Physician Decision-Making: Evaluaton of Data Used in a Computerized ICU

journal articleBiomedical Informatic

Computer-Based Data Entry for Nurses in the ICU

journal articleBiomedical Informatic

Development of a Computerized Laboratory Alerting System

journal articleBiomedical Informatic

Data Visualization of Budgeting Assumptions: An Illustrative Case of Trans-disciplinary Applied Knowledge

Trans-disciplinary research combines different fields into new conceptual and methodological frameworks. In this study, the SECI model of knowledge creation, which consists of Socialization, Externalization, Combination, and Internalization conversion modes, is used to analyze the implementation of a structured budgeting visualization system by a trans-disciplinary team. Through applied research in implementing a global budgeting system, budgeting assumptions are made explicit through visualization, transforming the approach to the budgeting process and its accuracy. This visualization, in turn, is enabled by assumptions underlying revenue planning, business services and employee compensation, and a visual process. The system displays a stepped approach, indicated by icons, representing the tasks involved in the budget process. For example, the system requires uploading the previous year’s information, setting the assumptions, calculating the suggested figures based on assumptions, and amending the proposed outcome. As adapted by Rice and Rice (2005), SECI is applied as the socialization of tacit-to-tacit budgeting assumption knowledge is solidified during the design phase of this transformation exercise. The externalization phase, in which budgeting assumptions are transformed from tacit to explicit, is evidenced during the configuration phase of the new system. The systemic collaboration results in the explicit assumptions being collectively leveraged across the regions during and after the “go-live” phase of system development. Finally, the internalization phase involves the explicit assumptions being transformed into new tacit knowledge as the experts evolve new assumptions derived from the transformation process. Semiotics provides variance information through hue, with, for example, darker colours indicating higher variances. This trans-disciplinary communication provides the means for increased efficiency and effectiveness. The resulting budget framework is visually validated through a heatmap by comparing the budgeting accuracy and assumption complexity between the different regions where it was implemented. In summary, value is added in developing a new data visualization process, focusing on the role of budgeting assumptions and using planning process visualizations. This approach improves communication efficiency, effectiveness, and understanding of budgeting while enhancing accuracy

Does administrative data reflect individual experience? Comparing an index of poverty with individually collected data on financial well-being in a multi-ethnic community

The Income Deprivation Affecting Children Index (IDACI) uses administrative data to count children living in households in receipt of both in-work and out-of-work means-tested benefits and provides small area ranking as an indicator of child poverty in neighbourhoods. Benefit take-up rates within an area will affect its reliability. We aimed to examine benefit take-up rates and compare area ranking by the IDACI with ranking using individually reported data across areas of varying ethnic composition. Mothers living in areas with high minority ethnic density were less likely to report claiming a benefit than those in majority White or mixed areas, despite reporting lower incomes. The correlation between self-reported material difficulties and worsening IDACI rank was much lower in areas characterised by minority ethnic populations. Further investigation into the performance of area-based deprivation measures in areas with high minority ethnic density is needed

Surgical-PEARL protocol:a multicentre prospective cohort study exploring aetiology, management and outcomes for patients with congenital anomalies potentially requiring surgical intervention

INTRODUCTION: Congenital anomalies affect over 2% of pregnancies. Surgical advances have reduced mortality and improved survival for patients with congenital anomalies potentially requiring surgical (CAPRS) intervention. However, our understanding of aetiology, diagnostic methods, optimal management, outcomes and prognostication is limited. Existing birth cohorts have low numbers of individual heterogenous CAPRS. The Surgical Paediatric congEnital Anomalies Registry with Long term follow-up (Surgical-PEARL) study aims to establish a multicentre prospective fetal, child and biological parent cohort of CAPRS. METHODS AND ANALYSIS: From 2022 to 2027, Surgical-PEARL aims to recruit 2500 patients with CAPRS alongside their biological mothers and fathers from up to 15 UK centres. Recruitment will be antenatal or postnatal dependent on diagnosis timing and presentation to a recruitment site. Routine clinical data including antenatal scans and records, neonatal intensive care unit (NICU) records, diagnostic and surgical data and hospital episode statistics will be collected. A detailed biobank of samples will include: parents’ blood and urine samples; amniotic fluid if available; children’s blood and urine samples on admission to NICU, perioperatively or if the child has care withdrawn or is transferred for extracorporeal membrane oxygenation; stool samples; and surplus surgical tissue. Parents will complete questionnaires including sociodemographic and health data. Follow-up outcome and questionnaire data will be collected for 5 years. Once established we will explore the potential of comparing findings in Surgical-PEARL to general population cohorts born in the same years and centres. ETHICS AND DISSEMINATION: Ethical and health research authority approvals have been granted (IRAS Project ID: 302251; REC reference number 22/SS/0004). Surgical-PEARL is adopted onto the National Institute for Health Research Clinical Research Network portfolio. Findings will be disseminated widely through peer-reviewed publication, conference presentations and through patient organisations and newsletters. TRIAL REGISTRATION NUMBER: ISRCTN12557586