User requirements on the future laboratory information systems

[SIMS REIN: a multi-source information system for end-stage renal disease]

In France, the prevalence of End-Stage Renal Disease (ESRD) is not precisely known. The sources of information are scattered and not coordinated. Consequently, care is ill adapted to meet the demand. The Multi-Source Information System is the basis of the Renal Epidemiology and Information Network (REIN). It is dedicated to improve and organise our medical and epidemiological knowledge of ESRD and to aid public health decision-making in this area. The proposed approach is based on the datawarehouses. This model allows a unified vision of scattered data into distinct databases, for a better management, be it particular (patient follow-up) or global (regional follow-up), with a finality of aid in decision-making. Several categories of problems were considered: the global conception of the information system, the organisation of the datawarehouse, which offers different viewpoints of the data, the integration of heterogeneous data coming from different sources, data exchange and definition of a specific ontology.

Open laboratory information systems: a case study

The EU-AIM project "OpenLabs" specified an open systems architecture for a clinical laboratory information system (LIS) environment and coined the term "open LIS". Since this conception has not yet been realized into systems and modules commercially available, two university hospitals in Norway had to specify an alternative model for openness when they, in a joint project, screened the market for a new LIS. To be open, a LIS must be (1) based on main-trend hardware and system software running under a standardized operating system, (2) designed for network-based distributed computing, (3) have sufficient documentation available to local staff, (4) be configurable through parameters, tables and scripts, and (5) have general and configurable access mechanisms both to real-time processes and to the database. The present study describes the selection process and examines the compliance of the selected LIS (NetLab) with this model of openness. It is shown that local staff have been able to adapt this LIS to various and changing requirements in the laboratory.

Specifying an open clinical laboratory information system

This paper presents an overview of the architectural infrastructure in which existing laboratory information systems can be made to interoperate with additional modules offering a range of advanced clinical laboratory functionalities. The infrastructure is based on an open distributed computing platform, and its specification is described using the open distributed processing reference model.

Remote instrument telemaintenance

In the past decade, great technological progress has been made in telemaintenance of mainframe and mini computers. As hardware technology is now available at an acceptable cost, computer aided trouble-shooting can be adapted to laboratory instrumentation in order to significantly improve repair time, avoid instrument downtime by taking advantage of predictive methods, and provide general diagnostic assistance. Depending on the size of the instrument, the telemaintenance facility can be dedicated to a single instrument or alternatively a telemaintenance server can manage multiple distributed small instruments through a Local Area Network. As complex failures can occur, the local diagnosis capabilities may be exceeded and automatic dialing for connection to computerized Remote Maintenance Centers is needed. The main advantages of such a centre, as compared to local diagnosis systems, are the increased access to more information and experience of failures from instrument installations, and consequently the provision of training data updates for Artificial Neural Networks and Knowledge Based Systems in general. When an abnormal situation is detected or anticipated by a diagnosis module, an automatic alert is given to the user, local diagnosis is activated, and for simple solutions, instructions are given to the operator. In the last resort, a human expert can be alerted who, with remote control tools, can attend to the failures. For both local and remote trouble-shooting, the data provided by the instrument and connected workstation is of paramount importance for the efficiency and accuracy of the diagnosis. Equally, the importance of standardization of telemaintenance communication protocols is addressed.