Exploration of the Clinical Utility of High Risk Medication Regimens

University of Minnesota Ph.D. dissertation. November 2014. Major: Health Informatics. Advisor: Bonnie Westra. 1 computer file (PDF); vii, 124 pages.Title: Exploration of the Clinical Utility of High Risk Medication Regimens Background: Unnecessary hospital readmissions are a costly problem for the U.S. health care system. An automated algorithm was developed to target this problem and proven to predict elderly patients at greater risk of re-hospitalization based on their medication regimens. Objective: Create an automated algorithm for predicting elderly patients' medication-related risks for re-hospitalization (study 1), optimize the algorithm by improving the sensitivity of its medication criteria (study 2), and determine its usefulness within different patient populations (study 3). Materials and methods: Outcome and Assessment Information Set (OASIS) and medication data were reused from a previous, manual study of 911 patients from 15 Medicare-certified home health care agencies. Medication data was converted to standardized drug codes using APIs managed by the National Library of Medicine (NLM), and then integrated in an automated algorithm that calculations patients' high risk medication regime scores (HRMRs). A comparison of results between the automated and manual processes was conducted to determine HRMR score match rates (study 1). Odds Ratio analyses, literature reviews and clinical judgments were used to adjust the scoring of patients' High Risk Medication Regimens (HRMRs). Receiver Operating Characteristic (ROC) analysis evaluated whether these adjustments improved the predictive strength of the algorithm (study 2). Unsupervised clustering was used to determine patient population subgroups. HRMR scores were then applied to these subgroups, and ROC & FDR analysis evaluated whether the predictive strength of the algorithm increased for a specific patient population subgroup (study 3). Results: HRMR scores are composed of polypharmacy (number of drugs), potentially inappropriate medications (PIM) (drugs risky to the elderly), and Medication Regimen Complexity Index (MRCI) (complex dose forms, instructions or administration). The automated algorithm produced polypharmacy, PIM and MRCI scores that matched with 99, 87, 99 percent of the scores, respectively, from the manual analysis (study 1). Strongest ROC results for the HRMR components were .68 for polypharmacy when excluding supplements; and .60 for PIM and .69 for MRCI using the original HRMR criteria (study 2). Subgroups consisting of males who have adult children as primary caregivers show stronger AUC curves than the entire population. (study 3). Conclusion: The automated algorithm can predict elderly patients at risk of hospital readmissions and is improved by a modification to its polypharmacy criteria. A hypothesis for future study includes that the algorithm is more predictive in the subgroup of males who have adult children as their caregiver

Enriched mannose glycosylation contributes to Act d 2 allergenicity.

Allergens are responsible for the Th2 response in patients as part of complex mixtures of proteins, fatty acids and other molecules. Plant allergens have hitherto been included in several protein families that share no common biochemical features. Their physical, biochemical and immunological characteristics have been widely studied, but no definite conclusion has been reached about what makes a protein an allergen. N-glycosylation is characteristic of plant allergen sources but is not present in mammals

Personalised medicine of Cystic fibrosis

Treballs Finals de Grau de Farmàcia, Facultat de Farmàcia, Universitat de Barcelona, 2017. Tutor: Carlos Julián Ciudad i Gómez[en] The European commission defines personalised medicine as a medical approach that uses molecular insights into health and disease brought on by the sequencing of the genome to guide decision-making with regard to the prediction, prevention, diagnosis and treatment of illnesses. Its main aim is generally perceived to be “the right treatment for the right person at the right time”. This new approach to medicine attracted worldwide attention in 2012 when president Obama launched a research project with the objective to implement personalised medicine principles in America. On his speech, he used Ivacaftor as an example of the potential of personalised medicine. The importance of Ivacaftor development lays on the fact that it’s the first drug capable of treating cystic fibrosis aetiology rather than its symptoms in a specific subset of mutations. Given the impact Ivacaftor had in the media and that cystic fibrosis is not sufficiently known in our society, the objective of this project is to try to understand the underlying mechanisms of cystic fibrosis disease and shed light on what makes Ivacaftor a remarkable advancement in cystic fibrosis therapy and personalised medicine.[ca] La Comissió Europea defineix la medicina personalitzada com a un enfocament mèdic que utilitza els coneixements moleculars de salut i malaltia obtinguts a travès de la seqüenciació del genoma per guiar la presa de decisions pel que fa a la predicció, prevenció, diagnòstic i tractament de malalties. El seu objectiu principal generalment es defineix com "el tractament adequat per a la persona adequada en el moment adequat”. Aquest nou enfocament de la medicina va atreure l'atenció mundial al 2012 quan el president Obama va llançar una campanya d’investigació amb l’objectiu d’implementar els principis de la medicina personalitzada a Amèrica. En el seu discurs, va utilitzar l’Ivacaftor per exemplificar el potencial de la medicina ersonalitzada. El desenvolupament d’Ivacaftor és molt important ja que és el primer fàrmac que tracta l'etiologia de la fibrosi quística enlloc dels seus símptomes en un conjunt de mutacions. Atès al gran ressò mediàtic que l’Ivacaftor va assolir i la gran desconeixença de la societat sobre la fibrosis quística, l’objectiu d’aquest treball ha estat conèixer la fisiopatologia d’aquesta malaltia i entendre perquè aquest fàrmac suposa un gran avenç en medicina personalitzada i en la terapèutica de la fibrosis quística

Predicting Adverse Effects of Drugs

The number of drugs currently available at the commercial level is quite large. The therapeutic importance and the benefit of these are indisputable. However, unknown effects of individual drugs and/or the interaction of effects between drugs may have serious consequences for the health of the population.The use of some drugs may prove to be unsafe and risky, since the response and interaction of the population to their use differ substantially. It is known that in practice and despite all measures taken during the premarketing phase they may be insufficient, since factors such as the patients age, clinical history and interaction with other medicinal products may be at the apex of these undesirable effects.This report gives an overview of existing studies of detection and prevention of adverse drug effects and the possible contribution of informatics to the diagnosis of this problem. We go one step further and, propose to study and apply the use of Data Mining techniques to prevent the adverse effects of drugs

Systems biology and big data in asthma and allergy: recent discoveries and emerging challenges

Asthma is a common condition caused by immune and respiratory dysfunction, and it is often linked to allergy. A systems perspective may prove helpful in unravelling the complexity of asthma and allergy. Our aim is to give an overview of systems biology approaches used in allergy and asthma research. Specifically, we describe recent “omic”-level findings, and examine how these findings have been systematically integrated to generate further insight. Current research suggests that allergy is driven by genetic and epigenetic factors, in concert with environmental factors such as microbiome and diet, leading to early-life disturbance in immunological development and disruption of balance within key immuno-inflammatory pathways. Variation in inherited susceptibility and exposures causes heterogeneity in manifestations of asthma and other allergic diseases. Machine learning approaches are being used to explore this heterogeneity, and to probe the pathophysiological patterns or “endotypes” that correlate with subphenotypes of asthma and allergy. Mathematical models are being built based on genomic, transcriptomic, and proteomic data to predict or discriminate disease phenotypes, and to describe the biomolecular networks behind asthma. The use of systems biology in allergy and asthma research is rapidly growing, and has so far yielded fruitful results. However, the scale and multidisciplinary nature of this research means that it is accompanied by new challenges. Ultimately, it is hoped that systems medicine, with its integration of omics data into clinical practice, can pave the way to more precise, personalised and effective management of asthma.This work was supported by the National Health and Medical Research Council (NHMRC) of Australia via a postgraduate scholarship (ref. no. 1114753) to HHF Tang, research grant (1049539) to M Inouye and K Holt, and Fellowships (1061409) to K Holt and (1061435) to M Inouye. K Holt was further supported by a Senior Medical Research Fellowship from the Viertel Foundation of Australia

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

The nature of gut microbiota in early life:origin and impact of pioneer species

During early childhood, a complex ecosystem of thousands of species of microorganisms develops in our gastrointestinal tract. Disruptions in this development can have lifelong consequences and possibly increase the risk of diseases such as allergies and asthma. In this thesis, the influence of environmental and host factors on the early development of the microbiota was investigated. In addition, the microbiota composition of children in two birth cohorts in relation to the development of allergies and asthma was studied. The oral administration of specific beneficial bacteria, called probiotics, may be a way to specifically manipulate the gut microbiota to achieve health benefits. The last research studied how administering different types of probiotics, consisting of lactobacilli and bifid bacteria, affects the microbiota and health of premature infants. This thesis highlights that early childhood is a critical period in which targeted manipulation of the gut microbiota is possible in order to promote a healthy future and prevent the development of allergies and asthma

An Exploration of the Experiences of Adults that were Raised without Routine Childhood Vaccinations

This thesis explores the experiences of adults raised without routine childhood vaccinations. This is a highly contentious topic and despite the substantial number of children that are raised in this way, there is a paucity of literature exploring this group of people and the outcomes of such health care decisions. This study's theoretical framework is constructed from a phenomenological perspective. A phenomenological methodology guiding this study allowed the researcher to hear the participants' voices as they had experienced this phenomenon. Using a mixed method of data collection enabled the researcher to gain a breadth and depth of the phenomenon in question. Sixty-seven participants completed the open-ended online survey questionnaire and thirteen participants participated in the in-depth interviews. The data was collected from the survey questionnaire, which then informed the in-depth interviews that followed. Participants were found to have a high regard for their health and displayed proactive health conscious behaviours. A high level of contentment was found amongst participants in regards to the vaccine decision that was made on their behalf, with a great majority of participants found to have made the same non-vaccination decision for their own children. This thesis revealed the existence of a significant gap between the lived experience of individual's and the vaccine imperative placed upon the populace. Contributing to the literature, this study gleaned intergenerational insights, directly related to asking participants about vaccine decision-making regarding their own children. In addition, the project elucidated the way in which participants navigated between heterodox and orthodox medicine, in an attempt to meet their health care needs and preferences

Bridging the Gaps: Biomedicine, Complementary and Alternative Medicine in a Holistic Approach

The 4th international conference on holistic health and medicine was held during September 24-26, 2008 in Lexington, Kentucky in the United States of America. This conference brought many participants from 23 countries, both mainstream health care providers as well as holistic health practitioners to address the latest in knowledge and research, and in turn to find ways to collaborate and work together to provide the best possible care for their patients and clients. These conferences are held to build bridges between the various fractions of medicine and health care providers. The scientific program included plenary sessions, keynotes, workshops and research presentations, which were all peer-reviewed by an international scientific committee. Below we will present the abstracts from the conference

Update on Nutrition and Food Allergy

This book describes the causes, diagnosis, and effects of food allergy. It goes deeper into the molecular and cellular mechanisms of food allergy and, in particular, into effects of the processing of certain nutrients, e.g., cow’s milk on the allergenicity of proteins. The book also focuses on new nutrients, e.g., seaweed, and possible effects on allergy and inflammation