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Only 35.8% of healthcare managers in Somalia report adequate use of EMR data for decision-makingManagers in Somalia Show Limited Use of Electronic Health Records

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Key Takeaway
Note that EMR data use for decision-making is limited by system difficulty and lack of technical support.

This cross-sectional study evaluates the adequacy of using Electronic Medical Record (EMR) generated data for decision-making among 405 healthcare managers in public health facilities in Somalia. The study identifies several specific areas of use, including clinical guideline adherence (29.9%), provider performance (28.4%), and quality improvement (15.1%).

Several factors influenced the utilization of EMR data. Identifying patient care gaps was strongly associated with higher usage (AOR = 5.02), while technical support (AOR = 1.71) and creating performance dashboards (AOR = 2.25) also showed positive associations. Conversely, perceived system difficulty was negatively associated with EMR data use (AOR = 0.39). Notably, laboratory professionals were more likely to use EMR data than general practitioners (AOR = 2.96).

Factors such as diploma-level qualifications and less than one year of administrative experience were associated with lower EMR data usage. The findings suggest that while EMR systems are in place, their utility for decision-making is limited by usability and support issues. These results highlight the need to improve system usability and provide better technical support to enhance healthcare management capabilities.

A study looked at how healthcare managers in Somalia use data from electronic medical records (EMR) to make daily decisions. Researchers surveyed 405 managers across various public health facilities to see if these digital tools were being used effectively for things like following clinical guidelines, improving provider performance, and enhancing quality of care.

The findings showed that only about 36% of the managers reported using EMR data adequately for decision-making. Specifically, usage was even lower when it came to following clinical guidelines (29.9%) or tracking provider performance (28.4%). Only 15.1% of managers used this data for quality improvement efforts.

The study found that certain factors influenced how much data was used. For example, laboratory professionals were more likely to use EMR data than general practitioners. Having access to technical support and using tools like performance dashboards also linked to higher usage. However, when the system was perceived as difficult to use, managers were less likely to use the data. These results suggest that improving system usability and providing better training could help staff make better decisions.

What this means for you:
Only 36% of surveyed health managers in Somalia used electronic medical records for decision-making.

Common questions

How often are electronic records used for decision-making?

The study found that only 35.8% of healthcare managers reported using electronic medical record (EMR) data adequately for making decisions. This means a majority of the surveyed managers were not utilizing these digital tools to their full potential in their daily roles.

What factors help managers use more data?

Several factors were linked to higher usage of EMR data. These included having access to technical support, creating performance dashboards, and using the data to identify gaps in patient care. Laboratory professionals also showed a higher likelihood of using this data compared to general practitioners.

What makes it harder for staff to use these systems?

The study found that when managers perceived the electronic medical record system as difficult to use, they were less likely to use the data. This suggests that the ease of use and technical support are important factors in whether healthcare workers can effectively use digital tools.

Study Details

Study typeGuideline
EvidenceLevel 5
PublishedJun 2026
View Original Abstract ↓
Electronic medical record (EMR) systems have been introduced in public health facilities across Somalia to strengthen routine health information systems and support data-informed decision-making. However, evidence on the extent to which EMR-generated data are used for managerial and clinical decision-making remains limited. This study assessed EMR-generated data utilization and associated factors among healthcare managers in public health facilities in Somalia. A facility-based cross-sectional study was conducted from November to December 2025 across 45 public health facilities. A total of 405 healthcare managers were selected using a multistage cluster sampling technique. Data were collected using self-administered questionnaires and observational checklists developed based on the PRISM framework. The tool assessed organizational, technical, and behavioral factors influencing EMR data use. Data were entered and cleaned in Excel and analyzed using SPSS version 27. Descriptive statistics were used, and bivariable and multivariable binary logistic regression analyses identified factors associated with EMR-generated data utilization. Overall, 145 healthcare managers (35.8%) reported adequate use of EMR-generated data for decision-making. EMR data were most commonly used to assess clinical guideline adherence (29.9%) and provider performance (28.4%), but least used for quality improvement (15.1%). Diploma-level qualification (AOR = 0.49; 95% CI: 0.25–0.95) and ≤1 year of administrative experience (AOR = 0.57; 95% CI: 0.36–0.90) were associated with lower EMR data use. Laboratory professionals were more likely to use EMR data than general practitioners (AOR = 2.96; 95% CI: 1.07–8.16). Creating performance dashboards (AOR = 2.25; 95% CI: 1.19–4.24), identifying patient care gaps (AOR = 5.02; 95% CI: 2.42–10.44), and access to technical support (AOR = 1.71; 95% CI: 1.02–2.89) were positively associated with EMR data use, while perceived system difficulty was negatively associated with utilization (AOR = 0.39; 95% CI: 0.22–0.70). EMR-generated data use for decision-making remains limited in Somalia's public health facilities. Strengthening user capacity, improving system usability, and ensuring technical support are essential to promote routine data-driven decision-making.
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