Development and clinical implementation of a low-cost cloud-based electronic veterinary anesthesia record.

OBJECTIVE: To describe the development and clinical implementation of a low-cost, workflow-integrated, cloud-based electronic veterinary anesthesia record (EVAR) and to evaluate its association with changes in registry-level documentation completeness between preimplementation paper-based and postimplementation EVAR workflows. STUDY DESIGN: Pre-post implementation study. ANIMALS: A total of 984 anesthesia or sedation episodes in dogs and cats recorded in a departmental anesthesia registry, including 489 episodes in the paper-based period (April-December 2024) and 495 episodes in the EVAR period (April-December 2025) at a veterinary medical teaching hospital. METHODS: EVAR was developed using a cloud-based application suite. Case-linked spreadsheets integrated anesthesia requests, scheduling, consent documentation, perianesthetic recording, and postcase export. Registry-level completeness was assessed for 13 predefined variables comparable across periods. Variable-level differences were summarized as absolute percentage-point differences with 95% confidence intervals and Benjamini-Hochberg-adjusted p values. RESULTS: Increased registry-level completeness was observed for documentation of diagnosis (83.0%-99.8%), American Society of Anesthesiologists physical status classification (83.8%-97.0%), endotracheal tube information (36.0%-96.2%), and fluid type (34.4%-93.5%) (all adjusted p < 0.001). Cardiac murmur grade documentation (85.5%-68.7%) and anesthesia duration documentation (98.2%-93.9%) were less complete after EVAR implementation (adjusted p < 0.001 and adjusted p = 0.002, respectively). No technical failures or data-loss events were documented in administrator records or during routine implementation monitoring. The remaining variables showed small absolute differences. CONCLUSIONS: EVAR use was associated with improved registry-level completeness of selected perianesthetic variables compared with the previous paper-based workflow. CLINICAL RELEVANCE: These findings should be interpreted as improvement in registry-level documentation completeness, not as evidence of improved source-record completeness, data-entry accuracy, user experience, clinical outcomes, or patient safety.