Building Data-Driven Pathways From Routinely Collected Hospital Data:A Case Study on Prostate Cancer

Background: Routinely collected data in hospitals is complex, typically heterogeneous, and scattered across multiple Hospital Information Systems (HIS). This big data, created as a byproduct of health care activities, has the potential to provide a better understanding of diseases, unearth hidden patterns, and improve services and cost. The extent and uses of such data rely on its quality, which is not consistently checked, nor fully understood. Nevertheless, using routine data for the construction of data-driven clinical pathways, describing processes and trends, is a key topic receiving increasing attention in the literature. Traditional algorithms do not cope well with unstructured processes or data, and do not produce clinically meaningful visualizations. Supporting systems that provide additional information, context, and quality assurance inspection are needed. Objective: The objective of the study is to explore how routine hospital data can be used to develop data-driven pathways that describe the journeys that patients take through care, and their potential uses in biomedical research; it proposes a framework for the construction, quality assessment, and visualization of patient pathways for clinical studies and decision support using a case study on prostate cancer. Methods: Data pertaining to prostate cancer patients were extracted from a large UK hospital from eight different HIS, validated, and complemented with information from the local cancer registry. Data-driven pathways were built for each of the 1904 patients and an expert knowledge base, containing rules on the prostate cancer biomarker, was used to assess the completeness and utility of the pathways for a specific clinical study. Software components were built to provide meaningful visualizations for the constructed pathways. Results: The proposed framework and pathway formalism enable the summarization, visualization, and querying of complex patient-centric clinical information, as well as the computation of quality indicators and dimensions. A novel graphical representation of the pathways allows the synthesis of such information. Conclusions: Clinical pathways built from routinely collected hospital data can unearth information about patients and diseases that may otherwise be unavailable or overlooked in hospitals. Data-driven clinical pathways allow for heterogeneous data (ie, semistructured and unstructured data) to be collated over a unified data model and for data quality dimensions to be assessed. This work has enabled further research on prostate cancer and its biomarkers, and on the development and application of methods to mine, compare, analyze, and visualize pathways constructed from routine data. This is an important development for the reuse of big data in hospitals

Photothermal excitation of microcantilevers in liquid: effect of the excitation laser position on temperature and vibrational amplitude

Demands to improve the sensitivity and measurement speed of dynamic scanning force microscopy and cantilever sensing applications necessitate the development of smaller cantilever sensors. As a result, methods to directly drive cantilevers, such as photothermal or magnetic excitation, are gaining in importance. Presented is a report on the effect of photothermal excitation of microcantilevers on the increase in steady-state temperature and the dynamics of higher mode vibrations. First, the local temperature increase upon continuous irradiation with laser light at different positions along the cantilever was measured and compared with finite element analysis data. The temperature increase was highest when the heating laser was positioned at the free end of the cantilever. Next, the laser intensity was modulated to drive higher flexural modes to resonance. The dependence of the cantilever dynamics on the excitation laser position was assessed and was in good agreement with the analytical expressions. An optimal position to simultaneously excite all flexural modes of vibration with negligible heating was found at the clamped end of the cantilever. The reports findings are essential for optimisation of the excitation efficiency to minimise the rise in temperature and avoid damaging delicate samples or functionalisation layers

International variability in 20 m shuttle run performance in children and youth: who are the fittest from a 50-country comparison? A systematic literature review with pooling of aggregate results

Objectives To describe and compare 20 m shuttle run test (20mSRT) performance among children and youth across 50 countries; to explore broad socioeconomic indicators that correlate with 20mSRT performance in children and youth across countries and to evaluate the utility of the 20mSRT as an international population health indicator for children and youth. Methods A systematic review was undertaken to identify papers that explicitly reported descriptive 20mSRT (with 1-min stages) data on apparently healthy 9–17 year-olds. Descriptive data were standardised to running speed (km/h) at the last completed stage. Country-specific 20mSRT performance indices were calculated as population-weighted mean z-scores relative to all children of the same age and sex from all countries. Countries were categorised into developed and developing groups based on the Human Development Index, and a correlational analysis was performed to describe the association between country-specific performance indices and broad socioeconomic indicators using Spearman\u27s rank correlation coefficient. Results Performance indices were calculated for 50 countries using collated data on 1 142 026 children and youth aged 9–17 years. The best performing countries were from Africa and Central-Northern Europe. Countries from South America were consistently among the worst performing countries. Country-specific income inequality (Gini index) was a strong negative correlate of the performance index across all 50 countries. Conclusions The pattern of variability in the performance index broadly supports the theory of a physical activity transition and income inequality as the strongest structural determinant of health in children and youth. This simple and cost-effective assessment would be a powerful tool for international population health surveillance

The 20-m shuttle run: Assessment and interpretation of data in relation to youth aerobic fitness and health

Cardiorespiratory fitness (CRF) is a good summative measure of the body’s ability to perform continuous, rhythmic, dynamic, large-muscle group physical activity, and exercise. In children, CRF is meaningfully associated with health, independent of physical activity levels, and it is an important determinant of sports and athletic performance. Although gas-analyzed peak oxygen uptake is the criterion physiological measure of children’s CRF, it is not practical for population-based testing. Field testing offers a simple, cheap, practical alternative to gas analysis. The 20-m shuttle run test (20mSRT)—a progressive aerobic exercise test involving continuous running between 2 lines 20 m apart in time to audio signals—is probably the most widely used field test of CRF. This review aims to clarify the international utility of the 20mSRT by synthesizing the evidence describing measurement variability, validity, reliability, feasibility, and the interpretation of results, as well as to provide future directions for international surveillance. The authors show that the 20mSRT is an acceptable, feasible, and scalable measure of CRF and functional/exercise capacity, and that it has moderate criterion validity and high to very high reliability. The assessment is pragmatic, easily interpreted, and results are transferable to meaningful and understandable situations. The authors recommend that CRF, assessed by the 20mSRT, be considered as an international population health surveillance measure to provide additional insight into pediatric population health

Predicting melatonin suppression by light in humans:Unifying photoreceptor-based equivalent daylight illuminances, spectral composition, timing and duration of light exposure

Light‐induced melatonin suppression data from 29 peer‐reviewed publications was analysed by means of a machine‐learning approach to establish which light exposure characteristics (ie photopic illuminance, five α‐opic equivalent daylight illuminances [EDIs], duration and timing of the light exposure, and the dichotomous variables pharmacological pupil dilation and narrowband light source) are the main determinants of melatonin suppression. Melatonin suppression in the data set was dominated by four light exposure characteristics: (1) melanopic EDI, (2) light exposure duration, (3) pupil dilation and (4) S‐cone‐opic EDI. A logistic model was used to evaluate the influence of each of these parameters on the melatonin suppression response. The final logistic model was only based on the first three parameters, since melanopic EDI was the best single (photoreceptor) predictor that was only outperformed by S‐cone‐opic EDI for (photopic) illuminances below 21 lux. This confirms and extends findings on the importance of the metric melanopic EDI for predicting biological effects of light in integrative (human‐centric) lighting applications. The model provides initial and general guidance to lighting practitioners on how to combine spectrum, duration and amount of light exposure when controlling non‐visual responses to light, especially melatonin suppression. The model is a starting tool for developing hypotheses on photoreceptors’ contributions to light's non‐visual responses and helps identifying areas where more data are needed, like on the S‐cone contribution at low illuminances

L’humour passe à table

Entretien réalisé le 4 avril 2016 à la Chapelle des Cordeliers (Clermont-Ferrand), dans le cadre du festival LAC 2016.Interview at the Chapelle des Cordeliers (Clermont-Ferrand), during the LAC festival 2016, April 4th 2016

Making a case for cardiorespiratory fitness surveillance among children and youth

We review the evidence that supports cardiorespiratory fitness (CRF) as an important indicator of current and future health among school-aged children and youth, independent of physical activity levels. We discuss the merit of CRF measurement for population health surveillance and propose the development of CRF guidelines to help support regional, national, and international surveillance efforts