Biomed Inform Insights 2017 12;9:1178222617712994. Epub 2017 Jun 12.

Department of Research, Dascena, Inc, Hayward, CA, USA.

Algorithm-based clinical decision support (CDS) systems associate patient-derived health data with outcomes of interest, such as in-hospital mortality. However, the quality of such associations often depends on the availability of site-specific training data. Without sufficient quantities of data, the underlying statistical apparatus cannot differentiate useful patterns from noise and, as a result, may underperform. Read More

Biomed Inform Insights 2017 8;9:1178222617713018. Epub 2017 Jun 8.

Department of Biomedical Informatics, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA.

The objective of this study was to determine whether the Food and Drug Administration's Adverse Event Reporting System (FAERS) data set could serve as the basis of automated electronic health record (EHR) monitoring for the adverse drug reaction (ADR) subset of adverse drug events. We retrospectively collected EHR entries for 71 909 pediatric inpatient visits at Cincinnati Children's Hospital Medical Center. Natural language processing (NLP) techniques were used to identify positive diseases/disorders and signs/symptoms (DDSSs) from the patients' clinical narratives. Read More

Biomed Inform Insights 2017 11;9:1178222617700627. Epub 2017 Apr 11.

School of Biomedical Informatics, The University of Texas, Houston, TX, USA.

Personalized and precision vaccination requires consideration of an individual's sex and age. This article proposed systematic methods to study individual differences in adverse reactions following vaccination and chose trivalent influenza vaccine as a use case. Data were extracted from the Vaccine Adverse Event Reporting System from years 1990 to 2014. Read More

Biomed Inform Insights 2017 30;9:1178222617700626. Epub 2017 Mar 30.

Denver Public Health, Denver, CO, USA.

Introduction: Recent pertussis outbreaks in the United States suggest our response to local disease outbreaks (eg, vaccine-preventable Bordetella pertussis) may benefit from understanding and applying spatial analytical methods that use data from immunization information systems at a subcounty level.

Methods: A 2012 study on Denver, CO, residents less than 19 years of age confirmed pertussis cases and immunization information system records were geocoded and aggregated to the census tract (CT) level. An algorithm assessed whether individuals were up-to-date (UTD) for pertussis vaccines. Read More

Biomed Inform Insights 2017 30;9:1178222617697975. Epub 2017 Mar 30.

Department of Pharmacy Practice, University of Kansas School of Pharmacy, Kansas City, KS, USA.

This systematic review sought to assess the applications and implications of current medical informatics-based decision support systems related to medication prescribing and use. Studies published between January 2006 and July 2016 which were indexed in PubMed and written in English were reviewed, and 39 studies were ultimately included. Most of the studies looked at computerized provider order entry or clinical decision support systems. Read More

Biomed Inform Insights 2017 16;9:1178222617692538. Epub 2017 Feb 16.

Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Pharmacies have been endorsed as alternative vaccine delivery sites to improve vaccination rates through increased access to services. Our objective was to identify challenges and facilitators to adolescent and adult vaccination provision in pharmacy settings in the United States. We recruited 40 licensed pharmacists in states with different pharmacy vaccination laws. Read More

Biomed Inform Insights 2017 9;9:1178222616688893. Epub 2017 Feb 9.

Public Health Informatics Program and Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA.

The vision for management of immunization information is availability of real-time consolidated data and services for all ages, to clinical, public health, and other stakeholders. This is being executed through Immunization Information Systems (IISs), which are population-based and confidential computerized systems present in most US states and territories. Immunization Information Systems offer many functionalities, such as immunization assessment reports, client follow-up, reminder/recall feature, vaccine management tools, state-supplied vaccine ordering, comprehensive immunization history, clinical decision support/vaccine forecasting and recommendations, data processing, and data exchange. Read More

Biomed Inform Insights 2017 8;9:1178222616686067. Epub 2017 Feb 8.

Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.

Religious or spiritual struggles are clinically important to health care chaplains because they are related to poorer health outcomes, involving both mental and physical health problems. Identifying persons experiencing religious struggle poses a challenge for chaplains. One potentially underappreciated means of triaging chaplaincy effort are prayers written in chapel notebooks. Read More

Biomed Inform Insights 2017 10;9:1178222616685880. Epub 2017 Feb 10.

Centre for Rural Health Studies, Faculty of Medicine, Memorial University of Newfoundland St. John's, NL, Canada.

Objective: To assess the validity of the International Classification of Disease (ICD) codes for identifying patients with dyslipidemia in electronic medical record (EMR) data.

Methods: The EMRs of patients receiving primary care in St. John's, Newfoundland and Labrador (NL), Canada, were retrieved from the Canadian Primary Care Sentinel Surveillance Network database. Read More

Biomed Inform Insights 2016 22;8(Suppl 2):23-29. Epub 2016 Dec 22.

Minnesota Department of Health, St. Paul, MN, USA.

Immunization information systems (IIS) are population-based and confidential computerized systems maintained by public health agencies containing individual data on immunizations from participating health care providers. IIS hold comprehensive vaccination histories given across providers and over time. An important aspect to IIS is the clinical decision support for immunizations (CDSi), consisting of vaccine forecasting algorithms to determine needed immunizations. Read More

Biomed Inform Insights 2016 4;8(Suppl 2):15-21. Epub 2016 Dec 4.

Department of Medicine, Division of Epidemiology, Vanderbilt University Medical School, Nashville, TN, USA.

All preteens should receive tetanus-diphtheria-pertussis vaccine (Tdap), quadrivalent meningococcal vaccine (Men-ACWY), and the human papillomavirus (HPV) cancer vaccine series. In Tennessee, HPV vaccination rates have stagnated at low levels for a decade. Three fundamental strategies to reduce missed opportunities for immunization include administering all recommended vaccines at the same visit, making strong recommendations for vaccines, and auditing and feedback. Read More

Biomed Inform Insights 2016 19;8(Suppl 2):1-13. Epub 2016 Oct 19.

President, HLN Consulting, LLC, Palm Desert, CA, USA.

This article focuses on the requirements and current developments in clinical decision support technologies for immunizations (CDSi) in both the public health and clinical communities, with an emphasis on shareable solutions. The requirements of the Electronic Health Record Incentive Programs have raised some unique challenges for the clinical community, including vocabulary mapping, update of changing guidelines, single immunization schedule, and scalability. This article discusses new, collaborative approaches whose long-term goal is to make CDSi more sustainable for both the public and private sectors. Read More

Biomed Inform Insights 2016 19;8:29-38. Epub 2016 Jul 19.

Professor, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.

In natural language processing, stand-off annotation uses the starting and ending positions of an annotation to anchor it to the text and stores the annotation content separately from the text. We address the fundamental problem of efficiently storing stand-off annotations when applying natural language processing on narrative clinical notes in electronic medical records (EMRs) and efficiently retrieving such annotations that satisfy position constraints. Efficient storage and retrieval of stand-off annotations can facilitate tasks such as mapping unstructured text to electronic medical record ontologies. Read More

Biomed Inform Insights 2016 23;8(Suppl 1):13-22. Epub 2016 Jun 23.

Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.

The concept of optimizing health care by understanding and generating knowledge from previous evidence, ie, the Learning Health-care System (LHS), has gained momentum and now has national prominence. Meanwhile, the rapid adoption of electronic health records (EHRs) enables the data collection required to form the basis for facilitating LHS. A prerequisite for using EHR data within the LHS is an infrastructure that enables access to EHR data longitudinally for health-care analytics and real time for knowledge delivery. Read More

Biomed Inform Insights 2016 20;8(Suppl 1):1-11. Epub 2016 Jun 20.

Medical Informatics, Kaiser Permanente Southern California, San Diego, CA, USA.

In an era when most of our life activities are digitized and recorded, opportunities abound to gain insights about population health. Online product reviews present a unique data source that is currently underexplored. Health-related information, although scarce, can be systematically mined in online product reviews. Read More

Biomed Inform Insights 2016 25;8:19-27. Epub 2016 May 25.

School of Business and Economic, Universiti Brunei Darussalam, Brunei Darussalam.

Mobile technology enables health-care organizations to extend health-care services by providing a suitable environment to achieve mobile health (mHealth) goals, making some health-care services accessible anywhere and anytime. Introducing mHealth could change the business processes in delivering services to patients. mHealth could empower patients as it becomes necessary for them to become involved in the health-care processes related to them. Read More

Biomed Inform Insights 2016 22;8:11-8. Epub 2016 May 22.

Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA.

Objective: We describe the development and evaluation of a system that uses machine learning and natural language processing techniques to identify potential candidates for surgical intervention for drug-resistant pediatric epilepsy. The data are comprised of free-text clinical notes extracted from the electronic health record (EHR). Both known clinical outcomes from the EHR and manual chart annotations provide gold standards for the patient's status. Read More

Biomed Inform Insights 2016 19;8:1-10. Epub 2016 Jan 19.

College of Health Science, Department of Health Informatics and Administration, Center for Biomedical Data and Language Processing, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.

Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. Read More

Biomed Inform Insights 2015 1;7:1-9. Epub 2015 Apr 1.

University of Ibadan, Ibadan, Nigeria.

Nowadays, an electronic health information management system (EHIMS) is crucial for patient care in hospitals. This paper explores the aspects and elements that contribute to the success of EHIMS in Nigerian teaching hospitals. The study adopted a survey research design. Read More

Biomed Inform Insights 2013 1;6(Suppl 1):51-62. Epub 2013 Aug 1.

LIMSI-CNRS, Orsay, France.

Medical entity recognition is currently generally performed by data-driven methods based on supervised machine learning. Expert-based systems, where linguistic and domain expertise are directly provided to the system are often combined with data-driven systems. We present here a case study where an existing expert-based medical entity recognition system, Ogmios, is combined with a data-driven system, Caramba, based on a linear-chain Conditional Random Field (CRF) classifier. Read More

Biomed Inform Insights 2013 15;6(Suppl 1):39-50. Epub 2013 Jul 15.

Cognitive Science Research Group, School of Electronic Engineering and Computer Science, London, UK.

Previous research shows that aspects of doctor-patient communication in therapy can predict patient symptoms, satisfaction and future adherence to treatment (a significant problem with conditions such as schizophrenia). However, automatic prediction has so far shown success only when based on low-level lexical features, and it is unclear how well these can generalize to new data, or whether their effectiveness is due to their capturing aspects of style, structure or content. Here, we examine the use of topic as a higher-level measure of content, more likely to generalize and to have more explanatory power. Read More

Biomed Inform Insights 2013 22;6:35-45. Epub 2013 Jul 22.

Department of Pediatrics, Division of Respiratory Medicine, University of California, San Diego, USA. ; Department of Medicine, Division of Biomedical Informatics, University of California, San Diego, USA.

The database of Genotypes and Phenotypes (dbGaP) allows researchers to understand phenotypic contribution to genetic conditions, generate new hypotheses, confirm previous study results, and identify control populations. However, effective use of the database is hindered by suboptimal study retrieval. Our objective is to evaluate text classification techniques to improve study retrieval in the context of the dbGaP database. Read More

Biomed Inform Insights 2013 24;6(Suppl 1):29-37. Epub 2013 Jun 24.

University of Wisconsin-Milwaukee, Milwaukee, WI, USA.

Converting information contained in natural language clinical text into computer-amenable structured representations can automate many clinical applications. As a step towards that goal, we present a method which could help in converting novel clinical phrases into new expressions in SNOMED CT, a standard clinical terminology. Since expressions in SNOMED CT are written in terms of their relations with other SNOMED CT concepts, we formulate the important task of identifying relations between clinical phrases and SNOMED CT concepts. Read More

Biomed Inform Insights 2013 24;6(Suppl 1):17-27. Epub 2013 Jun 24.

Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.

Because of privacy concerns and the expense involved in creating an annotated corpus, the existing small-annotated corpora might not have sufficient examples for learning to statistically extract all the named-entities precisely. In this work, we evaluate what value may lie in automatically generated features based on distributional semantics when using machine-learning named entity recognition (NER). The features we generated and experimented with include n-nearest words, support vector machine (SVM)-regions, and term clustering, all of which are considered distributional semantic features. Read More

Biomed Inform Insights 2013 24;6(Suppl 1):7-16. Epub 2013 Jun 24.

Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN.

A large amount of medication information resides in the unstructured text found in electronic medical records, which requires advanced techniques to be properly mined. In clinical notes, medication information follows certain semantic patterns (eg, medication, dosage, frequency, and mode). Some medication descriptions contain additional word(s) between medication attributes. Read More

Biomed Inform Insights 2013 24;6(Suppl 1):3-5. Epub 2013 Jun 24.

Mayo Clinic, Rochester, MN.

Biomed Inform Insights 2013 24;6(Suppl 1):1-2. Epub 2013 Jun 24.

Biomed Inform Insights 2013 25;6:29-33. Epub 2013 Apr 25.

AT&T Interactive, Glendale, CA, USA.

Introduction: Syndromic surveillance is designed for early detection of disease outbreaks. An important data source for syndromic surveillance is free-text chief complaints (CCs), which are generally recorded in the local language. For automated syndromic surveillance, CCs must be classified into predefined syndromic categories. Read More

Biomed Inform Insights 2013 2;6:15-27. Epub 2013 Apr 2.

School of ITEE, University of Queensland, Australia.

Today's search engines and digital libraries offer little or no support for discovering those scientific artifacts (hypotheses, supporting/contradicting statements, or findings) that form the core of scientific written communication. Consequently, we currently have no means of identifying central themes within a domain or to detect gaps between accepted knowledge and newly emerging knowledge as a means for tracking the evolution of hypotheses from incipient phases to maturity or decline. We present a hybrid Machine Learning approach using an ensemble of four classifiers, for recognizing scientific artifacts (ie, hypotheses, background, motivation, objectives, and findings) within biomedical research publications, as a precursory step to the general goal of automatically creating argumentative discourse networks that span across multiple publications. Read More

Biomed Inform Insights 2013 4;6:1-14. Epub 2013 Feb 4.

School of ITEE, The University of Queensland, Australia.

Over the course of the last few years there has been a significant amount of research performed on ontology-based formalization of phenotype descriptions. The intrinsic value and knowledge captured within such descriptions can only be expressed by taking advantage of their inner structure that implicitly combines qualities and anatomical entities. We present a meta-model (the Phenotype Fragment Ontology) and a processing pipeline that enable together the automatic decomposition and conceptualization of phenotype descriptions for the human skeletal phenome. Read More

Biomed Inform Insights 2012 30;5(Suppl. 1):129-36. Epub 2012 Jan 30.

University Pierre et Marie Curie, Paris 6, CNRS, UMR7606, LIP6, France.

WE STUDY THE DISCRIMINATION OF EMOTIONS ANNOTATED IN FREE TEXTS AT THE SENTENCE LEVEL: a sentence can either be associated with no emotion (neutral) or multiple labels of emotion. The proposed system relies on three characteristics. We implement an early fusion of grams of increasing orders transposing an approach successfully employed in the related task of opinion mining. Read More