Quantifying multifaceted needs captured at the point of care. Development of a Disabilities Terminology Set and Disabilities Complexity Scale.

AIMS: To develop a Disabilities Terminology Set and quantify the multifaceted needs of disabled children and their families in a district disability clinic population. METHOD: Data from structured electronic clinic letters of children attending paediatric disability clinics from June 2007 to May 2012 in Sunderland, north-east England collected at the point of clinical care were analysed to determine appropriate terms for consistent recording of each need and issue. Terms were collated to count the number of needs per child. RESULTS: A Systemized Nomenclature of Medicine - Clinical Terms subset of 296 terms was identified and published, and 8392 consultations for 1999 children were reviewed. The required number of clinic appointments correlated strongly with the number of needs identified. Children with intellectual disabilities in addition to cerebral palsy and epilepsy had more than double the number of conditions, technology dependencies, and family-reported issues than those without. Disabled children who subsequently died had the highest burden of needs (p=0.007). INTERPRETATION: Detailed data about needs generated outputs useful for local care pathway development and service planning. Sufficient evidence was provided for successful business cases leading to the appointment of additional paediatric disability consultants. Counting numbers of needs and issues quantifies complexity in a straightforward way. This could underpin needs-based commissioning of services.

PPARalpha siRNA-treated expression profiles uncover the causal sufficiency network for compound-induced liver hypertrophy.

Uncovering pathways underlying drug-induced toxicity is a fundamental objective in the field of toxicogenomics. Developing mechanism-based toxicity biomarkers requires the identification of such novel pathways and the order of their sufficiency in causing a phenotypic response. Genome-wide RNA interference (RNAi) phenotypic screening has emerged as an effective tool in unveiling the genes essential for specific cellular functions and biological activities. However, eliciting the relative contribution of and sufficiency relationships among the genes identified remains challenging. In the rodent, the most widely used animal model in preclinical studies, it is unrealistic to exhaustively examine all potential interactions by RNAi screening. Application of existing computational approaches to infer regulatory networks with biological outcomes in the rodent is limited by the requirements for a large number of targeted permutations. Therefore, we developed a two-step relay method that requires only one targeted perturbation for genome-wide de novo pathway discovery. Using expression profiles in response to small interfering RNAs (siRNAs) against the gene for peroxisome proliferator-activated receptor alpha (Ppara), our method unveiled the potential causal sufficiency order network for liver hypertrophy in the rodent. The validity of the inferred 16 causal transcripts or 15 known genes for PPARalpha-induced liver hypertrophy is supported by their ability to predict non-PPARalpha-induced liver hypertrophy with 84% sensitivity and 76% specificity. Simulation shows that the probability of achieving such predictive accuracy without the inferred causal relationship is exceedingly small (p < 0.005). Five of the most sufficient causal genes have been previously disrupted in mouse models; the resulting phenotypic changes in the liver support the inferred causal roles in liver hypertrophy. Our results demonstrate the feasibility of defining pathways mediating drug-induced toxicity from siRNA-treated expression profiles. When combined with phenotypic evaluation, our approach should help to unleash the full potential of siRNAs in systematically unveiling the molecular mechanism of biological events.

Implementation of SNOMED CT in an online clinical database.

A number of strategies have been published to accelerate the use of electronic health records in caring for patients across the UK. These visions of 'eHealth' have a common requirement for robust interoperability between different systems with the use of appropriate information and data standards. SNOMED CT, a comprehensive terminology that NHS England intends to adopt across all care settings by 2020, is a key component of these standards but there is currently limited experience in its use in live clinical settings. Within NHS Wales, an electronic patient record system has been developed since 2009 with a focus on a core generic clinical information model built using SNOMED CT. Our experience is that SNOMED CT is a usable and clinician-friendly terminology but that its size and scope must be considered during implementation.

An intelligent ventilation and oxygenation management system in neonatal intensive care using fuzzy trend template fitting.

This paper describes an open loop feedback intelligent system for neonatal intensive care management. The system provides a tool enabling the user to make the final decision to accept or reject the advice given. The system collects 18 parameters from the bedside monitor and ventilator using a Medical Information Bus (MIB) system. Comparison between the system's recommendations and seven clinical users (three doctors and four nurses) actions was made during monitoring of seven neonates with gestation age of 27-31 weeks for 124.13 h (mu=17.7329, sigma=5.3843 h, range=10.40-23.85 h). The validation process compared the recommendations triggered by the system with the user feedback (agree, disagree, wait). The system made 191 recommendations in total, 33 of which (17%) were for ventilation and 158 (83%) for oxygenation. The clinician agreed with the system ventilation decisions in 30 occasions (91%) and in 148 occasions for the system oxygenation decisions (94%). The overall percentage of the agreement between the system and the clinician was 93%.

Neonatal nurse staffing and delivery of clinical care in the SSBC Newborn Network.

OBJECTIVE: To measure nursing workload and timely completion of essential tasks in relation to the staffing levels recommended by the British Association of Perinatal Medicine (BAPM) in Staffordshire, Shropshire and Black Country Newborn Network. METHODS: A prospective observational study was conducted measuring the time taken by selected nurses to undertake the necessary tasks for babies receiving different levels of care in the Network's six constituent neonatal units. An independent observer was used. The unit and individual's workload was evaluated against BAPM standards. Delays in essential predetermined tasks were recorded. The impact on quantity of care given and on the number of delayed tasks were compared between those with the recommended workload or less and those overstretched. RESULTS: Between October 2008 and February 2009, 89 nurses were observed caring for 244 neonates over 534 h. 54% of nursing shifts failed to meet BAPM standards. Nurses with workload greater than the BAPM-recommended levels demonstrated a 28% decrease in median time spent on clinical care per baby. 92 (17%) essential tasks were delayed >1 h or not done. Delays/omissions were more likely when BAPM standards were not met (53% vs 40%, p=0.049). In nursing observations without delays/omissions, accommodating for adequate nursing breaks and working in the same area, nurses could cater for no more than 1.2, 1.5 and 2.7 babies in intensive care, high dependency care and special care, respectively. CONCLUSION: Understaffing leads to measurable problems including delays to essential treatment and reduced clinical care. BAPM standards are not aspirational and should be regarded as a minimum. Further research on optimising nursing care efficiency with limited nursing resources is necessary.

The challenge of the information culture for the paediatrician.

'Liberating the NHS' and the new outcomes framework place information at the heart of the management of the National Health Service (NHS) and develop further the quality framework defined by Lord Darzi. In support of children, paediatricians have a responsibility to understand the informatics agenda and to ensure that data collection is as accurate as possible. There are particular difficulties in supplying a comprehensive health record for children and providing them with the benefits of access to their health records. It is essential that paediatricians work to ensure that these problems are overcome and that children do not miss out because of legal, practical and ethical issues which can be overcome, but often are permitted to stand in the way of real improvements.