Can we identify older people most vulnerable to living in cold homes during winter?

Purpose

Living in a cold home increases the risk of dying in winter, especially in older people. However, it is unclear which individual factors predict whether older people are living in cold homes.

Evaluating and Valuing Drugs for Rare Conditions: No Easy Answers

We find ourselves in an era of unprecedented growth in the development and use of so-called “orphan” drugs to treat rare diseases, which are poised to represent more than one-fifth of pharmaceutical expenditures by 2022. This widespread use has been facilitated by legislative and regulatory incentives in both the United States and abroad, yet US payers and health systems have not yet made a concerted effort to understand whether and how rare diseases require special considerations on their part and how to adapt traditional methods of health technology assessment and economic evaluation to accommodate these situations. In this article, we explore the general ethical dilemmas that rare diseases present, steps taken by health technology assessment bodies worldwide to define the level of rarity that would necessitate special measures and the modifications to their assessment and valuation processes needed, and the contextual components for rare-disease evaluation that lie outside of the assessment framework as a guide to US decision makers on constructing a formal and relevant process stateside.     

Commonality of Risk Factors for Mothers’ Poor Oral Health and General Health: Baseline Analysis of a Population-Based Birth Cohort Study

Maternal and Child Health Journal - Objective The association between and commonality of risk factors for poor self-rated oral health (SROH) and general health (SRGH) among new mothers has not been...     

Falls Risk Prediction for Older Inpatients in Acute Care Medical Wards: Is There an Interest to Combine an Early Nurse Assessment and the Artificial Neural Network Analysis?

Background

Identification of the risk of falls is important among older inpatients. This study aims to examine performance criteria (i.e.; sensitivity, specificity, positive predictive value, negative predictive value and accuracy) for fall prediction resulting from a nurse assessment and an artificial neural networks (ANNs) analysis in older inpatients hospitalized in acute care medical wards.

Methods

A total of 848 older inpatients (mean age, 83.0±7.2 years; 41.8% female) admitted to acute care medical wards in Angers University hospital (France) were included in this study using an observational prospective cohort design. Within 24 hours after admission of older inpatients, nurses performed a bedside clinical assessment. Participants were separated into non-fallers and fallers (i.e.; ≥1 fall during hospitalization stay). The analysis was conducted using three feed forward ANNs (multilayer perceptron [MLP], averaged neural network, and neuroevolution of augmenting topologies [NEAT]).

Results

Seventy-three (8.6%) participants fell at least once during their hospital stay. ANNs showed a high specificity, regardless of which ANN was used, and the highest value reported was with MLP (99.8%). In contrast, sensitivity was lower, with values ranging between 98.4 to 14.8%. MLP had the highest accuracy (99.7).

Conclusions

Performance criteria for fall prediction resulting from a bedside nursing assessment and an ANNs analysis was associated with a high specificity but a low sensitivity, suggesting that this combined approach should be used more as a diagnostic test than a screening test when considering older inpatients in acute care medical ward.

     

The Jefferson Scale of Empathy: a nationwide study of measurement properties,underlying components,latent variable structure,and national norms in medical students

The Jefferson Scale of Empathy (JSE) is a broadly used instrument developed to measure empathy in the context of health professions education and patient care. Evidence in support of psychometrics of the JSE has been reported in health professions students and practitioners with the exception of osteopathic medical students. This study was designed to examine measurement properties, underlying components, and latent variable structure of the JSE in a nationwide sample of first-year matriculants at U.S. colleges of osteopathic medicine, and to develop a national norm table for the assessment of JSE scores. A web-based survey was administered at the beginning of the 2017–2018 academic year which included the JSE, a scale to detect “good impression” responses, and demographic/background information. Usable surveys were received from 6009 students enrolled in 41 college campuses (median response rate?=?92%). The JSE mean score and standard deviation for the sample were 116.54 and 10.85, respectively. Item-total score correlations were positive and statistically significant (p?<?0.01), and Cronbach α?=?0.82. Significant gender differences were observed on the JSE scores in favor of women. Also, significant differences were found on item scores between top and bottom third scorers on the JSE. Three factors of Perspective Taking, Compassionate Care, and Walking in Patient’s Shoes emerged in an exploratory factor analysis by using half of the sample. Results of confirmatory factor analysis with another half of the sample confirmed the 3-factor model. We also developed a national norm table which is the first to assess students’ JSE scores against national data.