Development and implementation of a multi-centre information system for paediatric and infant critical care

With no UK collective information system, a need existed to establish an integrated information system for public and private sector hospitals providing paediatric and infant critical care services. A lack of information in the past made it difficult for those procuring, providing and monitoring services to make informed, evidence-based decisions using reliable integrated data.

To develop and implement a collective multi-purpose information system for paediatric and infant critical care that was easily adaptable to any UK infant or paediatric critical care setting. Information outputs had to fulfil policy requirements and meet the needs of stakeholders.

Two minimum datasets, corresponding data definitions, survey forms and a user database were developed through a process of consultation by utilising an information partnership. Design, content, development and implementation issues were identified, discussed and resolved through a co-ordinated collaborative process.

Data collection was implemented in all London and Brighton National Health Service (NHS) general and cardio-thoracic paediatric intensive care (PIC) units, several private PIC units and one NHS tertiary referral neonatal unit (NNU) 24 months from project start.

The development of universal integrated information systems for defined settings of care is achievable within reasonable timeframes; however, successful development and implementation requires working within an information partnership to maximise co-ordination, co-operation and collaboration. Those collecting and using data must be identified and involved in all aspects of development from project start. Financial and manpower resources must be well planned. Datasets should be as small as possible in order to make the collection of complete and valid data realistically achievable. When considering service-based information needs, considerable thought should be given to a multi-purpose; multi-use approach based on the most refined minimum dataset possible.