Patient data mapping solution

Our client is a leading U.S. healthcare provider with a growing network of healthcare facilities across the country. With the increasing number of diverse patient data sources, including different medical institutions and insurance companies, patient information had become inconsistent, fragmented, incorrect, and duplicated.

The following problems affected patient data:

• inconsistent data entry
• lack of standardized IDs
• irrelevant data
• identical names

While our client’s initial request was for centralized data storage, addressing the underlying challenge of siloed and inconsistent patient data became a critical aspect of the solution.

We designed a comprehensive patient data mapping module within the data warehouse solution, enabling patient data standardization and unification.

The module collects data from different sources—such as electronic medical records (EMRs), hospital data, EMR claims, and payor claims—standardizes and cleanses it, and integrates it into one reliable database.

Our approach to patient data mapping includes:

• Patient data collection. Patient data is collected and mapped through the identified data flows and sources according to the mapping rules.
• Data cleansing and standardization. Combining natural language processing (NLP) and rule-based mapping, patient data is cleansed and standardized, ensuring data consistency.
• Record linkage. Data records for the same patient are identified and linked using a tool for patient validation and through manual patient data mapping and unmapping by data stewards.
• Golden records creation. Patient golden records are created by matching and merging algorithms. Preset conditions allow for secure and easy storing, sorting, and manipulation of golden data.

Patient golden records help easily identify a patient and match their identity with the information in the database. They also allow system users to create the cross-organizational healthcare reports necessary for analyzing and estimating certain metrics, including data on patients, clinics, hospitals, and payors. This ensures data accuracy, saves time on data collection, facilitates patient care, enhances decision-making, and improves treatment outcomes.

Practical case

A patient undergoes medical treatment at a hospital. Once their inpatient care is concluded, they see a clinic healthcare practitioner for a follow-up. The hospital and clinic have different databases, which can result in incomplete information, delayed treatment, or even malpractice. Patient data mapping links cross-organizational data, giving healthcare practitioners complete and reliable patient information so they are better equipped to provide proper care.

We created a solution for patient data mapping to ensure the accuracy and consistency of patient data. Patient golden records eliminate data duplicates and inaccurate data and help healthcare organizations match patients with their medical information. This facilitates operational efficiency, enhances patient care, and improves outcomes.