Computational Advances in Drug Safety: Systematic and Mapping Review of Knowledge Engineering Based Approaches

Drug Safety (DS) is a domain with significant public health and social impact. Knowledge Engineering (KE) is the Computer Science discipline elaborating on methods and tools for developing “knowledge-intensive” systems, depending on a conceptual “knowledge” schema and some kind of “reasoning” process. The present systematic and mapping review aims to investigate KE-based approaches employed for DS and highlight the introduced added value as well as trends and possible gaps in the domain. Journal articles published between 2006 and 2017 were retrieved from PubMed/MEDLINE and Web of Science® (873 in total) and filtered based on a comprehensive set of inclusion/exclusion criteria. The 80 finally selected articles were reviewed on full-text, while the mapping process relied on a set of concrete criteria (concerning specific KE and DS core activities, special DS topics, employed data sources, reference ontologies/terminologies, and computational methods, etc.). The analysis results are publicly available as online interactive analytics graphs. The review clearly depicted increased use of KE approaches for DS. The collected data illustrate the use of KE for various DS aspects, such as Adverse Drug Event (ADE) information collection, detection, and assessment. Moreover, the quantified analysis of using KE for the respective DS core activities highlighted room for intensifying research on KE for ADE monitoring, prevention and reporting. Finally, the assessed use of the various data sources for DS special topics demonstrated extensive use of dominant data sources for DS surveillance, i.e., Spontaneous Reporting Systems, but also increasing interest in the use of emerging data sources, e.g., observational healthcare databases, biochemical/genetic databases, and social media. Various exemplar applications were identified with promising results, e.g., improvement in Adverse Drug Reaction (ADR) prediction, detection of drug interactions, and novel ADE profiles related with specific mechanisms of action, etc. Nevertheless, since the reviewed studies mostly concerned proof-of-concept implementations, more intense research is required to increase the maturity level that is necessary for KE approaches to reach routine DS practice. In conclusion, we argue that efficiently addressing DS data analytics and management challenges requires the introduction of high-throughput KE-based methods for effective knowledge discovery and management, resulting ultimately, in the establishment of a continuous learning DS system

Knowledge-driven entity recognition and disambiguation in biomedical text

Entity recognition and disambiguation (ERD) for the biomedical domain are notoriously difficult problems due to the variety of entities and their often long names in many variations. Existing works focus heavily on the molecular level in two ways. First, they target scientific literature as the input text genre. Second, they target single, highly specialized entity types such as chemicals, genes, and proteins. However, a wealth of biomedical information is also buried in the vast universe of Web content. In order to fully utilize all the information available, there is a need to tap into Web content as an additional input. Moreover, there is a need to cater for other entity types such as symptoms and risk factors since Web content focuses on consumer health. The goal of this thesis is to investigate ERD methods that are applicable to all entity types in scientific literature as well as Web content. In addition, we focus on under-explored aspects of the biomedical ERD problems -- scalability, long noun phrases, and out-of-knowledge base (OOKB) entities. This thesis makes four main contributions, all of which leverage knowledge in UMLS (Unified Medical Language System), the largest and most authoritative knowledge base (KB) of the biomedical domain. The first contribution is a fast dictionary lookup method for entity recognition that maximizes throughput while balancing the loss of precision and recall. The second contribution is a semantic type classification method targeting common words in long noun phrases. We develop a custom set of semantic types to capture word usages; besides biomedical usage, these types also cope with non-biomedical usage and the case of generic, non-informative usage. The third contribution is a fast heuristics method for entity disambiguation in MEDLINE abstracts, again maximizing throughput but this time maintaining accuracy. The fourth contribution is a corpus-driven entity disambiguation method that addresses OOKB entities. The method first captures the entities expressed in a corpus as latent representations that comprise in-KB and OOKB entities alike before performing entity disambiguation.Die Erkennung und Disambiguierung von Entitäten für den biomedizinischen Bereich stellen, wegen der vielfältigen Arten von biomedizinischen Entitäten sowie deren oft langen und variantenreichen Namen, große Herausforderungen dar. Vorhergehende Arbeiten konzentrieren sich in zweierlei Hinsicht fast ausschließlich auf molekulare Entitäten. Erstens fokussieren sie sich auf wissenschaftliche Publikationen als Genre der Eingabetexte. Zweitens fokussieren sie sich auf einzelne, sehr spezialisierte Entitätstypen wie Chemikalien, Gene und Proteine. Allerdings bietet das Internet neben diesen Quellen eine Vielzahl an Inhalten biomedizinischen Wissens, das vernachlässigt wird. Um alle verfügbaren Informationen auszunutzen besteht der Bedarf weitere Internet-Inhalte als zusätzliche Quellen zu erschließen. Außerdem ist es auch erforderlich andere Entitätstypen wie Symptome und Risikofaktoren in Betracht zu ziehen, da diese für zahlreiche Inhalte im Internet, wie zum Beispiel Verbraucherinformationen im Gesundheitssektor, relevant sind. Das Ziel dieser Dissertation ist es, Methoden zur Erkennung und Disambiguierung von Entitäten zu erforschen, die alle Entitätstypen in Betracht ziehen und sowohl auf wissenschaftliche Publikationen als auch auf andere Internet-Inhalte anwendbar sind. Darüber hinaus setzen wir Schwerpunkte auf oft vernachlässigte Aspekte der biomedizinischen Erkennung und Disambiguierung von Entitäten, nämlich Skalierbarkeit, lange Nominalphrasen und fehlende Entitäten in einer Wissensbank. In dieser Hinsicht leistet diese Dissertation vier Hauptbeiträge, denen allen das Wissen von UMLS (Unified Medical Language System), der größten und wichtigsten Wissensbank im biomedizinischen Bereich, zu Grunde liegt. Der erste Beitrag ist eine schnelle Methode zur Erkennung von Entitäten mittels Lexikonabgleich, welche den Durchsatz maximiert und gleichzeitig den Verlust in Genauigkeit und Trefferquote (precision and recall) balanciert. Der zweite Beitrag ist eine Methode zur Klassifizierung der semantischen Typen von Nomen, die sich auf gebräuchliche Nomen von langen Nominalphrasen richtet und auf einer selbstentwickelten Sammlung von semantischen Typen beruht, die die Verwendung der Nomen erfasst. Neben biomedizinischen können diese Typen auch nicht-biomedizinische und allgemeine, informationsarme Verwendungen behandeln. Der dritte Beitrag ist eine schnelle Heuristikmethode zur Disambiguierung von Entitäten in MEDLINE Kurzfassungen, welche den Durchsatz maximiert, aber auch die Genauigkeit erhält. Der vierte Beitrag ist eine korpusgetriebene Methode zur Disambiguierung von Entitäten, die speziell fehlende Entitäten in einer Wissensbank behandelt. Die Methode wandelt erst die Entitäten, die in einem Textkorpus ausgedrückt aber nicht notwendigerweise in einer Wissensbank sind, in latente Darstellungen um und führt anschließend die Disambiguierung durch

An Evaluation of Medication Safety related Communications in the Patient Healthcare Pathway in Kuwait

Background: Patient safety is a recognised public health issue. When post-market medication safety information emerges, the benefits and risks of the medication concerned are usually evaluated by drug regulatory agencies. The outcomes of such pharmacovigilance activities are communicated to the public, patients and other healthcare professionals (HCPs). The aim of these medication safety communications might vary from improving the intended recipients’ knowledge or attitudes to outlining specific actions to be followed by them. However, it is currently recognised that sharing medication-related information does not improve patients’ safety on its own if not accompanied by an accurate implementation of these recommendations in clinical practice. Despite their importance in protecting patient safety and subsequently affecting public health, no previous study was found to have evaluated or described the process of creating and disseminating medication safety communications by the Kuwaiti drug regulatory agency. Equally, no study was found to have investigated the impact of or the factors affecting the implementation of regulatory-related medication safety communications in Kuwait. Therefore, this thesis aimed to address these gaps in knowledge by evaluating medication safety communications in the patient healthcare pathway in Kuwait. Methods: This multiphase study was preceded by a systematic literature review of the factors affecting HCPs’ implementation of regulatory-related medication safety communications, using a narrative synthesis approach. Following the systematic review, multiphase research was initiated. This consisted of three phases, each of which focused on a specific stakeholder group involved in the process of medication safety communication. Phase 1 involved Kuwait Drug and Food Control (KDFC), an administration within the Ministry of Health (MOH), as the regulatory agency responsible for pharmacovigilance activities. This was a convergent mixed-methods study. Data collection in this phase included documents produced by KDFC or issued to KDFC relating to medication safety and three face-to-face interviews with KDFC employees involved in pharmacovigilance activities. Documents were analysed using a descriptive quantitative approach and a framework analysis technique. Phase 2 focused on healthcare professionals working in MOH hospitals in Kuwait. This phase was an exploratory mixed-methods study, where focus group discussions were conducted followed by the distribution of an online survey. The focus group discussions were analysed using a thematic analysis technique. In the second part of this phase, an online survey was developed based on Phase 1, the focus group discussions and the systematic literature review. Survey data analysis included descriptive analysis (frequency and percentile) and statistical analysis including principal component analysis (PCA) and the Kruskal–Wallis H test, which was followed by a post hoc analysis of variables that had significant results. Other statistical tests applied included Fisher’s exact test, the Mann–Whitney U Test, and multivariate regression analysis. Participants’ answers to open-ended survey questions were analysed using a conventional content analysis technique. Phase 3 was an interpretive phenomenology study. This phase involved semi-structured phone interviews with six female patients of childbearing age who used a valproate-related medication for epilepsy or migraine. These patients had been prescribed the valproate-related medication in one of six secondary hospitals and one specialist neurology hospital within the MOH hospitals. An interpretive phenomenological analysis technique was applied to analyse the transcripts. Results: The results of the systematic literature review indicated that the factors affecting HCPs’ implementation of medication safety communications occur at multiple levels. These levels included the sources or senders of the safety information (delays in the delivery of medications safety communications), healthcare institutions (hospitals’ position and interpretations of the recommendations), the HCPs (knowledge of the content of medications safety communications), and the patients and/or their carers (willingness to use the medication concerned). Phase 1 revealed a lack of legislation and a pharmacovigilance-specific policy. Results from Phase 2 reflected poor knowledge of the concept of medication safety communications within the context of pharmacovigilance and a lack of familiarity with the tools used by KDFC to communicate emerging medication information among HCPs. In the survey, although the majority of HCPs who responded were aware of the teratogenicity of VRM (65.1%, (n = 110/169)), only 2.6% had responded correctly to the statements of the VRM KDFC recommendations. More than half of the participants (57%) reported changing their practice to accommodate at least one intended KDFC recommendation. Providing female patients with written information (37.2%) and counselling female patients about contraceptive use (37.2%) were the most reported intended changes in practice. The most reported barriers to implementation included not having the capacity in terms of time and/or the infrastructure to implement the recommendations (33.8%). Four themes originating from patient interviews included (1) the timeline of the patient’s experience (2) varied knowledge and perception with valproate use, (3) patient’s expectations from HCPs and (4) experiences and preferences towards medication safety communications. Conclusion: Medication safety communications are essential tools for disseminating information related to medication safety updates to HCPs, patients and the public. This research identified challenges at the level of the sender (KDFC) and the intended recipients (HCPs and patients) that could reduce the ability of KDFC’s medication safety communications to reach clinical practices. The first step in increasing their reach is to adapt electronic methods for disseminating such information. Involving stakeholders, such as HCPs and patients, in evaluating the clarity and understandability of KDFC’s medication safety communications should be the focus of future research

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

Framing the challenge of poor-quality medicines: problem definition and policy making in Cambodia, Laos, and Thailand

Falsified and substandard medicines (poor-quality medicines) represent a pressing global health threat that necessitates a stronger policy response. They pose a considerable threat to human lives and an obstacle to infectious disease control, also due to the associated risk of antimicrobial resistance. Policy efforts against poor-quality medicines include strengthening national drug regulation systems and countering the illicit trade in falsified medicines. Current global policy endeavours to improve access quality medicines however form an array of initiatives rather than a coordinated global response. Since the 1990s, academics and policy actors recognise that the circulation of poor-quality medicines represents a pressing global public health concern. This has generated widespread debate in the literature on the drivers and determinants of this policy issue. While past studies highlight widespread disagreement on definitions of the problem of poor-quality medicines, the existing body of literature pays little attention to the way that the problem is understood among policy actors across national and institutional settings. This thesis seeks to explore varying interpretations of this problem among policy actors in three low and middle-income countries. It explores the role of ideas in policy processes by evaluating the variations in perceptions of the problem and the policy developments against poor-quality medicines. The problem of poor-quality antimalarial medicines in the Greater Mekong Subregion (GMS) offers an interesting case study. Despite notable national policy efforts against poor-quality antimalarial medicines in the GMS, evidence suggests that the problem of poor-quality antimalarials persists. As trade liberalization in the region intensifies, there are concerns that reduced custom controls and higher mobility of people and goods may cause further increase in this illicit trade. Through framing analysis, I analyse variations in perceptions of this threat across institutional and national settings. A social constructivist approach to policy analysis guides the analysis of interpretations of this problem and how these interpretations influence policy developments. This study then compares similarities and differences in framings of the problem and in policy processes across countries. I reflect on the dominant frames across the three case countries (the security, health systems and regulatory frames) and on the potential for policy coordination against poor-quality essential medicines in Southeast-Asia. To operationalize this approach, this study relies on three methods of data collection, namely; a stakeholder map, a document analysis and semi-structured interviews with key policy actors

Timely and reliable evaluation of the effects of interventions: a framework for adaptive meta-analysis (FAME)

Most systematic reviews are retrospective and use aggregate data AD) from publications, meaning they can be unreliable, lag behind therapeutic developments and fail to influence ongoing or new trials. Commonly, the potential influence of unpublished or ongoing trials is overlooked when interpreting results, or determining the value of updating the meta-analysis or need to collect individual participant data (IPD). Therefore, we developed a Framework for Adaptive Metaanalysis (FAME) to determine prospectively the earliest opportunity for reliable AD meta-analysis. We illustrate FAME using two systematic reviews in men with metastatic (M1) and non-metastatic (M0)hormone-sensitive prostate cancer (HSPC)

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