PROSAFE: a European endeavor to improve quality of critical care medicine in seven countries.

BACKGROUND: Long-lasting shared research databases are an important source of epidemiological information and can promote comparison between different healthcare services. Here we present PROSAFE, an advanced international research network in intensive care medicine, with the focus on assessing and improving the quality of care. The project involved 343 ICUs in seven countries. All patients admitted to the ICU were eligible for data collection. METHODS: The PROSAFE network collected data using the same electronic case report form translated into the corresponding languages. A complex, multidimensional validation system was implemented to ensure maximum data quality. Individual and aggregate reports by country, region, and ICU type were prepared annually. A web-based data-sharing system allowed participants to autonomously perform different analyses on both own data and the entire database. RESULTS: The final analysis was restricted to 262 general ICUs and 432,223 adult patients, mostly admitted to Italian units, where a research network had been active since 1991. Organization of critical care medicine in the seven countries was relatively similar, in terms of staffing, case mix and procedures, suggesting a common understanding of the role of critical care medicine. Conversely, ICU equipment differed, and patient outcomes showed wide variations among countries. CONCLUSIONS: PROSAFE is a permanent, stable, open access, multilingual database for clinical benchmarking, ICU self-evaluation and research within and across countries, which offers a unique opportunity to improve the quality of critical care. Its entry into routine clinical practice on a voluntary basis is testimony to the success and viability of the endeavor.

An Interoperability Platform Enabling Reuse of Electronic Health Records for Signal Verification Studies.

Depending mostly on voluntarily sent spontaneous reports, pharmacovigilance studies are hampered by low quantity and quality of patient data. Our objective is to improve postmarket safety studies by enabling safety analysts to seamlessly access a wide range of EHR sources for collecting deidentified medical data sets of selected patient populations and tracing the reported incidents back to original EHRs. We have developed an ontological framework where EHR sources and target clinical research systems can continue using their own local data models, interfaces, and terminology systems, while structural interoperability and Semantic Interoperability are handled through rule-based reasoning on formal representations of different models and terminology systems maintained in the SALUS Semantic Resource Set. SALUS Common Information Model at the core of this set acts as the common mediator. We demonstrate the capabilities of our framework through one of the SALUS safety analysis tools, namely, the Case Series Characterization Tool, which have been deployed on top of regional EHR Data Warehouse of the Lombardy Region containing about 1 billion records from 16 million patients and validated by several pharmacovigilance researchers with real-life cases. The results confirm significant improvements in signal detection and evaluation compared to traditional methods with the missing background information.