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Effect of a Medication Decision Support System on Albumin Prescribing: A Pre-post Study in Intensive Care Units of
Naghme Dashti1, Hesamoddin Hosseinjani2, Saeid Eslami1,3
1Department of Medical Informatics, Mashhad University of Medical Sciences, Mashhad, Iran.
Objective:
Medication Decision Support Systems (MDSS) are increasingly integrated into hospital information systems to reduce prescribing errors and enhance evidence-based clinical decision-making. This study evaluates the effect of MDSS implementation on albumin prescribing in two intensive care units (ICUs) at Imam Reza Hospital, Mashhad, Iran.
Methods:
A quasi-experimental pre-post design was applied. Albumin prescription data were collected over two 3-month phases, before and after MDSS implementation. Total population sampling was used. Statistical analyses included Chi-square and independent-sample t-tests to assess differences in guideline adherence, alert responsiveness, and patient safety. P < 0.05 was considered significant, and 95% confidence intervals were reported where applicable.
Findings:
A total of 311 albumin prescription requests were reviewed. Following MDSS implementation, 60.15% of alerts led to prescription modification. Guideline adherence improved significantly (from 47.64% to 68.26%, P = 0.014), and patient safety rates increased (63.33% to 82.61%, P = 0.009). Alert responsiveness was highest in critical conditions such as acute respiratory distress syndrome and lowest in elective scenarios such as paracentesis.
Conclusion:
MDSS significantly improved guideline adherence and prescribing quality in ICU settings. However, system limitations such as alert fatigue and physician override in specific scenarios remain. Further research is warranted to evaluate MDSS scalability, long-term clinical impact, and application to broader drug categories.
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