Economic evaluations increasingly include the value of informal care, for example, in terms of caregiver health effects or time costs. If an economic evaluation uses caregiving time costs, appropriate measurement of caregiving time is an important first step prior to its valuation. There is no comprehensive overview of the measurement challenges for caregiving time. In this literature review, we searched Medline, Embase, Econlit and Scopus to identify measurement issues and associated studies which reported informal care time that addressed them. The search identified 27 studies that addressed nine measurement issues. There is limited evidence on how to address these issues, although some have received relatively more attention, including incremental time (considered in 16 studies), time measurement method comparisons (six studies) and the inclusion of intangible tasks (four studies). Non-response (considered in only one study) and carer and recipient identification (two studies) were the most wide-reaching measurement concerns, as these determine who is identified as carers. There was no evidence on the consequences of these measurement challenges in terms of impacts on cost-effectiveness ratios and on the total cost of health conditions, which would be a crucial next step. Future research on these issues should consider a range of different settings, as informal care is highly heterogeneous. The measurement of informal care is key for its inclusion in economic evaluations but there is little consensus on how to appropriately measure this type of care.

Risk-adjustment models are used to predict the cost of care for patients based on their observable characteristics, and to derive efficient and equitable budgets based on weighted capitation. Markers based on past care contacts can improve model fit, but their coefficients may be affected by provider variations in diagnostic, treatment and reporting quality. This is problematic when distinguishing need and supply influences on costs is required.We examine the extent of this bias in the national formula for mental health care using administrative records for 43.7 million adults registered with 7746 GP practices in England in 2015. We also illustrate a method to control for provider effects.A linear regression containing a rich set of individual, GP practice and area characteristics, and fixed effects for local health organisations, had goodness-of-fit equal to R2 = 0.007 at person level and R2 = 0.720 at GP practice level. The addition of past care markers changed substantially the coefficients on the other variables and increased the goodness-of-fit to R2 = 0.275 at person level and R2 = 0.815 at GP practice level. The further inclusion of provider effects affected the coefficients on GP practice and area variables and on local health organisation fixed effects, increasing goodness-of-fit at GP practice level to R2 = 0.848.With adequate supply controls, it is possible to estimate coefficients on past care markers that are stable and unbiased. Nonetheless, inconsistent reporting may affect need predictions and penalise populations served by underreporting providers.

We highlight the problem of loneliness, and argue that it is not only a public health issue but also an economic problem. We provide a brief review of findings from the key literature on the associations between loneliness, mental and physical health, and healthcare costs; and then present some evidence on its trends, the extent of socioeconomic inequalities and its links with health and healthcare usage, in Australia. We hope to encourage further economics research on loneliness, and related issues of social isolation and poor social support, to aid the design of policies and interventions to reduce loneliness.

OBJECTIVE: To quantify general practitioners' (GPs') turnover in England between 2007 and 2019, describe trends over time, regional differences and associations with social deprivation or other practice characteristics. DESIGN: A retrospective study of annual cross-sectional data. SETTING: All general practices in England (8085 in 2007, 6598 in 2019). METHODS: We calculated turnover rates, defined as the proportion of GPs leaving a practice. Rates and their median, 25th and 75th percentiles were calculated by year and region. The proportion of practices with persistent high turnover (>10%) over consecutive years were also calculated. A negative binomial regression model assessed the association between turnover and social deprivation or other practice characteristics. RESULTS: Turnover rates increased over time. The 75th percentile in 2009 was 11%, but increased to 14% in 2019. The highest turnover rate was observed in 2013-2014, corresponding to the 75th percentile of 18.2%. Over time, regions experienced increases in turnover rates, although it varied across English regions. The proportion of practices with high (10% to 40%) turnover within a year almost doubled from 14% in 2009 to 27% in 2019. A rise in the number of practices with persistent high turnover (>10%) for at least three consecutive years was also observed, from 2.7% (2.3%-3.1%) in 2007 to 6.3% (5.7%-6.9%) in 2017. The statistical analyses revealed that practice-area deprivation was moderately associated with turnover rate, with practices in the most deprived area having higher turnover rates compared with practices in the least deprived areas (incidence rate ratios 1.09; 95% CI 1.06 to 1.13). CONCLUSIONS: GP turnover has increased in the last decade nationally, with regional variability. Greater attention to GP turnover is needed, in the most deprived areas in particular, where GPs often need to deal with more complex health needs. There is a large cost associated with GP turnover and practices with very high persistent turnover need to be further researched, and the causes behind this identified, to allow support strategies and policies to be developed.

We process and integrate multiple timescales into one meaningful whole. Recent evidence suggests that the brain displays a complex multiscale temporal organization. Different regions exhibit different timescales as described by the concept of intrinsic neural timescales (INT); however, their function and neural mechanisms remains unclear. We review recent literature on INT and propose that they are key for input processing. Specifically, they are shared across different species, i.e., input sharing. This suggests a role of INT in encoding inputs through matching the inputs' stochastics with the ongoing temporal statistics of the brain's neural activity, i.e., input encoding. Following simulation and empirical data, we point out input integration versus segregation and input sampling as key temporal mechanisms of input processing. This deeply grounds the brain within its environmental and evolutionary context. It carries major implications in understanding mental features and psychiatric disorders, as well as going beyond the brain in integrating timescales into artificial intelligence.

BACKGROUND: Factors contributing to the accurate measurement of self-reported physical activity are not well understood in middle-aged adults. We investigated the associations between two self-reported surveys and objectively measured physical activity in middle-aged adults, and the influence of individual and sociodemographic factors on these associations, at different intensities utilizing an observational study design. METHODS: Participants (n = 156) wore a SenseWear Armband™ (SWA) for a continuous seven-day period over the triceps of the left arm, to measure energy expenditure in metabolic equivalents. Participants also completed the Physical Activity Recall questionnaire (PAR) and Active Australia Survey (AAS). Associations were analyzed separately in general linear models for each intensity. The influence of individual and sociodemographic factors was assessed through moderator analyses. RESULTS: The PAR and SWA were significantly positively associated at moderate (β = 0.68, 95% CI 0.16-1.20), vigorous (β = 0.36, 95% CI 0.20-0.53), moderate-to-vigorous physical activity (MVPA) (β = 0.52, 95% CI 0.20-0.83), and total METmins (β = 0.63, 95% CI 0.35-0.90), the AAS and SWA were associated at all intensities (moderate (β = 0.41, 95% CI 0.15-0.67), vigorous (β = 0.32, 95% CI 0.19-0.46), MVPA (β = 0.42, 95% CI 0.18-0.65) and total METmins (β = 0.62, 95% CI 0.29-0.96). A significant interaction between the PAR and sex for vigorous-intensity unveiled a weaker association in women. Both surveys tended to under-report physical activity. The largest margins of error were present at light and moderate intensities. For the PAR, participants reported over 20 hours, or 69% less light physical activity than recorded by the SWA per week. For the AAS, participants reported over 7 hours, or 38% less moderate physical activity. Compared to lighter intensities, time spent at a vigorous intensity was overreported by participants with the PAR and AAS by 91 and 43 minutes per week, respectively. The addition of Body Mass Index (BMI) resulted in non-significant interactions between the PAR and SWA for moderate-intensity, and the AAS and SWA for vigorous-intensity; a significant interaction between AAS and BMI indicated that the strength of the association differed by BMI for vigorous-intensity. CONCLUSIONS: The PAR and AAS are not equivalent to the SWA, and sex and BMI may alter the associations between the measures.

OBJECTIVES: People experiencing homelessness are frequent users of secondary care. Currently, there is no study of potentially preventable admissions for homeless patients in England. We aim to estimate the number of potentially preventable hospital admissions for homeless patients and compare to housed patients with similar characteristics. DESIGN: Retrospective matched cohort study. SETTING: Hospitals in England. PARTICIPANTS: 16 161 homeless patients and 74 780 housed patients aged 16-75 years who attended an emergency department (ED) in England in 2013/2014, matched on the basis of age, sex, ED attended and primary diagnosis. PRIMARY AND SECONDARY OUTCOME MEASURES: Annual counts of admissions, emergency admissions, ambulatory care-sensitive (ACS) emergency admissions, acute ACS emergency admissions and chronic ACS emergency admissions over the following 4 years (2014/2015-2017/2018). We additionally compare the prevalence of specific ACS conditions for homeless and housed patients. RESULTS: Mean admissions per 1000 patients per year were 470 for homeless patients and 230 for housed patients. Adjusted for confounders, annual admissions were 1.79 times higher (incident rate ratio (IRR)=1.79; 95% CI 1.69 to 1.90), emergency admissions 2.08 times higher (IRR=2.08; 95% CI 1.95 to 2.21) and ACS admissions 1.65 times higher (IRR=1.65; 95% CI 1.51 to 1.80), compared with housed patients. The effect was greater for acute (IRR=1.78; 95% CI 1.64 to 1.93) than chronic (IRR=1.45; 95% CI 1.27 to 1.66) ACS conditions. ACS conditions that were relatively more common for homeless patients were cellulitis, convulsions/epilepsy and chronic angina. CONCLUSIONS: Homeless patients use hospital services at higher rates than housed patients, particularly emergency admissions. ACS admissions of homeless patients are higher which suggests some admissions may be potentially preventable with improved access to primary care. However, these admissions comprise a small share of total admissions.

We describe a method for measuring three dimensional (3D) velocity fields of a fluid at high speed, by combining a correlation-based approach with in-line holography. While this method utilizes tracer particles contained within the flow, our method does not require the holographic reconstruction of 3D images. The direct flow reconstruction approach developed here allows for measurements at seeding densities in excess of the allowable levels for techniques based on image or particle reconstruction, thus making it suited for biological flow measurement, such as the flow in bioreactor. We outline the theory behind our method, which we term Holographic Correlation Velocimetry (HCV), and subsequently apply it to both synthetic and laboratory data. Moreover, because the system is based on in-line holography, it is very efficient with regard to the use of light, as it does not rely on side scattering. This efficiency could be utilized to create a very high quality system at a modest cost. Alternatively, this efficiency makes the system appropriate for high-speed flows and low exposure times, which is essential for imaging dynamic systems.

Physical forces can influence the embryonic development of many tissues. Within the cardiovascular system shear forces resulting from blood flow are known to be one of the regulatory signals that shape the developing heart. A key challenge in investigating the role of shear forces in cardiac development is the ability to obtain shear force measurements in vivo. Utilising the zebrafish model system we have developed a methodology that allows the shear force within the developing embryonic heart to be determined. Accurate wall shear measurement requires two essential pieces of information; high-resolution velocity measurements near the heart wall and the location and orientation of the heart wall itself. We have applied high-speed brightfield imaging to capture time-lapse series of blood flow within the beating heart between 3 and 6 days post-fertilization. Cardiac-phase filtering is applied to these time-lapse images to remove the heart wall and other slow moving structures leaving only the red blood cell movement. Using particle image velocimetry to calculate the velocity of red blood cells in different regions within the heart, and using the signal-to-noise ratio of the cardiac-phase filtered images to determine the boundary of blood flow, and therefore the position of the heart wall, we have been able to generate the necessary information to measure wall shear in vivo. We describe the methodology required to measure shear in vivo and the application of this technique to the developing zebrafish heart. We identify a reduction in shear at the ventricular-bulbar valve between 3 and 6 days post-fertilization and demonstrate that the shear environment of the ventricle during systole is constantly developing towards a more uniform level.

Computed tomography (CT) and spirometry are the mainstays of clinical pulmonary assessment. Spirometry is effort dependent and only provides a single global measure that is insensitive for regional disease, and as such, poor for capturing the early onset of lung disease, especially patchy disease such as cystic fibrosis lung disease. CT sensitively measures change in structure associated with advanced lung disease. However, obstructions in the peripheral airways and early onset of lung stiffening are often difficult to detect. Furthermore, CT imaging poses a radiation risk, particularly for young children, and dose reduction tends to result in reduced resolution. Here, we apply a series of lung tissue motion analyses, to achieve regional pulmonary function assessment in β-ENaC-overexpressing mice, a well-established model of lung disease. The expiratory time constants of regional airflows in the segmented airway tree were quantified as a measure of regional lung function. Our results showed marked heterogeneous lung function in β-ENaC-Tg mice compared to wild-type littermate controls; identified locations of airway obstruction, and quantified regions of bimodal airway resistance demonstrating lung compensation. These results demonstrate the applicability of regional lung function derived from lung motion as an effective alternative respiratory diagnostic tool.

PURPOSE: In vivo imaging of the pulmonary vasculature in small animals is difficult yet highly desirable in order to allow study of the effects of a host of dynamic biological processes such as hypoxic pulmonary vasoconstriction. Here the authors present an approach for the quantification of changes in the vasculature. METHODS: A contrast free angiography technique is validated in silico through the use of computer-generated images and in vivo through microcomputed tomography (μCT) of live mice conducted using a laboratory-based x-ray source. Subsequent image processing on μCT data allowed for the quantification of the caliber of pulmonary vasculature without the need for external contrast agents. These measures were validated by comparing with quantitative contrast microangiography in the same mice. RESULTS: Quantification of arterial diameters from the method proposed in this study is validated against laboratory-based x-ray contrast microangiography. The authors find that there is a high degree of correlation (R = 0.91) between measures from microangiography and their contrast free method. CONCLUSIONS: A technique for quantification of murine pulmonary vasculature without the need for contrast is presented. As such, this technique could be applied for longitudinal studies of animals to study changes to vasculature without the risk of premature death in sensitive mouse models of disease. This approach may also be of value in the clinical setting.