Tackling disinvestment in health care services

Rising levels of demand due to ageing populations and increases in long term conditions (White 2007), increased levels of expectation amongst patients and inflationary pressure caused by the rising cost of new technologies are amongst the explanations for the funding shortfalls in government funded health systems across the world (Newhouse 1992). The challenge facing these health systems has also been intensified by the worldwide economic downturn. Within health systems, efforts have been made to increase productivity and efficiency and to control costs without reducing quality (Garner and Littlejohns 2011) but the scale of the task necessitates further action (Donaldson et al. 2010). Beyond productivity and efficiency gains the next logical step for decision makers is disinvestment in cost-ineffective services, prioritisation of funding for one service over another or what Prasad (2012) refers to as ‘medical reversal’. The aims of this study were to explore the experiences of budget holders within the English National Health Service (NHS) in their attempts to implement programmes of disinvestment, and to consider factors which influence the success (or otherwise) of this activity. This paper begins with clarification of terminology and a summary of the current state of knowledge with regard to health service disinvestment, before presenting and discussing findings. The research suggests that disinvestment activity is varied across organisations and ranges from ‘invest to save’ schemes through to ‘true disinvestment.’ Although the majority of interviewees accept that disinvestment is necessary most had made little progress at the time of interview beyond ‘picking the low hanging fruit’. Interviewees identify a number of determinants of disinvestment such as: local/national relationships, co-ordination/ collaboration and; professional understanding and support

Investigation of magnetopause reconnection models using two colocated, low‐altitude satellites: A unifying reconnection geometry

Ion precipitation data from two co-orbiting Defense Meteorological Satellite Program satellites (F6 and F8) are used to investigate magnetopause reconnection models. We examine differential fluxes between 30 eV and 30 keV, from a Southern Hemisphere, prenoon pass during the morning of January 10, 1990. Data from the first satellite to pass through the region (F6) show two distinct ion energy dispersions •-1 ø of latitude apart, between 76 ø and 79 ø magnetic latitude. The electron data exhibit similar features at around the same region but with no or little energy dispersion, consistent with their high velocities. We suggest that the two energy dispersions can be explained by two separate injections resulting from two bursts of magnetopause reconnection. Data from the second satellite (F8), which moved through the same region I rain later, reveal the same energy-dispersed structures, only further poleward and with less overall flux. This temporal evolution is consistent with two recently reconnected flux tubes releasing their plasma as they move antisunward away from dayside merging sites. However, an observed overlap between the two ion energy dispersions suggests a more complex reconnection geometry than usual models can accommodate. We propose a generalized reconnection scenario that unifies the Bursty Single X-Line and the Multiple X-Line Reconnection models. A simple time-of-flight particle precipitation model is constructed to reproduce the ion dispersions and their overlap. The modeling results suggest that for time-dependent reconnection the dispersion overlap is observed clearly at low altitudes only for a short period compared with the evolution timescale of the ion precipitation

Empirical modeling of the quiet time nightside magnetosphere

Empirical modeling of plasma pressure and magnetic field for the quiet time nightside magnetosphere is investigated. Two models are constructed for this study. One model, referred to here as T89R, is basically the magnetic field model of Tsyganenko (1989) but is modified by the addition of an inner eastward ring current at a radial distance of ∼3 RE as suggested by observation. The other is a combination of the T89R model and the long version of the magnetic field model of Tsyganenko (1987) such that the former dominates the magnetic field in the inner magnetosphere, whereas the latter prevails in the distant tail. The distribution of plasma pressure, which is required to balance the magnetic force for each of these two field models, is computed along the tail axis in the midnight meridian. The occurrence of pressure anisotropy in the inner magnetospheric region is also taken into account by determining an empirical fit to the observed plasma pressure anisotropy. This effort is the first attempt to obtain the plasma pressure distribution in force equilibrium with magnetic stresses from an empirical field model with the inclusion of pressure anisotropy. The inclusion of pressure anisotropy alters the plasma pressure by as much as a factor of ∼3 in the inner magnetosphere. The deduced plasma pressure profile along the tail axis is found to be in good agreement with the observed quiet time plasma pressure for geocentric distances between ∼2 and ∼35 RE

Initial POLAR MFE observation of substorm signatures in the polar magnetosphere

This paper studies substorm influences in the polar magnetosphere using data from the POLAR magnetic field experiment (MFE). The POLAR spacecraft remains in the high altitude polar magnetosphere for extended periods around apogee. There it can stay at nearly constant altitude through all phases of a substorm, which was not possible on previous missions. We report such an event on March 28, 1996. Ground magnetometers monitored substorm activity, while the POLAR spacecraft, directly over the pole at (−0.8, −0.6, 8.5) RE in GSM coordinates, observed a corresponding perturbation in the total magnetic field strength. The total magnetic field first increased, then recovered toward quiet levels, consistent with erosion of magnetic flux from the dayside magnetosphere, followed by transport of that flux to the magnetotail, and eventual onset of tail reconnection and the return of that magnetic flux to the dayside magnetosphere

Making it without losing it: Type A, achievement motivation, and scientific attainment revisited

In a study by Matthews et al. (1980), responses by academic psychologists to the Jenkins Activity Survey for Health Prediction, a measure of the Type A construct, were found to be significantly, positively correlated with two measures of attainment, citations by others to published work and number of publications. In the present study, JAS responses from the Matthews et al. sample were subjected to a factor analysis with oblique rotation and two new subscales were developed on the basis of this analysis. The first, Achievement Strivings (AS) was found to be significantly correlated with both the publication and citation measures. The second scale, Impatience and Irritability (I/I), was uncorrelated with the achievement criteria. Data from other samples indicate that I/I is related to a number of health symptoms. The results suggest that the current formulation of the Type A construct may contain two components, one associated with positive achievement and the other with poor health

Impatience versus achievement strivings in the Type A pattern: Differential effects on students' health and academic achievement

Psychometric analyses of college students' responses to the Jenkins Activity Survey, a self-report measure of the Type A behavior pattern, revealed the presence of two relatively independent factors. Based on these analyses, two scales, labeled Achievement Strivings (AS) and Impatience and Irritability (II), were developed. In two samples of male and female college students, scores on AS but not on II were found to be significantly correlated with grade point average. Responses to a health survey, on the other hand, indicated that frequency of physical complaints was significantly correlated with II but not with AS. These results suggest that there are two relatively independent factors in the Type A pattern that have differential effects on performance and health. Future research on the personality factors related to coronary heart disease and other disorders might more profitably focus on the syndrome reflected in the II scale than on the Type A pattern