Clinical text data in machine learning: Systematic review

Background: Clinical narratives represent the main form of communication within healthcare providing a personalized account of patient history and assessments, offering rich information for clinical decision making. Natural language processing (NLP) has repeatedly demonstrated its feasibility to unlock evidence buried in clinical narratives. Machine learning can facilitate rapid development of NLP tools by leveraging large amounts of text data. Objective: The main aim of this study is to provide systematic evidence on the properties of text data used to train machine learning approaches to clinical NLP. We also investigate the types of NLP tasks that have been supported by machine learning and how they can be applied in clinical practice. Methods: Our methodology was based on the guidelines for performing systematic reviews. In August 2018, we used PubMed, a multi-faceted interface, to perform a literature search against MEDLINE. We identified a total of 110 relevant studies and extracted information about the text data used to support machine learning, the NLP tasks supported and their clinical applications. The data properties considered included their size, provenance, collection methods, annotation and any relevant statistics. Results: The vast majority of datasets used to train machine learning models included only hundreds or thousands of documents. Only 10 studies used tens of thousands of documents with a handful of studies utilizing more. Relatively small datasets were utilized for training even when much larger datasets were available. The main reason for such poor data utilization is the annotation bottleneck faced by supervised machine learning algorithms. Active learning was explored to iteratively sample a subset of data for manual annotation as a strategy for minimizing the annotation effort while maximizing predictive performance of the model. Supervised learning was successfully used where clinical codes integrated with free text notes into electronic health records were utilized as class labels. Similarly, distant supervision was used to utilize an existing knowledge base to automatically annotate raw text. Where manual annotation was unavoidable, crowdsourcing was explored, but it remains unsuitable due to sensitive nature of data considered. Beside the small volume, training data were typically sourced from a small number of institutions, thus offering no hard evidence about the transferability of machine learning models. The vast majority of studies focused on the task of text classification. Most commonly, the classification results were used to support phenotyping, prognosis, care improvement, resource management and surveillance. Conclusions: We identified the data annotation bottleneck as one of the key obstacles to machine learning approaches in clinical NLP. Active learning and distant supervision were explored as a way of saving the annotation efforts. Future research in this field would benefit from alternatives such as data augmentation and transfer learning, or unsupervised learning, which does not require data annotation

Neurocognitive impairment is associated with lower health literacy among persons living with HIV infection.

This study sought to determine the effects of HIV-associated neurocognitive disorders (HAND) on health literacy, which encompasses the ability to access, understand, appraise, and apply health-related information. Participants included 56 HIV seropositive individuals, 24 of whom met Frascati criteria for HAND, and 24 seronegative subjects who were comparable on age, education, ethnicity, and oral word reading. Each participant was administered a brief battery of well-validated measures of health literacy, including the Expanded Numeracy Scale (ENS), Newest Vital Sign (NVS), Rapid Estimate of Adult Literacy in Medicine (REALM), and Brief Health Literacy Screen (BHLS). Results revealed significant omnibus differences on the ENS and NVS, which were driven by poorer performance in the HAND group. There were no significant differences on the REALM or the BHLS by HAND status. Among individuals with HAND, lower scores on the NVS were associated with greater severity of neurocognitive dysfunction (e.g., working memory and verbal fluency) and self-reported dependence in activities of daily living. These preliminary findings suggest that HAND hinders both fundamental (i.e., basic knowledge, such as numeracy) and critical (i.e., comprehension and application of healthcare information) health literacy capacities, and therefore may be an important factor in the prevalence of health illiteracy. Health literacy-focused intervention may play an important role in the treatment and health trajectories among persons living with HIV infection

Social & Legal Perspectives on Underuse of Medication-Assisted Treatment for Opioid Dependence

Medication-assisted treatment (MAT) in combination with counseling is considered the most effective treatment for opioid dependence by the World Health Organization, U.S. Department of Health and Human Services, and American Society of Addiction Medicine. Two MAT medications, buprenorphine and methadone, are considered essential medicines by the World Health Organization. Despite MAT’s effectiveness, it is severely underused in U.S. treatment settings, including physicians’ offices, hospitals, the Veterans Administration, residential treatment centers, prisons, and drug courts. The dissertation examines social and legal reasons for under-use of MAT in the U.S., including dominance of abstinence-only treatment methods, separation of addiction treatment from mainstream medical treatment, insurance barriers, statutory and regulatory barriers, under-education of physicians in addiction medicine, under-education of mental health counselors in MAT, lack of physician involvement in the criminal justice system, and public understanding of addiction as a spiritual disease rather than a brain disease. The dissertation concludes with suggestions for expanding access to MAT, including government funding incentives and integration of MAT into existing addiction treatment centers and educational programs

Social & Legal Perspectives on Underuse of Medication-Assisted Treatment for Opioid Dependence

Medication-assisted treatment (MAT) in combination with counseling is considered the most effective treatment for opioid dependence by the World Health Organization, U.S. Department of Health and Human Services, and American Society of Addiction Medicine. Two MAT medications, buprenorphine and methadone, are considered essential medicines by the World Health Organization. Despite MAT’s effectiveness, it is severely underused in U.S. treatment settings, including physicians’ offices, hospitals, the Veterans Administration, residential treatment centers, prisons, and drug courts. The dissertation examines social and legal reasons for under-use of MAT in the U.S., including dominance of abstinence-only treatment methods, separation of addiction treatment from mainstream medical treatment, insurance barriers, statutory and regulatory barriers, under-education of physicians in addiction medicine, under-education of mental health counselors in MAT, lack of physician involvement in the criminal justice system, and public understanding of addiction as a spiritual disease rather than a brain disease. The dissertation concludes with suggestions for expanding access to MAT, including government funding incentives and integration of MAT into existing addiction treatment centers and educational programs

An ontology for formal representation of medication adherence-related knowledge : case study in breast cancer

Indiana University-Purdue University Indianapolis (IUPUI)Medication non-adherence is a major healthcare problem that negatively impacts the health and productivity of individuals and society as a whole. Reasons for medication non-adherence are multi-faced, with no clear-cut solution. Adherence to medication remains a difficult area to study, due to inconsistencies in representing medicationadherence behavior data that poses a challenge to humans and today’s computer technology related to interpreting and synthesizing such complex information. Developing a consistent conceptual framework to medication adherence is needed to facilitate domain understanding, sharing, and communicating, as well as enabling researchers to formally compare the findings of studies in systematic reviews. The goal of this research is to create a common language that bridges human and computer technology by developing a controlled structured vocabulary of medication adherence behavior—“Medication Adherence Behavior Ontology” (MAB-Ontology) using breast cancer as a case study to inform and evaluate the proposed ontology and demonstrating its application to real-world situation. The intention is for MAB-Ontology to be developed against the background of a philosophical analysis of terms, such as belief, and desire to be human, computer-understandable, and interoperable with other systems that support scientific research. The design process for MAB-Ontology carried out using the METHONTOLOGY method incorporated with the Basic Formal Ontology (BFO) principles of best practice. This approach introduces a novel knowledge acquisition step that guides capturing medication-adherence-related data from different knowledge sources, including adherence assessment, adherence determinants, adherence theories, adherence taxonomies, and tacit knowledge source types. These sources were analyzed using a systematic approach that involved some questions applied to all source types to guide data extraction and inform domain conceptualization. A set of intermediate representations involving tables and graphs was used to allow for domain evaluation before implementation. The resulting ontology included 629 classes, 529 individuals, 51 object property, and 2 data property. The intermediate representation was formalized into OWL using Protégé. The MAB-Ontology was evaluated through competency questions, use-case scenario, face validity and was found to satisfy the requirement specification. This study provides a unified method for developing a computerized-based adherence model that can be applied among various disease groups and different drug categories

Functional Organization of the Human Brain: How We See, Feel, and Decide.

The human brain is responsible for constructing how we perceive, think, and act in the world around us. The organization of these functions is intricately distributed throughout the brain. Here, I discuss how functional magnetic resonance imaging (fMRI) was employed to understand three broad questions: how do we see, feel, and decide? First, high-resolution fMRI was used to measure the polar angle representation of saccadic eye movements in the superior colliculus. We found that eye movements along the superior-inferior visual field are mapped across the medial-lateral anatomy of a subcortical midbrain structure, the superior colliculus (SC). This result is consistent with the topography in monkey SC. Second, we measured the empathic responses of the brain as people watched a hand get painfully stabbed with a needle. We found that if the hand was labeled as belonging to the same religion as the observer, the empathic neural response was heightened, creating a strong ingroup bias that could not be readily manipulated. Third, we measured brain activity in individuals as they made free decisions (i.e., choosing randomly which of two buttons to press) and found the activity within fronto-thalamic networks to be significantly decreased compared to being instructed (forced) to press a particular button. I also summarize findings from several other projects ranging from addiction therapies to decoding visual imagination to how corporations are represented as people. Together, these approaches illustrate how functional neuroimaging can be used to understand the organization of the human brain

Identifying Transfer of Care Gaps: Electronic Health Record Capture of Perioperative Handoff Communications

Transitions in patient care are held together by interdisciplinary handoff communications intended to coordinate the patient\u27s ongoing care requirements. Patients with complexity in care encumber the transfer of care process requiring a higher level of care coordination between the interdisciplinary team (Coleman, 2003; Naylor et al., 2004). While the literature is abundant on the characteristics and quality of handoff communications, it is limited on the requirements of what data is necessary for ongoing care following transfer communications (Galatzan & Carrington, 2018). This dissertation explores the verbal information transferred during Operating Room (OR) to Post Anesthesia Care Unit (PACU) nursing handoff communications and whether the data is captured in the electronic health record (EHR) to represent the information critical to ongoing patient care and care planning. the study builds on the Kennedy Integrated Theoretical Framework (KITF) (Kennedy, 2012) integrating cognition theory, patterns of knowledge theory, and clinical communication space theory to support the human-technology characteristics within perioperative handoffs. Evidence of wisdom was present in the KITF in addition to elements of non-verbal communication patterns emerging from shared common ground contributed to the framework\u27s expansion. to understand the contributions of the perioperative nursing interface terminology, the Perioperative Nursing Data Set (PNDS), makes to postsurgical care transitions, the study examines nursing diagnoses, interventions, interim outcomes and goals relationships to the handoff data communicated between OR and PACU Registered Nurses. Study findings revealed a complex fragmented process of verbal communications and electronic documentation for the handoff process. While the EHR is prominent in data procurement for the handoff process, the design of handoff artifacts (e.g., paper, electronic) significantly impact the value of information received. Incomplete handoff tools or missing EHR data adds to a cycle of information decay while contributing to increase cognitive load and potentiating opportunities for information and knowledge loss. the absence of nursing diagnoses in the automation of the PNDS challenges the integrity of the language within the documentation platform and raises considerations for hierarchical representation within interface terminologies. This study reinforces literature to reconsider user requirements in the design and functionality of healthcare information technology (HIT) to enable data and information flow and preserve knowledge development. the inclusion of mobile technology, cognitive support aids including clinical decision support tools, and other HIT will further enable the effectiveness of transfer communication, knowledge development, and the safety of ongoing patient care

The Role of the Hippocampus in Representations of Emotional Memory

Although the hippocampus has long been implicated in contextual fear learning, the exact function of this brain structure is unclear. It is generally thought to encode a spatial context with which a fear memory can be associated, but how it may accomplish this and whether it plays a role in emotional memory is largely unknown. It is also unclear whether the hippocampus acts as a single unitary structure, or whether the dorsal and ventral poles, which exhibit differential connectivity to other brain regions, function independently. This dissertation examines the involvement of the hippocampus in emotional learning. A contextual fear conditioning paradigm using a predator odor as an ethologically relevant fearful stimulus was developed and lesions and immunohistochemistry were used to examine differential involvement of the dorsal and ventral hippocampus in response to fear learning. Long-term physiological recordings of dorsal place cells were then conducted to determine the effects of fear conditioning and also fear extinction on contextual representations in the hippocampus. Additionally, cells in the ventral hippocampus were assessed for responses to visuospatial manipulations and changing odor cues of varying emotional valence. It was found that the dorsal and ventral hippocampal regions are both independently required for contextual fear conditioning, and neurons in each region are differentially activated in response to fear learning. Furthermore, place cells in the dorsal hippocampus remapped in response to fear conditioning and stabilized those new fields in the long term. Extinction training caused many place cells to remap once again, suggesting that the dorsal hippocampus encodes varying representations of `fearful\u27 and `safe\u27 contexts. Finally, cells in the ventral hippocampus exhibited stronger responses to anxiogenic contextual cues compared to dorsal cells. In conclusion, these data suggest that the hippocampus is involved in emotional learning and that its function may vary along its longitudinal axis

Inventing Psychiatric Drug Maintenance

This dissertation explores a major change in the way the maintenance of recovery from mental illness was authoritatively represented between the mid 1950s and the present. A shift from individual case reports to clinical trials as medicines authoritative knowledge-framework made possible a view of mental health as something to be achieved then maintained pharmaceutically. Through a controversial experiment that both produced and studied responders to maintenance drugs, it became possible to assess maintenance drugs in terms of an idealized, optimized state, rather than in relation to a personalized baseline. This new, idealized understanding of mental health emerged in the early 1970s and operated alongside traditional concepts of psychiatric diagnosis and prognosis, where each disease category implied an expected trajectory that interventions could only temporarily alter, for example by sedating or restraining. It harmonized with a managerial style of thinking among mental hospital psychiatrists who imagined a future in which medicated inmates would flow and circulate through institutions, achieving live release, rather than sedimenting into long-term custodial care. Pharmaceutically-maintained mental health unfolded in treatment phases, in the margins of epidemiological diagrams, in the minds eye of life insurance company medical directors as financial payouts due to suicide, in the pages of medical journals devoted to narrative medicine and in the decisions of physicians considering self-reporting to medical regulators. Mental health achieved and maintained with drugs, viewed from the perspective of business or occupational risk managers was seen as inherently untrustworthy, fragile, and at risk of failing. The result was on the one hand, a medical discourse that confidently represented and even promoted the idea that mental health could be pharmacologically maintained, and on the other a discourse of corporate risk management that saw fragility and risk among anyone who used mind altering drugs. Diverging from studies that isolate specific categories of mental illness, the dissertation bridges histories of pharmacology, medical epistemology, insurance, and professionalization. It shows how a science of maintenance psychiatric drugs evolved to favor the interests of its makers, while at the same time stacking the odds against the very consumers it claimed to serve

Conveying meaning through design in a safety critical medical system

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityMedication errors account for a significant number of medical errors. Giving medications to patients is an activity that carries a high risk of error. In an effort to improve patient safety in this area several approaches have been employed. Many of these have taken a systems approach in that they consider how organisational factors such as medicines management, staffing levels, ward layout, shift patterns and staff training have contributed to the errors. None of these studies describe errors in detailed form at task level. This Thesis addresses the gap in knowledge by presenting a systematic analysis of the component tasks of hospital drug administration where none exists and goes on to describe novel design artefacts that assist the identification of drugs. The thesis highlights how hierarchical task analysis, a human factors technique, can be applied to the hospital drug administration task. Task analysis techniques have been used in many high-risk domains in industry as a means of analysing human activity in complex systems but remains an underused technique in health care. Used with the Systematic Human Error Reduction and Prediction Approach (SHERPA), hierarchical task analysis provides an effective way of predicting where errors in the drug administration task are likely to occur. SHERPA uses a taxonomy of human error modes to highlight types of error and makes suggestions to reduce these errors. Medication errors take many forms however it was decided to focus on the immediate interaction between the nurse and the patient. The measures considered to potentially have a significant influence were adding conspicuous labelling to medication packages. These were enhanced by icons intended to represent categories of drugs. Constructing a three dimensional representation of the icon design was considered to provide nurses with an additional channel of information. Technological solutions were proposed and a patient identity bracelet that uses a programmable chip to link the patient to their prescribed medication was viewed as having a huge potential to simplify the checking aspect of administering medications in which the nurse compares a medication order which is often badly written with available drug stock. The device prevents nurses giving medications to the wrong patient. It also prevents them administering an overdose.Anthony Anson medical fun