors of the manuscript have read and agreed to its content and are accountable for all aspects of the accuracy and integrity of the manuscript in accordance with ICMJE (International Committee of Medical Journal Editors) criteria Funding: None Author Contribution Nor, Abdiweli, Mohamed, and Dr. Fidow made significant contributions to the following aspects of the study: the conception, training of the data collectors, design, data collection, supervision, data analysis, interpretation, and write-up of the manuscript. They have contributed to the existing literature review, developing the research matrix, revising the manuscript, preparing regression tables, and analyzing and interpreting the data as well. Finally, all authors reviewed and approved the final manuscript. Acknowledgement The authors would like to extend their heartfelt thanks to the following for their participation and support in this study: The Regional Medical Officer, Banadir Regional Administration (BRA), The District Health Officers, The facility in-charges, The health professionals, The data collectors, and The supervisors. Data Availability The data sets generated during the current study are available from the corresponding author on reasonable request. References Qian J, Shiferaw S, Seme A, Esmale OE, Denboba W, Stierman E, et al. Data for local decision-making, not a mere reporting requirement: development of an index to measure facility-level use of HMIS data. J Glob Heal Rep. 2023;7:1–12. Ngusie HS, Ahmed MH, Kasaye MD, Kanfe SG. Utilisation of health management information and its determinant factors among health professionals working at public health facilities in North Wollo Zone, Northeast Ethiopia: a cross-sectional study. BMJ Open. 2022;12(4):1–10. Sako S, Gilano G, Chisha Y, Shewangizaw M, Fikadu T. Routine Health Information Utilization and Associated Factors among Health Professionals Working in Public Health Facilities of the South Region, Ethiopia. Ethiop J Health Sci. 2022;32(2):433–44. Yehula CM, Walle AD, Tegegne MD, Endehabtu BF, Wubante SM, Melaku MS, et al. Health information utilization and its associated factors among health professionals in northwest Ethiopia: A crossectional study. Inf Med Unlocked. 2023;40(June):4–9. Gobena T, Shore H, Berhanie D, Kenay A, Wondirad Y, Ayanle M. Routine Health Information System Data Quality and Associated Factors in Selected Public Health Facilities of Jigjiga Woreda, Somali Regional State’s, Eastern Ethiopia. Ethiop J Heal Dev. 2022;36(Special Issue 1). Farah A. Health Management Information System Data Use Practice and Its Determinants at Health Centers and Woreda Health Office in Fafan Zone, Somali Region,. 2022. Dagnew E, Woreta SA, Shiferaw AM. Routine health information utilization and associated factors among health care professionals working at public health institution in North Gondar, Northwest Ethiopia. BMC Health Serv Res. 2018;18(1):1–8. Mekuria S, Adem HA, Ayele BH, Musa I, Berhanie D. Utilization of routine health information system and associated factors among health professionals in public health facilities in dire dawa, eastern ethiopia: a cross-sectional study. Res Sq. 2021;1–19. Chanyalew MA, Yitayal M, Atnafu A, Tilahun B. Routine health information system utilization for evidence-based decision making in Amhara national regional state, northwest Ethiopia: a multi-level analysis. BMC Med Inform Decis Mak [Internet]. 2021;21(1):1–10. https://doi.org/10.1186/s12911-021-01400-5 Nguyen TN, Nielsen P. The dynamics of information system development in developing countries: From mutual exclusion to hybrid vigor. Electron J Inf Syst Dev Ctries. 2023;(February):1–21. Demsash AW, Kassie SY, Dubale AT, Chereka AA, Ngusie HS, Hunde MK, et al. Health professionals’ routine practice documentation and its associated factors in a resource-limited setting: A cross-sectional study. BMJ Heal Care Inf. 2023;30(1):1–7. Pam A, Aggrey C, Odongo AO, Kerochi A. Factors Influencing Utilization of Routine Health Information For Decision Making Among Health Workers: A Case Study of Health Facilities in Moyo District, Uganda. 2022;1–15. Donaldson M, CUNY Academic Works Improving National Health Management Information Systems. Stakeholder Views in Selected Sub-Saharan African Countries How does access to this work benefit you ? Let us know ! : 2021. Kanfe SG, Debele GR, Berhanu RD, Ngusie HS, Ahmed MH. Utilisation of district health information system and its associated factors among health professionals working at public health facilities of the southwest of Ethiopia: Cross-sectional survey. BMJ Open. 2021;11(8):1–7. Mboera LEG, Rumisha SF, Mbata D, Mremi IR, Lyimo EP, Joachim C. Data utilisation and factors influencing the performance of the health management information system in Tanzania. BMC Health Serv Res. 2021;21(1):4–11. Bagyendera M, Nabende P, Nabukenya J. Critical factors influencing data use and utilization in health systems: a focus on data and interoperability standards for health information exchange (HIE) in Uganda’s health care system. Oxf Open Digit Heal. 2023;1:1–8. S1386505605000560. Abajebel S, Jira C, Beyene W. Utilization of health information system at district level in jimma zone oromia regional state, South west ethiopia. Ethiop J Health Sci. 2011;21(Suppl 1):65–76. Shiferaw AM, Zegeye DT, Assefa S, Yenit MK. Routine health information system utilization and factors associated thereof among health workers at government health institutions in East Gojjam Zone, Northwest Ethiopia. BMC Med Inf Decis Mak. 2017;17(1):1–9. Wude H, Woldie M, Melese D, Lolaso T, Balcha B. Utilization of routine health information and associated factors among health workers in Hadiya Zone, Southern Ethiopia. PLoS One [Internet]. 2020;15(5):1–11. http://dx.doi.org/10.1371/journal.pone.0233092 Mary K, Otieno G, Mawenzi R. Utilization of routine health data in decision-making by management teams in selected level 4 hospitals in Nakuru County, Kenya. Int Acad J Heal. 2023;2(1):314–40. Government F. Federal Government of Somalia Ministry of Health and Human Services. 2022;(March 2018). Yehula CM, Walle AD, Tegegne MD, Endehabtu BF, Wubante SM, Melaku MS, et al. Health information utilization and its associated factors among health professionals in northwest Ethiopia: A crossectional study. Inf Med Unlocked. 2023;40(January):4–9. Negera D, Zewdie A, Kera AM, Degefa GH. Health information use and associated factors among healthcare professionals in Ilu Aba Bor zone, Oromia region, Ethiopia: An institution-based cross-sectional study. BMJ Open. 2023;13(3):1–8. Msiska KEM, Kumitawa A, Kumwenda B. Factors affecting the utilisation of electronic medical records system in Malawian central hospitals. Malawi Med J. 2017;29(3):247–53. Abera E, Daniel K, Letta T, Tsegaw D. Utilization of Health Management Information System and Associated Factors in Hadiya Zone Health Centers, Southern Ethiopia. Res Heal Sci. 2016;1(2):98. Boadu RO, Obiri-Yeboah J, Okyere Boadu KA, Kumasenu Mensah N, Amoh-Agyei G. Assessment of RHIS Quality Assurance Practices in Tarkwa Submunicipal Health Directorate, Ghana. Adv Public Heal. 2021;2021. Obwocha W, Ayodo G, Nyangura A, Thomas O. Utilization of Healthcare Information Among Healthcare Workers in Gucha Subcounty, Kisii County, Kenya. J Heal Educ Res Dev. 2016;04(04). Hotchkiss DR, Aqil A, Lippeveld T, Mukooyo E. Evaluation of the Performance of Routine Information System Management (PRISM) framework: Evidence from Uganda. BMC Health Serv Res. 2010;10. Ayele G, Abera A, Ayele A, Gudina D, Firdisa D. Utilization of routine health data and its determinants among healthcare workers in public health facilities of harari region, eastern Ethiopia. BMC Health Serv Res. 2024;24(1):1–7. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5071178","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":381042712,"identity":"de8f20de-af8b-48bf-8691-d9d4900185cc","order_by":0,"name":"Nor Haji Osman","email":"","orcid":"","institution":"Postgraduate of applied statistics and research, Jamhuriya University, Mogadishu Somalia","correspondingAuthor":false,"prefix":"","firstName":"Nor","middleName":"Haji","lastName":"Osman","suffix":""},{"id":381042713,"identity":"5f48aad8-e645-4cef-9320-c9bfe42f1b32","order_by":1,"name":"Abdiweli Mohamed Abdi","email":"","orcid":"","institution":"Center for Postgraduate Studies, Horseed International University, Mogadishu, Somalia","correspondingAuthor":false,"prefix":"","firstName":"Abdiweli","middleName":"Mohamed","lastName":"Abdi","suffix":""},{"id":381042714,"identity":"2d2c7390-47ad-4557-bf44-46459eda8b92","order_by":2,"name":"Mohamed Abdelrahman Mohamed","email":"","orcid":"","institution":"Department of public health research, National Institute of Health, Mogadishu, Somalia","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"Abdelrahman","lastName":"Mohamed","suffix":""},{"id":381042715,"identity":"f7811067-7699-4dcf-96db-018e9fbc0f72","order_by":3,"name":"Nur Ahmed","email":"","orcid":"","institution":"Advanced Medical Research Center, Jamhuriya University, Mogadishu Somalia","correspondingAuthor":false,"prefix":"","firstName":"Nur","middleName":"","lastName":"Ahmed","suffix":""},{"id":381042716,"identity":"ce30d406-7bf8-496f-a11e-ca811f002750","order_by":4,"name":"Osman Abubakar Fiidow","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYNACGwkehgMMjA+ATB4+4rSkgbUwG4C0sBGpBYgPMLBJgNgEtRicP534uSDBQobveI9Z5dccOxk2BuaHj27g03Ijd7P0jAQJHskzZ8xuy25LBjqMzdg4B68W3g3SvD8keIB6t92W3MYM1MLDJo1Xy/mzm3/zJEC0FEtuqydCy4HcbdIwLYwftx0mrEUSqNKaB+yX85+lGbcd52FjJuAXPqDDbvMk1NnzHW9L/PhzW7U9P3vzw8f4tKAAZh4wSaxyEGD8QYrqUTAKRsEoGDEAAJT6RWrY4A19AAAAAElFTkSuQmCC","orcid":"","institution":"Faculty of Health Science, Salaam University, Mogadishu, Somalia","correspondingAuthor":true,"prefix":"","firstName":"Osman","middleName":"Abubakar","lastName":"Fiidow","suffix":""}],"badges":[],"createdAt":"2024-09-11 12:39:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5071178/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5071178/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79419553,"identity":"52ac40bf-1914-487f-a62a-be14f933c08d","added_by":"auto","created_at":"2025-03-28 08:02:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1326474,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5071178/v1/6965aad3-5a70-4da8-b579-e62ce9328c80.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Utilization of Health Management Information System and its Determinants Among Health Professionals Working at Public Health Facilities in Banadir Region, Somalia. A cross-sectional study","fulltext":[{"header":"Background","content":"\u003cp\u003eThe Health Management Information System (HMIS) constitutes one of the six building blocks of a health system that integrates data collection, processing, reporting, and use.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e HMIS is a system that permits for the gathering, storing, compiling, transmission, analysis, and usage of health data that support decision- makers and stakeholders in managing and planning resources at every level of health services.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e The health information system's main purpose is to generate health-quality information or information that users of the health system can utilize to make reasonable choices.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e The utilization of data serves as the fundamental aspect within the agenda of the information revolution.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e A well-designed health information utilization policy can assist policymakers and planners in developing appropriate health regulations that enhance the health outcomes of the population.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Health professionals can benefit from using health information that is produced by care delivery institutions. This information can help them to understand the specific situations of their patients and to choose the best course of action.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e The enhancement of the efficiency and efficacy of healthcare services is contingent on the establishment of efficient health management information systems across all tiers of the healthcare delivery system.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e The classification of HMIS is twofold- It falls into the categories of conventional health information system and population-centered health information system. Consequently, regular health information system is one that makes it easier to capture, store, retrieve, and process medical data to optimize health-related decision-making processes.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e A Health Information System is a system that has been intended to facilitate the gathering and processing of data, data utilization, and report dissemination of health and health-related information to elevate healthcare outcomes.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e The World Health Organization (WHO) offers a definition of Health Information System as a comprehensive system which assimilates the data collecting, data processing, data reporting, and utilization of essential data to enhance efficiency and effectiveness of healthcare services using optimal managing across entire levels of the healthcare system.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Regular health data is essential for the smooth operation of the healthcare system, allowing for strategic planning and informed decision-making to strengthen overall care.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eInformation utilization across all levels of the healthcare system through efficient data interpretation, analysis, and application possesses significant importance. Nevertheless, the predominant concerns lie in the inadequate quality of data (incompleteness and incorrectness) and limited utilization.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Routine health information systems in developing countries are failing to offer the crucial data support required for making informed decisions due to multiple reasons.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eInsufficient documentation procedures result in to inaccurate, Low quality and insufficient documentation has an impact on patient care continuity and management.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe reasons include, the weak information culture, inadequate data analysis, inadequately skilled healthcare professionals, and the excessive workloads associated with HMIS tasks, particularly in the health sector.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAlthough HMIS is acknowledged and accepted as a source of regular health data in SubSaharan African countries, health programs usually do not use it effectively enough to advise decision-makers.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e District health information system (DHIS) is used in more than sixty nations and the majority of global programs are more focused on using DHIS to track health outcomes.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e In many developing countries, routine health data is not used effectively by health care providers. They just report the data without getting enough feedback or seeing the benefits of information. This is especially true for healthcare workers and data managers at district and facility levels of the healthcare systems. Studies from Africa show that the level of routine health information utilization is low\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, 60% in Tanzania\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, 59% in Uganda\u003csup\u003e16\u003c/sup\u003e and 22% in Kenya.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Also, studies conducted in Jimma, southwest Ethiopia 32.9%\u003csup\u003e18\u003c/sup\u003e and Gojjam, northern Ethiopia 45.8%.\u003csup\u003e19\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe usage is not very high.subsequent research conducted in this area revealed that health professionals typically utilize little of the data from the HMIS system and spend 40% or more of their time filling out forms.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e The percentage of facility reporting in Tanzania Mainland was high, reaching 98% in the period of 2018\u0026ndash;2020. The proportion of births that took place in health institutions also increased significantly, from 71.2% in 2016 to 81.7% in 2020, indicating improved access and quality of maternal health services.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e The existing literature, mostly based on quantitative methods, shows that the data quality and use are low. The factors that affect the data quality in the country's HMIS include individual factors, such as insufficient knowledge, and organizational factors, such as inadequate training.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e In Kenya Completeness was 61.1%, consistency was 80%.\u003csup\u003e21\u003c/sup\u003e Research shows that using routine health information depends on three main things: the availability of technical factors, how willing and comfortable people are to use it (behavioral factors), and the support provided by the organization.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e The Department of Policy and Planning in the Ministry of Health of Somalia established a dedicated Health Management Information System (HMIS) Section in 2012. However, the effective functioning of the HMIS Section has been hindered by the challenges of limited resources, particularly in the area of data collection from various health facilities across different regions, districts, and villages within the country. In 2017, DHIS2 became the main health information management system for collecting service utilization and basic epidemiology data in public health facility in Somalia.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e The successful execution of the HMIS Section's responsibilities and the fulfillment of its mandate to manage the health information system mainly depend on availability of adequate resources.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e To address these resource limitations, the HMIS Section receives support from the Global Fund through UNICEF. This assistance has a vital role in enhancing the capacity and capabilities of the HMIS Section to overcome the challenges related to data collection. Additionally, the Government of Somalia contributes by providing the necessary funding for the salaries of the central staff involved in the operation of the HMIS Section.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e This strategy presents an opportunity to address the challenges we have experienced, where HISs in the health sector is fragmented, technical, and financial efforts are misaligned, duplicative and wasteful, and decision-making processes at district, region, state and federal level do not have capacity to exploit available data for strategic insights. We are confident that a systematic and coordinated implementation of this strategy will help foster an environment, infrastructure, people and organizational capabilities required to meet the challenges found in our health sector.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e The utilization of routine health information is a critical component of effective healthcare management and decision-making within the health system on every stage. In Somalia, public health institutions rely on routine health data to monitor and evaluate the performance of health programs and to inform policy decisions. However, there is limited information on the utilization of health data, and its determinants amongst healthcare workers in public health care facilities in Banadir Region, Somalia. The current study aimed to investigate the utilization of HMIS and its determinants among healthcare employees at public health care facilities in Banadir region Somalia.\u003c/p\u003e"},{"header":"Methods and Materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Area\u003c/h2\u003e \u003cp\u003e A cross-sectional study design was conducted from March to June 2024 to assess the utilization of health management information and its determinants among health care professionals working at public health facilities in Banadir Region, Somalia.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Population\u003c/h3\u003e\n\u003cp\u003eThe study included all health professionals who are employed at public health facilities, with at least six months experience prior to the data collection period. However, health professionals who are on leave or absent, and those who were unwilling to participate for any reason were excluded.\u003c/p\u003e\n\u003ch3\u003eSample Size Determination\u003c/h3\u003e\n\u003cp\u003eThe determination of sample size was conducted utilizing the single population proportion formula, with the assumption of 50% as P, A 95% level of confidence, with a 5% margin of error, a design effect of 2, and a 10% non-response rate. Based on the above assumptions, the sample size is n\u0026thinsp;=\u0026thinsp;Z\u003csup\u003e2\u003c/sup\u003e x p (1-p) / d\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;+\u0026thinsp;nonresponse rate; \u003cb\u003e(n\u0026thinsp;=\u003c/b\u003e\u0026thinsp;1.96\u003csup\u003e2\u003c/sup\u003e x 0.50 (1\u0026ndash;0.50) / 0.05\u003csup\u003e2\u003c/sup\u003e = 384\u0026thinsp;+\u0026thinsp;non response rate (10%)\u0026thinsp;=\u0026thinsp;405\u003c/p\u003e\n\u003ch3\u003eSampling procedure\u003c/h3\u003e\n\u003cp\u003eThe study employed a stage of simple random sampling procedure. Banadir region consisted of 17 districts, administratively grouped into four geographic divisions considered as clusters. The West part comprising four districts: Dharkenley, Wadajir, Kahda, and Daynile. The East section consisting of four districts: Kaaraan, Heliwaa, Yaaqshid, and Shibis. The Central with five districts: Shangani, Abdiaziz, Hamarweyne, Boondheere, and Wardhiigley, and the Waliyow Cadde part consisting of four districts: Hodan, Howlwadaag, Waabari, and Hamarjajab. Two districts were randomly selected from each part, using simple random sampling, and a total of eight districts (Dayniile, Wadajir, Yaaqshid,, Hamarweyne, Shangani, Hodan, and Hamarjajab, Karan) were included in the study.\u003c/p\u003e \u003cp\u003eThere was a total of 32 public health facilities (6 hospitals, and 26 health centers) in Banadir region and we considered these public health facilities located within these randomly selected eight districts. As a result, non-equal proportion sampling was used to allocate the participants. We included a total of 6 hospitals and 26 health centers, and we reached out to a total of 405 healthcare professionals who worked permanently in the chosen public health facilities.\u003c/p\u003e\n\u003ch3\u003eData Collection instrument and procedure\u003c/h3\u003e\n\u003cp\u003eThe study data was gathered using a self-administrated questionnaire that was adopted as of the PRISM conceptual.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e The questionnaire consisted of six main sections. Section 1 asked questions about sociodemographic characteristics (6 questions), section 2 focused on technical characteristics (17 questions), section 3 looked at organizational factors (9 questions), section 4 asked about behavioral characteristics (11 questions), and Section 5 measured the use of health information (13 questions).\u003c/p\u003e \u003cp\u003eA standardized questionnaire that had been pretested was used to collect the data. Utilization of health management information of the respondents was evaluated with questions on a 5-point Likert scale, ranging from \u0026lsquo;1\u0026thinsp;=\u0026thinsp;strongly disagree\u0026rsquo; to \u0026lsquo;5\u0026thinsp;=\u0026thinsp;strongly agree\u0026rsquo;. The definition of routine health information utilization encompasses various activities such as treating the patients, prioritizing diseases, drug procurement, ensuring data quality, allocating the resources, for planning, for evaluating department performance, evaluating staff performance, selecting the experience among the health facility, sharing health information, making decisions, and the mobilization in the community and discussion. The data gathering tool included the Likert scale for all these components, ranging from \"strongly disagree\" to \"strongly agree.\" Finally, we used the mean scores of health workers to categorize their routine health information utilization as \"good\" when their score was higher than the mean value, or \"poor\" when it was the same as or lower. Healthcare workers were defined as any medical staff who gathered health data with the intention of using it to improve the overall health status. To ensure the correctness and the consistency of the data collection, a total of four data collectors in the districts and a supervisor received a one-day training session for data gathering before the data collection period. After that the study participants of the healthcare professionals were informed about the objectives of the study.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eThe data were cleaned and coded in excel and moved into SPSS version 27 for the data analysis, whereby frequency, percentage, means and standard deviation were used to summarize the results of the dependent and the independent variables. To ascertain whether there is a substantial degree of relationship between the variables and the overall association between the adoption of Health Management Information System and the independent variables, an odds ratio (OR) was employed. To account for confounders, variables with a p-value of less than 0.25 in the bivariate analysis were included in a multivariate logistic regression data analysis. To ascertain which independent variables significantly affect the dependent variable, a binary logistic regression analysis was used. Explanatory variables with a p-value of \u0026lt;\u0026thinsp;0.05 was deemed to have a significant relationship with the outcome variable, and their adjusted odds ratio, along with their 95% confidence intervals were presented.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic characteristics of the health care professionals\u003c/h2\u003e \u003cp\u003eA total of 405 health care professionals working at public health facilities in Banadir Region participated in this study, with a 100% response rate. 186 (45.9%) of the respondents were male, while 219 (54.1%) were female, with the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD age of the study participants being 29.42\u0026thinsp;\u0026plusmn;\u0026thinsp;6.10 years. In terms of the level of education, the study revealed that the majority 291 (72.1%) of the study participants had a bachelor's degree. The rest, 65 (16.0%) and 47 (11.6%) were diploma and master\u0026rsquo;s degree holders, respectively. Most of the participants were 187 (46.2%), 67 (16.5%) were nurses and midwives respectively (see Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for details).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of health care professionals working at public health facilities in Banadir Region, Somalia, 2024\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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (n\u0026thinsp;=\u0026thinsp;405)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge in years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;=30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBSc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaster\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProfession\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical Doctor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNursing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMidwife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePharmacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDistricts\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeynile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHamarweyne\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHamarjajab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHodan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKaran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShingani\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWadajir\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYaqshid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of Health Facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.0\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\u003e \u003cb\u003ePlease insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003ehere.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTechnical characteristics of health care professionals\u003c/h2\u003e \u003cp\u003eOf the total participants, 304 (75.1%) did not attend training on HMIS for the last 12 months prior to the data collection. The study also revealed that 169 (41.7%) did not set the standard for indicators. Regarding the on-the-job training, the majority (68.1%, 276) received on job training on the ground, while 31.9% (129) did not. In terms of HMIS utilization orientation, 62.7% (254) received orientation, while 37.3% (151) did not (see Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e for details).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTechnical characteristics of health care professionals working at public health facilities in Banadir Region-Somalia, 2024\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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (n\u0026thinsp;=\u0026thinsp;405)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\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\u003eDid you attend training on HMIS in the last 12 Months?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eOn job training program\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eOrientation on Utilization of HMIS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eHMIS tools recording for daily activities\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eElectronic devices in routine health information utilization\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderstand set of indicators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eStandardized set of indicators\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eDisplayed health indicator targets\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eDiscussed the monthly performance progress using the standard indicators\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eCorrectly and completely filled by the health professionals\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eChanged the collected data into information\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eReported the collected data in the last three months\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.3\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\u003e \u003cb\u003ePlease insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003ehere.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eThe types of HMIS training received in the last 12 months\u003c/h2\u003e \u003cp\u003eThe type of HMIS (Health Management Information System) training that the 405 healthcare workers in Banadir Region have received over the last 12 months. 46 healthcare workers (11.4%) received training in health information collection, while 359 (88.6%) did not receive any training. 25 (6.2%) received training in health information analysis, while 380 (93.8%) did not receive any training. 22 (5.4%) received training in health information presentation, while 383 (94.6%) did not receive any training. Finally, only 9 (2.2%) received training in health information use, while 396 (97.8%) received no training.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eOrganizational characteristics of the health care professionals\u003c/h2\u003e \u003cp\u003eMost respondents, 333 (82.2%), reported using routine health information for decision-making, while 72 individuals (17.8%) indicated they did not use routine health information for decision-making. In terms of staff awareness of their responsibilities, a significant proportion of participants, 352 (86.9%), reported being aware of their responsibilities, while 53 (13.1%) stated that they were not aware. 189 (46.7%) reported the presence of awards in the health facility as a motivation for good work, while 216 (53.3%) indicated the absence of such awards. The study also indicated whether the facility has a data quality check system. Most respondents, 330 (81.5%), reported that their facility has a data quality check system, while 75 (18.5%) reported the absence of such a system.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePlease insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003ehere.\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOrganizational characteristics of health care professionals working at public health facilities in Banadir Region, Somalia, 2024\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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (n\u0026thinsp;=\u0026thinsp;405)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\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\u003eRoutine health information for decision-making\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eStaff are aware of responsibilities\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAward in the health facility as a motivation for good work\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAccountability for poor performance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAre there factors influencing the information use?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility has a data quality check system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eRegular monitoring and evaluation supervision for the health information system\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eWhat interval do you receive feedback?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFor every report\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuarterly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnnual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRoutine health information utilization of the health care professionals\u003c/h2\u003e \u003cp\u003eThe current study found that most of the respondents (77.5%) utilized routine health information for patient treatment, 76.5% used for prioritizing diseases, 70.4% as drug procurement, 75.1% in monitoring daily activities related to health services, 76.8% for verification of data quality, 68.9% for allocation of resources, 77.5% for planning, 77.3% for the assessment of departmental performance, 81.5% for the assessment of employee performance, 77% for selecting the experience in the facility, 76.8% for sharing health information, 76.3% for making decisions, and 78.8% for discussions and mobilizations among the community.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePlease insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u003cb\u003ehere.\u003c/b\u003e\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\u003eRoutine health information utilization characteristics of health care professionals working at public health facilities in Banadir Region, Somalia, 2024\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eActivities employed for the utilization of the routine health information\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e(n= %405)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation for treating patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e314(77.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91(22.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation for disease prioritization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e310(76.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95(23.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation for drug procurement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e285(70.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120(29.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFor monitoring day to day health service activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e304(75.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e101(24.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation use for data quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e311(76.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94(23.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFor resource allocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e279(68.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e126(31.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFor departments performance evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e313(77.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92(22.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFor planning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e311(77.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94(23.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFor monitoring the performance of staff\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e330(81.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75(18.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFor selecting good experience within the facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e312(77.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93(23.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFor sharing of best experience for health facilities and stakeholders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e311(76.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94(23.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFor decision making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e309(76.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96(23.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation use for community mobilization and discussion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e319(78.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86(21.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eBehavioral characteristics of the health care professionals\u003c/h2\u003e \u003cp\u003eMost healthcare providers (56.5%) didn\u0026rsquo;t demand health information. 29.9% of healthcare providers exhibited a poor attitude towards data collection. Only 22.2% considered the routine health information system to be useless. 15.6% feel that collecting information adds no value to their activities. Eighty-one percent (81.2%) hold the opinion that the data they gather lacks customization for patient treatment. According to 30.9% of respondents, routine health information is useful for monitoring facility performance. 47.9% of health facility staff properly documented their activities and kept records. 61.2% do not feel committed to using routine health information outputs to improve the target community's health status. 46.4% of respondents understand and appreciate their roles and responsibilities in managing routine health information. 51.4% do not frequently use routine health information, and data collection benefits both patients and health facilities. 62.7% of respondents do not believe that decisions based on evidence improve service delivery quality.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePlease insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e \u003cb\u003ehere.\u003c/b\u003e\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\u003eBehavioral characteristics of health care professionals working at public health facilities in Banadir Region-Somalia, 2024\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e(n= %405)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare providers demand information\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e176(43.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e229(56.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth professionals have a poor attitude toward data collection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e121(29.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e284(70.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe routine health information system is useless\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e90(22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e315(77.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollecting information adds no value for my activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63(15.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e342(84.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe collected data is not customized to patients' treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76(18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e329(81.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoutine health information is useful for monitoring facility performance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e125(30.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e280(69.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth facilities\u0026rsquo; staff document their activities and keep records\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e194(47.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e211(52.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoutine health information outputs give feel committed in improving health status of the target community\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e157(38.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e248(61.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderstand and appreciate my role and responsibilities regarding to managed routine health information\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e188(46.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e217(53.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequent use of routine health information and data collection had benefit of patients as well as health facilities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e197(48.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e208(51.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecisions based on evidence improve services delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e151(37.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e254(62.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eFactors influencing Health Management Information Utilization of the health care professionals\u003c/h2\u003e \u003cp\u003eThe bivariable logistic regression data analysis revealed that variables such as sex, education, profession, type of health facility, ever-trained status, information collection, analysis, presentation, on-the-job training, orientation, HMIS tool recording, standard indicator, supervision, staff responsibilities, accountability, demand information, and customization were associated with good routine health information utilization. The above variables were further used to a multivariate logistic regression data analysis, finding that the type of facility, standard indicators, ever-trained HMIS, information collection, information for decision-making, awareness of staff responsibilities, information output, and appropriate roles and responsibilities were significantly associated with the utilization routine health data at a p-value of \u0026lt;\u0026thinsp;0.05. The study found that health centers were significantly more likely to utilize health management information than hospitals (AOR\u0026thinsp;=\u0026thinsp;3.181, 95% CI: 1.169 to 8.657, p\u0026thinsp;=\u0026thinsp;0.024). Not attending training on the Health data within the last 12 months was associated with a significantly lower utilization rate (AOR\u0026thinsp;=\u0026thinsp;0.31, 95% CI: 0.007 to 0.126, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting a potential negative impact of recent training on utilization. Similarly, the absence of health information analysis training significantly reduced utilization (AOR\u0026thinsp;=\u0026thinsp;0.165, 95% CI: 0.029 to 0.926, p\u0026thinsp;=\u0026thinsp;0.041). On the other hand, using electronic devices (AOR\u0026thinsp;=\u0026thinsp;4.192, 95% CI: 1.422 to 12.359, p\u0026thinsp;=\u0026thinsp;0.009) and employing a standardized set of indicators (AOR\u0026thinsp;=\u0026thinsp;0.188, 95% CI: 0.047 to 0.745, p\u0026thinsp;=\u0026thinsp;0.017) were both significantly associated with increased utilization. Moreover, using regular data for decision-making had a significant positive impact (AOR\u0026thinsp;=\u0026thinsp;14.954, 95% CI: 2.886 to 77.475, p\u0026thinsp;=\u0026thinsp;0.001), emphasizing the importance of incorporating health data into decision-making processes. Attitude, output, and role were also influential factors, with good attitude (AOR\u0026thinsp;=\u0026thinsp;0.095, 95% CI: 0.013 to 0.706, p\u0026thinsp;=\u0026thinsp;0.021), good output (AOR\u0026thinsp;=\u0026thinsp;0.025, 95% CI: 0.002 to 0.407, p\u0026thinsp;=\u0026thinsp;0.009), and good role (AOR\u0026thinsp;=\u0026thinsp;0.012, 95% CI: 0.01 to 0.230, p\u0026thinsp;=\u0026thinsp;0.003) being significantly linked with increased utilization. These findings highlight the importance of training, technology adoption, standardized indicators, and positive attitudes and behaviors in promoting effective health management information utilization. (Table\u0026nbsp;7).\u003c/p\u003e \u003cp\u003e \u003cb\u003ePlease insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e \u003cb\u003ehere.\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with routine health information utilization among health care professionals at public health facilities in Banadir Region, Somalia, 2024\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHealth management information utilization\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eType of the health facility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109 (72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.751 (0.483 to 1.167)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.181 (1.169 to 8.657)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87 (34.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168 (65.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eDid you attend any training on Health Information System in the last 12 month?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (19.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e246(80.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71 (70.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (29.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.08 (6.005 to 16.780)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.31 (0.007 to 0.126)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eHealth information analysis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrained\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14(56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUn-Trained\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115(30.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e265(69.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.341(0.150 to 0.774)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.165(0.029 to 0.926)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eDo you use electronic device in routine health information utilization?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (46.3%)1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102 (53.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (19.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174 (80.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.273 (0.175 to 0.426)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.192 (1.422 to 12.359)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eStandardized set of indicators\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65(38.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104(61.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64(27.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e172(72.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.595(0.390 to 0.908)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.188 (0.047 to 0.745)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eRoutine health information for decision-making\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42(58.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30(41.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87(26.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e246(73.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.253(0.149 to 0.429)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.954 (2.886 to 77.475)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eHealth professionals have a poor attitude toward data collection\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111(39.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e173 (60.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (14.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103 (85.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.671 (2.109 to 6.393)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.095 (0.013 to 0.706)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eRoutine health information outputs give feel committed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101(40.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e147 (59.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129(82.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.165 (1.957 to 5.120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.025 (0.002 to 0.407)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eUnderstand and appreciate the role and responsibilities\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105(48.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112(51.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24(12.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e164(87.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.406(3.869 to 10.608)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012 (0.01 to 0.230)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe objective of this study was to examine the utilization of the Health Management Information System and its influencing factors among healthcare workers employed in public health facilities in Banadir Region, Somalia, employing tools from the PRISM framework. The outcomes of the current study suggested that the level of health management information utilization was good in (68.1%). This finding is consistent with studies conducted in Malawi\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e with 68.8% and Ethiopia with 65.8% and 69.3%, respectively.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e However, the present finding is lower than other research in Ghana 77%\u003csup\u003e27\u003c/sup\u003e and Ethiopia 78.5%.\u003csup\u003e7\u003c/sup\u003e This finding is higher than other studies carried out in Tanzania 60\u003csup\u003e15\u003c/sup\u003e, Kenya 48.1%\u003csup\u003e28\u003c/sup\u003e and Uganda 59%.\u003csup\u003e29\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eStudy area, sample size, the emphasis on HMIS training to build staff capacity on health information usage, countries' health information system (HIS) structures, and healthcare workers' motivation to use the HMIS may explain variations between different study findings.\u003c/p\u003e \u003cp\u003eHealth center participants used the health management system three times better than hospital participants.Similar results were seen in Ethiopian research.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e The reason could be that governments may pay less attention to hospitals compared to health centers.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eNot attending health information systems training within the previous 12 months was strongly negatively associated with good utilization. Similar findings were reported elsewhere.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e This underscores the significance of HMIS-specific training in enhancing the information utilization skills of healthcare workers.\u003c/p\u003e \u003cp\u003eA statistically significant association was observed between HMIS (Health Management Information System) utilization and predictors, including supervision and standard indicators. Another study reported similar results.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Supervision and setting standard indicators might enhance employee performance and motivation.\u003c/p\u003e \u003cp\u003eThis is the first study of its kind in Somalia, providing valuable baseline data for future research and public health data initiatives. However, it's essential to highlight that the study was limited to public health facilities in Banadir region, so the findings may not be representative of the entire country.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings of this study indicate that more than one-third of healthcare practitioners in public health care facilities poorly utilize routine health information systems. The findings indicates that the use of health information falls short of the national Health Management Information System (HMIS) expectations. The study identified several key factors that significantly impact the health information system's utilization rate. These factors include a lack of training on the HMIS system, inadequate use of electronic devices for routine health data collection. Staff responsibilities and the role for health information utilization remain unclear, data quality checks and facility supervision are inadequate, and the demand for health information within the facilities is limited. Therefore, providing of health information system training for all staff in the facility, strengthening facility encourage and empower healthcare providers' ability to make decisions in Banadir region public health care facilities should be essential. The study is highly recommended regularly monitoring and ensuring the availability of the above factors in health facilities. The finding also recommended conducting further research into the culture and attitudes of healthcare workers towards routine data generation.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eEthics consideration\u003c/h2\u003e \u003cp\u003e This study involved human participants, and the researchers obtained ethical clearance from the ethical review board of the Somali National Institute of Health (NIH/IRB/07/MAR/2024). Additionally, the researchers obtained a supporting letter from the Jamhuriya University for Science and Technology. Informed consent was obtained from each study participant after they were informed of the study's objectives and potential benefits. To maintain the confidentiality of the information provided by the study subjects, the data collection procedure was conducted anonymously.\u003c/p\u003e \u003c/div\u003e\u003cp\u003e \u003ch2\u003eDeclaration of conflicting interests\u003c/h2\u003e \u003cp\u003eThe authors have no competing interests to disclose\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent for publication:\u003c/h2\u003e \u003cp\u003e All authors of the manuscript have read and agreed to its content and are accountable for all aspects of the accuracy and integrity of the manuscript in accordance with ICMJE (International Committee of Medical Journal Editors) criteria\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eNone\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eNor, Abdiweli, Mohamed, and Dr. Fidow made significant contributions to the following aspects of the study: the conception, training of the data collectors, design, data collection, supervision, data analysis, interpretation, and write-up of the manuscript. They have contributed to the existing literature review, developing the research matrix, revising the manuscript, preparing regression tables, and analyzing and interpreting the data as well. Finally, all authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to extend their heartfelt thanks to the following for their participation and support in this study: The Regional Medical Officer, Banadir Regional Administration (BRA), The District Health Officers, The facility in-charges, The health professionals, The data collectors, and The supervisors.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data sets generated during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eQian J, Shiferaw S, Seme A, Esmale OE, Denboba W, Stierman E, et al. Data for local decision-making, not a mere reporting requirement: development of an index to measure facility-level use of HMIS data. J Glob Heal Rep. 2023;7:1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNgusie HS, Ahmed MH, Kasaye MD, Kanfe SG. Utilisation of health management information and its determinant factors among health professionals working at public health facilities in North Wollo Zone, Northeast Ethiopia: a cross-sectional study. BMJ Open. 2022;12(4):1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSako S, Gilano G, Chisha Y, Shewangizaw M, Fikadu T. Routine Health Information Utilization and Associated Factors among Health Professionals Working in Public Health Facilities of the South Region, Ethiopia. Ethiop J Health Sci. 2022;32(2):433\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYehula CM, Walle AD, Tegegne MD, Endehabtu BF, Wubante SM, Melaku MS, et al. Health information utilization and its associated factors among health professionals in northwest Ethiopia: A crossectional study. Inf Med Unlocked. 2023;40(June):4\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGobena T, Shore H, Berhanie D, Kenay A, Wondirad Y, Ayanle M. Routine Health Information System Data Quality and Associated Factors in Selected Public Health Facilities of Jigjiga Woreda, Somali Regional State\u0026rsquo;s, Eastern Ethiopia. Ethiop J Heal Dev. 2022;36(Special Issue 1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarah A. Health Management Information System Data Use Practice and Its Determinants at Health Centers and Woreda Health Office in Fafan Zone, Somali Region,. 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDagnew E, Woreta SA, Shiferaw AM. Routine health information utilization and associated factors among health care professionals working at public health institution in North Gondar, Northwest Ethiopia. BMC Health Serv Res. 2018;18(1):1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMekuria S, Adem HA, Ayele BH, Musa I, Berhanie D. Utilization of routine health information system and associated factors among health professionals in public health facilities in dire dawa, eastern ethiopia: a cross-sectional study. Res Sq. 2021;1\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChanyalew MA, Yitayal M, Atnafu A, Tilahun B. Routine health information system utilization for evidence-based decision making in Amhara national regional state, northwest Ethiopia: a multi-level analysis. BMC Med Inform Decis Mak [Internet]. 2021;21(1):1\u0026ndash;10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12911-021-01400-5\u003c/span\u003e\u003cspan address=\"10.1186/s12911-021-01400-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNguyen TN, Nielsen P. The dynamics of information system development in developing countries: From mutual exclusion to hybrid vigor. Electron J Inf Syst Dev Ctries. 2023;(February):1\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDemsash AW, Kassie SY, Dubale AT, Chereka AA, Ngusie HS, Hunde MK, et al. Health professionals\u0026rsquo; routine practice documentation and its associated factors in a resource-limited setting: A cross-sectional study. BMJ Heal Care Inf. 2023;30(1):1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePam A, Aggrey C, Odongo AO, Kerochi A. Factors Influencing Utilization of Routine Health Information For Decision Making Among Health Workers: A Case Study of Health Facilities in Moyo District, Uganda. 2022;1\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDonaldson M, CUNY Academic Works Improving National Health Management Information Systems. Stakeholder Views in Selected Sub-Saharan African Countries How does access to this work benefit you ? Let us know ! : 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanfe SG, Debele GR, Berhanu RD, Ngusie HS, Ahmed MH. Utilisation of district health information system and its associated factors among health professionals working at public health facilities of the southwest of Ethiopia: Cross-sectional survey. BMJ Open. 2021;11(8):1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMboera LEG, Rumisha SF, Mbata D, Mremi IR, Lyimo EP, Joachim C. Data utilisation and factors influencing the performance of the health management information system in Tanzania. BMC Health Serv Res. 2021;21(1):4\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBagyendera M, Nabende P, Nabukenya J. Critical factors influencing data use and utilization in health systems: a focus on data and interoperability standards for health information exchange (HIE) in Uganda\u0026rsquo;s health care system. Oxf Open Digit Heal. 2023;1:1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS1386505605000560.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbajebel S, Jira C, Beyene W. Utilization of health information system at district level in jimma zone oromia regional state, South west ethiopia. Ethiop J Health Sci. 2011;21(Suppl 1):65\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShiferaw AM, Zegeye DT, Assefa S, Yenit MK. Routine health information system utilization and factors associated thereof among health workers at government health institutions in East Gojjam Zone, Northwest Ethiopia. BMC Med Inf Decis Mak. 2017;17(1):1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWude H, Woldie M, Melese D, Lolaso T, Balcha B. Utilization of routine health information and associated factors among health workers in Hadiya Zone, Southern Ethiopia. PLoS One [Internet]. 2020;15(5):1\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1371/journal.pone.0233092\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0233092\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMary K, Otieno G, Mawenzi R. Utilization of routine health data in decision-making by management teams in selected level 4 hospitals in Nakuru County, Kenya. Int Acad J Heal. 2023;2(1):314\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGovernment F. Federal Government of Somalia Ministry of Health and Human Services. 2022;(March 2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYehula CM, Walle AD, Tegegne MD, Endehabtu BF, Wubante SM, Melaku MS, et al. Health information utilization and its associated factors among health professionals in northwest Ethiopia: A crossectional study. Inf Med Unlocked. 2023;40(January):4\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNegera D, Zewdie A, Kera AM, Degefa GH. Health information use and associated factors among healthcare professionals in Ilu Aba Bor zone, Oromia region, Ethiopia: An institution-based cross-sectional study. BMJ Open. 2023;13(3):1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMsiska KEM, Kumitawa A, Kumwenda B. Factors affecting the utilisation of electronic medical records system in Malawian central hospitals. Malawi Med J. 2017;29(3):247\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbera E, Daniel K, Letta T, Tsegaw D. Utilization of Health Management Information System and Associated Factors in Hadiya Zone Health Centers, Southern Ethiopia. Res Heal Sci. 2016;1(2):98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoadu RO, Obiri-Yeboah J, Okyere Boadu KA, Kumasenu Mensah N, Amoh-Agyei G. Assessment of RHIS Quality Assurance Practices in Tarkwa Submunicipal Health Directorate, Ghana. Adv Public Heal. 2021;2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eObwocha W, Ayodo G, Nyangura A, Thomas O. Utilization of Healthcare Information Among Healthcare Workers in Gucha Subcounty, Kisii County, Kenya. J Heal Educ Res Dev. 2016;04(04).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHotchkiss DR, Aqil A, Lippeveld T, Mukooyo E. Evaluation of the Performance of Routine Information System Management (PRISM) framework: Evidence from Uganda. BMC Health Serv Res. 2010;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAyele G, Abera A, Ayele A, Gudina D, Firdisa D. Utilization of routine health data and its determinants among healthcare workers in public health facilities of harari region, eastern Ethiopia. BMC Health Serv Res. 2024;24(1):1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","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":"Information utilization, healthcare professionals, Banadir Region, Somalia","lastPublishedDoi":"10.21203/rs.3.rs-5071178/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5071178/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHealth Information Management System (HMIS) is a system that permits for the gathering, storing, compiling, transmission, analysis, and usage of health data that support decision- makers and stakeholders in managing and planning resources at every level of health service. This study aimed to assess the utilization of health information management system and its determinants amongst healthcare professionals employed at public health facilities in Banadir Region, Somalia.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional research was carried out from March to June 2024 at public health care facilities in eight randomly selected districts of Banadir region. A total of 405 public healthcare professionals were chosen by using simple random sampling. The data was analyzed by using the Statistical Package for Social Sciences version 27.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe present study indicated a good level of health information utilization at 68.1%. In a multivariate logistic regression analysis, the type of facility (AOR\u0026thinsp;=\u0026thinsp;3.18, 95% CI: 1.169\u0026ndash;8.657), attending training on Health Information System (AOR\u0026thinsp;=\u0026thinsp;0.31, 95% CI: 0.007\u0026ndash;0.126), use of standard indicators (AOR\u0026thinsp;=\u0026thinsp;0.188, 95% CI: 0.047\u0026ndash;0.745), utilization of health information for decision-making (AOR\u0026thinsp;=\u0026thinsp;14.954, 95% CI: 2.886\u0026ndash;77.475), and health information analysis (AOR\u0026thinsp;=\u0026thinsp;0.165, 95% CI: 0.029\u0026ndash;0.926) were significantly associated with good health information utilization.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study revealed that more than one-third of health care workers had poor health information utilization, therefore, providing health information system training for the staff, strengthening facility support, and empowering the healthcare system's decision-making ability in the Banadir region should be a priority.\u003c/p\u003e","manuscriptTitle":"Utilization of Health Management Information System and its Determinants Among Health Professionals Working at Public Health Facilities in Banadir Region, Somalia. A cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-12 12:59:00","doi":"10.21203/rs.3.rs-5071178/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":"9ada7c53-be51-4427-b8da-7b19da4eb230","owner":[],"postedDate":"December 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-28T07:53:58+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-12 12:59:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5071178","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5071178","identity":"rs-5071178","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}