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Objective To determine the association between poor sleep quality, fatigue, and self-reported safety outcomes among Emergency Medical Services (EMS) workers. Methods We used convenience sampling of EMS agencies and a cross-sectional survey design. We administered the 19-item Pittsburgh Sleep Quality Index (PSQI), 11-item Chalder Fatigue Questionnaire (CFQ), and 44-item EMS Safety Inventory (EMS-SI) to measure sleep quality, fatigue, and safety outcomes, respectively. We used a consensus process to develop the EMS-SI, which was designed to capture three composite measurements of EMS worker injury, medical errors and adverse events (AE), and safety compromising behaviors. We used hierarchical logistic regression to test the association between poor sleep quality, fatigue, and three composite measures of EMS worker safety outcomes. Results We received 547 surveys from 30 EMS agencies (a 35.6% mean agency response rate). The mean PSQI score exceeded the benchmark for poor sleep (6.9, 95%CI 6.6, 7.2). Greater than half of respondents were classified as fatigued (55%, 95%CI 50.7, 59.3). Eighteen percent of respondents reported an injury (17.8%, 95%CI 13.5, 22.1), forty-one percent a medical error or AE (41.1%, 95%CI 36.8, 45.4), and 89% (95%CI 87, 92) safety compromising behaviors. After controlling for confounding, we identified 1.9 greater odds of injury (95%CI 1.1, 3.3), 2.2 greater odds of medical error or AE (95%CI 1.4, 3.3), and 3.6 greater odds of safety compromising behavior (95%CI 1.5, 8.3) among fatigued respondents versus non-fatigued respondents. Conclusions In this sample of EMS workers, poor sleep quality and fatigue is common. We provide preliminary evidence of an association between sleep quality, fatigue, and safety outcomes.

Several cost-of-illness (COI) studies related to diabetes mellitus have been performed over the last three decades. This review examines the results of these COI studies, identifies the strengths and limitations of the various methods utilised, and suggests future research that will help determine the economic burden of diabetes more accurately. Diabetes imposes a large economic burden on society. The economic cost of diabetes is estimated to be as much as dollars US 100 billion per year in the US alone (1997 values). This estimated cost has increased notably over time, primarily due to price inflation and the increasing prevalence of diabetes. Differing methodologies have significantly influenced the cost estimates and made comparisons between COI studies problematic. For example, early reports tended to rely exclusively on data where diabetes was listed as the primary diagnosis or reason for healthcare use. To better capture the costs associated with diabetes-related complications, later studies have included costs related to diabetes as a secondary or tertiary diagnosis using the attributable risk methodology. Given the types of long-term complications that are associated with diabetes, attempts at capturing these secondary costs are appropriate. However, estimates of attributable risk can be limited by the epidemiological data currently available. The tremendous economic burden of diabetes makes the disease an important clinical and public health problem. In order to formulate an effective response to this problem, it is important to track future economic trends as healthcare delivery, morbidity and mortality patterns evolve. Future research efforts should focus on refining methods to estimate costs, improving the interpretation of study findings, and facilitating comparisons between studies.

Survival in type 1 diabetes has improved, but the impact on life expectancy in the U.S. type 1 diabetes population is not well established. Our objective was to estimate the life expectancy of the Pittsburgh Epidemiology of Diabetes Complications (EDC) study cohort and quantify improvements by comparing two subcohorts based on year of diabetes diagnosis (1950–1964 [n = 390] vs. 1965–1980 [n = 543]). The EDC study is a prospective cohort study of 933 participants with childhood-onset (aged <17 years) type 1 diabetes diagnosed at Children’s Hospital of Pittsburgh from 1950 to 1980. Mortality ascertainment was censored 31 December 2009. Abridged cohort life tables were constructed to calculate life expectancy. Death occurred in 237 (60.8%) of the 1950–1964 subcohort compared with 88 (16.2%) of the 1965–1980 subcohort. The life expectancy at birth for those diagnosed 1965–1980 was ∼15 years greater than participants diagnosed 1950–1964 (68.8 [95% CI 64.7–72.8] vs. 53.4 [50.8–56.0] years, respectively) (P < 0.0001); this difference persisted regardless of sex or pubertal status at diagnosis. This improvement in life expectancy emphasizes the need for insurance companies to update analysis of the life expectancy of those with childhood-onset type 1 diabetes because weighting of insurance premiums is based on outdated estimates.