We reviewed published research on natural hazards and community disaster resilience to identify how relationships between people and their experiences of disaster interact to shape possibilities for positive transformative change. Research commonly analyzes processes within and across individual and collective or structural spheres of a social system, but rarely investigates interactions across all three. We present a framework focused on ‘spheres of influence’ to address this. The Framework shows how positive relationships that prioritize restoring shared, meaningful and purposeful identities can lead to expansive and incremental capacity for transformative outcomes for sustainability: a process we liken to the butterfly effect.

Sustainability and disaster resilience frameworks commonly neglect the role of agentive social processes in influencing wider structural transformation for sustainability. We applied relational agency and social practice theory to conceptualize transformative pathways for enhanced sustainability through a review of peer-reviewed literature relating to natural hazards and community disaster resilience. We sought to answer two questions: 1. What are the social practices that influence transformative change for disaster resilience in the context of individual, collective and structural spheres of influence? 2. What are the social influencing processes involved, identified through relational agency? We found that empirical studies tend to focus on individual and collective or structural spheres but rarely offer a relational analysis across all three. Our findings highlight that positive relationships that prioritize restoring shared, meaningful and purposeful identities can act as a resource, which can lead to expansive and incremental transformative outcomes for sustainability: a process we liken to the butterfly effect. We present a Sphere of Influence Framework that highlights socialized practices influenced by relationality, which can be applied as a strategic planning tool to increase capacity for resilience. Future research should explore how socio-political practices (the structural sphere) influence distributed power within collective and individual spheres.

Disasters can generate extraordinary social dynamics. So, how can we optimize these dynamics for enhanced sustainability?

New approaches are needed to safely reduce emergency admissions to hospital by targeting interventions effectively in primary care. A predictive risk stratification tool (PRISM) identifies each registered patient's risk of an emergency admission in the following year, allowing practitioners to identify and manage those at higher risk. We evaluated the introduction of PRISM in primary care in one area of the United Kingdom, assessing its impact on emergency admissions and other service use.

We conducted a randomized stepped wedge trial with cluster-defined control and intervention phases, and participant-level anonymized linked outcomes. PRISM was implemented in eleven primary care practice clusters (total thirty-two practices) over a year from March 2013. We analyzed routine linked data outcomes for 18 months.

We included outcomes for 230,099 registered patients, assigned to ranked risk groups.

Overall, the rate of emergency admissions was higher in the intervention phase than in the control phase: adjusted difference in number of emergency admissions per participant per year at risk, delta = .011 (95 percent Confidence Interval, CI .010, .013). Patients in the intervention phase spent more days in hospital per year: adjusted delta = .029 (95 percent CI .026, .031). Both effects were consistent across risk groups.

Primary care activity increased in the intervention phase overall delta = .011 (95 percent CI .007, .014), except for the two highest risk groups which showed a decrease in the number of days with recorded activity.

Introduction of a predictive risk model in primary care was associated with increased emergency episodes across the general practice population and at each risk level, in contrast to the intended purpose of the model. Future evaluation work could assess the impact of targeting of different services to patients across different levels of risk, rather than the current policy focus on those at highest risk.

Emergency admissions to hospital are a major financial burden on health services. In one area of the United Kingdom (UK), we evaluated a predictive risk stratification tool (PRISM) designed to support primary care practitioners to identify and manage patients at high risk of admission. We assessed the costs of implementing PRISM and its impact on health services costs. At the same time as the study, but independent of it, an incentive payment (‘QOF’) was introduced to encourage primary care practitioners to identify high risk patients and manage their care.

We conducted a randomized stepped wedge trial in thirty-two practices, with cluster-defined control and intervention phases, and participant-level anonymized linked outcomes. We analysed routine linked data on patient outcomes for 18 months (February 2013 – September 2014). We assigned standard unit costs in pound sterling to the resources utilized by each patient. Cost differences between the two study phases were used in conjunction with differences in the primary outcome (emergency admissions) to undertake a cost-effectiveness analysis.

We included outcomes for 230,099 registered patients. We estimated a PRISM implementation cost of GBP0.12 per patient per year.

Costs of emergency department attendances, outpatient visits, emergency and elective admissions to hospital, and general practice activity were higher per patient per year in the intervention phase than control phase (adjusted δ = GBP76, 95 percent Confidence Interval, CI GBP46, GBP106), an effect that was consistent and generally increased with risk level.

Despite low reported use of PRISM, it was associated with increased healthcare expenditure. This effect was unexpected and in the opposite direction to that intended. We cannot disentangle the effects of introducing the PRISM tool from those of imposing the QOF targets; however, since across the UK predictive risk stratification tools for emergency admissions have been introduced alongside incentives to focus on patients at risk, we believe that our findings are generalizable.

A predictive risk stratification tool (PRISM) to estimate a patient's risk of an emergency hospital admission in the following year was trialled in general practice in an area of the United Kingdom. PRISM's introduction coincided with a new incentive payment (‘QOF’) in the regional contract for family doctors to identify and manage the care of people at high risk of emergency hospital admission.

Alongside the trial, we carried out a complementary qualitative study of processes of change associated with PRISM's implementation. We aimed to describe how PRISM was understood, communicated, adopted, and used by practitioners, managers, local commissioners and policy makers. We gathered data through focus groups, interviews and questionnaires at three time points (baseline, mid-trial and end-trial). We analyzed data thematically, informed by Normalisation Process Theory (1).

All groups showed high awareness of PRISM, but raised concerns about whether it could identify patients not yet known, and about whether there were sufficient community-based services to respond to care needs identified. All practices reported using PRISM to fulfil their QOF targets, but after the QOF reporting period ended, only two practices continued to use it. Family doctors said PRISM changed their awareness of patients and focused them on targeting the highest-risk patients, though they were uncertain about the potential for positive impact on this group.

Though external factors supported its uptake in the short term, with a focus on the highest risk patients, PRISM did not become a sustained part of normal practice for primary care practitioners.

Depression is a prevalent long-term condition that is associated with substantial resource use. Telehealth may offer a cost-effective means of supporting the management of people with depression.

To investigate the cost-effectiveness of a telehealth intervention (‘Healthlines’) for patients with depression.

A prospective patient-level economic evaluation conducted alongside a randomised controlled trial. Patients were recruited through primary care, and the intervention was delivered via a telehealth service. Participants with a confirmed diagnosis of depression and PHQ-9 score ≥10 were recruited from 43 English general practices. A series of up to 10 scripted, theory-led, telephone encounters with health information advisers supported participants to effect a behaviour change, use online resources, optimise medication and improve adherence. The intervention was delivered alongside usual care and was designed to support rather than duplicate primary care. Cost-effectiveness from a combined health and social care perspective was measured by net monetary benefit at the end of 12 months of follow-up, calculated from incremental cost and incremental quality-adjusted life years (QALYs). Cost–consequence analysis included cost of lost productivity, participant out-of-pocket expenditure and the clinical outcome.

A total of 609 participants were randomised – 307 to receive the Healthlines intervention plus usual care and 302 to receive usual care alone. Forty-five per cent of participants had missing quality of life data, 41% had missing cost data and 51% of participants had missing data on either cost or utility, or both. Multiple imputation was used for the base-case analysis. The intervention was associated with incremental mean per-patient National Health Service/personal social services cost of £168 (95% CI £43 to £294) and an incremental QALY gain of 0.001 (95% CI −0.023 to 0.026). The incremental cost-effectiveness ratio was £132 630. Net monetary benefit at a cost-effectiveness threshold of £20 000 was –£143 (95% CI –£164 to –£122) and the probability of the intervention being cost-effective at this threshold value was 0.30. Productivity costs were higher in the intervention arm, but out-of-pocket expenses were lower.

The Healthlines service was acceptable to patients as a means of condition management, and response to treatment after 4 months was higher for participants randomised to the intervention. However, the positive average intervention effect size was modest, and incremental costs were high relative to a small incremental QALY gain at 12 months. The intervention is not likely to be cost-effective in its current form.

Acting on harmful command hallucinations is a major clinical concern. Our COMMAND CBT trial approximately halved the rate of harmful compliance (OR = 0.45, 95% CI 0.23–0.88, p = 0.021). The focus of the therapy was a single mechanism, the power dimension of voice appraisal, was also significantly reduced. We hypothesised that voice power differential (between voice and voice hearer) was the mediator of the treatment effect.

The trial sample (n = 197) was used. A logistic regression model predicting 18-month compliance was used to identify predictors, and an exploratory principal component analysis (PCA) of baseline variables used as potential predictors (confounders) in their own right. Stata's paramed command used to obtain estimates of the direct, indirect and total effects of treatment.

Voice omnipotence was the best predictor although the PCA identified a highly predictive cognitive-affective dimension comprising: voices’ power, childhood trauma, depression and self-harm. In the mediation analysis, the indirect effect of treatment was fully explained by its effect on the hypothesised mediator: voice power differential.

Voice power and treatment allocation were the best predictors of harmful compliance up to 18 months; post-treatment, voice power differential measured at nine months was the mediator of the effect of treatment on compliance at 18 months.

Evaluate antimicrobial stewardship interventions targeted to reduce highly active antiretroviral therapy (HAART)– or opportunistic infection (Ol)–related medication errors and increase error resolution.

Retrospective before-after study.

Academic medical center.

Inpatients who were prescribed antiretroviral therapy before the intervention (January 1, 2011, to October 31, 2011) and after the intervention (July 1, 2012, to December 31, 2012). Patients treated with lamivudine or tenofovir monotherapy for hepatitis B were excluded.

Antimicrobial stewardship interventions included education, modification of electronic medication records, collaboration with the infectious diseases (ID) department, and prospective audit and review of HAART and OI regimens by an ID clinical pharmacist.

Data for 162 admissions from the preintervention period and 110 admissions from the postintervention period were included. The number of admissions with a medication error was significantly reduced after the intervention (81 [50%] of 162 admissions vs 37 (34%) of 110 admissions; P < .00)1. A total of 124 errors occurred in the preintervention group (mean no. of errors, 1.5 per admission), and 43 errors occurred in the postintervention group (mean no. of errors, 1.2 per admission). The most common error types were major drug interactions and dosing in the preintervention group and renal adjustment and OI-related errors in the postintervention group. A significantly higher error resolution rate was observed in the postintervention group (36% vs 74%; P < .001). After adjustment for potential confounders with logistic regression, admission in the postintervention group was independently associated with fewer medication errors (odds ratio, 0.4 [95% confidence interval, 0.24-0.77]; P = .005). Overall, presence of an ID consultant demonstrated a higher error resolution rate (32% without a consultation vs 68% with a consultation; P = .002).

Multifaceted, multidisciplinary stewardship efforts reduced the rate and increased the overall resolution of HAART-related medication errors.