BACKGROUND: Previous research has provided evidence that socioeconomic status has an impact on invasive treatments use after acute myocardial infarction. In this paper, we compare the socioeconomic inequality in the use of high-technology diagnosis and treatment after acute myocardial infarction between the US, Quebec and Belgium paying special attention to financial incentives and regulations as explanatory factors.

METHODS: We examined hospital-discharge abstracts for all patients older than 65 who were admitted to hospitals during the 1993-1998 period in the US, Quebec and Belgium with a primary diagnosis of acute myocardial infarction. Patients' income data were imputed from the median incomes of their residential area. For each country, we compared the risk-adjusted probability of undergoing each procedure between socioeconomic categories measured by the patient's area median income.

RESULTS: Our findings indicate that income-related inequality exists in the use of high-technology treatment and diagnosis techniques that is not justified by differences in patients' health characteristics. Those inequalities are largely explained, in the US and Quebec, by inequalities in distances to hospitals with on-site cardiac facilities. However, in both Belgium and the US, inequalities persist among patients admitted to hospitals with on-site cardiac facilities, rejecting the hospital location effect as the single explanation for inequalities. Meanwhile, inequality levels diverge across countries (higher in the US and in Belgium, extremely low in Quebec).

CONCLUSIONS: The findings support the hypothesis that income-related inequality in treatment for AMI exists and is likely to be affected by a country's system of health care.

Background Optimal treatment for patients with both type 2 diabetes mellitus and stable ischemic heart disease has not been established.

Methods We randomly assigned 2368 patients with both type 2 diabetes and heart disease to undergo either prompt revascularization with intensive medical therapy or intensive medical therapy alone and to undergo either insulin-sensitization or insulin-provision therapy. Primary end points were the rate of death and a composite of death, myocardial infarction, or stroke (major cardiovascular events). Randomization was stratified according to the choice of percutaneous coronary intervention (PCI) or coronary-artery bypass grafting (CABG) as the more appropriate intervention.

Results At 5 years, rates of survival did not differ significantly between the revascularization group (88.3%) and the medical-therapy group (87.8%, P=0.97) or between the insulin-sensitization group (88.2%) and the insulin-provision group (87.9%, P=0.89). The rates of freedom from major cardiovascular events also did not differ significantly among the groups: 77.2% in the revascularization group and 75.9% in the medical-treatment group (P=0.70) and 77.7% in the insulin-sensitization group and 75.4% in the insulin-provision group (P=0.13). In the PCI stratum, there was no significant difference in primary end points between the revascularization group and the medical-therapy group. In the CABG stratum, the rate of major cardiovascular events was significantly lower in the revascularization group (22.4%) than in the medical-therapy group (30.5%, P=0.01; P=0.002 for interaction between stratum and study group). Adverse events and serious adverse events were generally similar among the groups, although severe hypoglycemia was more frequent in the insulin-provision group (9.2%) than in the insulin-sensitization group (5.9%, P=0.003).

Conclusions Overall, there was no significant difference in the rates of death and major cardiovascular events between patients undergoing prompt revascularization and those undergoing medical therapy or between strategies of insulin sensitization and insulin provision. (ClinicalTrials.gov number, NCT00006305.)

The members of the writing group (Robert L. Frye, M.D., Mayo Clinic, Rochester, MN; Phyllis August, M.D., M.P.H., New York Hospital Queens, Queens, NY; Maria Mori Brooks, Ph.D., Regina M. Hardison, M.S., Sheryl F. Kelsey, Ph.D., Joan M. MacGregor, M.S., and Trevor J. Orchard, M.B., B.Ch., University of Pittsburgh, Pittsburgh; Bernard R. Chaitman, M.D., Saint Louis University, St. Louis; Saul M. Genuth, M.D., Case Western Reserve University, Cleveland; Suzanne H. Goldberg, R.N., M.S.N., National Heart, Lung, and Blood Institute, Bethesda, MD; Mark A. Hlatky, M.D., Stanford University, Palo Alto, CA; Teresa L.Z. Jones, M.D., National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD; Mark E. Molitch, M.D., Feinberg School of Medicine, Northwestern University, Chicago; Richard W. Nesto, M.D., Lahey Clinic Medical Center, Burlington, MA; Edward Y. Sako, M.D., Ph.D., University of Texas Health Science Center, San Antonio; and Burton E. Sobel, M.D., University of Vermont, Burlington) assume responsibility for the overall content and integrity of the article.

The coverage, cost, and quality problems of the U.S. health care system are evident. Sustainable health care reform must go beyond financing expanded access to care to substantially changing the organization and delivery of care. The FRESH-Thinking Project held a series of workshops during which physicians, health policy experts, health insurance executives, business leaders, hospital administrators, economists, and others who represent diverse perspectives came together. This group agreed that the following 8 recommendations are fundamental to successful reform:

1. Replace the current fee-for-service payment system with a payment system that encourages and rewards innovation in the efficient delivery of quality care. The new payment system should invest in the development of outcome measures to guide payment.
2. Establish a securely funded, independent agency to sponsor and evaluate research on the comparative effectiveness of drugs, devices, and other medical interventions.
3. Simplify and rationalize federal and state laws and regulations to facilitate organizational innovation, support care coordination, and streamline financial and administrative functions.
4. Develop a health information technology infrastructure with national standards of interoperability to promote data exchange.
5. Create a national health database with the participation of all payers, delivery systems, and others who own health care data. Agree on methods to make deidentified information from this database on clinical interventions, patient outcomes, and costs available to researchers.
6. Identify revenue sources, including a cap on the tax exclusion of employer-based health insurance, to subsidize health care coverage with the goal of insuring all Americans.
7. Create state or regional insurance exchanges to pool risk, so that Americans without access to employer-based or other group insurance could obtain a standard benefits package through these exchanges. Employers should also be allowed to participate in these exchanges for their employees' coverage.
8. Create a health coverage board with broad stakeholder representation to determine and periodically update the affordable standard benefit package available through state or regional insurance exchanges.

Background: Induction of labor is on the rise in the U.S., increasing from 9.5 percent in 1990 to 22.1 percent in 2004. Although, it is not entirely clear what proportion of these inductions are elective (i.e. without a medical indication), the overall rate of induction of labor is rising faster than the rate of pregnancy complications that would lead to a medically indicated induction. However, the maternal and neonatal effects of induction of labor are unclear. Many studies compare women with induction of labor to those in spontaneous labor. This is problematic, because at any point in the management of the woman with a term gestation, the clinician has the choice between induction of labor and expectant management, not spontaneous labor. Expectant management of the pregnancy involves nonintervention at any particular point in time and allowing the pregnancy to progress to a future gestational age. Thus, women undergoing expectant management may go into spontaneous labor or may require indicated induction of labor at a future gestational age.

Objectives: The Stanford-UCSF Evidence-Based Practice Center examined the evidence regarding four Key Questions: 1) What evidence describes the maternal risks of elective induction versus expectant management? 2) What evidence describes the fetal/neonatal risks of elective induction versus expectant management? 3) What is the evidence that certain physical conditions/patient characteristics are predictive of a successful induction of labor? and 4) How is a failed induction defined?

Methods: We performed a systematic review to answer the Key Questions. We searched MEDLINE^® (1966-2007) and bibliographies of prior systematic reviews and the included studies for English language studies of maternal and fetal outcomes after elective induction of labor. We evaluated the quality of included studies. When possible, we synthesized study data using random effects models. We also evaluated the potential clinical outcomes and cost-effectiveness of elective induction of labor versus expectant management of pregnancy labor at 41, 40, and 39 weeks' gestation using decision-analytic models.

Results: Our searches identified 3,722 potentially relevant articles, of which 76 articles met inclusion criteria. Nine RCTs compared expectant management with elective induction of labor. We found that overall, expectant management of pregnancy was associated with an approximately 22 percent higher odds of cesarean delivery than elective induction of labor (OR 1.22, 95 percent CI 1.07–1.39; absolute risk difference 1.9, 95 percent CI: 0.2–3.7 percent). The majority of these studies were in women at or beyond 41 weeks of gestation (OR 1.21, 95 percent CI 1.01–1.46). In studies of women at or beyond 41 weeks of gestation, the evidence was rated as moderate because of the size and number of studies and consistency of the findings. Among women less than 41 weeks of gestation, there were three trials which reported no difference in risk of cesarean delivery among women who were induced as compared to expectant management (OR 1.73; 95 percent CI: 0.67–4.5, P=0.26), but all of these trials were small, non-U.S., older, and of poor quality. When we stratified the analysis by country, we found that the odds of cesarean delivery were higher in women who were expectantly managed compared to elective induction of labor in studies conducted outside the U.S. (OR 1.22; 95 percent CI 1.05–1.40) but were not statistically different in studies conducted in the U.S. (OR 1.28; 95 percent CI 0.65–2.49). Women who were expectantly managed were also more likely to have meconium-stained amniotic fluid than those who were electively induced (OR 2.04; 95 percent CI: 1.34–3.09). Observational studies reported a consistently lower risk of cesarean delivery among women who underwent spontaneous labor (6 percent) compared with women who had an elective induction of labor (8 percent) with a statistically significant decrease when combined (OR 0.63; 95 percent CI: 0.49–0.79), but again utilized the wrong control group and did not appropriately adjust for gestational age. We found moderate to high quality evidence that increased parity, a more favorable cervical status as assessed by a higher Bishop score, and decreased gestational age were associated with successful labor induction (58 percent of the included studies defined success as achieving a vaginal delivery anytime after the onset of the induction of labor; in these instances, induction was considered a failure when it led to a cesarean delivery).

In the decision analytic model, we utilized a baseline assumption of no difference in cesarean delivery between the two arms as there was no statistically significant difference in the U.S. studies or in women prior to 41 0/7 weeks of gestation. In each of the models, women who were electively induced had better overall outcomes among both mothers and neonates as estimated by total quality-adjusted life years (QALYs) as well as by reduction in specific perinatal outcomes such as shoulder dystocia, meconium aspiration syndrome, and preeclampsia. Additionally, induction of labor was cost-effective at $10,789 per QALY with elective induction of labor at 41 weeks of gestation, $9,932 per QALY at 40 weeks of gestation, and $20,222 per QALY at 39 weeks of gestation utilizing a cost-effectiveness threshold of $50,000 per QALY. At 41 weeks of gestation, these results were generally robust to variations in the assumed ranges in univariate and multi-way sensitivity analyses. However, the findings of cost-effectiveness at 40 and 39 weeks of gestation were not robust to the ranges of the assumptions. In addition, the strength of evidence for some model inputs was low, therefore our analyses are exploratory rather than definitive.

Conclusions: Randomized controlled trials suggest that elective induction of labor at 41 weeks of gestation and beyond may be associated with a decrease in both the risk of cesarean delivery and of meconium-stained amniotic fluid. The evidence regarding elective induction of labor prior to 41 weeks of gestation is insufficient to draw any conclusion. There is a paucity of information from prospective RCTs examining other maternal or neonatal outcomes in the setting of elective induction of labor. Observational studies found higher rates of cesarean delivery with elective induction of labor, but compared women undergoing induction of labor to women in spontaneous labor and were subject to potential confounding bias, particularly from gestational age. Such studies do not inform the question of how elective induction of labor affects maternal or neonatal outcomes. Elective induction of labor at 41 weeks of gestation and potentially earlier also appears to be a cost-effective intervention, but because of the need for further data to populate these models our analyses are not definitive. Despite the evidence from the prospective, RCTs reported above, there are concerns about the translation of such findings into actual practice, thus, there is a great need for studying the translation of such research into settings where the majority of obstetric care is provided.

BACKGROUND: Both genetic and environmental factors contribute to human diseases. Most common diseases are influenced by a large number of genetic and environmental factors, most of which individually have only a modest effect on the disease. Though genetic contributions are relatively well characterized for some monogenetic diseases, there has been no effort at curating the extensive list of environmental etiological factors.

RESULTS: From a comprehensive search of the MeSH annotation of MEDLINE articles, we identified 3,342 environmental etiological factors associated with 3,159 diseases. We also identified 1,100 genes associated with 1,034 complex diseases from the NIH Genetic Association Database (GAD), a database of genetic association studies. 863 diseases have both genetic and environmental etiological factors available. Integrating genetic and environmental factors results in the "etiome", which we define as the comprehensive compendium of disease etiology. Clustering of environmental factors may alert clinicians of the risks of added exposures, or synergy in interventions to alter these factors. Clustering of both genetic and environmental etiological factors puts genes in the context of environment in a quantitative manner.

CONCLUSION: In this paper, we obtained a comprehensive list of associations between disease and environmental factors using MeSH annotation of MEDLINE articles. It serves as a summary of current knowledge between etiological factors and diseases. By combining the environmental etiological factors and genetic factors from GAD, we computed the "etiome" profile for 863 diseases. Comparing diseases across these profiles may have utility for clinical medicine, basic science research, and population-based science.