Patient Name Variation Finder

<p>This workflow enables users to enter any patient name and instantly discover all known variations of that name across a patient dataset. By combining a high-performance fuzzy-matching index with real-time user input, the app identifies duplicates, near-duplicates, and alternate spellings that typically appear across clinical, administrative, and legacy systems.</p><p>The process begins by loading the master dataset of patient names, which may contain typos, formatting inconsistencies, or multiple system-specific identifiers for the same person. A <strong>Single-Field Indexer</strong> creates an optimized fuzzy-search index over the canonical patient names. When the user enters a patient name, the workflow normalizes the input to match the dataset’s preprocessing and ensures consistent matching behavior.</p><p>The <strong>Approximate Index Matcher</strong> then performs a fast, fault-tolerant search against the index, detecting all names that are similar to the user’s input—even with character swaps, deletions, insertions, or spacing differences. Matching results are scored, filtered by similarity threshold, and expanded into full variation clusters by joining back to the source dataset. This reveals every version of the patient’s name, along with all related patient IDs and metadata.</p><p>Finally, the Data App presents the results in an interactive table, allowing users to inspect identity clusters, validate potential duplicates, and export findings for master-data cleanup or downstream deduplication workflows.</p><p>The workflow provides a robust, user-friendly tool for improving patient identity quality, consolidating fragmented records, and enhancing master-patient indexing through deterministic fuzzy matching.</p>