Application + Platform Development | AI + Data Transformation | Healthcare

Turning Fragmented Records into Research-Ready Data

A leading pediatric hospital wanted to study patients with specific diagnoses and co-morbidities to strengthen evidence-based medicine. But medical records, lab results, and billing information sat in incompatible systems, limiting the research team’s ability to analyze treatment patterns across patient populations.

Aditi partnered with the hospital to build an integrated disease management system and clinical registry. By bringing patient information into a structured resource, the system helped the hospital unlock several million dollars in research grants and supported the development of evidence-based guidelines.

At a glance

Medical records, labs, billing systems, and EMRs

Data sources

Disease management system and clinical registry

Clinical data resource

System helped unlock several million dollars in grants

Research funding

The Challenge

When scattered data holds back discovery

The Challenge

The hospital’s pediatric research team needed to gather and connect information from multiple sources to study treatment patterns across patient populations. Its goal was a clinical registry that could support population studies and the development of evidence-based medicine protocols.

The information was scattered across lab reports, billing systems, and medical records, including handwritten notes. Sources differed in format, access protocols, and rules for data use. The hospital also had to account for HIPAA requirements when capturing and using sensitive patient information.

The Solution

Turning Data Silos into a Research Engine

The Solution

Aditi partnered with the hospital to build an integrated disease management system—designed to securely capture patient data, consolidate it into a usable format, and populate a robust clinical registry that could power pediatric research and care innovation.

  • Intelligent Architecture & Integration: Aditi deployed an application engineer and a technical director to design and build a scalable system using Java, J2EE, and Oracle. The team established data standards and engineered a data warehouse structure capable of bringing together patient records from multiple siloed systems—including labs, billing, and EMRs.
  • Compliance-First Approach: Every component of the system was developed with HIPAA requirements in mind, ensuring that all patient data remained secure and confidential throughout ingestion, storage, and use. Aditi also aligned the solution to support reimbursement justifications using billing data tied directly to patient outcomes—bridging the gap between care quality and operational needs.

Business Outcomes

GrantsMillions in research grants secured.
The new disease management system helped the hospital unlock several million dollars in grants by providing clean, structured data that demonstrated treatment efficacy across patient populations.
ProtocolsEvidence-based protocols developed.
The insights drawn from the system enabled physicians to establish evidence-based guidelines now used by the wider pediatric care community—directly improving outcomes for children with complex conditions.
ComplianceCompliance and reimbursement alignment.
By tying patient outcomes to billing data, the hospital was able to validate its treatment decisions and ensure the financial sustainability of innovative care models.

The impact of Aditi’s work extended beyond the hospital walls—contributing to both institutional funding and broader healthcare advancement.

What Changed

Before the engagement, incompatible records constrained the hospital’s ability to study diagnoses and treatment patterns across patient populations.

The integrated system gave the research team a structured clinical resource for those studies, while connecting patient outcomes with the billing information needed to support treatment and reimbursement decisions.

Technology Environment

Technology Environment

Java, J2EE, Oracle, Data warehouse structure

Technology Environment

  • Java
  • J2EE
  • Oracle
  • Data warehouse structure

Ready to connect the data that can advance healthcare outcomes?