Building a patient safety toolkit for use in general practice

Despite 340 000 000 primary care consultations annually in the UK, most of the literature on patient safety has focused on hospital-based services. To improve safety in primary care settings, we must know what methods, tools and indicators are available to measure and monitor patient safety. In collaboration with patient safety experts at the University of Dundee, we were able to identify a number of existing tools, and many of these were adopted for use in the Patient Safety Toolkit

Morphometric and gene expression analyses of stromal expansion during development of the bovine fetal ovary

During ovarian development stroma from the mesonephros penetrates and expands into the ovarian primordium and thus appears to be involved, at least physically, in the formation of ovigerous cords, follicles and surface epithelium. Cortical stromal development during gestation in bovine fetal ovaries (n = 27) was characterised by immunohistochemistry and by mRNA analyses. Stroma was identified by immunostaining of stromal matrix collagen type I and proliferating cells were identified by Ki67 expression. The cortical and medullar volume expanded across gestation, with the rate of cortical expansion slowing over time. During gestation, the proportion of stroma in the cortex and total volume in the cortex significantly increased (P  0.05). The expression levels of 12 genes out of 18 examined, including osteoglycin (OGN) and lumican (LUM), were significantly increased later in development (P < 0.05) and the expression of many genes was positively correlated with other genes and with gestational age. Thus, the rate of cortical stromal expansion peaked in early gestation due to cell proliferation, whilst late in development expression of extracellular matrix genes increased.M.D. Hartanti, A K. Hummitzsch, H.F. Irving-Rodgers, W.M. Bonner, K.J. Copping, R.A. Anderson, I.C. McMillen, V.E.A. Perry and R.J. Rodger

A patient safety toolkit for family practices

Objectives: Major gaps remain in our understanding of primary care patient safety. We describe a toolkit for measuring patient safety in family practices. Methods: Six tools were used in 46 practices. These tools were: NHS Education for Scotland Trigger Tool, NHS Education for Scotland Medicines Reconciliation Tool, Primary Care Safequest, Prescribing Safety Indicators, PREOS-PC, and Concise Safe Systems Checklist. Results: PC-Safequest showed that most practices had a well-developed safety climate. However, the Trigger Tool revealed that a quarter of events identified were associated with moderate or substantial harm, with a third originating in primary care and avoidable. Although medicines reconciliation was undertaken within 2 days in >70% of cases, necessary discussions with a patient/carer did not always occur. The prescribing safety indicators identified 1,435 instances of potentially hazardous prescribing or lack of recommended monitoring (from 92,649 patients). The Concise Safe Systems Checklist found that 25% of staff thought their practice provided inadequate follow-up for vulnerable patients discharged from hospital and inadequate monitoring of non-collection of prescriptions. Most patients had a positive perception of the safety of their practice although 45% identified at least one safety problem in the past year. Conclusions: Patient safety is complex and multidimensional. The Patient Safety Toolkit is easy to use and hosted on a single platform with a collection of tools generating practical and actionable information. It enables family practices to identify safety deficits that they can review and change procedures to improve their patient safety across a key sets of patient safety issues

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

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

Risk management to prioritise the eradication of new and emerging invasive non-native species

Robust tools are needed to prioritise the management of invasive non-native species (INNS). Risk assessment is commonly used to prioritise INNS, but fails to take into account the feasibility of management. Risk management provides a structured evaluation of management options, but has received little attention to date. We present a risk management scheme to assess the feasibility of eradicating INNS that can be used, in conjunction with existing risk assessment schemes, to support prioritisation. The Non-Native Risk Management scheme (NNRM) can be applied to any predefined area and any taxa. It uses semi-quantitative response and confidence scores to assess seven key criteria: Effectiveness, Practicality, Cost, Impact, Acceptability, Window of opportunity and Likelihood of re-invasion. Scores are elicited using expert judgement, supported by available evidence, and consensus-building methods. We applied the NNRM to forty-one INNS that threaten Great Britain (GB). Thirty-three experts provided scores, with overall feasibility of eradication assessed as ‘very high’ (8 species), ‘high’ (6), ‘medium’ (8), ‘low’ (10) and ‘very low’ (9). The feasibility of eradicating terrestrial species was higher than aquatic species. Lotic freshwater and marine species scored particularly low. Combining risk management and existing risk assessment scores identified six established species as priorities for eradication. A further six species that are not yet established were identified as priorities for eradication on arrival as part of contingency planning. The NNRM is one of the first INNS risk management schemes that can be used with existing risk assessments to prioritise INNS eradication in any area

Connecting Earth Observation to High-Throughput Biodiversity Data

There is much interest in using Earth Observation (EO) technology to track biodiversity, ecosystem functions, and ecosystem services, understandable given the fast pace of biodiversity loss. However, because most biodiversity is invisible to EO, EO-based indicators could be misleading, which can reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing, and modern ecological modelling to extract much more of the information available in EO data. This approach is achievable now, 62 offering efficient and near-real time monitoring of management impacts on biodiversity and its functions and services

Connecting Earth observation to high-throughput biodiversity data

Understandably, given the fast pace of biodiversity loss, there is much interest in using Earth observation technology to track biodiversity, ecosystem functions and ecosystem services. However, because most biodiversity is invisible to Earth observation, indicators based on Earth observation could be misleading and reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing and modern ecological modelling to extract much more of the information available in Earth observation data. This approach is achievable now, offering efficient and near-real-time monitoring of management impacts on biodiversity and its functions and services