Girgis v. State Farm Mut. Auto. Ins. Co.: Rescinding the Physical Contact Requirement in Ohio Uninsured Motorist Claims

Nearly every state has a requirement concerning uninsured motorist coverage, although state statutes differ in their scope and language. There has been a great volume of literature discussing the applicability of uninsured motorist coverage in cases involving hit and run drivers. This casenote will set out the various state statutory approaches to hit and run vehicles under uninsured motorist coverage, as well as evaluate the Ohio Supreme Court\u27s historical approach to the physical contact doctrine. The casenote will thoroughly address the Girgis opinion and its underlying rationale, as well as the repercussions of abrogating the physical contract doctrine. Finally, this note will analyze the potential effectiveness of the corroborative evidence doctrine, and will put forward an alternative approach addressing the issue of how innocent victims of hit and run accidents should have to prove they are entitled to compensation from their uninsured motorist policy

Early recognition of multiple sclerosis using natural language processing of the electronic health record

Background Diagnostic accuracy might be improved by algorithms that searched patients’ clinical notes in the electronic health record (EHR) for signs and symptoms of diseases such as multiple sclerosis (MS). The focus this study was to determine if patients with MS could be identified from their clinical notes prior to the initial recognition by their healthcare providers. Methods An MS-enriched cohort of patients with well-established MS (n = 165) and controls (n = 545), was generated from the adult outpatient clinic. A random sample cohort was generated from randomly selected patients (n = 2289) from the same adult outpatient clinic, some of whom had MS (n = 16). Patients’ notes were extracted from the data warehouse and signs and symptoms mapped to UMLS terms using MedLEE. Approximately 1000 MS-related terms occurred significantly more frequently in MS patients’ notes than controls’. Synonymous terms were manually clustered into 50 buckets and used as classification features. Patients were classified as MS or not using Naïve Bayes classification. Results Classification of patients known to have MS using notes of the MS-enriched cohort entered after the initial ICD9[MS] code yielded an ROC AUC, sensitivity, and specificity of 0.90 [0.87-0.93], 0.75[0.66-0.82], and 0.91 [0.87-0.93], respectively. Similar classification accuracy was achieved using the notes from the random sample cohort. Classification of patients not yet known to have MS using notes of the MS-enriched cohort entered before the initial ICD9[MS] documentation identified 40% [23–59%] as having MS. Manual review of the EHR of 45 patients of the random sample cohort classified as having MS but lacking an ICD9[MS] code identified four who might have unrecognized MS. Conclusions Diagnostic accuracy might be improved by mining patients’ clinical notes for signs and symptoms of specific diseases using NLP. Using this approach, we identified patients with MS early in the course of their disease which could potentially shorten the time to diagnosis. This approach could also be applied to other diseases often missed by primary care providers such as cancer. Whether implementing computerized diagnostic support ultimately shortens the time from earliest symptoms to formal recognition of the disease remains to be seen

UNITED STATES-LATIN AMERICAN TRADE RELATIONS: IMPORTANCE TO U.S. AGRICULTURAL POLICY DECISIONS

International Relations/Trade,

Predicting hospital stay, mortality and readmission in people admitted for hypoglycaemia: prognostic models derivation and validation

Aims/hypothesis: Hospital admissions for hypoglycaemia represent a significant burden on individuals with diabetes and have a substantial economic impact on healthcare systems. To date, no prognostic models have been developed to predict outcomes following admission for hypoglycaemia. We aimed to develop and validate prediction models to estimate risk of inpatient death, 24 h discharge and one month readmission in people admitted to hospital for hypoglycaemia. Methods: We used the Hospital Episode Statistics database, which includes data on all hospital admission to National Health Service hospital trusts in England, to extract admissions for hypoglycaemia between 2010 and 2014. We developed, internally and temporally validated, and compared two prognostic risk models for each outcome. The first model included age, sex, ethnicity, region, social deprivation and Charlson score (‘base’ model). In the second model, we added to the ‘base’ model the 20 most common medical conditions and applied a stepwise backward selection of variables (‘disease’ model). We used C-index and calibration plots to assess model performance and developed a calculator to estimate probabilities of outcomes according to individual characteristics. Results: In derivation samples, 296 out of 11,136 admissions resulted in inpatient death, 1789/33,825 in one month readmission and 8396/33,803 in 24 h discharge. Corresponding values for validation samples were: 296/10,976, 1207/22,112 and 5363/22,107. The two models had similar discrimination. In derivation samples, C-indices for the base and disease models, respectively, were: 0.77 (95% CI 0.75, 0.80) and 0.78 (0.75, 0.80) for death, 0.57 (0.56, 0.59) and 0.57 (0.56, 0.58) for one month readmission, and 0.68 (0.67, 0.69) and 0.69 (0.68, 0.69) for 24 h discharge. Corresponding values in validation samples were: 0.74 (0.71, 0.76) and 0.74 (0.72, 0.77), 0.55 (0.54, 0.57) and 0.55 (0.53, 0.56), and 0.66 (0.65, 0.67) and 0.67 (0.66, 0.68). In both derivation and validation samples, calibration plots showed good agreement for the three outcomes. We developed a calculator of probabilities for inpatient death and 24 h discharge given the low performance of one month readmission models. Conclusions/interpretation: This simple and pragmatic tool to predict in-hospital death and 24 h discharge has the potential to reduce mortality and improve discharge in people admitted for hypoglycaemia

The Galactic Center with Roman

We advocate for a Galactic center (GC) field to be added to the Galactic Bulge Time Domain Survey (GBTDS). The new field would yield high-cadence photometric and astrometric measurements of an unprecedented ${\sim}$3.3 million stars toward the GC. This would enable a wide range of science cases, such as finding star-compact object binaries that may ultimately merge as LISA-detectable gravitational wave sources, constraining the mass function of stars and compact objects in different environments, detecting populations of microlensing and transiting exoplanets, studying stellar flares and variability in young and old stars, and monitoring accretion onto the central supermassive black hole. In addition, high-precision proper motions and parallaxes would open a new window into the large-scale dynamics of stellar populations at the GC, yielding insights into the formation and evolution of galactic nuclei and their co-evolution with the growth of the supermassive black hole. We discuss the possible trade-offs between the notional GBTDS and the addition of a GC field with either an optimal or minimal cadence. Ultimately, the addition of a GC field to the GBTDS would dramatically increase the science return of Roman and provide a legacy dataset to study the mid-plane and innermost regions of our Galaxy.Comment: 19 pages, 3 figures. Submitted to the NASA Roman Core Community Surveys White Paper Cal

Roman CCS White Paper: Characterizing the Galactic population of isolated black holes

Although there are estimated to be 100 million isolated black holes (BHs) in the Milky Way, only one has been found so far, resulting in significant uncertainty about their properties. The Galactic Bulge Time Domain Survey provides the only opportunity in the coming decades to grow this catalog by order(s) of magnitude. This can be achieved if 1) Roman's astrometric potential is fully realized in the observation strategy and software pipelines, 2) Roman's observational gaps of the Bulge are minimized, and 3) observations with ground-based facilities are taken of the Bulge to fill in gaps during non-Bulge seasons. A large sample of isolated BHs will enable a broad range of astrophysical questions to be answered, such as massive stellar evolution, origin of gravitational wave sources, supernova physics, and the growth of supermassive BHs, maximizing Roman's scientific return.Comment: 20 pages. Submitted in response to Nancy Grace Roman Space Telescope white paper call: https://roman.gsfc.nasa.gov/science/ccs_white_papers.htm

Adjuncts or adversaries to shared decision-making? Applying the Integrative Model of behavior to the role and design of decision support interventions in healthcare interactions

Background A growing body of literature documents the efficacy of decision support interventions (DESI) in helping patients make informed clinical decisions. DESIs are frequently described as an adjunct to shared decision-making between a patient and healthcare provider, however little is known about the effects of DESIs on patients' interactional behaviors-whether or not they promote the involvement of patients in decisions. Discussion Shared decision-making requires not only a cognitive understanding of the medical problem and deliberation about the potential options to address it, but also a number of communicative behaviors that the patient and physician need to engage in to reach the goal of making a shared decision. Theoretical models of behavior can guide both the identification of constructs that will predict the performance or non-performance of specific behaviors relevant to shared decision-making, as well as inform the development of interventions to promote these specific behaviors. We describe how Fishbein's Integrative Model (IM) of behavior can be applied to the development and evaluation of DESIs. There are several ways in which the IM could be used in research on the behavioral effects of DESIs. An investigator could measure the effects of an intervention on the central constructs of the IM - attitudes, normative pressure, self-efficacy, and intentions related to communication behaviors relevant to shared decision-making. However, if one were interested in the determinants of these domains, formative qualitative research would be necessary to elicit the salient beliefs underlying each of the central constructs. Formative research can help identify potential targets for a theory-based intervention to maximize the likelihood that it will influence the behavior of interest or to develop a more fine-grained understanding of intervention effects. Summary Behavioral theory can guide the development and evaluation of DESIs to increase the likelihood that these will prepare patients to play a more active role in the decision-making process. Self-reported behavioral measures can reduce the measurement burden for investigators and create a standardized method for examining and reporting the determinants of communication behaviors necessary for shared decision-making

Evaluating the health and economic impact of osteoarthritis pain in the workforce: results from the National Health and Wellness Survey

<p>Abstract</p> <p>Background</p> <p>There has been increasing recognition that osteoarthritis (OA) affects younger individuals who are still participants in the workforce, but there are only limited data on the contribution of OA pain to work productivity and other outcomes in an employed population. This study evaluated the impact of OA pain on healthcare resource utilization, productivity and costs in employed individuals.</p> <p>Methods</p> <p>Data were derived from the 2009 National Health and Wellness Survey. Univariable and multivariable analyses were used to characterize employed individuals (full-time, part-time, or self-employed) ≥20 years of age who were diagnosed with OA and had arthritis pain in the past month relative to employed individuals not diagnosed with OA or not experiencing arthritis pain in the past month. Work productivity was assessed using the Work Productivity and Activity Impairment (WPAI) questionnaire; health status was assessed using the physical (PCS) and mental component summary (MCS) scores from the SF-12v2 Health Survey and SF-6D health utilities; and healthcare utilization was evaluated by type and number of resources within the past 6 months. Direct and indirect costs were estimated and compared between the two cohorts.</p> <p>Results</p> <p>Individuals with OA pain were less likely to be employed. Relative to workers without OA pain (n = 37,599), the OA pain cohort (n = 2,173) was significantly older (mean age 52.1 ± 11.5 years vs 41.4 ± 13.2 years; <it>P </it>< 0.0001) and with a greater proportion of females (58.2% vs 45.9%; <it>P </it>< 0.0001). OA pain resulted in greater work impairment than among workers without OA pain (34.4% versus 17.8%; <it>P </it>< 0.0001), and was primarily due to presenteeism (impaired activity while at work). Health status, assessed both by the SF-12v2 and the SF-6D was significantly poorer among workers with OA pain (<it>P </it>< 0.0001), and healthcare resource utilization was significantly higher (<it>P </it>< 0.0001) than workers without OA pain. Total costs were higher in the OA pain cohort ($15,047 versus$8,175; <it>P </it>< 0.0001), driven by indirect costs that accounted for approximately 75% of total costs.</p> <p>Conclusions</p> <p>A substantial proportion of workers suffer from OA pain. After controlling for confounders, the impact of OA pain was significant, resulting in lower productivity and higher costs.</p

Osteoarthritis and functional disability: results of a cross sectional study among primary care patients in Germany

Contains fulltext : 52359.pdf ( ) (Open Access)BACKGROUND: The aim of the study was to determine factors associated with functional disability in patients with OA. METHODS: 1250 questionnaires were distributed to OA outpatients from 75 general practices; 1021 (81.6%) were returned. Questionnaires included sociodemographic data, the short form of the Arthritis Impact Measurement Scale (AIMS2-SF), and the Patient Health Questionnaire (PHQ-9) to assess concomitant depression. A hierarchical stepwise multiple regression analysis with the AIMS2-SF dimension "lower body" as dependent was performed. RESULTS: Main factors associated with functional disability were depression symptoms, as reflected in a high score of the PHQ-9 (beta = 0.446; p < 0.0009), pain as reflected in the AIMS2-SF symptom scale (beta = 0.412; p = 0.001), and few social contacts (beta = 0.201; p < 0.042). A high body mass index was associated with lower functional ability (beta = 0.332; p = 0.005) whereas a higher educational level (beta = -0.279; p = 0.029) predicted less impairment. Increased age was a weak predictor (beta = 0.178; p = 0.001) of disability. With a p of 0.062 the radiological severity according to the grading of Kellgren and Lawrence slightly surpassed the required significance level for remaining in the final regression model. CONCLUSION: The results emphasize that psychological as well as physical factors need to be addressed similarly to improve functional ability of patients suffering from OA. More research with multifaceted and tailored interventions is needed to determine how these factors can be targeted appropriately

Human resources for health care delivery in Tanzania: a multifaceted problem

BACKGROUND: Recent years have seen an unprecedented increase in funds for procurement of health commodities in developing countries. A major challenge now is the efficient delivery of commodities and services to improve population health. With this in mind, we documented staffing levels and productivity in peripheral health facilities in southern Tanzania. METHOD: A health facility survey was conducted to collect data on staff employed, their main tasks, availability on the day of the survey, reasons for absenteeism, and experience of supervisory visits from District Health Teams. In-depth interview with health workers was done to explore their perception of work load. A time and motion study of nurses in the Reproductive and Child Health (RCH) clinics documented their time use by task. RESULTS: We found that only 14% (122/854) of the recommended number of nurses and 20% (90/441) of the clinical staff had been employed at the facilities. Furthermore, 44% of clinical staff was not available on the day of the survey. Various reasons were given for this. Amongst the clinical staff, 38% were absent because of attendance to seminar sessions, 8% because of long-training, 25% were on official travel and 20% were on leave. RCH clinic nurses were present for 7 hours a day, but only worked productively for 57% of time present at facility. Almost two-third of facilities had received less than 3 visits from district health teams during the 6 months preceding the survey. CONCLUSION: This study documented inadequate staffing of health facilities, a high degree of absenteeism, low productivity of the staff who were present and inadequate supervision in peripheral Tanzanian health facilities. The implications of these findings are discussed in the context of decentralized health care in Tanzania