Automatically identifying drug conflicts in clinical practice guidelines

Clinical Practice Guidelines (CPGs) are documents developed in a systematic way that aim to improve the quality of health care, reduce variations in medical practice, and reduce health care costs. However, when concurrently apply them, this can lead to adverse drug-drug interactions that can impair the patient’s condition. Several efforts have been made in order to provide systems capable of identifying these conflicts. However, the current approaches for this purpose have some limitations. This paper presents a solution that represents CPGs as Computer-Interpretable Guidelines (CIGs) and allows for the automatic drug conflict identification and resolution. Also, we provide the identification of improvements to include in a future model. Moreover, this system provides clinical recommendations in an agenda, being capable of identifying drug interactions when drugs are prescribed simultaneously and provide conflict-free alternatives.This work has been supported by COMPETE: POCI-01-0145-FEDER-0070 43 and FCT Fundac¸ao para a Ciencia e Tecnologia within the Project Scope UID/CEC/00319/2013. The work of Tiago Oliveira was supported by JSPS KAKENHI Grant Number JP18K18115

Annotating patient clinical records with syntactic chunks and named entities: the Harvey corpus

The free text notes typed by physicians during patient consultations contain valuable information for the study of disease and treatment. These notes are difficult to process by existing natural language analysis tools since they are highly telegraphic (omitting many words), and contain many spelling mistakes, inconsistencies in punctuation, and non-standard word order. To support information extraction and classification tasks over such text, we describe a de-identified corpus of free text notes, a shallow syntactic and named entity annotation scheme for this kind of text, and an approach to training domain specialists with no linguistic background to annotate the text. Finally, we present a statistical chunking system for such clinical text with a stable learning rate and good accuracy, indicating that the manual annotation is consistent and that the annotation scheme is tractable for machine learning

Conflict resolution in clinical treatments

Dissertação de mestrado integrado em Engenharia InformáticaCurrently, in the health area, there is a need for systems that provide support for the decision of health professionals through specific recommendations for each patient based on Clinical Practice Guidelines (CPGs) for automatic interpretation. CPGs are documents that have enormous importance in the daily life of health professionals, playing a key role in reducing variations in medical practice, improving the quality of health care, and reducing health care costs. These documents reflect knowledge about how best to diagnose and treat diseases in the form of a list of clinical recommendations. However, there may be conflicts and interactions in the application of these clinical recommendations, that which in their maximum exponent may impair the patient’s clinical condition. These conflicts are transported to decision support systems, creating the need to develop computational methods to solve these same conflicts. In the case of multimorbid patients, this resolution of conflicts can be very problematic because these patients suffer from several pathologies at the same time, and that the use of a drug for one particular pathology may have a detrimental effect on the application of another drug in another pathology. Therefore, the objective of this dissertation topic is the determination of conflicts and interactions between drugs and the determination of these same alternatives.Atualmente na área da saúde, existe uma necessidade de existirem sistemas que forneçam apoio à decisão dos profissionais de saúde através de recomendações específicas para cada paciente com base em protocolos clínicos para interpretação automática. Os protocolos clínicos são documentos que têm enorme importância no dia-a-dia dos profissionais de saúde, desempenhando um papel fundamental na redução das variações na prática médica, na melhoria da qualidade dos cuidados de saúde e na redução dos custos de saúde. Estes documentos reflectem o conhecimento sobre a melhor forma de diagnosticar e tratar doenças na forma de uma lista de recomendações clínicas. Contudo, podem existir conflitos e interações na aplicação destas recomendações clínicas, que no seu expoente máximo poderão levar a um agravamento do estado clínico do paciente, nomeadamente no caso da aplicação de diferentes fármacos. Estes conflitos são transportados para os sistemas de apoio à decisão, criando a necessidade de desenvolver métodos computacionais de resolução destes mesmos conflitos. No caso dos pacientes multimórbidos esta resolução de conflitos pode ser bastante problemática devido ao facto destes pacientes sofrerem de várias patologias ao mesmo tempo, e que a utilização de um fármaco para uma determinada patologia possa vir a ter um efeito nocivo na aplicação de outro fármaco noutra patologia. Sendo assim, o objetivo deste tema de dissertação é a determinação dos conflitos e interações entre fármacos e a determinação dessas mesmas alternativas

A framework for automated conflict detection and resolution in medical guidelines

This research is supported by the MRC-funded UK Research and Innovation grant MR/S003819/1 and by EPSRC grant EP/M014290/1.Common chronic conditions are routinely treated following standardised procedures known as clinical guidelines. For patients suffering from two or more chronic conditions, known as multimorbidity, several guidelines have to be applied simultaneously, which may lead to severe adverse effects when the combined recommendations and prescribed medications are inconsistent or incomplete. This paper presents an automated formal framework to detect, highlight and resolve conflicts in the treatments used for patients with multimorbidities focusing on medications. The presented extended framework has a front-end which takes guidelines captured in a standard modelling language and returns the visualisation of the detected conflicts as well as suggested alternative treatments. Internally, the guidelines are transformed into formal models capturing the possible unfoldings of the guidelines. The back-end takes the formal models associated with multiple guidelines and checks their correctness with a theorem prover, and inherent inconsistencies with a constraint solver. Key to our approach is the use of an optimising constraint solver which enables us to search for the best solution that resolves/minimises conflicts according to medication efficacy and the degree of severity in case of harmful combinations, also taking into account their temporal overlapping. The approach is illustrated throughout with a real medical example.Publisher PDFPeer reviewe

Annotated Bibliography: Understanding Ambulatory Care Practices in the Context of Patient Safety and Quality Improvement.

The ambulatory care setting is an increasingly important component of the patient safety conversation. Inpatient safety is the primary focus of the vast majority of safety research and interventions, but the ambulatory setting is actually where most medical care is administered. Recent attention has shifted toward examining ambulatory care in order to implement better health care quality and safety practices. This annotated bibliography was created to analyze and augment the current literature on ambulatory care practices with regard to patient safety and quality improvement. By providing a thorough examination of current practices, potential improvement strategies in ambulatory care health care settings can be suggested. A better understanding of the myriad factors that influence delivery of patient care will catalyze future health care system development and implementation in the ambulatory setting

Clinically Actionable Hypercholesterolemia and Hypertriglyceridemia in Children with Nonalcoholic Fatty Liver Disease

OBJECTIVE: To determine the percentage of children with nonalcoholic fatty liver disease (NAFLD) in whom intervention for low-density lipoprotein cholesterol or triglycerides was indicated based on National Heart, Lung, and Blood Institute guidelines. STUDY DESIGN: This multicenter, longitudinal cohort study included children with NAFLD enrolled in the National Institute of Diabetes and Digestive and Kidney Diseases Nonalcoholic Steatohepatitis Clinical Research Network. Fasting lipid profiles were obtained at diagnosis. Standardized dietary recommendations were provided. After 1 year, lipid profiles were repeated and interpreted according to National Heart, Lung, and Blood Institute Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction. Main outcomes were meeting criteria for clinically actionable dyslipidemia at baseline, and either achieving lipid goal at follow-up or meeting criteria for ongoing intervention. RESULTS: There were 585 participants, with a mean age of 12.8 years. The prevalence of children warranting intervention for low-density lipoprotein cholesterol at baseline was 14%. After 1 year of recommended dietary changes, 51% achieved goal low-density lipoprotein cholesterol, 27% qualified for enhanced dietary and lifestyle modifications, and 22% met criteria for pharmacologic intervention. Elevated triglycerides were more prevalent, with 51% meeting criteria for intervention. At 1 year, 25% achieved goal triglycerides with diet and lifestyle changes, 38% met criteria for advanced dietary modifications, and 37% qualified for antihyperlipidemic medications. CONCLUSIONS: More than one-half of children with NAFLD met intervention thresholds for dyslipidemia. Based on the burden of clinically relevant dyslipidemia, lipid screening in children with NAFLD is warranted. Clinicians caring for children with NAFLD should be familiar with lipid management

Professional Judgment in an Era of Artificial Intelligence and Machine Learning

Though artificial intelligence (AI) in healthcare and education now accomplishes diverse tasks, there are two features that tend to unite the information processing behind efforts to substitute it for professionals in these fields: reductionism and functionalism. True believers in substitutive automation tend to model work in human services by reducing the professional role to a set of behaviors initiated by some stimulus, which are intended to accomplish some predetermined goal, or maximize some measure of well-being. However, true professional judgment hinges on a way of knowing the world that is at odds with the epistemology of substitutive automation. Instead of reductionism, an encompassing holism is a hallmark of professional practice—an ability to integrate facts and values, the demands of the particular case and prerogatives of society, and the delicate balance between mission and margin. Any presently plausible vision of substituting AI for education and health-care professionals would necessitate a corrosive reductionism. The only way these sectors can progress is to maintain, at their core, autonomous professionals capable of carefully intermediating between technology and the patients it would help treat, or the students it would help learn