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Population Health Management – often abbreviated to PHM – is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive tool which can be linked to a healthcare system's data warehouse and employed to readily perform key PHM tasks such as population segmentation, risk stratification, and deriving various performance metrics and descriptive summaries. Developed through open-source code in a large healthcare system in South West England, and used by others around the country, this paper demonstrates the importance of a scalable, purpose-built solution for improving the uptake of PHM in health services. [ABSTRACT FROM AUTHOR]

We examine the cost-effectiveness of treating epilepsy with anti-epileptic medicines in autistic children, looking at impacts on healthcare providers (in England, Ireland, Italy and Spain) and children's families (in Ireland). We find carbamazepine to be the most cost-effective drug to try first in children with newly diagnosed focal seizures. For England and Spain, oxcarbazepine is the most cost-effective treatment when taken as additional treatment for those children whose response to monotherapy is suboptimal. In Ireland and Italy, gabapentin is the most cost-effective option. Our additional scenario analysis presents the aggregate cost to families with autistic children who are being treated for epilepsy: this cost is considerably higher than healthcare provider expenditure. [ABSTRACT FROM AUTHOR]

The relationship between economic activity and suicides has been the subject of much scrutiny, but the focus in the extant literature has been almost exclusively on estimating associations rather than causal effects. In this paper, using data from England and Wales between January 1, 1997 and December 31, 2017, we propose a plausible set of assumptions to estimate the causal impacts of well-known macroeconomic variables on the daily suicide rate. Our identification strategy relies on scheduled macroeconomic announcements and professional economic forecasts. An important advantage of using these variables to model suicide rates is that they can efficiently capture the elements of 'surprise or shock' via the observed difference between how the economy actually performed and how it was expected to perform. Provided that professional forecasts are unbiased and efficient, the estimated 'surprises or shocks' are 'as good as random', and therefore are exogenous. We employ time series regressions and present robust evidence that these exogenous macroeconomic shocks affect the suicide rate. Overall, our results are consistent with economic theory that shocks that reduce estimated permanent income, and therefore expected lifetime utility, can propel suicide rates. Specifically, at the population level, negative shocks to consumer confidence and house prices accelerate the suicide rate. However, there is evidence of behavioural heterogeneity between sexes, states of the economy, and levels of public trust in government. Negative shocks to the retail price index (RPI) raise the suicide rate for males. Negative shocks to the growth rate in gross domestic product (GDP) raise the population suicide rate when the economy is doing poorly. When public trust in government is low, increases in the unemployment rate increase the suicide rate for females. • Changing macroeconomic conditions may cause anxiety and trigger suicidal behaviour. • We study the causal impact of macroeconomic shocks on suicides in England and Wales. • We isolate exogenous shocks via the spread between actual and expected activity. • Macroeconomic shocks that lower expected permanent income raise the suicide rate. • How suicides respond to shocks varies between sexes and states of the economy. [ABSTRACT FROM AUTHOR]

Introduction: Medicines Management Technicians have been shown to be an underused resource in medicines optimisation and medicines waste. In the United Kingdom, there are national recommendations for the clinical pharmacy service in cancer services ambulatory units, despite these recommendations, there was no clinical pharmacy service on the day case unit at a specialist tertiary centre in England. A lot of the patient pathways had been in place for many years and had not progressed with the changes in the clinical pathways. The main objectives of this study were to analyse how a medicines management technician could reduce medicines waste, improve the current pathway, increase medicines optimisation and ultimately improve the patient experience in an oncology day case unit at a specialist tertiary centre in England. Methods: A prospective mixed methods study was carried out at Weston Park Hospital. Descriptive statistical analysis was conducted on the quantitative data collected, and thematic analysis was carried out on the qualitative data collected by questionnaire to staff members and patients. Results: This study has shown that a medicines management technician can complete some of the tasks more traditionally done by the chemotherapy nurses on the day case unit, increasing their capacity for more clinically appropriate tasks. A medicines management technician can work as part of the wider multidisciplinary team on a day case unit contributing to medicines optimisation and cost savings for the oncology directorate. Conclusions: This study has shown that a medicines management technician can act as a valued member of the wider multidisciplinary team, improving communication and patient pathways, improving medicines optimisation and contributing to cost saving initiatives. Further studies are required to assess whether a medicines management technician role can be of the same value on a haematology day case unit. [ABSTRACT FROM AUTHOR]

Intensive cereal farming results in various unintended consequences for the environment including water pollution. Current uptake of on-farm best management measures in the UK is delivering limited benefits and alternative management futures need to be modelled to make informed decisions. The Farmscoper (FARMSCale Optimization of Pollutant Emission Reductions) tool was used to examine two management scenarios for intensive cereal farms in eastern England. The first was based on increased uptake of those measures currently recommended by advisory visits and following walkover surveys. The second was founded on mechanistic understanding of on-farm pollutant sources embedded in the Farmscoper tool. Optimization of measure selection used a multi-objective genetic algorithm. The technically possible reductions (e.g., 10 to 21% for sediment and 12 to 18% for total phosphorus) of current pollutant emissions to water due to uptake of the mechanistic scenario exceeded those resulting from the current advice scenario (≤5%), but with mixed impacts on costs ranging from a saving of £34.8/ha/yr to an increase of £19.0/ha/yr, relative to current best management costs. The current advice scenario generated corresponding cost savings of between £30.4/ha/yr and £73.40/ha/yr. Neither scenario is sufficiently impactful on unintended consequences, pointing to the need for structural change in land cover. [ABSTRACT FROM AUTHOR]

Objectives: To assess the cost‐effectiveness of the WISDOM self‐management intervention for type 2 diabetes compared with care as usual. Design: We performed a difference‐in‐differences analysis to estimate differences in risk factors for diabetes complications between people in the WISDOM group (n = 25, 276) and a control group (n = 15, 272) using GP records. A decision analytic model was then used to extrapolate differences in risk factors into costs and outcomes in the long term. Setting: Participating GP practices in West Hampshire and Southampton, UK. Participants: All people diagnosed with type 2 diabetes between January 1990 and March 2020 (n = 40,548). Outcomes Diabetes‐related complications, quality‐adjusted life years (QALYs) and costs to the English National Health Service at 5 years and lifetime. Interventions: The WISDOM intervention included risk stratification, self‐management education programme to professionals and people with type 2 diabetes, and monitoring of key treatment targets. Results: WISDOM was associated with less atrial fibrillation [p = 0.001], albuminuria [p = 0.002] and blood pressure [p = 0.098]. Among all people in the intervention group, WISDOM led to 51 [95%CI: 25; 76] QALYs gained and saved £278,036 [95%CI: −631,900; 176,392] in the first 5 years after its implementation compared with care as usual. During those people' lifetime, WISDOM led to 253 [95%CI: 75; 404] QALYs gained and cost saving of £126,380 [95%CI: −1,466,008; 1,339,628]. The gains in QALYs were a result of reduced diabetes‐related complications through improved management of the associated risk factors. Conclusions: The WISDOM risk‐stratification and education intervention for type 2 diabetes appear to be cost‐effective compared to usual care by reducing diabetes complications. [ABSTRACT FROM AUTHOR]

Background: The novel coronavirus disease in 2019 (COVID-19) has placed unprecedented strain on healthcare providers, in particular, primary care services. General practitioners (GP) have to effectively manage patients remotely preserving social distancing. We aim to assess an app-based remote patient monitoring solution in reducing the workload of a clinician and reflect this as time-saved in an economic context. Primary care COVID patients in West London deemed medium risk were recruited into the virtual ward. Patients were monitored for 14 days by telephone or by both the Huma app and telephone. Information on number of phone calls, duration of phone calls and duration of time spent reviewing the app data was recorded. Results: The amount of time spent reviewing one patient in the telephone only arm of the study was 490 min, compared with 280 min spent reviewing one patient who was monitored via both the Huma app and telephone. Based on employed clinicians monitoring patients, this equates to a 0.04 reduction of full-time equivalent staffing I.e. for every 100 patients, it would require 4 less personnel to remotely monitor them. There was no difference in mortality or adverse events between the two groups. Conclusion: App-based remote patient monitoring potentially holds large economic benefit to COVID-19 patients. In wake of further waves or future pandemics, and even in routine care, app-based remote monitoring patients could free up vital resources in terms of clinical team's time, allowing a better reallocation of services. [ABSTRACT FROM AUTHOR]