Managing interoperability and complexity in health systems

In recent years, we have witnessed substantial progress in the use of clinical informatics systems to support clinicians during episodes of care, manage specialised domain knowledge, perform complex clinical data analysis and improve the management of health organisations’ resources. However, the vision of fully integrated health information eco-systems, which provide relevant information and useful knowledge at the point-of-care, remains elusive. This journal Focus Theme reviews some of the enduring challenges of interoperability and complexity in clinical informatics systems. Furthermore, a range of approaches are proposed in order to address, harness and resolve some of the many remaining issues towards a greater integration of health information systems and extraction of useful or new knowledge from heterogeneous electronic data repositories

Ontology-driven, adaptive, medical questionnaires for patients with mild learning disabilities

Patients with Learning Disabilities (LD) have substantial and unmet healthcare needs, and previous studies have highlighted that they face both health inequalities and worse outcomes than the general population. Primary care practitioners are often the first port-of-call for medical consultations, and one issue faced by LD patients in this context is the very limited time available during consultations - typically less than ten minutes. In order to alleviate this issue, we propose a digital communication aid in the form of an ontology-based medical questionnaire that can adapt to a patient’s medical context as well as their accessibility needs (physical and cognitive). The application is intended to be used in advance of a consultation so that a primary care practitioner may have prior access to their LD patients’ self-reported symptoms. This work builds upon and extends previous research carried out in the development of adaptive medical questionnaires to include interactive and interface functionalities designed specifically to cater for patients with potentially complex accessibility needs. A patient’s current health status and accessibility profile (relating to their impairments) is used to dynamically adjust the structure and content of the medical questionnaire. As such, the system is able to significantly limit and focus questions to immediately relevant concerns while discarding irrelevant questions. We propose that our ontology-based design not only improves the relevance and accessibility of medical questionnaires for patients with LDs, but also provides important benefits in terms of medical knowledge-base modularity, as well as for software extension and maintenance

New compounds based on 1H-pyrrolo[2,3-b] pyridine as potent TNIK inhibitors against colorectal cancer cells. Molecular modeling studies

Cancer is a disease caused by the incorrect transformation of cells that proliferate abnormally, and it is one of the leading causes of mortality worldwide. As a result, new compounds with potential anticancer activity must be designed. In this article, three – dimensional Quantitative Structure-Activity Relationship is used to study thirty-one compounds of 1H-pyrrolo[2,3-b]pyridine derivatives as potent TNIK inhibitors against colorectal cancer cells. Their pIC50 varied from 7.37 to 9.92. The two contours, Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices (CoMSIA) are critical in determining the nature of the groups that enhance or reduce activity. The models CoMFA and CoMSIA indicate strong reliability with (Q2 = 0.65; R2 = 0.86; rtest2 = 0.97) and (Q2= 0.74; R2 = 0. 96; rtest2 = 0. 95), respectively. Based on the good findings produced by the contour maps generated by the approach model, we have suggested five drugs with strong activity against colorectal cancer cells. In addition, the ADMET characteristics of these newly designed compounds were examined in silico. These compounds were further evaluated by molecular docking, showing that two molecules, Y4 and Y5, exhibit favorable interactions with the targeted receptor and a high total score. Our vision is to develop new medicines with strong TNIK inhibitory activities that target Traf2 and Nck-interacting kinase TNIK as a therapeutic target

Evaluation of random forest and ensemble methods at predicting complications following cardiac surgery

Cardiac patients undergoing surgery face increased risk of postoperative complications, due to a combination of factors, including higher risk surgery, their age at time of surgery and the presence of co-morbid conditions. They will therefore require high levels of care and clinical resources throughout their perioperative journey (i.e. before, during and after surgery). Although surgical mortality rates in the UK have remained low, postoperative complications on the other hand are common and can have a significant impact on patients’ quality of life, increase hospital length of stay and healthcare costs. In this study we used and compared several machine learning methods – random forest, AdaBoost, gradient boosting model and stacking – to predict severe postoperative complications after cardiac surgery based on preoperative variables obtained from a surgical database of a large acute care hospital in Scotland. Our results show that AdaBoost has the best overall performance (AUC = 0.731), and also outperforms EuroSCORE and EuroSCORE II in other studies predicting postoperative complications. Random forest (Sensitivity = 0.852, negative predictive value = 0.923), however, and gradient boosting model (Sensitivity = 0.875 and negative predictive value = 0.920) have the best performance at predicting severe postoperative complications based on sensitivity and negative predictive value

'It's about what I'm able to do' : using the capabilities approach to understand the relationship between quality of life and vascular access in patients with end-stage kidney failure

Prevalence rates of End-Stage Kidney Failure (ESKF) have risen in across the world in recent years, making it one of the most common chronic illnesses. The main treatment for ESKF is haemodialysis, where one is 'connected' to a dialysis machine to clean and filter the blood via a surgically-created portal, also known as 'vascular access'. Without functioning vascular access, dialysis is impossible. People with ESKF have different experiences with their access modalities, but universally describe their access point as a 'lifeline'. Previous research has emphasised the impact it can have on wellbeing (Kalloo et al, 2016; Casey et al, 2014; Quinn et al, 2008), and specifically on short- and long-term outcomes. Capturing Quality of Life (QoL) within ESKF populations has traditionally focused upon assessing wellbeing from an objective, normative, top-down stance, rather than appreciating the nuanced effect vascular access can have as experienced by those living with kidney failure. In this article, we argue current QoL measures used with ESKF groups are insufficient at capturing the impact of vascular access on wellbeing. Using the accounts of twenty-four haemodialysis patients, we share insights into the direct and indirect influences vascular access has upon QoL, using Nussbaum's Capabilities Approach as an analytical lens. By prioritising and privileging the voices of those directly affected, the Vascular Access Specific Quality of Life (VA Specific-QOL) model provides a starting point for a more representative way to assess wellbeing in this group

Localization and Absorption of Light in 2D Composite Metal-Dielectric Films at the Percolation Threshold

We study in this paper the localization of light and the dielectric properties of thin metal-dielectric composites at the percolation threshold and around a resonant frequency where the conductivities of the two components are of the same order. In particular, the effect of the loss in metallic components are examined. To this end, such systems are modelized as random $L-C$ networks, and the local field distribution as well as the effective conductivity are determined by using two different methods for comparison: an exact resolution of Kirchoff equations, and a real space renormalization group method. The latter method is found to give the general behavior of the effective conductivity but fails to determine the local field distribution. It is also found that the localization still persists for vanishing losses. This result seems to be in agreement with the anomalous absorption observed experimentally for such systems.Comment: 14 page latex, 3 ps figures. submitte