StatSoft Poland, together with the Military Institute of Medicine in Warsaw, built a comprehensive analytical ecosystem for the Military Institute of Medicine — from a data warehouse, through a research environment for physicians, to management reports and an Polish National Health Fund (NHF) reimbursement optimizer.

Challenge

The Military Institute of Medicine in Warsaw (MIM) is one of the largest and most highly regarded medical institutions in Poland — serving both clinical functions and conducting extensive research programs. The hospital faced typical yet serious challenges characteristic of large medical facilities.

Clinical, laboratory, and administrative data were scattered across multiple separate IT systems — the Hospital Information System (HIS), the Radiology Information System (RIS), the Laboratory Information System (LIS), and specialized departmental systems. Each system operated independently, storing information in different formats and databases (Sybase, Microsoft SQL Server, XML and CSV files).

Key problems: No single “source of truth” for patient and treatment process data. Researchers had to manually collect data for studies in spreadsheets — a time-consuming, error-prone process that discouraged new research initiatives. Management lacked an up-to-date, consistent view of key hospital indicators. Settlements with the National Health Fund required tedious manual verification, and the lack of early warning about contract limit overruns exposed the hospital to financial losses.

The objective of the “TeleMedNet — Medical Scientific-Diagnostic Platform” project, co-financed by the European Regional Development Fund under the Innovative Economy Operational Programme, was — within the scope of the Military Institute of Medicine’s tasks — to build a reliable IT infrastructure ensuring validated clinical data and supporting both innovative scientific research and effective hospital management.

Solution

StatSoft Poland, in collaboration with experts from the Military Institute of Medicine, designed and implemented a comprehensive platform for medical knowledge integration, analysis, and publishing, consisting of seven closely interconnected components. The system architecture was built around the central STATMED Medical Data Warehouse, which integrated data from all of the hospital’s source systems into a single, consistent repository

STATMED Medical Data Warehouse

A central database combining relational and multidimensional (OLAP) structures — optimized for both reporting and exploratory analysis.

Data Loading Module (ETL)

Automated data extraction from HIS, RIS, LIS, and other sources, with cleansing, validation, and transformation into the target warehouse structure.

Medical Research Environment and wizard (MRE)

An advanced wizard module within STATISTICA software, guiding researchers step by step: from data filtering, through variable and spreadsheet layout selection,
to automated statistical analysis.

Management Portal

A set of interactive web reports
with key hospital indicators — from mortality and bed occupancy rates to patient volume forecasts.

NHF Reimbursement Reports

Dedicated reports monitoring the execution of National Health Fund contracts, with early warning indicators for limit overruns.

DRG Optimizer

A web-based tool identifying the DRG (Diagnosis-Related Group) for each hospitalization episode, along with the conditions required to qualify. Diagnosis Related Groups (DRG) is a health care services billing method, used by the National Health Fund, which assumes that certain groups of patients require similar treatment.

Management Reports (TeleMedNet II)

Control charts and indicators (deaths, hospital-acquired infections, length of stay, operating room utilization) built with Dundas and SSRS technology.

The Medical Research Environment, the platform’s flagship component, was designed with physicians and researchers in mind — its interface uses medical terminology and data is grouped according to medical documentation elements. The MRE wizard enables selection from approximately 60 data attributes grouped into 9 thematic categories, defining temporal relationships between variables, and automating repeatable analyses using STATISTICA macros and workspaces.

During the TeleMedNet II project, the system was significantly expanded — a multi-level data structure was introduced (hospitalization → stay → procedure → lab result), along with advanced text and time-based filtering, a permissions model based on Active Directory groups, and integration with STATISTICA Enterprise Server for automated analyses.

Results

The implementation of the TeleMedNet platform delivered measurable benefits across all areas of hospital operations, particularly in management, reimbursement, and the preparation and execution of scientific research.

✓ A single, consistent view of data — researchers and managers gained access to an integrated, validated source of information instead of scattered and inconsistent data from multiple systems.

✓ Radical acceleration of research work — the MRE wizard reduced data preparation time for analysis from days or weeks to minutes, freeing physicians from the tedious task of collecting data in spreadsheets.

✓ Access to previously unavailable analyses — the multi-level data structure and advanced filters enabled research that had not previously been considered due to the complexity of data acquisition.

✓ Improved data quality across the entire hospital — implementing validation processes for warehouse data loading forced improvements in data collection procedures in the source systems.

✓ Optimization of NHF revenue — the DRG Optimizer and contract monitoring reports enabled early detection of limit overruns and optimal selection of reimbursement groups.

✓ Real-time management decision support — the Management Portal with bed occupancy forecasts, mortality analysis, and physician performance monitoring provided management with the tools to make well-informed decisions.

✓ Automation of repeatable analyses — the processing mechanism in MRE and integration with STATISTICA Enterprise Server enabled fully automated, recurring report and analysis generation.

“

The key to the project’s success was a deep understanding of hospital data sources and information flows, as well as the needs of both researchers and hospital managers.

— TeleMedNet Project Team (Kulach, Jakubowski, Murawski — StatSoft Poland / Military Institute of Medicine)

Summary

The TeleMedNet project demonstrates how a comprehensive approach to medical data integration and analysis can simultaneously support scientific research, improve hospital management quality, and optimize reimbursement processes. The platform built by StatSoft Poland transformed scattered, hard-to-access clinical data into a structured, analysis-ready knowledge base — accessible to both researchers conducting advanced statistical studies and management making daily operational decisions.

The success of the implementation is confirmed by the continuation of cooperation within the TeleMedNet II project, in which the platform was significantly expanded with new analytical capabilities, an advanced permissions model, and management reports with control charts. This solution represents a model example of applying advanced data analytics in the healthcare sector — where information quality directly translates into treatment quality and the economic efficiency of a facility.

Authors: StatSoft oraz Wojskowy Instytut Medyczny

Learn More:

Practical Predictive Analytics and Decisioning Systems for Medicine

Platform for Data Integration and Analysis and Publishing Medical Knowledge as Done in a Large Hospital; 1019 – 1029; Leslaw Kulach MSc, Piotr Murawski MSc.

Case Study: A Platform for Medical Knowledge Integration, Analysis, and Publishing in a Large Hospital

Challenge

Solution

Results

Summary