Routine Health Information System Utilization and Its Associated Factors among Healthcare Professionals in Debre Berhan Town, Ethiopia

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Introduction
Routine health information system (RHIS) is the process of gathering, processing, utilization, and dissemination of healthrelated data for enhanced program, resource, and healthcare outcome [1]. Health information must be used often for daily patient management, illness prioritization, health education, resource allocation, decision-making, planning, evaluation, and monitoring of healthcare operations [2]. Along with resources, indicators, data sources, data management, information products, distribution, and use, it is one of the six components of a healthcare system. Producing and using information for other health system processes is its main goal. The purpose of a health information system is to deliver high-quality health information that gives relevant evidence to help people make decisions about their health [3].
RHIS effectively reduces workloads while improving patient care standards. It helps with problem-solving and system improvement and is useful for identifying problems and gaps in the healthcare system [4]. Ethiopia has also created opportunities for District Health Information System (DHIS) utilization that disseminate user-friendly DHIS versions across entire regions of Ethiopia. "The Federal Ministry of Health (FMOH) is deploying and putting DHIS into practice to improve decision-making in public health facilities" [5].
Information that is thorough, accurate, detailed, and valuable falls under the category of quality information.
The quality of the information in the RHIS translates to quality data, which includes the data's comprehensiveness, validity, accuracy, and suitability for use, among other benefits, as information is the product of data transformation. RHIS is projected to provide precise and practical information for healthcare system planning and decision-making [6].
Healthcare workers in Ethiopia use the RHIS on average at 57.42%, which is lower than the amount considered to be acceptable nationally [2]. Similar findings from a study conducted in East Gojjam showed that just 45.8% of healthcare professionals regularly use health information at a high level [7]. According to another survey, routine health information (RHI) is used by 63.1% of people in Ethiopia's south region [8] and 69.3% of people in Hadiya zone's study units/departments of health centers [9].
Although the official expectation is 80%, the majority of indicators in Ethiopia's RHISs have poor data quality [10]. Moreover, in our study setting, little is known about the proportion of health information system utilization and the main associated factors that affect RHIS among healthcare professionals. Therefore, the goal of this study was to evaluate how frequently health professionals used the health information system and related parameters in the health facilities in Debre Berhan Town, North Shoa, Amhara, Ethiopia, in 2022.

Methodology
An institution-based cross-sectional quantitative survey including health professionals was conducted at Public Health Facilities in Debre Berhan North Shoa, Amhara region, Ethiopia, from February 22 to September 22, 2022. A total of 114,652 people live in the town, 51,843 of them men and 62,809 of them women, according to Central Statistical Authority (CSA) figures. The town has three medical facilities, nine health posts, a reputable comprehensive specialized hospital, and a private hospital. It is located 130 km north-east of Addis Ababa, the nation's capital. There are currently 504 medical experts working in the Debre Behan hospital and 54, 45, and 47 in 04, 07, and 08 Kebele health centers, respectively.

Inclusion and Exclusion
Criteria. All medical professionals with more than 6 months of experience working in Debre Berhan Town public health facilities were included in the study during the data collection period. However, medical staff members on extended study leaves were not included in the study during the data collection.
2.2. Sample Size Determination. "The sample size was determined by using a single population proportion technique using the following assumptions (95% confidence interval and Z α /2 with a significant level of alpha (α) of 0.05, which is 1.96. A 5% margin of error (d = 0.05), P = 79% which is the study conducted in North Gondar" [1]. The sample size becomes 255. So with adjustment for 1.5 design effect the subjects were chosen by using probability proportional to sample size. A z-value of 1.96 was used at 95% CI and d of 5% (n = sample size, p = probability, d = margin of error). n = z2 p (1−p)/ d 2 × design effect, n = (1.96) 2 × (0.79)(0.21)/(0.05) 2 × 1.5 = 0.64/ (0.05) 2 × 1.5 = 383. Therefore, after adjusting for design effect, the total study participants were 383 health professionals.
2.3. Sampling Technique and Procedure. Stratified sampling technique was used to recruit study subjects from public health facilities in Debre Berhan town (one hospital and three health centers). Health professionals who completed the self-administered questionnaire were chosen by a rigor's random selection process. First, the study participants were chosen based on their occupations using the stratified sample technique then, after the division of health workers into professions. The necessary sample size was calculated in accordance with the size of the preferred healthcare facility. The total number of health facility employs who worked during the study period and the number of samples needed in each chosen health facility were used to conduct systematic random sampling in order to obtain the individual sample at the chosen health institution. The first participant was chosen by random out of the first "k" units after obtaining the sampling fraction in the chosen factory ( Figure 1).

Data Collection Method and Procedures
An organized interview instrument was used to collect the data. Additionally, we pretested the tool on 5% of research participants and found that it was appropriate for the study. The literature was used to select variables that might affect how frequently healthcare professionals use health information systems. To ensure the consistency of the questionnaire, the quantitative data were initially prepared in English, translated to Amharic, the native language, and then translated back to English.
Four health information technicians who worked in the Woreda health office and health facility gathered the necessary data. Data collectors received instruction on several aspects of the study. Technical, behavioral, and organizational aspects are the main determinants of adoption of RHISs, and these elements were taken into consideration when developing the questionnaire based on the revision and conclusions of the pertinent literature study. The questionnaire consists of five main parts. Part 1 includes sociodemographic factors Technical and organizational factors have each 10 questions with a response of Yes or No questions. Behavioral factors affecting of RHIU of the respondents were assessed using 5-point Likert scale questions that ranged from "1 = strongly disagree" to "5 = strongly agree". The fact that participation was optional and that there were no conditions on withdrawal was also made clear to participants. Acknowledgment was sent to study participants in order to collect the essential data from them.

Data Processing and Analysis
Using Epi-data version 3.1, the acquired data was entered and carefully reviewed for accuracy. In order to further clean and analyze the entered data, the data was exported to SPSS version 21. The data was edited, coded, checked, and organized to provide a format appropriate for additional analysis. The content validity index (CVI) is generated for the entire test after the inclusion of domains and indicators has been determined. CVI is just the average of all domain and indicator CVR values that fulfill the CVR cut off of 0.62. The Hosmer-Lomeshow goodness of fit test was used to evaluate the model's fitness. Variance inflation factor (VIF) and a normal P-P plot were used to verify model assumptions such as multicollinearity and outlier, respectively. In order to determine the strength of the link, each independent variable was fitted independently into a binary logistic regression model. A multiple logistic regression model was fitted to the variables with a p-value of less than 0.20 [11]. In order to find independent variables that were substantially associated with the use of RHIS, an Adjusted Odds Ratio (AOR) value with a 95% confidence interval was determined. A p-value of 0.05 was utilized as the level of significance for the final qualifiers as factors associated with RHIS utilization. Behavioral factors have a 5-point Likert scale measure, ranging from "1 = strongly disagree" to "5 = strongly agree". After data collection the Likert scale questioners changed in to Yes/No form for analysis purposes. First each 10-item Likert scale questions ranging from "1 = strongly disagree" to "5 = strongly agree" recodes in to 0 and 1. If the health professional respond this Likert scale questions ranging from 1 = strongly disagree to 3 = neutral labeled as 0 whereas value from 4 = agree to 5 = strongly agree labelled as 1 (or 0 denoted  Advances in Public Health 3 as No and 1 denoted as Yes). RHIU have a 5-point Likert scale measure, ranging from "1 = strongly disagree" to "5 = strongly agree".  use of both manual paper and computer-based files, feeling guilty not accomplishing their targets, orientation on data collection during employ, discussion on monthly performance, information use skills, supportive supervision, provision of regular feedback, trained in data management and use, reward for good work were factors associated with good RHIU at a p-value of less than 0.25 (Table 6).

Multivariate Analysis of Associated Factors.
With the use of RHI, the bivariable logistic regression analysis revealed significant associations between sociodemographic characteristics type of institution, level of education, working department, and year of experience at p-values 0.25. The crude odds ratio for one of the factors thought to influence how frequently people use RHI revealed that it was always very significant.
However, following corrected multiple logistic regression, the bulk of those covariates are not statistically significant. In this study, higher odds of good RHIS utilization were noted among health professionals who had perceived complexity of RHIS formats (AOR = 2.18; 95% CI: 1.23, 3.88), training on HMIS (AOR = 8.94; 95% CI: 1.77, 18.55), and feeling guilty if not accomplishing their target and performances (AOR = 2.96; 95% CI: 1.33, 6.60) and those who were working at hospitals (AOR = 2.10; 95% CI: 0.74, 2.82). As the result indicates, type of institution was found to be significantly associated with RHI use (AOR = 2.10; 95% CI: 1.028, 4.502). Those health professionals who work in hospitals were 2.10 times more likely to utilize good RHI than those who work in health centers.
Complexity of RHIS was found to be significantly associated with good RHI use (AOR = 2.19; 95% CI: 1.23, 3.88). The Feeling guilty of not accomplishing their target and performances were found to be significantly associated with good RHI use (AOR = 2.96; 95% CI: 1.33, 6.60). Health professionals who feeling guilty of not accomplishing their target and performances were 2.96 times (AOR = 2.19; 95% CI: 1.23, 3.88) more likely utilize RHIS when compared with these who perceived not feeling guilty of not accomplishing their target performance (Table 6).

Discussion
This study aimed to assess the parameters associated with RHIU by healthcare professionals in Debre Berhan Town public health facilities in North Shoa, Ethiopia. Overall, 42.6% of healthcare professionals used regular health information efficiently, according to the study's findings. The way regular health information was used by healthcare practitioners was typically unsatisfactory and fell short of what was anticipated on a national level. A study showed that, 57.42% of the time, health professionals in Ethiopia gathered RHI [2]. The health professionals' perception of the RHIS formats' complexity, their lack of HMIS training, and their lack of data management expertise could all be contributing factors to the low levels of RHIU shown in this study.
This finding was almost in line with a study finding in Addis Ababa health centers where utilization of HMIS at health facilities was 41.7% [12]. However, this finding is higher than that of a study conducted in Cote'dvorie (38%) [13], Kenya (34%) [14] and, Jimma zone 32.9% [15]. The possible explanations for this variation might be due to differences in study period and recent governmental concern for RHIU. It justifies that in the former study there is no information technician at each institution but nowadays more than 80% of health facilities has such technician. It was also higher than the study finding at health facilities in Western Amhara in which good utilization of RHIS was 38.4% [16]. This variation might be the study conducted only in health center and department or unit heads, in the current study in which all healthcare professional working in hospital and health centers were included. "The utilization of RHI among health professionals of this study was higher than a study conducted in Addis Ababa city in which odd of utilization of RHIS was 37.3%" [6]. This variation might be the study conducted only health center in all the study units or departments of health centers. In this study both health centre and hospital incorporated. This implies that emphasis given by health workers and district offices in Addis Ababa to strengthen RHIS was very low.
The outcome of this trial, however, was less favorable than that of the Ghanaian study [17]. The extent and scope of the study's study area and subject matter are two considerations that can apply to this difference. Unlike the study in Ghana, which also covered district, community, and other health offices, the current study primarily paid attention to public health institutions. Additionally, Ghana has had a longer period than Ethiopia for the establishment of DHIS. This finding was also less than that of a study conducted in North Gondar, which found that the trend of RHI usage among health professionals was (78.5%) [1]. This might be due to health professionals in North Gondar have available standard set indictors at their offices, good governance, and good data analysis skills.
Compared to a study conducted in the Hadiya zone 69.3% [18], health professionals in this study used less health information, and East Gojjam zone 45.8% [7]. This variation   might be due to this study conducted only health centers and also good data handling skills, data analysis skills, and data information presentation skills of health professionals. But in the current study both health center and hospital participated. Similarly this study finding was lower than the study conducted in Dire Dawa (53.1%) [19], and a study conducted in resource limited setting, Ethiopia 53.1% [20]. This might be due to health professionals had friendly format for reporting, good supportive supervision, and provide regular feedback to their staffs. This justifies that complicity of RHIS formats in the current study hard to utilize RHIS. This study also lower than a study conducted in southwest Ethiopia 57.3% [5] and another study in East Wollega (57.9%) [21]. This might be due to trained and good staff motivation, regular supervision, regular feedback, and decision based on superior directives and performance monitoring by health professionals. And also, in this study health professionals RHI use is poor when compared to study done in North Wollo where the utilization of RHI among health professionals was 58.4% [22]. This might be due to health professional's good perceived culture of health information use, standard set of indicators, and government special emphasis to the utilization of RHI for evidence-based decision making and HMIS training. Similarly, the finding was lower than those of studies reported from outside Ethiopia that is Uganda (59%) [23],Tanzania (60%) [24]. This might be due to the difference in health information system structures and health professional attitude for RHIS.
Multivariable logistic regression analysis shows type of institution was significant association with RHIU. In this study health professional working at hospital were two times higher to utilize RHIS when compared with those working at health centres. The proportion of good health information utilization was 29.07% at health centers and 46.46% at hospital. In contrast, a study conducted in East Gojjam [7], and North Gondar [1] the odds of utilization RHI was higher among health workers at health centres 84.9% when compared with those at hospital. This might be because there were well established RHISs and presence of better organizational support at hospital encourages staff to use RHI for evidence-based decision than health centers.
Complexity of health information system was another determinant factor of RHIU. Health professionals who had low perceived complexity of RHIS were two times more likely utilize RHI when compared than who perceived complexity of RHIS. This result supported by a study conducted in Addis Ababa city administration, 2022 [25], Dire Dawa [19], eastern Ethiopia Health professionals who had low perceived complexity of RHIS were two times more likely utilize RHI when compared than their counterpart [19,25]. This is might be due to complexity of RHIS makes hard to utilize RHI.
The odds of utilization RHI were about nine times higher among trained health professionals when compared with health professionals who are not trained on RHI. This study supported by a study conducted in Illu Aba Bora zone, southwest Ethiopia, Hodiya zone, a systematic review, and metaanalysis study in Ethiopia, Oromia special zone Amhara, North Wollo zone, [2,5,18,22,26]. This result also supported by a study conducted in East Gojjam, HMIS training were significant association with RHIU.
In contrast, a study conducted in North Shoe zone, Oromia region, Ethiopia, the odds of RHIU were 0.72 times less likely utilize health information system among health professionals who had taken training on health information system when compared with health workers who are not trained on RHI [27]. This might be due to health professionals perceived feeling guilty not accomplished their target performance timely in the current study. 10 Advances in Public Health The odds of RHIU among health professionals were three times more likely to utilize RHIS among health professionals who had perceived feeling guilty if not accomplishing their target performance on time when compared with those who not feeling guilty of not accomplishing their target performance.

Conclusion
This study found that the overall utilization of RHI among health professionals was low. Type of institution, complexity of RHIS, taking training on data managements in the last 1 year, and feeling guilty not accomplishing their target performance were found to have significant associations with RHIU. The study suggested further investigation on culture of health information utilization among healthcare providers where routine data are generated.

Recommendations to Zone Health Department and Woreda Health
Offices. Thorough HMIS training should be made available to help health workers understand and use the system more effectively.

Recommendations to Policies
Maker. Efforts must be made to reduce complexity of RHIS for Health Professionals in the facilities by giving training on HMIS.

Data Availability
The first author or the last author will provide the data gathered for this study upon reasonable request.

Additional Points
Limitation of the Study. The cross-sectional design of the study prevents it from demonstrating a cause-and-effect link between the dependent and independent variables.

Disclosure
A verbal informed consent form outlining the study's goals and participants' rights was given to every study participant. The questionnaires were securely handled after completion, and all access to the results was strictly controlled. Participants were all chosen at random without any bias.