Overview

A leading healthcare organization was required to manage 1000+ datasets containing drug names in various formats. One significant challenge in dealing with drug names in multiple formats is that it often leads to data management errors and inefficiencies.

The organization required a powerful yet cost-effective solution to identify and correct misspelled words, expand abbreviations, standardize drug names, and map the standardized drug names to an industry-standard drug database for accurate and reliable data management.

Challenges

The project posed several intricate challenges in managing, validating, and enhancing the data to meet industry standards and ensure high confidence scores.

• Managing and processing a variety of complex data attributes to ensure completeness and accuracy.
• Applying a range of validation rules to confirm the integrity and consistency of the data.
• Mapping data to an industry-standard database to ensure compatibility and adherence to required formats.
• Conducting comprehensive checks and updates to identify and correct any inconsistencies or errors in the data.
• Enhancing the data’s confidence score to improve its reliability and usability for critical business decisions.

Solutions

We implemented a robust, automated data quality solution across key stages, enabling fast and accurate drug identification while enhancing data quality.

Correcting Errors with NLP

We applied Natural Language Processing (NLP) to identify and correct spelling mistakes in drug names, significantly reducing the risk of misinterpretation and errors.

Expanding Abbreviations

Our custom algorithm efficiently expanded commonly used abbreviations in drug names, improving clarity and reducing ambiguity across the data.

Standardizing Drug Names

We standardized and formatted drug names through a seamless integration process, improving patient safety by ensuring consistent data representation.

Ensuring Consistency

By addressing variations in naming conventions, abbreviations, and misspellings, we reduced errors, leading to a more reliable and uniform dataset.

Automated Data Mapping

We leveraged advanced automated mapping techniques to align drug names with an industry-standard database, ensuring consistency and accuracy.

Human-in-the-Loop & Validation

Combining automated mapping with manual oversight, we applied data validation rules to enhance the data’s reliability and ensure high-quality results.

Results

By implementing our solution, we delivered outstanding results—boosting data accuracy, ensuring industry compliance, and empowering the client with high-quality data for smarter decision-making and improved outcomes.

Over 99% Accuracy in Data Mapping

We achieved more than 99% accuracy in mapping drug names to the industry-standard database, ensuring reliable and precise data.

Alignment with Industry Standards

Our solution ensured the client’s data aligned with industry norms, significantly reducing the risk of medication errors and improving compliance.

Enhanced Data Quality

The standardized and accurately mapped data elevated overall data quality, enhancing the client’s data-driven decision-making and optimizing their reporting processes.