Investigating the prevalence and causes of prescribing errors in general practice: the PRACtICe Study

Aim: To determine the prevalence and nature of prescribing errors in general practice; to explore the causes, and to identify defences against error. Methods: 1) Systematic reviews; 2) Retrospective review of unique medication items prescribed over a 12 month period to a 2% sample of patients from 15 general practices in England; 3) Interviews with 34 prescribers regarding 70 potential errors; 15 root cause analyses, and six focus groups involving 46 primary health care team members Results: The study involved examination of 6,048 unique prescription items for 1,777 patients. Prescribing or monitoring errors were detected for one in eight patients, involving around one in 20 of all prescription items. The vast majority of the errors were of mild to moderate severity, with one in 550 items being associated with a severe error. The following factors were associated with increased risk of prescribing or monitoring errors: male gender, age less than 15 years or greater than 64 years, number of unique medication items prescribed, and being prescribed preparations in the following therapeutic areas: cardiovascular, infections, malignant disease and immunosuppression, musculoskeletal, eye, ENT and skin. Prescribing or monitoring errors were not associated with the grade of GP or whether prescriptions were issued as acute or repeat items. A wide range of underlying causes of error were identified relating to the prescriber, patient, the team, the working environment, the task, the computer system and the primary/secondary care interface. Many defences against error were also identified, including strategies employed by individual prescribers and primary care teams, and making best use of health information technology. Conclusion: Prescribing errors in general practices are common, although severe errors are unusual. Many factors increase the risk of error. Strategies for reducing the prevalence of error should focus on GP training, continuing professional development for GPs, clinical governance, effective use of clinical computer systems, and improving safety systems within general practices and at the interface with secondary care.

The impact of North Atlantic sea surface temperature errors on the simulation of North Atlantic European region climate

Current state-of-the-art climate models fail to capture accurately the path of the Gulf Stream and North Atlantic Current. This leads to a warm bias near the North American coast, where the modelled Gulf Stream separates from the coast further north, and a cold anomaly to the east of the Grand Banks of Newfoundland, where the North Atlantic Current remains too zonal in this region. Using an atmosphere-only model forced with the sea surface temperature (SST) biases in the North Atlantic, we consider the impact they have on the mean state and the variability in the North Atlantic European region in winter. Our results show that the SST errors produce a mean sea-level pressure response that is similar in magnitude and pattern to the atmospheric circulation errors in the coupled climate model. The work also suggests that errors in the coupled model storm tracks and North Atlantic Oscillation, compared to reanalysis data, can also be explained partly by these SST errors. Our results suggest that both the error in the Gulf Stream separation location and the path of the North Atlantic Current around the Grand Banks play important roles in affecting the atmospheric circulation. Reducing these coupled model errors could improve significantly the representation of the large-scale atmospheric circulation of the North Atlantic and European region.

Breakdown of hydrostatic balance at convective scales in the forecast errors in the Met Office Unified Model

For data assimilation in numerical weather prediction, the initial forecast-error covariance matrix Pf is required. For variational assimilation it is particularly important to prescribe an accurate initial matrix Pf, since Pf is either static (in the 3D-Var case) or constant at the beginning of each assimilation window (in the 4D-Var case). At large scales the atmospheric flow is well approximated by hydrostatic balance and this balance is strongly enforced in the initial matrix Pf used in operational variational assimilation systems such as that of the Met Office. However, at convective scales this balance does not necessarily hold any more. Here we examine the extent to which hydrostatic balance is valid in the vertical forecast-error covariances for high-resolution models in order to determine whether there is a need to relax this balance constraint in convective-scale data assimilation. We use the Met Office Global and Regional Ensemble Prediction System (MOGREPS) and a 1.5 km resolution version of the Unified Model for a case study characterized by the presence of convective activity. An ensemble of high-resolution forecasts valid up to three hours after the onset of convection is produced. We show that at 1.5 km resolution hydrostatic balance does not hold for forecast errors in regions of convection. This indicates that in the presence of convection hydrostatic balance should not be enforced in the covariance matrix used for variational data assimilation at this scale. The results show the need to investigate covariance models that may be better suited for convective-scale data assimilation. Finally, we give a measure of the balance present in the forecast perturbations as a function of the horizontal scale (from 3–90 km) using a set of diagnostics. Copyright © 2012 Royal Meteorological Society and British Crown Copyright, the Met Office

A global perspective on Langmuir turbulence in the ocean surface boundary layer.

The turbulent mixing in thin ocean surface boundary layers (OSBL), which occupy the upper 100 m or so of the ocean, control the exchange of heat and trace gases between the atmosphere and ocean. Here we show that current parameterizations of this turbulent mixing lead to systematic and substantial errors in the depth of the OSBL in global climate models, which then leads to biases in sea surface temperature. One reason, we argue, is that current parameterizations are missing key surface-wave processes that force Langmuir turbulence that deepens the OSBL more rapidly than steady wind forcing. Scaling arguments are presented to identify two dimensionless parameters that measure the importance of wave forcing against wind forcing, and against buoyancy forcing. A global perspective on the occurrence of waveforced turbulence is developed using re-analysis data to compute these parameters globally. The diagnostic study developed here suggests that turbulent energy available for mixing the OSBL is under-estimated without forcing by surface waves. Wave-forcing and hence Langmuir turbulence could be important over wide areas of the ocean and in all seasons in the Southern Ocean. We conclude that surfacewave- forced Langmuir turbulence is an important process in the OSBL that requires parameterization.

Landscape, regional and global estimates of nitrogen flux from land to sea: errors and uncertainties

Regional to global scale modelling of N flux from land to ocean has progressed to date through the development of simple empirical models representing bulk N flux rates from large watersheds, regions, or continents on the basis of a limited selection of model parameters. Watershed scale N flux modelling has developed a range of physically-based approaches ranging from models where N flux rates are predicted through a physical representation of the processes involved, through to catchment scale models which provide a simplified representation of true systems behaviour. Generally, these watershed scale models describe within their structure the dominant process controls on N flux at the catchment or watershed scale, and take into account variations in the extent to which these processes control N flux rates as a function of landscape sensitivity to N cycling and export. This paper addresses the nature of the errors and uncertainties inherent in existing regional to global scale models, and the nature of error propagation associated with upscaling from small catchment to regional scale through a suite of spatial aggregation and conceptual lumping experiments conducted on a validated watershed scale model, the export coefficient model. Results from the analysis support the findings of other researchers developing macroscale models in allied research fields. Conclusions from the study confirm that reliable and accurate regional scale N flux modelling needs to take account of the heterogeneity of landscapes and the impact that this has on N cycling processes within homogenous landscape units.

Climate spectrum estimation in the presence of timescale errors.

We introduce an algorithm (called REDFITmc2) for spectrum estimation in the presence of timescale errors. It is based on the Lomb-Scargle periodogram for unevenly spaced time series, in combination with the Welch's Overlapped Segment Averaging procedure, bootstrap bias correction and persistence estimation. The timescale errors are modelled parametrically and included in the simulations for determining (1) the upper levels of the spectrum of the red-noise AR(1) alternative and (2) the uncertainty of the frequency of a spectral peak. Application of REDFITmc2 to ice core and stalagmite records of palaeoclimate allowed a more realistic evaluation of spectral peaks than when ignoring this source of uncertainty. The results support qualitatively the intuition that stronger effects on the spectrum estimate (decreased detectability and increased frequency uncertainty) occur for higher frequencies. The surplus information brought by algorithm REDFITmc2 is that those effects are quantified. Regarding timescale construction, not only the fixpoints, dating errors and the functional form of the age-depth model play a role. Also the joint distribution of all time points (serial correlation, stratigraphic order) determines spectrum estimation.

Validating the reported random errors of ACE‐FTS measurements

In order to validate the reported precision of space‐based atmospheric composition measurements, validation studies often focus on measurements in the tropical stratosphere, where natural variability is weak. The scatter in tropical measurements can then be used as an upper limit on single‐profile measurement precision. Here we introduce a method of quantifying the scatter of tropical measurements which aims to minimize the effects of short‐term atmospheric variability while maintaining large enough sample sizes that the results can be taken as representative of the full data set. We apply this technique to measurements of O3, HNO3, CO, H2O, NO, NO2, N2O, CH4, CCl2F2, and CCl3F produced by the Atmospheric Chemistry Experiment–Fourier Transform Spectrometer (ACE‐FTS). Tropical scatter in the ACE‐FTS retrievals is found to be consistent with the reported random errors (RREs) for H2O and CO at altitudes above 20 km, validating the RREs for these measurements. Tropical scatter in measurements of NO, NO2, CCl2F2, and CCl3F is roughly consistent with the RREs as long as the effect of outliers in the data set is reduced through the use of robust statistics. The scatter in measurements of O3, HNO3, CH4, and N2O in the stratosphere, while larger than the RREs, is shown to be consistent with the variability simulated in the Canadian Middle Atmosphere Model. This result implies that, for these species, stratospheric measurement scatter is dominated by natural variability, not random error, which provides added confidence in the scientific value of single‐profile measurements.

O_3-N_2O correlations from the Atmospheric Chemistry Experiment: revisiting a diagnostic of transport and chemistry in the stratosphere

Our knowledge of stratospheric O3-N2O correlations is extended, and their potential for model-measurement comparison assessed, using data from the Atmospheric Chemistry Experiment (ACE) satellite and the Canadian Middle Atmosphere Model (CMAM). ACE provides the first comprehensive data set for the investigation of interhemispheric, interseasonal, and height-resolved differences of the O_3-N_2O correlation structure. By subsampling the CMAM data, the representativeness of the ACE data is evaluated. In the middle stratosphere, where the correlations are not compact and therefore mainly reflect the data sampling, joint probability density functions provide a detailed picture of key aspects of transport and mixing, but also trace polar ozone loss. CMAM captures these important features, but exhibits a displacement of the tropical pipe into the Southern Hemisphere (SH). Below about 21 km, the ACE data generally confirm the compactness of the correlations, although chemical ozone loss tends to destroy the compactness during late winter/spring, especially in the SH. This allows a quantitative comparison of the correlation slopes in the lower and lowermost stratosphere (LMS), which exhibit distinct seasonal cycles that reveal the different balances between diabatic descent and horizontal mixing in these two regions in the Northern Hemisphere (NH), reconciling differences found in aircraft measurements, and the strong role of chemical ozone loss in the SH. The seasonal cycles are qualitatively well reproduced by CMAM, although their amplitude is too weak in the NH LMS. The correlation slopes allow a "chemical" definition of the LMS, which is found to vary substantially in vertical extent with season.

Development of warm SST errors in the southern tropical Atlantic in CMIP5 decadal hindcasts

SST errors in the tropical Atlantic are large and systematic in current coupled general-circulation models. We analyse the growth of these errors in the region of the south-eastern tropical Atlantic in initialised decadal hindcasts integrations for three of the models participating in the Coupled Model Inter-comparison Project 5. A variety of causes for the initial bias development are identified, but a crucial involvement is found, in all cases considered, of ocean-atmosphere coupling for their maintenance. These involve an oceanic “bridge” between the Equator and the Benguela-Angola coastal seas which communicates sub-surface ocean anomalies and constitutes a coupling between SSTs in the south-eastern tropical Atlantic and the winds over the Equator. The resulting coupling between SSTs, winds and precipitation represents a positive feedback for warm SST errors in the south-eastern tropical Atlantic.

A diagnostic study of waves on the tropopause

The spatial structure and phase velocity of tropopause disturbances localized around the subpolar jet in the Southern Hemisphere are investigated using 6-hourly European Centre for Medium-Range Weather Forecasts reanalysis data covering 15 yr (1979–93). The phase velocity and phase structure of the tropopause disturbances are in good agreement with those of an edge wave vertically trapped at the tropopause. However, the vertical distribution of the ratio of potential to kinetic energy exhibits maxima above and below the tropopause and a minimum around the tropopause, in contradiction to edge wave theory for which the ratio is unity throughout the troposphere and stratosphere. This difference in vertical structure between the observed tropopause disturbances and edge wave theory is attributed to the effects of a finite-depth tropopause together with the next-order corrections in Rossby number to quasigeostrophic dynamics

The Köppen climate classification as a diagnostic tool for general circulation models

Koppen climate classification was applied to the output of atmospheric general circulation models and coupled atmosphere-ocean circulation models. The classification was used to validate model control runs of the present climate and to analyse greenhouse gas warming simulations The most prominent results of the global warming con~putationsw ere a retreat of regions of permafrost and the increase of areas with tropical rainy climates and dry climates.