Assessing Radiation Dose Optimization in a Regional Hospital Radiography Department

Thesis Abstract

This study investigates radiation dose optimization practices in a regional hospital radiography department to address elevated patient and staff exposure while maintaining diagnostic image quality. The problem centers on suboptimal dose management protocols, variability in technique selection, and dependence on outdated equipment, which collectively threaten radiation safety and workflow efficiency. The aim is to quantify existing dose levels, identify determinants of dose variation, and evaluate the impact of targeted optimization interventions on patient dose and image quality. Specific objectives include (1) characterizing current patient entrance skin doses (ESDs) and average glandular doses (AGDs) across common radiographic procedures; (2) assessing adherence to dose optimization principles (collimation, shielding, exposure parameter selection, and repeat-rate) by radiographers; (3) examining the relationship between technique factors, equipment performance, and dose metrics using regression analysis; (4) evaluating image quality using objective metrics and radiologist/technologist satisfaction; (5) implementing a dose optimization protocol—encompassing structured training, protocol standardization, and dose-tracking software—and assessing its impact over six months. The methodology adopts a convergent mixed-methods design. The study population comprises radiography staff (n=28) and adult and pediatric radiographic examinations conducted in the department over a 12-month baseline period, yielding a sample of approximately 3,500 radiographs. Quantitative data will be collected from dose measurements recorded by digital radiography (DR) systems, exposure indices (EI), and patient demographics, alongside image quality scores generated via a standardized checklists and dual observer ratings. Qualitative insights will be obtained through semi-structured interviews with radiographers (n=12) and focus groups with radiologists (n=6) to contextualize quantitative findings. Instruments include calibrated dosimetry data extraction templates, a validated image quality assessment tool, exposure parameter logs, and a customizable dose-tracking and feedback software module. Validity and reliability will be ensured through pilot testing (n=50 radiographs), inter-rater reliability analysis (Cohen’s kappa for image quality), and triangulation of occupational dose data with workflow observations. Data will be analyzed using multiple linear regression to identify predictors of patient dose, analysis of variance (ANOVA) to compare dose and image quality across procedures, and time-series analysis to evaluate dose trends before and after protocol implementation. Mediation analysis will explore whether workflow changes mediate the relationship between training and dose reduction. The study will situate its theoretical grounding in the Health Belief Model to understand radiographer adoption of dose-saving behaviors and the Theory of Planned Behavior to interpret intention-behavior gaps, augmented by the ALARA (As Low As Reasonably Achievable) principle as a normative framework. Expected findings include statistically significant reductions in mean ESDs/AGDs for key extremity and chest radiographs, without compromising objective image quality or radiologist satisfaction; reduced repeat rates; improved protocol concordance, and positive shifts in radiographer attitudes toward dose optimization. The contribution to knowledge lies in providing context-specific, evidence-based dose optimization benchmarks for regional hospital settings, integrating quantitative dose metrics with qualitative insights to inform scalable, low-cost interventions. Practically, the study will generate a reproducible optimization toolkit comprising standardized exposure protocols, decision-support prompts within the radiography information system, targeted training modules, and a monitoring dashboard for ongoing dose tracking. The main conclusion is that a structured, multi-faceted optimization program—grounded in ALARA and behavior theory—can achieve meaningful dose reductions while preserving diagnostic quality in a regional hospital radiography department. Recommendations include institutionalizing continuous dose auditing, periodic hands-on refresher trainings, enhancement of equipment maintenance schedules, investment in dose-management software, and extension of the optimization framework to adjacent departments to sustain improvements and facilitate benchmarking against national standards.