Transformational Change in maternity services in England: a longitudinal qualitative study of a national transformation programme ‘Early Adopter’

Background Large system transformation in health systems is designed to improve quality, outcomes and efficiency. Using empirical data from a longitudinal study of national policy-driven transformation of maternity services in England, we explore the utility of theory-based rules regarding ‘what works’ in large system transformation. Methods A longitudinal, qualitative case study was undertaken in a large diverse urban setting involving multiple hospital trusts, local authorities and other key stakeholders. Data was gathered using interviews, focus groups, non-participant observation, and a review of key documents in three phases between 2017 and 2019. The transcripts of the individual and focus group interviews were analysed thematically, using a combined inductive and deductive approach drawing on simple rules for large system transformation derived from evidence synthesis and the findings are reported in this paper. Results Alignment of transformation work with Best et al’s rules for ‘what works’ in large system transformation varied. Interactions between the rules were identified, indicating that the drivers of large system transformation are interdependent. Key challenges included the pace and scale of change that national policy required, complexity of the existing context, a lack of statutory status for the new ‘system’ limiting system leaders’ power and authority, and concurrent implementation of a new overarching system alongside multifaceted service change. Conclusions Objectives and timescales of transformation policy and plans should be realistic, flexible, responsive to feedback, and account for context. Drivers of large system transformation appear to be interdependent and synergistic. Transformation is likely to be more challenging in recently established systems where the basis of authority is not yet clearly established.

Displacement Transformations as a Tool to Study Many-Body Localization

We obtain eigenstates of interacting disorder Hamiltonians using unitary displacement transformations that rotate the state of the system. The method generates excited states if the strength of these transformations is chosen to optimize the energy, while decreasing the energy variance. We apply the method to analyse the localization properties of one-dimensional spinless fermions with short range interactions, reaching relatively large system sizes. We quantify the degree of localization through the size and disorder dependence of the inverse participation ratio.

A lifecycle cost model considering both component and system burn-in for operationally unrepairable systems

PurposeThis study presents a lifecycle cost model considering multi-level burn-in for operationally unrepairable systems including assembly and warranty costs. A numerical method to obtain system reliability under component replacement during burn-in is also presented with derived error bounds.Design/methodology/approachThe final system reliability after component and system burn-in is obtained and warranty costs are computed. On failure during operation, the system is replaced with another that undergoes an identical burn-in procedure. Cost behaviours for a small and large system are shown in a numerical example.FindingsThere are more cost savings when system burn-in is conducted for a large system whereas a strategy focusing on component burn-in only can also result in cost savings for small systems. In addition, a minimum system burn-in duration is required before cost savings are achieved for these operationally unrepairable systems.Originality/valueThe operationally unrepairable system is a niche class of systems which small satellites fall under and no such study has been conducted before. The authors present a different approach towards the testing of small satellites for a constellation mission.

Asymptotic Analysis for Systems with Deferred Abandonment

This short paper concerns the analysis of the M/M/k queueing system with customer abandonment. In this system, service managers provide a finite buffer space, which is a waiting area that prevents customers from abandoning the system. Abandonment of the system can occur from reneging (exiting from the queue while waiting), and/or balking (leaving the system without waiting). We derive an analytical expression to represent the impact of the buffer space capacity on the delay probability and the abandonment probability for a system with deferred abandonment. The result indicates the provision of the buffer space in a large system could only increase the delay probability while the abandonment probability remains unchanged. Despite the benevolent intentions of service managers, providing a buffer space may exacerbate the performance of larger systems.

COVID-19 symptoms, patient contacts, PCR-positivity and seropositivity among healthcare personnel in a Maryland healthcare system

In a large system-wide healthcare personnel (HCP) testing experience using SARS-CoV-2 PCR and serologic testing early in the COVID-19 pandemic, we did not find increased infection risk related to COVID-19 patient contact. Our findings support workplace policies for HCP protection and underscore the role of community exposure and asymptomatic infection.

Multiscale Thermodynamics: Energy, Entropy, and Symmetry from Atoms to Bulk Behavior

Here, we investigate how the local properties of particles in a thermal bath may influence the thermodynamics of the bath, and consequently alter the statistical mechanics of subsystems that comprise the bath. We are guided by the theory of small-system thermodynamics, which is based on two primary postulates: that small systems can be treated self-consistently by coupling them to an ensemble of similarly small systems, and that a large ensemble of small systems forms its own thermodynamic bath. We adapt this “nanothermodynamics” to investigate how a large system may subdivide into an ensemble of smaller subsystems, causing internal heterogeneity across multiple size scales. For the semi-classical ideal gas, maximum entropy favors subdividing a large system of “atoms” into an ensemble of “regions” of variable size. The mechanism of region formation could come from quantum exchange symmetry that makes atoms in each region indistinguishable, while decoherence between regions allows atoms in separate regions to be distinguishable by their distinct locations. Combining regions reduces the total entropy, as expected when distinguishable particles become indistinguishable, and as required by a theorem in quantum mechanics for sub-additive entropy. Combining large volumes of small regions gives the usual entropy of mixing for a semi-classical ideal gas, resolving Gibbs paradox without invoking quantum symmetry for particles that may be meters apart. Other models presented here are based on Ising-like spins, which are solved analytically in one dimension. Focusing on the bonds between the spins, we find similarity in the equilibrium properties of a two-state model in the nanocanonical ensemble and a three-state model in the canonical ensemble. Thus, emergent phenomena may alter the thermal behavior of microscopic models, and the correct ensemble is necessary for fully-accurate predictions. Another result using Ising-like spins involves simulations that include a nonlinear correction to Boltzmann’s factor, which mimics the statistics of indistinguishable states by imitating the dynamics of spin exchange on intermediate lengths. These simulations exhibit 1/f-like noise at low frequencies (f), and white noise at higher f, similar to the equilibrium thermal fluctuations found in many materials.