Intelligent Transportation Systems: Helping Public Transit Support Welfare to Work Initiatives

This study was conducted to identify ITS technologies that transit systems are using, and particularly to aid in the progress of the Welfare to Work Initiative. Two different surveys were used to gather information for this study. First, a survey was developed and administered to identify transit systems that use ITS. A second survey was designed and administered to better target the systems that use ITS. It could be concluded that transit systems were satisfied with the ITS technologies implemented and many reported their intent to implement additional ITS technologies in the future. Costs were found to be probably the largest barrier to implementing the technologies, along with transit systems reluctance to invest in rapidly changing technologies

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Estimating institutional physician turnover attributable to self-reported burnout and associated financial burden: a case study

Abstract Background Awareness of the economic cost of physician attrition due to burnout in academic medical centers may help motivate organizational level efforts to improve physician wellbeing and reduce turnover. Our objectives are: 1) to use a recent longitudinal data as a case example to examine the associations between physician self-reported burnout, intent to leave (ITL) and actual turnover within two years, and 2) to estimate the cost of physician turnover attributable to burnout. Methods We used de-identified data from 472 physicians who completed a quality improvement survey conducted in 2013 at two Stanford University affiliated hospitals to assess physician wellness. To maintain the confidentially of survey responders, potentially identifiable demographic variables were not used in this analysis. A third party custodian of the data compiled turnover data in 2015 using medical staff roster. We used logistic regression to adjust for potentially confounding factors. Results At baseline, 26% of physicians reported experiencing burnout and 28% reported ITL within the next 2 years. Two years later, 13% of surveyed physicians had actually left. Those who reported ITL were more than three times as likely to have left. Physicians who reported experiencing burnout were more than twice as likely to have left the institution within the two-year period (Relative Risk (RR) = 2.1; 95% CI = 1.3–3.3). After adjusting for surgical specialty, work hour categories, sleep-related impairment, anxiety, and depression in a logistic regression model, physicians who experienced burnout in 2013 had 168% higher odds (Odds Ratio = 2.68, 95% CI: 1.34–5.38) of leaving Stanford by 2015 compared to those who did not experience burnout. The estimated two-year recruitment cost incurred due to departure attributable to burnout was between $15,544,000 and$55,506,000. Risk of ITL attributable to burnout was 3.7 times risk of actual turnover attributable to burnout. Conclusions Institutions interested in the economic cost of turnover attributable to burnout can readily calculate this parameter using survey data linked to a subsequent indicator of departure from the institution. ITL data in cross-sectional studies can also be used with an adjustment factor to correct for overestimation of risk of intent to leave attributable to burnout

Historical criteria that distinguish syncope from seizures

We prospectively sought evidence-based criteria that distinguished between seizures and syncope