| It consists on the creation of a customizable “Renal Data Finder” software application for automatic electronic data extraction, to be initially implemented in Renal Units running the same patient data management system. For this project it has been decided by the participating Units to consider only main clinical data of patients with Chronic Renal Failure (CRF) in conservative therapy, all collected in the electronic chart during the outpatient activity. |
| In particular a minimum common dataset has been defined, to allow the largest participation of the Units (age, gender, nephropathy, duration of disease and of CRF, diabetes at starting, followed by single values of serum creatinine, 24 hrs proteinuria, hemoglobin and hypertension collected at each clinical control during the follow-up). |
| A specific plug-in of the electronic chart has been developed and distributed to each participating Unit, with the aim to automatically recognize and extract the predefined information stored in the electronic medical records and then to export almost instantaneously these data in a preconfigured database. |
| The final merge of all the database has been performed directly via Internet by means of File Transfer Protocol or email attachments, or through shipping of conventional storage media. |
| After the set-up phase of the project (definitions, standards, software installation, local troubleshooting problems) an open work session has recently taken place with the participation of the Units, demonstrating the real-time assembling of a single unique common database containing data from > 1000 patients with CRF (see below for some preliminary data). |
| Diabetes (%) |
Mean F.U. |
Prot > 1 gr/die |
S. creat mg/dl |
|
(months) |
% |
(at first control) |
(at last control) |
|
| 14% |
59±47 |
19% |
2.17±1.0 |
2.80±1.7 |
| We consider the Renal Data Finder an example of “intelligent” data management and aggregation techniques for the support of clinical and research studies, to be performed even among different patient data management systems and within European institutional cooperations, allowing epidemiological analysis and investigations with “minimal” human efforts and taking a step forward the EDTA Registry main indications: |
| • Collect all existing specifications (on core datasets, definitions, standards, interfaces and protocols) |
| • Define dataset to be collected |
| • Propose specifications (a template for electronic data-extraction/data collection) |
| • Reach consensus with software developers, national/regional registries and renal centers |
| • Implementation of these specifications in patient data management systems |
Giuliano Colasanti |
| On behalf of the Renal Data Finder Group |
VPN Network in use at San Carlo Hospital