A Data Analytics Suite for Exploratory Predictive, and Visual Analysis of Type 2 Diabetes

Long-term management of chronic disorders such as Type 2 Diabetes (T2D) requires personalised care for patients due to variation in patient characteristics and their response to a specific line of treatment. The availability of large volumes of electronic records of T2D patient data provides opportunities for application of big data analysis to gain insights into the disease manifestation and its impact on patients. Data science in healthcare has the potential to identify hidden knowledge from the database, re-confirm existing knowledge, and aid in personalising treatment. In this paper, we present a suite of data analytics for T2D disease management that allows clinicians and researchers to identify associations between different patient biological markers and T2D related complications. The analytics suite consists of exploratory, predictive, and visual analytics with capabilities including multi-tier classification of T2D patient profiles that associate them to specific conditions, T2D related complication risk prediction, and prediction of patient response to a particular line of treatment. The analytics presented in this paper explore advanced data analysis techniques, which are potential tools for clinicians in decision-making that can contribute to better management of T2D

Percutaneous revascularization for ischemic left ventricular dysfunction: Cost-effectiveness analysis of the REVIVED-BCIS2 trial

BACKGROUND: Percutaneous coronary intervention (PCI) is frequently undertaken in patients with ischemic left ventricular systolic dysfunction. The REVIVED (Revascularization for Ischemic Ventricular Dysfunction)-BCIS2 (British Cardiovascular Society-2) trial concluded that PCI did not reduce the incidence of all-cause death or heart failure hospitalization; however, patients assigned to PCI reported better initial health-related quality of life than those assigned to optimal medical therapy (OMT) alone. The aim of this study was to assess the cost-effectiveness of PCI+OMT compared with OMT alone. METHODS: REVIVED-BCIS2 was a prospective, multicenter UK trial, which randomized patients with severe ischemic left ventricular systolic dysfunction to either PCI+OMT or OMT alone. Health care resource use (including planned and unplanned revascularizations, medication, device implantation, and heart failure hospitalizations) and health outcomes data (EuroQol 5-dimension 5-level questionnaire) on each patient were collected at baseline and up to 8 years post-randomization. Resource use was costed using publicly available national unit costs. Within the trial, mean total costs and quality-adjusted life-years (QALYs) were estimated from the perspective of the UK health system. Cost-effectiveness was evaluated using estimated mean costs and QALYs in both groups. Regression analysis was used to adjust for clinically relevant predictors. RESULTS: Between 2013 and 2020, 700 patients were recruited (mean age: PCI+OMT=70 years, OMT=68 years; male (%): PCI+OMT=87, OMT=88); median follow-up was 3.4 years. Over all follow-ups, patients undergoing PCI yielded similar health benefits at higher costs compared with OMT alone (PCI+OMT: 4.14 QALYs, £22 352; OMT alone: 4.16 QALYs, £15 569; difference: −0.015, £6782). For both groups, most health resource consumption occurred in the first 2 years post-randomization. Probabilistic results showed that the probability of PCI being cost-effective was 0. CONCLUSIONS: A minimal difference in total QALYs was identified between arms, and PCI+OMT was not cost-effective compared with OMT, given its additional cost. A strategy of routine PCI to treat ischemic left ventricular systolic dysfunction does not seem to be a justifiable use of health care resources in the United Kingdom