1,502 research outputs found

    A review of human factors principles for the design and implementation of medication safety alerts in clinical information systems.

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    The objective of this review is to describe the implementation of human factors principles for the design of alerts in clinical information systems. First, we conduct a review of alarm systems to identify human factors principles that are employed in the design and implementation of alerts. Second, we review the medical informatics literature to provide examples of the implementation of human factors principles in current clinical information systems using alerts to provide medication decision support. Last, we suggest actionable recommendations for delivering effective clinical decision support using alerts. A review of studies from the medical informatics literature suggests that many basic human factors principles are not followed, possibly contributing to the lack of acceptance of alerts in clinical information systems. We evaluate the limitations of current alerting philosophies and provide recommendations for improving acceptance of alerts by incorporating human factors principles in their design

    Analysing the bioactive makeup of demineralised dentine matrix on bone marrow mesenchymal stem cells for enhanced bone repair

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    Dentine matrix has proposed roles for directing mineralised tissue repair in dentine and bone; however, the range of bioactive components in dentine and specific biological effects on bone-derived mesenchymal stem cells (MSCs) in humans are less well understood. The aims of this study were to further elucidate the biological response of MSCs to demineralised dentine matrix (DDM) in enhancing wound repair responses and ascertain key contributing components. Dentine was obtained from human teeth and DDM proteins solubilised with ethylenediaminetetraacetic acid (EDTA). Bone marrow derived MSCs were commercially obtained. Cells with a more immature phenotype were then selected by preferential fibronectin adhesion (FN-BMMSCs) for use in subsequent in vitro assays. DDM at 10 Ī¼g/mL reduced cell expansion, attenuated apoptosis and was the minimal concentration capable of inducing osteoblastic differentiation. Enzyme-linked immunosorbent assay (ELISA) quantification of growth factors indicated physiological levels produced the above responses; transforming growth factor Ī² (TGF-Ī²1) was predominant (15.6 ng/mg DDM), with relatively lower concentrations of BMP-2, FGF, VEGF and PDGF (6.2-4.7 ng/mg DDM). Fractionation of growth factors from other DDM components by heparin affinity chromatography diminished osteogenic responses. Depletion of biglycan from DDM also attenuated osteogenic potency, which was partially rescued by the isolated biglycan. Decorin depletion from DDM had no influence on osteogenic potency. Collectively, these results demonstrate the potential of DDM for the delivery of physiological levels of growth factors for bone repair processes, and substantiate a role for biglycan as an additional adjuvant for driving osteogenic pathways

    Measuring patient safety in primary care: The development and validation of the ā€œPatient Reported Experiences and Outcomes of Safety in Primary Careā€ (PREOS-PC)

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    This is the author accepted manuscript. The final version is available from Annals of Family Medicine via the DOI in this recordPURPOSE We set out to develop and validate a patient-reported instrument for measuring experiences and outcomes related to patient safety in primary care. METHOD The instrument was developed in a multistage process supported by an international expert panel and informed by a systematic review of instruments, a meta-synthesis of qualitative studies, 4 patient focus groups, 18 cognitive interviews, and a pilot study. The trial version of Patient Reported Experiences and Outcomes of Safety in Primary Care (PREOS-PC) covered 5 domains and 11 scales: practice activation (1 scale); patient activation (1 scale); experiences of patient safety events (1 scale); harm (6 scales); and general perceptions of patient safety (2 scales). The questionnaire was posted to 6,736 patients in 45 practices across England. We used ā€œgold standardā€ psychometric methods to evaluate its acceptability, reliability, structural and construct validity, and ability to discriminate among practices. RESULTS 1,244 completed questionnaires (18.5%) were returned. Median itemspecific response rate was 91.3% (interquartile range 28.0%). No major ceiling or floor effects were observed. All 6 multi-item scales showed high internal consistency (Cronbachā€™s Ī± 0.75-0.96). Factor analysis, correlation between scales, and known group analyses generally supported structural and construct validity. The scales demonstrated a heterogeneous ability to discriminate between practices. The final version of PREOS-PC consisted of 5 domains, 8 scales, and 58 items. CONCLUSIONS PREOS-PC is a new multi-dimensional patient safety instrument for primary care developed with experts and patients. Initial testing shows its potential for use in primary care, and future developments will further address its use in actual clinical practice.UK National Institute for Health Research School for Primary Care Research (NIHR SPCR

    Quantifying hypoxia with diffuse reflectance spectroscopy for advanced prognostication and real-time response monitoring in rectal cancer: an in vivo feasibility study

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    Tumour hypoxia is a critical factor in treatment failure and resistance, and its accurate measurement with diffuse reflectance spectroscopy (DRS) could be used for prognostic and response monitoring purposes. In this in vivo characterisation study, we sequentially measured oxygenation trends over the entire course of tumour growth in mice using a multi-depth, fibre-optic DRS probe. Results demonstrated a clear downtrend in oxygenation over time. This progression was not always linear, with significant heterogeneity over time and between mice. Our findings will be further validated against gold standards prior to investigating whether hypoxia can be used to predict radiotherapy responses

    Primary care medication safety surveillance with integrated primary and secondary care electronic health records: a cross-sectional study

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    Introduction: The extent of preventable medication-related hospital admissions and medication-related issues in primary care is significant enough to justify developing decision support systems for medication safety surveillance. The prerequisite for such systems is defining a relevant set of medication safety-related indicators and understanding the influence of both patient and general practice characteristics on medication prescribing and monitoring. Objective: The aim of the study was to investigate the feasibility of linked primary and secondary care electronic health record data for surveillance of medication safety, examining not only prescribing but also monitoring, and associations with patient- and general practice-level characteristics. Methods: A cross-sectional study was conducted using linked records of patients served by one hospital and over 50 general practices in Salford, UK. Statistical analysis consisted of mixed-effects logistic models, relating prescribing safety indicators to potential determinants. Results: The overall prevalence (proportion of patients with at least one medication safety hazard) was 5.45 % for prescribing indicators and 7.65 % for monitoring indicators. Older patients and those on multiple medications were at higher risk of prescribing hazards, but at lower risk of missed monitoring. The odds of missed monitoring among all patients were 25 % less for males, 50 % less for patients in practices that provide general practitioner training, and threefold higher in practices serving the most deprived compared with the least deprived areas. Practices with more prescribing hazards did not tend to show more monitoring issues. Conclusions:Systematic collection, collation, and analysis of linked primary and secondary care records produce plausible and useful information about medication safety for a health system. Medication safety surveillance systems should pay close attention to patient age and polypharmacy with respect to both prescribing and monitoring failures; treat prescribing and monitoring as different statistical processes, rather than a combined measure of prescribing safety; and audit the socio-economic equity of missed monitoring

    Sample size calculations for cluster randomised controlled trials with a fixed number of clusters

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    Background\ud Cluster randomised controlled trials (CRCTs) are frequently used in health service evaluation. Assuming an average cluster size, required sample sizes are readily computed for both binary and continuous outcomes, by estimating a design effect or inflation factor. However, where the number of clusters are fixed in advance, but where it is possible to increase the number of individuals within each cluster, as is frequently the case in health service evaluation, sample size formulae have been less well studied. \ud \ud Methods\ud We systematically outline sample size formulae (including required number of randomisation units, detectable difference and power) for CRCTs with a fixed number of clusters, to provide a concise summary for both binary and continuous outcomes. Extensions to the case of unequal cluster sizes are provided. \ud \ud Results\ud For trials with a fixed number of equal sized clusters (k), the trial will be feasible provided the number of clusters is greater than the product of the number of individuals required under individual randomisation (nin_i) and the estimated intra-cluster correlation (Ļ\rho). So, a simple rule is that the number of clusters (Īŗ\kappa) will be sufficient provided: \ud \ud Īŗ\kappa > nin_i x Ļ\rho\ud \ud Where this is not the case, investigators can determine the maximum available power to detect the pre-specified difference, or the minimum detectable difference under the pre-specified value for power. \ud \ud Conclusions\ud Designing a CRCT with a fixed number of clusters might mean that the study will not be feasible, leading to the notion of a minimum detectable difference (or a maximum achievable power), irrespective of how many individuals are included within each cluster. \ud \u
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