Promoting inclusion oral-health:social interventions to reduce oral health inequities

The aim of this collection of papers is to provide the reader with a cogent understanding of the role of evidence in the development of social or community-based interventions to promote inclusion oral-health and reduce oral health, health, and psychosocial inequities. In addition, this material will include various methods used for their implementation and evaluation. At the outset, the reader will be offered a working definition of inclusion oral-health, which will be modelled on the work of Luchenski et al. [1]. The interventions described are theoretically underpinned by a pluralistic definition of evidence-based practice [2] and the radical discourse of health promotion as postulated by Laverack and Labonte [3] and others [4,5]. This Special Issue will consist of eight papers, including an introduction. The first three papers will examine the various sources of evidence used to transform top-down into bottom-up community-based interventions for people experiencing homelessness; people in custody and for families residing in areas of high social deprivation. The final four papers will report on the implementation and evaluation of social or community-based interventions. This collection of research papers will highlight the importance of focusing on prevention and the adoption of a common risk factor agenda to tackle oral health, health and psychosocial inequities felt by those most excluded in our societies

The role of nursing in multimorbidity care

Background Multimorbidity (the co-occurrence of two or more chronic conditions in the same person) affects around one in three persons, and it is strongly associated with a range of negative outcomes including worsening physical function, increased health care use, and premature death. Due to the way healthcare is provided to people with multimorbidity, treatment can become burdensome, fragmented and inefficient. In people with palliative conditions, multimorbidity is increasingly common. Better models of care are needed. Methods A mixed-methods programme of research designed to inform the development of a nurse-led intervention for people with multimorbidity and palliative conditions. A mixed-methods systematic review explored nurse-led interventions for multimorbidity and their effects on outcomes. A cross-sectional study of 63,328 emergency department attenders explored the association between multimorbidity, complex multimorbidity (≥3 conditions affecting ≥3 body systems), and disease-burden on healthcare use and inpatient mortality. A focussed ethnographic study of people with multimorbidity and life-limiting conditions and their carers (n=12) explored the concept of treatment burden. Findings Nurse-led interventions for people with multimorbidity generally focus on care coordination (i.e., case management or transitional care); patients view them positively, but they do not reliably reduce health care use or costs. Multimorbidity and complex multimorbidity were significantly associated with admission from the emergency department and reattendance within 30 and 90 days. The association was greater in those with more conditions. There was no association with inpatient mortality. People with multimorbidity and palliative conditions experienced treatment burden in a manner consistent with existing theoretical models. This thesis also noted the effect of uncertainty on the balance between capacity and workload and proposes a model of how these concepts relate to one another. Discussion This thesis addresses a gap in what is known about the role of nurses in providing care to the growing number of people with multimorbidity. A theory-based nurse-led intervention is proposed which prioritises managing treatment burden and uncertainty. Conclusions Nursing in an age of multimorbidity necessitates a perspective shift which conceptualises chronic conditions as multiple overlapping phenomena situated within an individual. The role of the nurse should be to help patients navigate the complexity of living with multiple chronic conditions

AI in Healthcare: Implications for Family Medicine and Primary Care

Artificial Intelligence (AI) has begun to transform industries including healthcare. Unfortunately, Primary Care and the discipline of Family Medicine have tended to lag behind in the implementation of this novel technology. Although the relationship between Family Medicine and AI is in its infancy greater engagement from Primary Care Physician’s (PCP’s) is a must due to the increasing shortage of practitioners. AI has the chance to overturn this problem as well as speed up its development. Considering the vast majority of PCP’s utilize Electronic Medical Records (EMR’s) the field is ripe for innovation. Regrettably, much of the information available remains unused for practice disruption. Primary Care offers a large data platform that can be leveraged with the use of technology to deliver ground-breaking trails forward to provide better comprehensive care for a wide-variety of patients from various backgrounds. The purpose of this chapter is to provide context to AI implementation as it relates to Primary Care and the practice of Family Medicine

Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe

International Society for Disease Surveillance Conference 2011: Building the Future of Public Health Surveillance: Building the Future of Public Health Surveillance

Daniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-04204pubpub1117

Thirty-third Annual Symposium of Trinity College Research

2020 annual volume of abstracts for science research projects conducted by students at Trinity College

Medical Informatics and Data Analysis

During recent years, the use of advanced data analysis methods has increased in clinical and epidemiological research. This book emphasizes the practical aspects of new data analysis methods, and provides insight into new challenges in biostatistics, epidemiology, health sciences, dentistry, and clinical medicine. This book provides a readable text, giving advice on the reporting of new data analytical methods and data presentation. The book consists of 13 articles. Each article is self-contained and may be read independently according to the needs of the reader. The book is essential reading for postgraduate students as well as researchers from medicine and other sciences where statistical data analysis plays a central role