The Prevalence and Cross-Sectional Associations of Neuropathic-like Pain Among Older, Community-Dwelling Women with Arthritis.

OBJECTIVE: To estimate the prevalence and examine the associations of neuropathic-like pain in a community-based sample of older Australian women with arthritis. DESIGN: Population based cross-sectional survey. SETTING: Participants were recruited from the 1946-1951 cohort of the Australian Longitudinal Study of Women's Health. SUBJECTS: Women with self-reported arthritis (n = 147). METHODS: Primary outcome measure was self-reported neuropathic-like pain, defined as scores ≥12 via the painDETECT screening tool. Descriptive statistics summarized health and socio-demographic characteristics, and comparisons made using student's t-test or Wilcoxon Rank Sum test, and Chi-square tests. Independent health and demographic variables were examined by univariable logistic regression, and significant variables included in multiple variable logistic regression modelling. RESULTS: Thirty-nine women (26.5%) were screened as having neuropathic-like pain. Women with neuropathic-like pain were more likely to have poorer health, worse pain, higher pain catastrophizing, more fatigue, and more depression than women with nociceptive pain. Neuropathic-like pain was significantly associated with higher scores on the SF-MPQ sensory scale and pain catastrophizing scale, and with more medication use. CONCLUSIONS: Neuropathic-like pain in women with arthritis was common and is associated with greater disability and poorer quality of life.

Factors associated with the health care cost in older Australian women with arthritis: an application of the Andersen's Behavioural Model of Health Services Use.

OBJECTIVE: Factors associated with the utilisation of health care have not been rigorously examined in people with arthritis. The objective of this study was to examine the determinants of health care utilisation and costs in older women with arthritis using the Andersen's behavioural model as a framework. STUDY DESIGN: Longitudinal cohort study. METHODS: Participants of Surveys 3 to 5 of the Australian Longitudinal Study on Women's Health who reported arthritis were included in the study. Information about health care utilisation and unit prices were based on linked Medicare Australia data, which included prescription medicines and health services. Total health care costs of participants with arthritis were measured for the years 2002 to 2003, 2005 to 2006, and 2008 to 2009, which corresponded to the survey years. Potential explanatory variables of the health care cost and other characteristics of the participants were collected from the health surveys. Explanatory variables were grouped into predisposing characteristics, enabling factors and need variables conforming to the Andersen's Behavioural Model of Health Services Use. Longitudinal data analysis was conducted using generalized estimating equations. RESULTS: A total of 5834 observations were included for the three periods. Regression analysis results show that higher health care cost in older Australian women with arthritis was significantly associated with residing in an urban area, having supplementary health insurance coverage, more comorbid conditions, using complementary and alternative medicine, and worse physical functioning. It was also found that predisposing characteristics (such as the area of residence) and enabling factors (such as health insurance coverage) accounted for more variance in the health care cost than need variables (such as comorbid conditions). CONCLUSION: These results may indicate an inefficient and unfair allocation of subsidised health care among older Australian women with arthritis, where individuals with less enabling resources and more socio-economic disadvantages have a lower level of health care utilisation. Future research may focus on evaluating the effectiveness of policies designed to reduce excessive out-of-pocket costs and to improve equity in health care access in the older population.

Reporting unit context data to stakeholders in long-term care: a practical approach.

BACKGROUND: The importance of reporting research evidence to stakeholders in ways that balance complexity and usability is well-documented. However, guidance for how to accomplish this is less clear. We describe a method of developing and visualising dimension-specific scores for organisational context (context rank method). We explore perspectives of leaders in long-term care nursing homes (NHs) on two methods for reporting organisational context data: context rank method and our traditionally presented binary method-more/less favourable context. METHODS: We used a multimethod design. First, we used survey data from 4065 healthcare aides on 290 care units from 91 NHs to calculate quartiles for each of the 10 Alberta Context Tool (ACT) dimension scores, aggregated at the care unit level based on the overall sample distribution of these scores. This ordinal variable was then summed across ACT scores. Context rank scores were assessed for associations with outcomes for NH staff and for quality of care (healthcare aides' instrumental and conceptual research use, job satisfaction, rushed care, care left undone) using regression analyses. Second, we used a qualitative descriptive approach to elicit NH leaders' perspectives on whether the methods were understandable, meaningful, relevant, and useful. With 16 leaders, we conducted focus groups between December 2017 and June 2018: one in Nova Scotia, one in Prince Edward Island, and one in Ontario, Canada. Data were analysed using content analysis. RESULTS: Composite scores generated using the context rank method had positive associations with healthcare aides' instrumental research use (p < .0067) and conceptual research use and job satisfaction (p < .0001). Associations were negative between context rank summary scores and rushed care and care left undone (p < .0001). Overall, leaders indicated that data presented by both methods had value. They liked the binary method as a starting point but appreciated the greater level of detail in the context rank method. CONCLUSIONS: We recommend careful selection of either the binary or context rank method based on purpose and audience. If a simple, high-level overview is the goal, the binary method has value. If improvement is the goal, the context rank method will give leaders more actionable details.

Outcome and Cost of Optimal Control of Dyslipidemia in Adults With High Risk for Cardiovascular Disease.

BACKGROUND: We assessed the impact of optimal dyslipidemia control on mortality and costs in adults at high risk for cardiovascular disease (HRCVD). METHODS: We linked Alberta health databases to identify patients aged ≥ 18 years with HRCVD between April 2012 and March 2017. The first HRCVD event was considered the index event. Patients were categorized into (1) optimal control and (2) suboptimal control of dyslipidemia based on biomarkers and lipid-lowering therapy during the year post-index event. We measured the association between optimal dyslipidemia control and mortality and health care costs using difference-in-difference and propensity score-matching methods. RESULTS: The study included 459,739 patients with HRCVD (43,776 [9.5%] optimal patients). The optimal patients were older (median age = 62 vs 55 years; P < 0.001), included fewer female patients (37.7% vs 52%; P < 0.001), and featured a higher proportion of secondary prevention patients (15.7% vs 1.7%; P < 0.001). Compared with suboptimal patients, the optimal patients had lower adjusted mortality (0.7% vs 1.9% at 1-year and 2.9% vs 5.1% at 3-year post-index event; both P < 0.001), and higher adjusted health care costs (CA$3758 and CA$6844 at 1-year and 3-year post-index event, respectively; both P < 0.001). Among the secondary prevention group, the optimal patients had lower adjusted mortality (2.4% and 5% absolute reduction at 1-year and 3-year post-index event, respectively; both P < 0.001) at no additional costs. The results were robust across 5 definitions of optimal dyslipidemia control. CONCLUSIONS: Patients with optimal dyslipidemia control have lower mortality and incur modestly higher costs. However, secondary prevention patients experience lower mortality at no additional costs.

Importance of clinical educators to research use and suggestions for better efficiency and effectiveness: results of a cross-sectional survey of care aides in Canadian long-term care facilities.

OBJECTIVE: This study explored the effect of clinical educators as facilitators of research use and how it may be modified by organisational context in the settings. DESIGN: Cross-sectional observational study. SETTING: A representative sample of 91 residential long-term care (LTC) facilities across Western Canada. PARTICIPANTS: We used surveys to collect data from the frontline care aides and information about the organisational context of the care units. OUTCOME MEASURE AND EXPLANATORY VARIABLES: We assessed research use (the outcome) with the Conceptual Research Utilization (CRU) scale. Explanatory variables in the multiple regression analysis were facilitation, organisational context and the interaction terms. Facilitation was measured by the frequency of contacts between care aides and clinical educator or person who brings new ideas about resident care. Three core organisational context variables were measured using the Alberta Context Tool. RESULTS: We included data of 3873 care aides from 294 care units in the LTC facilities. We found significant associations between CRU and facilitation, leadership, culture and evaluation. Interactions of facilitation x leadership and facilitation x culture were negative. The coefficient of the facilitation x evaluation term in the regression model was positive (0.019, 95% CI 0.012 to 0.026), suggesting synergistic effects between facilitation and a well-developed process to evaluate care quality using relevant data. CONCLUSIONS: Findings indicate clinical educators are effective facilitators of research use among the care aides, but the effect is modified by organisational context. For greatest impact, managers can direct efforts of the clinical educators to care units where leadership and culture ratings are lowest, but a proficient feedback and evaluation process is in place. This understanding enables managers to deploy clinical educators (a scarce resource in LTC settings) most efficiently.

Cost of arthritis: a systematic review of methodologies used for direct costs.

A substantial amount of healthcare and costs are attributable to arthritis, which is a very common chronic disease. This paper presents the results of a systematic review of arthritis cost studies published from 2008 to 2013. MEDLINE, Embase, EconLit databases were searched, as well as governmental and nongovernmental organization websites. Seventy-one reports met the inclusion/exclusion criteria, and 24 studies were included in the review. Among these studies, common methods included the use of individual-level data, bottom-up costing approach, use of both an arthritis group and a control group to enable incremental cost computation of the disease, and use of regression methods such as generalized linear models and ordinary least squares regression to control for confounding variables. Estimates of the healthcare cost of arthritis varied considerably across the studies depending on the study methods, the form of arthritis and the population studied. In the USA, for example, the estimated healthcare cost of arthritis ranged from $1862 to $14,021 per person, per year. The reviewed study methods have strengths, weaknesses and potential improvements in relation to estimating the cost of disease, which are outlined in this paper. Caution must be exercised when these methods are applied to cost estimation and monitoring of the economic burden of arthritis.

Factors associated with higher healthcare costs in individuals living with arthritis: evidence from the quantile regression approach.

OBJECTIVE: To examine the factors associated with higher healthcare cost in women with arthritis, using generalized linear models (GLMs) and quantile regression (QR). METHODS: This is a cross-sectional healthcare cost study of individuals with arthritis that focused on older Australian women. Cost data were drawn from the Medicare Australia datasets. RESULTS: GLM results show that healthcare cost was significantly associated with various socio-demographic and health factors. Although QR analysis results show the same direction of association between these factors and healthcare cost as in the GLMs, they indicate progressively increased effect sizes at the 50th, 75th, 90th and 95th percentiles. CONCLUSION: Findings suggest traditional regression models such as GLMs that assume a single rate of change to accurately describe the relationships between explanatory variables and healthcare costs across the entire distribution of cost can produce biased results. QR should be considered in future healthcare cost research.