Authors : Hazel Galas Lampitoc; Dr. Reagan Recafort

Volume/Issue : Volume 11 - 2026, Issue 2 - February

Google Scholar : https://tinyurl.com/mrx8mfcm

Scribd : https://tinyurl.com/yut32kvr

DOI : https://doi.org/10.38124/ijisrt/26feb553

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Biomedical imaging relies heavily on the interoperability between PACS, RIS, and HIS for an efficient workflow and timely clinical decision-making that is critical not only for clinical practice but also patient care. Even though some hospitals have developed advanced digital infrastructures, many hospitals suffer from difficulties around interoperability, database performance, workflow bottlenecks, and user competency issues. This study investigated the technical, operational, and people -based factors impacting imaging integration performance at Dr. Sulaiman Al-Habib Hospital, Riyadh, Saudi Arabia. Using a quantitative descriptivecorrelational design, data was pulled from 40 selected personnel in imaging and IT using a validated 40 -item Likert-scale questionnaire. Results revealed high system integration, database management, and integration performance levels, and moderate to high workflow efficiency. Correlation and regression analyses revealed a strong and significant relationship between all parameters and 68% explains of variation in integration performance were due to technical and operational reasons. Database administration and workflow efficiencies are the most positive (moderate to strong) by user competency differences. A second key finding is that organized subsystem optimization is necessary to enhance the imaging integration process, as they stress. Structured Abstract. Background. PACS, RIS, and HIS should be integrated to provide an effective biomedical image. Continued interoperability, database effectiveness, workflow consistency and user acceptability concerns can create challenges to the efficient workflow and clinical efficacy of imaging. Methods. A descriptive, quantitative, correlational design was utilized in the analysis of system integration, database organization, workflow productivity, and imaging integration functionality. Data were gathered via a va lidated 40-item Likert-scale questionnaire among 40 IT and Dr. Sulaiman Al-Habib Hospital imaging practitioners. Analysis included descriptive statistics; Pearson correlations; regression and moderation testing. Results. System integration, database management, and workflow efficiency were also identified as highperforming and robustly linked with integration effectiveness and performance. Linear regression analysis found that 68% of this performance variance is accounted for by regression analysis. User competency, however, is shown to moderate performance with respect to the DBMS, and workflow efficiency effect. Conclusion. Imaging integration performance is manifested from the interaction of technical, operational and human subsystems. We believe improving its interoperability, database architecture, processes in workflow and competency of the user is important in improving imaging outcomes.

Keywords : PACS; RIS; HIS; Biomedical Imaging; System Integration; Database Management; Workflow Efficiency; User Competency; Health Informatics; Interoperability; Radiology Workflow; Systems-Driven Framework; General Systems Theory.

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