Intensive care research coordinators: who are they and what do they do? Results of a binational survey.

Research coordinators in intensive care are a growing specialty about which little is known. This cross-sectional study surveyed the Australia and New Zealand Intensive Care Research Coordinators' Group (n = 49) regarding demographics, education, employment history, job structure, and role content. Most research coordinators were highly qualified and experienced nurses who undertake pharmaceutical trials, multicenter projects, departmental medical and nursing research, audits and data registries, and their own projects.     

Lymphocytic adenohypophysitis of pregnancy with complete recovery

A case of lymphocytic adenohypophysitis in a postpartum woman who became symptomatic during her 8th month of pregnancy is presented. The clinical presentation, endocrine findings, pathological findings, and operative management are discussed. Transient hypopituitarism is documented. Unlike most previously published cases, this woman had complete recovery of anterior pituitary function.     

Association between particulate air pollution and first hospital admission for childhood respiratory illness in Vancouver, Canada

In this study, the authors assessed the impact of particulate air pollution on first respiratory hospitalization. Study subjects were children less than 3 years of age living in Vancouver, British Columbia, who had their first hospitalization as a result of any respiratory disease (ICD-9 codes 460-519) during the period from June 1, 1995, to March 31, 1999. The authors used logistic regression to estimate the associations between ambient concentrations of particulate matter (PM) and first hospitalization. The adjusted odds ratios for first respiratory hospitalization associated with mean and maximal PM10-2.5 with a lag of 3 days were 1.12 (95% confidence interval: 0.98, 1.28) and 1.13 (1.00, 1.27). After adjustment for gaseous pollutants, the corresponding odds ratios were 1.22 (1.02, 1.48) and 1.14 (0.99, 1.32). The data indicated the possibility of harmful effects from coarse PM on first hospitalization for respiratory disease in early childhood.     

Income-Related Health Inequalities in Canada and the United States: A Decomposition Analysis

Objectives. We examined income-related inequalities in self-reported health in the United States and Canada and the extent to which they are associated with individual-level risk factors and health care system characteristics.Methods. We estimated income inequalities with concentration indexes and curves derived from comparable survey data from the 2002 to 2003 Joint Canada–US Survey of Health. Inequalities were then decomposed by regression and decomposition analysis to distinguish the contributions of various factors.Results. The distribution of income accounted for close to half of income-related health inequalities in both the United States and Canada. Health care system factors (e.g., unmet needs and health insurance status) and risk factors (e.g., physical inactivity and obesity) contributed more to income-related health inequalities in the United States than to those in Canada.Conclusions. Individual-level health risk factors and health care system characteristics have similar associations with health status in both countries, but they both are far more prevalent and much more concentrated among lower-income groups in the United States than in Canada.Increasing evidence indicates that the roots of health inequalities lie in an array of social, economic, and political attributes of nation-states.^1–4 Nations differ both in their average levels of population health and in the extent to which health is distributed unequally by socioeconomic status. Income-related inequalities in mortality, which are relatively stable in Canada,⁵ have been increasing steadily in the United States. In the early 1980s, the life expectancy gap in the United States between the poorest and most affluent decile was 2.8 years. By the late 1990s, this gap had increased to 4.5 years.⁶ The socioeconomic distribution of infant mortality in the two countries is also different, with declines across socioeconomic groups in Canada over recent decades,⁵ but widening gaps in the United States that are attributable to relatively higher declines for the affluent.⁷What are the underlying causes of these disparities? Are determinants of population health distributed differently by income in these neighboring countries? Or is the association between these determinants and health stronger in the United States than in Canada? We aimed to identify the potential influence of health care and other policies on income-related inequalities in health by decomposing those inequalities in both the United States and Canada into relative contributions from a set of known determinants of health.     

Who should receive recruitment and retention incentives? Improved targeting of rural doctors using medical workforce data

Objective: The objective of this study was to define an improved classification for allocating incentives to support the recruitment and retention of doctors in rural Australia. Design and setting: Geo‐coded data (n = 3636 general practitioners (GPs)) from the national Medicine in Australia: Balancing Employment and Life study were used to examine statistical variation in four professional indicators (total hours worked, public hospital work, on call after‐hours and difficulty taking time off) and two non‐professional indicators (partner employment and schooling opportunities) which are all known to be related to difficulties with recruitment and retention. Main outcome measures: The main outcome measure used for the study was an association of six sentinel indicators for GPs with practice location and population size of community. Results: Four distinct homogeneous population size groups were identified (0–5000, 5001‐15 000, 15 001–50 000 and >50 000). Although geographical remoteness (measured using the Australian Standard Geographical Classification – Remoteness Areas (ASGC‐RA)) was statistically associated with all six indicators (P < 0.001), population size provided a more sensitive measure in directing where recruitment and retention incentives should be provided. A new six‐level rurality classification is proposed, based on a combination of four population size groups and the five ASGC‐RA levels. A significant increase in statistical association is measured in four of six indicators (and a slight increase in one indicator) using the new six‐level classification versus the existing ASGC‐RA classification. Conclusions: This new six‐level geographical classification provides a better basis for equitable resource allocation of recruitment and retention incentives to doctors based on the attractiveness of non‐metropolitan communities, both professionally and non‐professionally, as places to work and live.     

Geographical classifications to guide rural health policy in Australia

The Australian Government's recent decision to replace the Rural Remote and Metropolitan Area (RRMA) classification with the Australian Standard Geographical Classification - Remoteness Areas (ASGC-RA) system highlights the ongoing significance of geographical classifications for rural health policy, particularly in relation to improving the rural health workforce supply. None of the existing classifications, including the government's preferred choice, were designed specifically to guide health resource allocation, and all exhibit strong weaknesses when applied as such. Continuing reliance on these classifications as policy tools will continue to result in inappropriate health program resource distribution. Purely 'geographical' classifications alone cannot capture all relevant aspects of rural health service provision within a single measure. Moreover, because many subjective decisions (such as the choice of algorithm and breakdown of groupings) influence a classification's impact and acceptance from its users, policy-makers need to specify explicitly the purpose and role of their different programs as the basis for developing and implementing appropriate decision tools such as 'rural-urban' classifications. Failure to do so will continue to limit the effectiveness that current rural health support and incentive programs can have in achieving their objective of improving the provision of health care services to rural populations though affirmative action programs.     

Comparing quality of care outcomes between assisted living and nursing homes before and during the COVID-19 pandemic

Background

While assisted living (AL) and nursing home (NHs) residents in share vulnerabilities, AL provides fewer staffing resources and services. Research has largely neglected AL, especially during the COVID-19 pandemic. Our study compared trends of practice-sensitive, risk-adjusted quality indicators between AL and NHs, and changes in these trends after the start of the pandemic.

Methods

This repeated cross-sectional study used population-based resident data in Alberta, Canada. Using Resident Assessment Instrument data (01/2017–12/2021), we created quarterly cohorts, using each resident's latest assessment in each quarter. We applied validated inclusion/exclusion criteria and risk-adjustments to create nine quality indicators and their 95% confidence intervals (CIs): potentially inappropriate antipsychotic use, pain, depressive symptoms, total dependency in late-loss activities of daily living, physical restraint use, pressure ulcers, delirium, weight loss, urinary tract infections. Run charts compared quality indicators between AL and NHs over time and segmented regressions assessed whether these trends changed after the start of the pandemic.

Results

Quarterly samples included 2015–2710 AL residents and 12,881–13,807 NH residents. Antipsychotic use (21%–26%), pain (20%–24%), and depressive symptoms (17%–25%) were most common in AL. In NHs, they were physical dependency (33%–36%), depressive symptoms (26%–32%), and antipsychotic use (17%–22%). Antipsychotic use and pain were consistently higher in AL. Depressive symptoms, physical dependency, physical restraint use, delirium, weight loss were consistently lower in AL. The most notable segmented regression findings were an increase in antipsychotic use during the pandemic in both settings (AL: change in slope = 0.6% [95% CI: 0.1%–1.0%], p = 0.0140; NHs: change in slope = 0.4% [95% CI: 0.3%–0.5%], p < 0.0001), and an increase in physical dependency in AL only (change in slope = 0.5% [95% CI: 0.1%–0.8%], p = 0.0222).

Conclusions

QIs differed significantly between AL and NHs before and during the pandemic. Any changes implemented to address deficiencies in either setting need to account for these differences and require monitoring to assess their impact.