Boston University

About: Boston University is a education organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 48688 authors who have published 119622 publications receiving 6276020 citations. The organization is also known as: BU & Boston U.

A Reengineered Hospital Discharge Program to Decrease Rehospitalization: A Randomized Trial

Abstract: One in 5 hospitalizations is complicated by postdischarge adverse events (1, 2), some of which may lead to preventable emergency department visits or readmissions. Despite this finding, hospital discharge procedures have not been standardized (3). In addition, the declining presence of primary care providers (PCPs) in hospitals has not been adequately accompanied by systems to ensure that patient data are transferred to subsequent caregivers (4, 5). For example, discharge summaries frequently lack critical data and are not sent to the PCP in a timely fashion (6, 7), resulting in outpatient clinicians being unaware of test results that were pending at discharge (8) and evaluations that were scheduled to be done after discharge not being completed (9). Similarly, patients are often left unprepared at discharge; many do not understand their discharge medications and cannot recall their chief diagnoses (10). With more than 32 million adult discharges in the United States each year (11), these deficiencies in the transition of care increase illness, unnecessary hospital utilization, and cost. Some peridischarge interventions have shown a reduction in hospital readmission rates and cost (12-14), emergency department visits (15), and postdischarge adverse events (16), whereas some have shown little or no effect (17-20). Peridischarge interventions have also shown improved PCP follow-up and outpatient work-ups (21) and higher patient satisfaction (15). Most of these studies have focused on specific diagnoses (14, 22, 23) or highly selected populations, such as geriatric adults (12, 13, 19, 24). Some have focused on specific aspects of the discharge, such as increasing access to primary care follow-up (25), connecting with transitional nursing services (26), or improving patients′ ability to advocate for themselves after discharge (12). To date, no study has evaluated a standardized discharge intervention that includes patient education, comprehensive discharge planning, and postdischarge telephone reinforcement in a general medical population. Context Emergency department visits and rehospitalizations are common after hospital discharge. Contribution This trial demonstrated that a nurse discharge advocate and clinical pharmacist working together to coordinate hospital discharge, educate patients, and reconcile medications led to fewer follow-up emergency visits and rehospitalizations than usual care alone. Caution The trial was conducted at a single center, and not all eligible patients were enrolled. Implication A systematic approach to hospital discharges can reduce unnecessary health service use. —The Editors In 2004, we began an in-depth examination of hospital discharge, for which we designed a package of services to minimize discharge failures—a process called reengineered discharge (RED) (Table 1) (3, 27). We did a randomized, controlled trial to evaluate the clinical effect of implementing RED among patients admitted to a general medical service. Table 1 Components of Reengineered Hospital Discharge

Man is to computer programmer as woman is to homemaker? debiasing word embeddings

Abstract: The blind application of machine learning runs the risk of amplifying biases present in data. Such a danger is facing us with word embedding, a popular framework to represent text data as vectors which has been used in many machine learning and natural language processing tasks. We show that even word embeddings trained on Google News articles exhibit female/male gender stereotypes to a disturbing extent. This raises concerns because their widespread use, as we describe, often tends to amplify these biases. Geometrically, gender bias is first shown to be captured by a direction in the word embedding. Second, gender neutral words are shown to be linearly separable from gender definition words in the word embedding. Using these properties, we provide a methodology for modifying an embedding to remove gender stereotypes, such as the association between the words receptionist and female, while maintaining desired associations such as between the words queen and female. Using crowd-worker evaluation as well as standard benchmarks, we empirically demonstrate that our algorithms significantly reduce gender bias in embeddings while preserving the its useful properties such as the ability to cluster related concepts and to solve analogy tasks. The resulting embeddings can be used in applications without amplifying gender bias.

Aging of skeletal muscle: a 12-yr longitudinal study

Abstract: The present study examines age-related changes in skeletal muscle size and function after 12 yr. Twelve healthy sedentary men were studied in 1985–86 (T1) and nine (initial mean age 65.4 ± 4.2 yr) ...