Journal of Health Economics and Outcomes Research最新文献

Highlighting other risk factors for cardiovascular disease could enhance Adeniji and Obembe's study.

Background: Health state utilities are measures of health-related quality of life that reflect the value placed on improvements in patients' health status and are necessary for estimation of quality-adjusted life-years. Health state utility data on Fabry disease (FD) are limited. In this study we used vignette (scenario) construction and valuation to develop health state utilities. Objectives: The aim of this study was to use vignette construction and valuation to estimate health state utility values suitable for inclusion in economic models of FD treatments. Methods: Health state vignettes were developed from semistructured qualitative telephone interviews with patients with FD and informed by published literature and input from an expert. Each vignette was valued in an online survey by members of the United Kingdom (UK) general population using the composite time trade-off (TTO) method, which aims to determine the time the respondent would trade to live in full health compared with each impaired health state. Results: Eight adults (50% women) with FD from the UK were interviewed. They were recruited via various approaches, including patient organizations and social media. The interviewees' responses, evidence from published literature, and input from a clinical expert informed the development of 6 health state vignettes (pain, moderate clinically evident FD [CEFD], severe CEFD, end-stage renal disease [ESRD], stroke, and cardiovascular disease [CVD]) and 3 combined health states (severe CEFD + ESRD, severe CEFD + CVD, and severe CEFD + stroke). A vignette valuation survey was administered to 1222 participants from the UK general population who were members of an external surveying organization and agreed to participate in this study; 1175 surveys were successfully completed and included in the analysis. Responses to TTO questions were converted into utility values for each health state. Pain was the highest valued health state (0.465), and severe CEFD + ESRD was the lowest (0.033). Discussion: Overall, mean utility values declined as the severity of the vignettes increased, indicating that respondents were more willing to trade life-years to avoid a severe health state. Conclusions: Health state vignettes reflect the effects of FD on all major health-related quality-of-life domains and may help to support economic modeling for treatment of FD.

In their article, Mowitz et al investigated the burden of comorbidities and healthcare resource utilization among extremely premature infants enrolled in Medicaid, laying a foundation for further policy action.

Background: Breast cancer is the most common cancer among women in the United States. Newly diagnosed patients with breast cancer often experience anxiety, depression, and stress. However, the impact of psychological distress on healthcare resource utilization (HCRU) and costs has not been adequately assessed. Objectives: To evaluate the incidence and prevalence of anxiety, depression, and stress reaction/adjustment disorder among patients newly diagnosed with breast cancer, to examine HCRU and costs, and to assess the association of these psychiatric disorders with costs. Methods: This retrospective observational cohort study was conducted using a large US administrative claims database with an index date of newly diagnosed breast cancer. Demographics and comorbidities (including anxiety, depression, and stress reaction/adjustment disorder) were assessed using data collected 12 months before and after the index date. HCRU and costs were assessed using data collected 12 months after the index date. Generalized linear regressions were performed to examine the association between healthcare costs and anxiety, depression, and stress reaction/adjustment disorder. Results: Of 6392 patients with newly diagnosed breast cancer, 38.2% were diagnosed with psychiatric disorders including anxiety (27.7%), depression (21.9%), or stress reaction/adjustment disorder (6%). The incidence of these psychiatric disorders was 15% and the prevalence was 23.2%. Patients with anxiety, depression, or stress reaction/adjustment disorder had higher rates of several types of HCRU (P < .0001) and higher total all-cause costs compared with patients without these psychiatric disorders (P < .0001). Patients with incident anxiety, depression, or stress reaction/adjustment disorder incurred higher all-cause costs in the first year following breast cancer diagnosis than those with prevalent anxiety, depression, or stress reaction/adjustment disorder (P < .0003), or those without these psychiatric disorders (P < .0001). Discussion: Of patients with anxiety, depression, or stress reaction/adjustment disorder, those with incident psychiatric disorders had higher healthcare costs, suggesting that new-onset psychological distress may contribute to higher costs incurred by the payer. Timely treatment of psychiatric disorders in this population may improve clinical outcomes and reduce HCRU and costs. Conclusions: Anxiety, depression, and stress reaction/adjustment disorder were common among patients newly diagnosed with breast cancer and were associated with increased healthcare costs in the first year following breast cancer diagnosis.

Background: Cardiovascular diseases (CVDs) impose an enormous and growing economic burden on households in sub-Saharan Africa (SSA). Like many chronic health conditions, CVD predisposes families to catastrophic health expenditure (CHE), especially in SSA due to the low health insurance coverage. This study assessed the impact of CVD on the risks of incurring higher CHE among households in Ghana and South Africa. Methods: The World Health Organization (WHO) Study on Global AGEing and Adult Health (WHO SAGE), Wave 1, implemented 2007-2010, was utilized. Following standard procedure, CHE was defined as the health expenditure above 5%, 10%, and 25% of total household expenditure. Similarly, a 40% threshold was applied to household total nonfood expenditure, also referred to as the capacity to pay. To compare the difference in mean CHE by household CVD status and the predictors of CHE, Student's t-test and logistic regression were utilized. Results: The share of medical expenditure in total household spending was higher among households with CVD in Ghana and South Africa. Households with CVD were more likely to experience greater CHE across all the thresholds in Ghana. Households who reported having CVD were twice as likely to incur CHE at 5% threshold (odds ratio [OR], 1.946; confidence interval [CI], 0.965-1.095), 3 times as likely at 10% threshold (OR, 2.710; CI, 1.401-5.239), and 4 times more likely to experience CHE at both 25% and 40% thresholds, (OR, 3.696; CI, 0.956-14.286) and (OR, 4.107; CI, 1.908-8.841), respectively. In South Africa, households with CVD experienced higher CHE across all the thresholds examined compared with households without CVDs. However, only household CVD status, household health insurance status, and the presence of other disease conditions apart from CVD were associated with incurring CHE. Households who reported having CVD were 3 times more likely to incur CHE compared with households without CVD (OR, 3.002; CI, 1.013-8.902). Conclusions: Our findings suggest that CVD predisposed households to risk of higher CHE. Equity in health financing presupposes that access to health insurance should be predicated on individual health needs. Thus, targeting and prioritizing the health needs of individuals with regard to healthcare financing interventions in SSA is needed.