Enhancing Prescription Practices and Mitigating Medication Errors through Prescription Audits: A Quality Improvement Initiative at a Tertiary Healthcare Facility

Background: Errors in prescribing medications are a considerable preventable harm in healthcare. Handwritten prescriptions are still widely used in resource-limited settings, which further increases the risk of errors in documentation. Such errors can be identified, quantified and corrected using regular prescription audits, thus optimising patient care and medication use safety. Methods: A cross-sectional audit of 3,120 inpatient and 980 outpatient prescriptions was conducted using a mixed-methods approach over six months across six departments in a tertiary healthcare facility in South India. All the prescriptions were assessed using a pre-validated 15-parameter checklist, including prescriber identification, formatting standards, timing, dosage, and drug interaction risks. Variation in error trends over time was visualised by constructing Statistical Process Control (SPC) charts. Results: Among the inpatient prescriptions, departments such as Neurology (92.2%) and Medicine (59%) recorded the highest error rates. The most frequent inpatient errors were omission of prescriber identity (60%), missing timing of medication (28%), and formatting inconsistencies (6%). Outpatient prescriptions had been compared for month-wise compliance variation, with key issues being missing prescriber details (23%), use of non-standard abbreviations (19%), and potential drug interactions (14%). The SPC charts do not merely reflect isolated incidents but also prove persistent, statistically significant deviations. Conclusion: Prescription safety is not entirely a matter of clinical knowledge but also system design. Our study shows that various patterns can be observed distinctly and reflect vulnerabilities specific to the institution and cannot be addressed by individual behaviour vigilance. Prescription audits must also evolve from being retrospective tools to becoming real-time components of quality assessment.