Trucks involved in fatal accidents codebook 2001 (Version May 25, 2005)

This report provides one-way frequencies for all the vehicles in UMTRI’s file of Trucks Involved in Fatal Accidents (TIFA), 2001. The 2002 TIFA file is a census of all medium and heavy trucks involved in a fatal accident in the United States. The TIFA database provides coverage of all medium and heavy trucks recorded in the Fatality Analysis Reporting System (FARS) file. TIFA combines vehicle, accident, and occupant records from FARS with information about the physical configuration and operating authority of the truck from the TIFA survey.University of Michigan, Ann Arbor, Transportation Research Institute, Center for National Truck and Bus Statistics, Affiliates ProgramFederal Motor Carrier Safety Administration, Washington, D.C.http://deepblue.lib.umich.edu/bitstream/2027.42/3132/2/48532_A42.pd

Buses involved in fatal accidents codebook 2001 (Version December 16, 2004)

Special reportThis report provides one-way frequencies for all vehicles in UMTRI’s file of Buses Involved in Fatal Accidents (BIFA), 2001. The 2001 BIFA file is a census of all buses involved in a fatal accident in the United States. The BIFA database provides coverage of buses recorded in the Fatality Analysis Reporting System (FARS) file. BIFA combines vehicle, accident, and occupant records from FARS with information about the physical configuration and operating authority of the bus from the BIFA survey.Federal Motor Carrier Safety Administration, Washington, D.C.http://deepblue.lib.umich.edu/bitstream/2027.42/3135/2/96235_A03.pd

Buses involved in fatal accidents codebook 2002 (Version February 16, 2005)

Special reportThis report provides one-way frequencies for all vehicles in UMTRI’s file of Buses Involved in Fatal Accidents (BIFA), 2002. The 2002 BIFA file is a census of all buses involved in a fatal accident in the United States. The BIFA database provides coverage of buses recorded in the Fatality Analysis Reporting System (FARS) file. BIFA combines vehicle, accident, and occupant records from FARS with information about the physical configuration and operating authority of the bus from the BIFA survey.Federal Motor Carrier Safety Administration, Washington, D.C.http://deepblue.lib.umich.edu/bitstream/2027.42/3136/2/96235_A04.pd

Buses involved in fatal accidents factbook 2002

http://www.umtri.umich.edu/cntbs/doc/bifafactbook2002.pdfSpecial ReportThis document presents aggregate statistics on buses involved in traffic accidents in 2002. The statistics are derived from the Buses Involved in Fatal Accidents (BIFA) file, compiled by the University of Michigan Transportation Research Institute. The BIFA database is a census of all buses involved in a fatal accident in the United States, and provides coverage of buses recorded in the Fatality Analysis Reporting System (FARS) file. BIFA combines vehicle, accident, and occupant records from FARS with information about the physical configuration and operating authority of the bus from the BIFA survey.University of Michigan, Ann Arbor, Transportation Research Institute, Center for National Truck and Bus Statistics, Affiliates Programhttp://deepblue.lib.umich.edu/bitstream/2027.42/13912/2/95746A04.pd

Trucks involved in fatal accidents codebook 2002 (Version September 21, 2004)

This report provides one-way frequencies for all the vehicles in UMTRI’s file of Trucks Involved in Fatal Accidents (TIFA), 2002. The 2002 TIFA file is a census of all medium and heavy trucks involved in a fatal accident in the United States. The TIFA database provides coverage of all medium and heavy trucks recorded in the Fatality Analysis Reporting System (FARS) file. TIFA combines vehicle, accident, and occupant records from FARS with information about the physical configuration and operating authority of the truck from the TIFA survey.University of Michigan, Ann Arbor, Transportation Research Institute, Center for National Truck and Bus Statistics, Affiliates ProgramFederal Motor Carrier Safety Administration, Washington, D.C.http://deepblue.lib.umich.edu/bitstream/2027.42/3131/2/48532_A41.pd

Trucks involved in fatal accidents codebook 2003 (Version November 11, 2005)

"Special Report, Task A"This report provides documentation for UMTRI’s file of Trucks Involved in Fatal Accidents (TIFA), 2003, including distributions of the code values for each variable in the file. The 2003 TIFA file is a census of all medium and heavy trucks involved in a fatal accident in the United States. The TIFA database provides coverage of all medium and heavy trucks recorded in the Fatality Analysis Reporting System (FARS) file. TIFA combines vehicle, accident, and occupant records from FARS with information about the physical configuration and operating authority of the truck from the TIFA survey.http://deepblue.lib.umich.edu/bitstream/2027.42/13906/2/48532A43.pd

Doing away with the drab age

This article surveys recent developments in the study of mid-Tudor literature; some of the problems the area has traditionally faced and still faces; and the opportunities for new research it offers, especially that which exploits new technology. It traces the deleterious effect that C. S. Lewis’ epithet ‘Drab Age’ has had upon the field, and how this has been compounded by institutional and market pressures in university education and academic publishing in the second half of the twentieth century. Nonetheless, interest in mid-16th century literature is being revived by historicist readings. The article maps out a number of areas ripe for future study, including life-writing, women’s writing, miscellanies, anonymous writing, cheap/ephemeral print, Inns of Court writing, translation, Tudor poetics, manuscripts, non-dramatic dialogue, paratext and anthologies of ‘tragical tales’. It calls for an unprejudiced reassessment of the aesthetics of mid-Tudor literature and draws attention to its humour and generic hybridity

Improving accuracy of medication identification in an older population using a medication bottle color symbol label system

<p>Abstract</p> <p>Background</p> <p>The purpose of this pilot study was to evaluate and refine an adjuvant system of color-specific symbols that are added to medication bottles and to assess whether this system would increase the ability of patients 65 years of age or older in matching their medication to the indication for which it was prescribed.</p> <p>Methods</p> <p>This study was conducted in two phases, consisting of three focus groups of patients from a family medicine clinic (n = 25) and a pre-post medication identification test in a second group of patient participants (n = 100). Results of focus group discussions were used to refine the medication label symbols according to themes and messages identified through qualitative triangulation mechanisms and data analysis techniques. A pre-post medication identification test was conducted in the second phase of the study to assess differences between standard labeling alone and the addition of the refined color-specific symbols. The pre-post test examined the impact of the added labels on participants' ability to accurately match their medication to the indication for which it was prescribed when placed in front of participants and then at a distance of two feet.</p> <p>Results</p> <p>Participants appreciated the addition of a visual aid on existing medication labels because it would not be necessary to learn a completely new system of labeling, and generally found the colors and symbols used in the proposed labeling system easy to understand and relevant. Concerns were raised about space constraints on medication bottles, having too much information on the bottle, and having to remember what the colors meant. Symbols and colors were modified if they were found unclear or inappropriate by focus group participants. Pre-post medication identification test results in a second set of participants demonstrated that the addition of the symbol label significantly improved the ability of participants to match their medication to the appropriate medical indication at a distance of two feet (p < 0.001) and approached significant improvement when placed directly in front of participants (p = 0.07).</p> <p>Conclusions</p> <p>The proposed medication symbol label system provides a promising adjunct to national efforts in addressing the issue of medication misuse in the home through the improvement of medication labeling. Further research is necessary to determine the effectiveness of the labeling system in real-world settings.</p

Association between community-level social risk and spending among Medicare beneficiaries: Implications for social risk adjustment and health equity

IMPORTANCE: Payers are increasingly using approaches to risk adjustment that incorporate community-level measures of social risk with the goal of better aligning value-based payment models with improvements in health equity. OBJECTIVE: To examine the association between community-level social risk and health care spending and explore how incorporating community-level social risk influences risk adjustment for Medicare beneficiaries. DESIGN, SETTING, AND PARTICIPANTS: Using data from a Medicare Advantage plan linked with survey data on self-reported social needs, this cross-sectional study estimated health care spending health care spending was estimated as a function of demographics and clinical characteristics, with and without the inclusion of Area Deprivation Index (ADI), a measure of community-level social risk. The study period was January to December 2019. All analyses were conducted from December 2021 to August 2022. EXPOSURES: Census block group-level ADI. MAIN OUTCOMES AND MEASURES: Regression models estimated total health care spending in 2019 and approximated different approaches to social risk adjustment. Model performance was assessed with overall model calibration (adjusted R2) and predictive accuracy (ratio of predicted to actual spending) for subgroups of potentially vulnerable beneficiaries. RESULTS: Among a final study population of 61 469 beneficiaries (mean [SD] age, 70.7 [8.9] years; 35 801 [58.2%] female; 48 514 [78.9%] White; 6680 [10.9%] with Medicare-Medicaid dual eligibility; median [IQR] ADI, 61 [42-79]), ADI was weakly correlated with self-reported social needs (r = 0.16) and explained only 0.02% of the observed variation in spending. Conditional on demographic and clinical characteristics, every percentile increase in the ADI (ie, more disadvantage) was associated with a $11.08 decrease in annual spending. Directly incorporating ADI into a risk-adjustment model that used demographics and clinical characteristics did not meaningfully improve model calibration (adjusted R2 = 7.90% vs 7.93%) and did not significantly reduce payment inequities for rural beneficiaries and those with a high burden of self-reported social needs. A postestimation adjustment of predicted spending for dual-eligible beneficiaries residing in high ADI areas also did not significantly reduce payment inequities for rural beneficiaries or beneficiaries with self-reported social needs. CONCLUSIONS AND RELEVANCE: In this cross-sectional study of Medicare beneficiaries, the ADI explained little variation in health care spending, was negatively correlated with spending conditional on demographic and clinical characteristics, and was poorly correlated with self-reported social risk factors. This prompts caution and nuance when using community-level measures of social risk such as the ADI for social risk adjustment within Medicare value-based payment programs

A Prescription for Improving Drug Formulary Decision Making

Gordon Schiff and colleagues present a new tool and checklist to help formularies make decisions about drug inclusion and to guide rational drug use