A mixed-methods study of challenges experienced by clinical teams in measuring improvement

Objective: Measurement is an indispensable element of most quality improvement (QI) projects, but it is undertaken to variable standards. We aimed to characterise challenges faced by clinical teams in undertaking measurement in the context of a safety QI programme that encouraged local selection of measures. Methods: Drawing on an independent evaluation of a multi-site improvement programme (Safer Clinical Systems), we combined a qualitative study of participating teams’ experiences and perceptions of measurement with expert review of measurement plans and analysis of data collected for the programme. Multidisciplinary teams of frontline clinicians at nine UK NHS sites took part across the two phases of the programme between 2011 and 2016. Results: Developing and implementing a measurement plan against which to assess their improvement goals was an arduous task for participating sites. The operational definitions of the measures that they selected were often imprecise or missed important details. Some measures used by the teams were not logically linked to the improvement actions they implemented. Regardless of the specific type of data used (routinely collected or selected ex-novo), the burdensome nature of data collection was underestimated. Problems also emerged in identifying and using suitable analytical approaches. Conclusion: Measurement is a highly technical task requiring a degree of expertise. Simply leveraging individual clinicians’ motivation is unlikely to defeat the persistent difficulties experienced by clinical teams when attempting to measure their improvement efforts. We suggest that more structural initiatives and broader capability-building programmes should be pursued by the professional community. Improving access to, and ability to use repositories of validated measures, and increasing transparency in reporting measurement attempts, is likely to be helpful

Nucleation and phase selection in undercooled melts: Magnetic alloys of industrial relevance (MAGNEPHAS)

Studies of phase selection and microstructure evolution in high-performance magnetic materials are an urgent need for optimization of production routes. Containerless solidification experiments by electromagnetic levitation and drop tube solidification were conducted in undercooled melts of Fe-Co, Fe-Ni soft magnetic, and Nd-Fe-B hard magnetic alloys. Melt undercooling under microgravity was achieved in the TEMPUS facility during parabolic flight campaigns. For Fe-Co and Fe-Ni alloys significant effects of microgravity on metastable phase formation were discovered. Microstructure modifications as well as metastable phase formation as function of undercooling and melt flow were elucidated in Nd-Fe-B. Modeling of solidification processes, fluid flow and heat transfer provide predictive tools for microstructure engineering from the melt. They were developed as a link between undercooling experiments under terrestrial and microgravity conditions and the production routes of magnetic materials

Patterns of healthcare utilisation in children and young people: a retrospective cohort study using routinely collected healthcare data in Northwest London

Objectives With a growing role for health services in managing population health, there is a need for early identification of populations with high need. Segmentation approaches partition the population based on demographics, long-term conditions (LTCs) or healthcare utilisation but have mostly been applied to adults. Our study uses segmentation methods to distinguish patterns of healthcare utilisation in children and young people (CYP) and to explore predictors of segment membership. Design Retrospective cohort study. Setting Routinely collected primary and secondary healthcare data in Northwest London from the Discover database. Participants 378,309 CYP aged 0-15 years registered to a general practice in Northwest London with one full year of follow-up. Primary and secondary outcome measures Assignment of each participant to a segment defined by seven healthcare variables representing primary and secondary care attendances, and description of utilisation patterns by segment. Predictors of segment membership described by age, sex, ethnicity, deprivation and LTCs. Results Participants were grouped into six segments based on healthcare utilisation. Three segments predominantly used primary care; two moderate utilisation segments differed in use of emergency or elective care, and a high utilisation segment, representing 16,632 (4.4%) children accounted for the highest mean presentations across all service types. The two smallest segments, representing 13.3% of the population, accounted for 62.5% of total costs. Younger age, residence in areas of higher deprivation, and presence of one or more LTCs were associated with membership of higher utilisation segments, but 75.0% of those in the highest utilisation segment had no LTC. Conclusions This article identifies six segments of healthcare utilisation in CYP and predictors of segment membership. Demographics and LTCs may not explain utilisation patterns as strongly as in adults which may limit the use of routine data in predicting utilisation and suggests children have less well-defined trajectories of service use than adults

Entropic Origin of the Growth of Relaxation Times in Simple Glassy Liquids

Transitions between ``glassy'' local minima of a model free-energy functional for a dense hard-sphere system are studied numerically using a ``microcanonical'' Monte Carlo method that enables us to obtain the transition probability as a function of the free energy and the Monte Carlo ``time''. The growth of the height of the effective free energy barrier with density is found to be consistent with a Vogel-Fulcher law. The dependence of the transition probability on time indicates that this growth is primarily due to entropic effects arising from the difficulty of finding low-free-energy saddle points connecting glassy minima.Comment: Four pages, plus three postscript figure

Time Scales for transitions between free energy minima of a hard sphere system

Time scales associated with activated transitions between glassy metastable states of a free energy functional appropriate for a dense hard sphere system are calculated by using a new Monte Carlo method for the local density variables. We calculate the time the system,initially placed in a shallow glassy minimum of the free energy, spends in the neighborhood of this minimum before making a transition to the basin of attarction of another free energy minimum. This time scale is found to increase with the average density. We find a crossover density near which this time scale increases very sharply and becomes longer than the longest times accessible in our simulation. This scale shows no evidence of dependence on sample size.Comment: 25 pages, Revtex, 6 postscript figures. Will appear in Phys Rev E, March 1996 or s

A Primary Care Nurse-Delivered Walking Intervention in Older Adults: PACE (Pedometer Accelerometer Consultation Evaluation)-Lift Cluster Randomised Controlled Trial.

Background: Brisk walking in older people can increase step-counts and moderate to vigorous intensity physical activity (MVPA) in ≥10-minute bouts, as advised in World Health Organization guidelines. Previous interventions have reported step-count increases, but not change in objectively measured MVPA in older people. We assessed whether a primary care nurse-delivered complex intervention increased objectively measured step-counts and MVPA. Methods and Findings: A total of 988 60–75 year olds, able to increase walking and randomly selected from three UK family practices, were invited to participate in a parallel two-arm cluster randomised trial; randomisation was by household. Two-hundred-ninety-eight people from 250 households were randomised between 2011 and 2012; 150 individuals to the intervention group, 148 to the usual care control group. Intervention participants received four primary care nurse physical activity (PA) consultations over 3 months, incorporating behaviour change techniques, pedometer step-count and accelerometer PA intensity feedback, and an individual PA diary and plan. Assessors were not blinded to group status, but statistical analyses were conducted blind. The primary outcome was change in accelerometry assessed average daily step-counts between baseline and 3 months, with change at 12 months a secondary outcome. Other secondary outcomes were change from baseline in time in MVPA weekly in ≥10-minute bouts, accelerometer counts, and counts/minute at 3 months and 12 months. Other outcomes were adverse events, anthropometric measures, mood, and pain. Qualitative evaluations of intervention participants and practice nurses assessed the intervention’s acceptability. At 3 months, eight participants had withdrawn or were lost to follow-up, 280 (94%) individuals provided primary outcome data. At 3 months changes in both average daily step-counts and weekly MVPA in ≥10-minute bouts were significantly higher in the intervention than control group: by 1,037 (95% CI 513–1,560) steps/day and 63 (95% CI 40–87) minutes/week, respectively. At 12 months corresponding differences were 609 (95% CI 104–1,115) steps/day and 40 (95% CI 17–63) minutes/week. Counts and counts/minute showed similar effects to steps and MVPA. Adverse events, anthropometry, mood, and pain were similar in the two groups. Participants and practice nurses found the intervention acceptable and enjoyable. Conclusions : The PACE-Lift trial increased both step-counts and objectively measured MVPA in ≥10-minute bouts in 60–75 year olds at 3 and 12 months, with no effect on adverse events. To our knowledge, this is the first trial in this age group to demonstrate objective MVPA increases and highlights the value of individualised support incorporating objective PA assessment in a primary care setting. Trial Registration: Controlled-Trials.com ISRCTN4212256

Comparison of data and process refinement

When is it reasonable, or possible, to refine a one place buffer into a two place buffer? In order to answer this question we characterise refinement based on substitution in restricted contexts. We see that data refinement (specifically in Z) and process refinement give differing answers to the original question, and we compare the precise circumstances which give rise to this difference by translating programs and processes into labelled transition systems, so providing a common basis upon which to make the comparison. We also look at the closely related area of subtyping of objects. Along the way we see how all these sorts of computational construct are related as far as refinement is concerned, discover and characterise some (as far as we can tell) new sorts of refinement and, finally, point up some research avenues for the future