Becton Dickinson (United Kingdom)

BackgroundInfusion failure may have severe consequences for patients receiving critical, short–half-life infusions. Continued interruptions to infusions can lead to subtherapeutic therapy.ObjectiveThis study aims to identify and rank determinants of the longevity of continuous infusions administered through syringe drivers, using nonlinear predictive models. Additionally, this study aims to evaluate key factors influencing infusion longevity and develop and test a model for predicting the likelihood of achieving successful infusion longevity.MethodsData were extracted from the event logs of smart pumps containing information on care profiles, medication types and concentrations, occlusion alarm settings, and the final infusion cessation cause. These data were then used to fit 5 nonlinear models and evaluate the best explanatory model.ResultsRandom forest was the best-fit predictor, with an F1-score of 80.42, compared to 5 other models (mean F1-score 75.06; range 67.48-79.63). When applied to infusion data in an individual syringe driver data set, the predictor model found that the final medication concentration and medication type were of less significance to infusion longevity compared to the rate and care unit. For low-rate infusions, rates ranging from 2 to 2.8 mL/hr performed best for achieving a balance between infusion longevity and fluid load per infusion, with an occlusion versus no-occlusion ratio of 0.553. Rates between 0.8 and 1.2 mL/hr exhibited the poorest performance with a ratio of 1.604. Higher rates, up to 4 mL/hr, performed better in terms of occlusion versus no-occlusion ratios.ConclusionsThis study provides clinicians with insights into the specific types of infusion that warrant more intense observation or proactive management of intravenous access; additionally, it can offer valuable information regarding the average duration of uninterrupted infusions that can be expected in these care areas. Optimizing rate settings to improve infusion longevity for continuous infusions, achieved through compounding to create customized concentrations for individual patients, may be possible in light of the study’s outcomes. The study also highlights the potential of machine learning nonlinear models in predicting outcomes and life spans of specific therapies delivered via medical devices.

Proposal of a risk analysis model to diminish negative impact on patient care by preanalytical errors in blood gas analysis (BGA). Here we designed a Failure Mode and Effects Analysis (FMEA) risk assessment template for BGA, based on literature references and expertise of an international team of laboratory and clinical health care professionals. The FMEA identifies pre-analytical process steps, errors that may occur whilst performing BGA (potential failure mode), possible consequences (potential failure effect) and preventive/corrective actions (current controls). Probability of failure occurrence (OCC), severity of failure (SEV) and probability of failure detection (DET) are scored per potential failure mode. OCC and DET depend on test setting and patient population e.g., they differ in primary community health centres as compared to secondary community hospitals and third line university or specialized hospitals. OCC and DET also differ between stand-alone and networked instruments, manual and automated patient identification, and whether results are automatically transmitted to the patient's electronic health record. The risk priority number (RPN=SEV×OCC×DET) can be applied to determine the sequence in which risks are addressed. RPN can be recalculated after implementing changes to decrease OCC and/or increase DET. Key performance indicators are also proposed to evaluate changes. This FMEA model will help health care professionals manage and minimize the risk of preanalytical errors in BGA.

Nationally, half of all deaths occur in hospital, with 94% having a 'do not attempt cardiopulmonary resuscitation' (DNACPR) notice in place at the time of death. Recent court rulings have raised the profile of practices surrounding DNACPR orders where patients lack capacity. Failure to consult with those close to the patient in relation to DNACPR decisions is a breach of the right to respect for private and family life under article8 of the Human Rights Act. A report from 2016 found that those close to the patient were not consulted before one out of every five DNACPR orders are placed. We advocate addressing the issue of resuscitation in patients with a fractured neck of femur who are approaching the end of their lives. Where the patient lacks capacity, there is a legal duty to consult with those close to the patient where it is practicable and appropriate to do so. There must be a convincing and well evidenced reason to proceed without consultation, and the orthopaedic surgeon should exercise extreme caution before doing so.

Personalised health care is an evolution, moving away from a disease-focused model of care, translating scientific and technological advances into benefits for patients, and placing them at the centre of the patients' health and care. Companion diagnostics emerge as a very specific and special group of in vitro diagnostics among the different technologies shaping the personalised health care spectrum. Companion diagnostics provide highly valuable information, allowing patients, health practitioners and payers to decide with a higher level of certainty on the potential benefits of a treatment or care pathway. Decreasing uncertainty may result in a more efficient selection of treatments and care, targeted at subpopulations that are most likely to benefit. Companion diagnostics account for a minimal portion of the already small expenditure on in vitro diagnostics (far less than 1% of total health care expenditure), and yet they provide the means to limit inefficient use of health care resources while optimising patient outcomes. It is clear that equal access to personalised health care is still an issue across the EU. One of the most common perceived barriers is affordability. The investment in companion diagnostics can provide long-term value for patients and health care systems, shifting resources to areas of need. Health systems do not fully recognise yet the value that companion diagnostics bring to make personalised health care more affordable across the EU. This inhibits patient access to personalised treatments and care, preventing improved outcomes. In many countries, market access frameworks for diagnostic tests are fragmented and not aligned with specific funding and reimbursement mechanisms, discouraging the use of these tests. Emerging evidence shows that patients are missing out on the appropriate tests and treatments while a reduction in the inefficient use of health care resources is not realised. This article outlines some of these market access barriers for companion diagnostics in the EU, including reimbursement challenges specific to some member states (Germany, the UK, and France). Furthermore, proposals addressing barriers and increasing timely patient access to companion diagnostics in the EU are presented.

While continued interest in the application of priority-setting technologies is perhaps unsurprising in a time of austerity, they require sensitive implementation for their full potential benefits to be realized. This article looks at the role and value of leadership in addressing problems of a lack of perceived legitimacy and governance that have been raised in connection with the rationing enterprise. The potential and limitations of key leadership concepts such as ‘sense-making’ and ‘framing’ are explored, and notions of relational leadership and the importance of leading with political astuteness are discussed.

The density ( ρc) of never-dried cotton has been measured in its wet state. It is found to be 1.536 ± 0.006 g cm−3. This quantity is essential when it is necessary to determine add-ons in grafting experiments, and the present method avoids the need of having to know the initial weight of never-dried cotton in such experiments.