2,975 results match your criteria Journal of the American Medical Informatics Association [Journal]


Speech recognition for clinical documentation from 1990 to 2018: a systematic review.

J Am Med Inform Assoc 2019 Feb 11. Epub 2019 Feb 11.

General Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, USA.

Objective: The study sought to review recent literature regarding use of speech recognition (SR) technology for clinical documentation and to understand the impact of SR on document accuracy, provider efficiency, institutional cost, and more.

Materials And Methods: We searched 10 scientific and medical literature databases to find articles about clinician use of SR for documentation published between January 1, 1990, and October 15, 2018. We annotated included articles with their research topic(s), medical domain(s), and SR system(s) evaluated and analyzed the results. Read More

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http://dx.doi.org/10.1093/jamia/ocy179DOI Listing
February 2019

Criteria2Query: a natural language interface to clinical databases for cohort definition.

J Am Med Inform Assoc 2019 Feb 7. Epub 2019 Feb 7.

Department of Biomedical Informatics, Columbia University, New York, New York, USA.

Objective: Cohort definition is a bottleneck for conducting clinical research and depends on subjective decisions by domain experts. Data-driven cohort definition is appealing but requires substantial knowledge of terminologies and clinical data models. Criteria2Query is a natural language interface that facilitates human-computer collaboration for cohort definition and execution using clinical databases. Read More

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http://dx.doi.org/10.1093/jamia/ocy178DOI Listing
February 2019

Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review.

J Am Med Inform Assoc 2019 Feb 6. Epub 2019 Feb 6.

School of Nursing, Columbia University, New York, New York, USA.

Objective: Natural language processing (NLP) of symptoms from electronic health records (EHRs) could contribute to the advancement of symptom science. We aim to synthesize the literature on the use of NLP to process or analyze symptom information documented in EHR free-text narratives.

Materials And Methods: Our search of 1964 records from PubMed and EMBASE was narrowed to 27 eligible articles. Read More

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http://dx.doi.org/10.1093/jamia/ocy173DOI Listing
February 2019

Incorporating a location-based socioeconomic index into a de-identified i2b2 clinical data warehouse.

J Am Med Inform Assoc 2019 Jan 31. Epub 2019 Jan 31.

Department of Emergency Medicine, University of Nebraska Medical Center, Omaha, Nebraska, USA.

Objective: Clinical research data warehouses are largely populated from information extracted from electronic health records (EHRs). While these data provide information about a patient's medications, laboratory results, diagnoses, and history, her social, economic, and environmental determinants of health are also major contributing factors in readmission, morbidity, and mortality and are often absent or unstructured in the EHR. Details about a patient's socioeconomic status may be found in the U. Read More

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http://dx.doi.org/10.1093/jamia/ocy172DOI Listing
January 2019

How scientists can take the lead in establishing ethical practices for social media research.

J Am Med Inform Assoc 2019 Jan 29. Epub 2019 Jan 29.

Department of Family Medicine and Public Health, Center for Wireless and Population Health Systems, University of California, San Diego, San Diego, California, USA.

Social media use has become ubiquitous in the United States, providing unprecedented opportunities for research. However, the rapidly evolving research landscape has far outpaced federal regulations for the protection of human subjects. Recent highly publicized scandals have raised legitimate concerns in the media about how social media data are being used. Read More

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http://dx.doi.org/10.1093/jamia/ocy174DOI Listing
January 2019

The impact of mobile technology on teamwork and communication in hospitals: a systematic review.

J Am Med Inform Assoc 2019 Jan 25. Epub 2019 Jan 25.

Institute of Global Health Innovation, Imperial College London, London, United Kingdom.

Objectives: Effective communication is critical to the safe delivery of care but is characterized by outdated technologies. Mobile technology has the potential to transform communication and teamwork but the evidence is currently uncertain. The objective of this systematic review was to summarize the quality and breadth of evidence for the impact of mobile technologies on communication and teamwork in hospitals. Read More

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http://dx.doi.org/10.1093/jamia/ocy175DOI Listing
January 2019

The journey to transparency, reproducibility, and replicability.

Authors:
Suzanne Bakken

J Am Med Inform Assoc 2019 Mar;26(3):185-187

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http://dx.doi.org/10.1093/jamia/ocz007DOI Listing

Can informatics innovation help mitigate clinician burnout?

Authors:
Suzanne Bakken

J Am Med Inform Assoc 2019 Feb;26(2):93-94

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http://dx.doi.org/10.1093/jamia/ocy186DOI Listing
February 2019

Spell checker for consumer language (CSpell).

J Am Med Inform Assoc 2019 Mar;26(3):211-218

Lister Hill National Center for Biomedical Communications National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.

Objective: Automated understanding of consumer health inquiries might be hindered by misspellings. To detect and correct various types of spelling errors in consumer health questions, we developed a distributable spell-checking tool, CSpell, that handles nonword errors, real-word errors, word boundary infractions, punctuation errors, and combinations of the above.

Methods: We developed a novel approach of using dual embedding within Word2vec for context-dependent corrections. Read More

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http://dx.doi.org/10.1093/jamia/ocy171DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6351975PMC
March 2019
2 Reads

Measuring the rate of manual transcription error in outpatient point-of-care testing.

J Am Med Inform Assoc 2019 Mar;26(3):269-272

Department of Laboratory Medicine, UW Medicine, Seattle, Washington, USA.

Many point-of-care laboratory tests are manually entered into the electronic health record by ambulatory clinic staff, but the rate of manual transcription error for this testing is poorly characterized. Using a dataset arising from a duplicated workflow that created a set of paired interfaced and manually entered point-of-care glucose measurements, we found that 260 of 6930 (3.7%) manual entries were discrepant from their interfaced result. Read More

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https://academic.oup.com/jamia/advance-article/doi/10.1093/j
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http://dx.doi.org/10.1093/jamia/ocy170DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6351970PMC
March 2019
8 Reads

Integrating ontologies of human diseases, phenotypes, and radiological diagnosis.

J Am Med Inform Assoc 2019 Feb;26(2):149-154

Department of Radiology and Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, USA.

Mappings between ontologies enable reuse and interoperability of biomedical knowledge. The Radiology Gamuts Ontology (RGO)-an ontology of 16 918 diseases, interventions, and imaging observations-provides a resource for differential diagnosis and automated textual report understanding in radiology. An automated process with subsequent manual review was used to identify exact and partial matches of RGO entities to the Disease Ontology (DO) and the Human Phenotype Ontology (HPO). Read More

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http://dx.doi.org/10.1093/jamia/ocy161DOI Listing
February 2019
2 Reads

Natural language processing and machine learning to identify alcohol misuse from the electronic health record in trauma patients: development and internal validation.

J Am Med Inform Assoc 2019 Mar;26(3):254-261

Health Sciences Division, Center for Health Outcomes and Informatics Research, Loyola University, Maywood, Illinois, USA.

Objective: Alcohol misuse is present in over a quarter of trauma patients. Information in the clinical notes of the electronic health record of trauma patients may be used for phenotyping tasks with natural language processing (NLP) and supervised machine learning. The objective of this study is to train and validate an NLP classifier for identifying patients with alcohol misuse. Read More

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http://dx.doi.org/10.1093/jamia/ocy166DOI Listing
March 2019
1 Read

Robust clinical marker identification for diabetic kidney disease with ensemble feature selection.

J Am Med Inform Assoc 2019 Mar;26(3):242-253

Department of Internal Medicine, Division of Medical Informatics, University of Kansas Medical Center, Kansas City, Kansas, USA.

Objective: Diabetic kidney disease (DKD) is one of the most frequent complications in diabetes associated with substantial morbidity and mortality. To accelerate DKD risk factor discovery, we present an ensemble feature selection approach to identify a robust set of discriminant factors using electronic medical records (EMRs).

Material And Methods: We identified a retrospective cohort of 15 645 adult patients with type 2 diabetes, excluding those with pre-existing kidney disease, and utilized all available clinical data types in modeling. Read More

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http://dx.doi.org/10.1093/jamia/ocy165DOI Listing
March 2019
1 Read

Twenty-five years of national health IT: exploring strategy, structure, and systems in the English NHS.

J Am Med Inform Assoc 2019 Mar;26(3):188-197

Management and Organisation Division, University of Leicester, School of Business, University Road, Leicester LE1 7RH, UK.

Objective: There is global interest in implementing national information systems to support healthcare, and the National Health Service in England (NHS) has a troubled 25-year history in this sphere. Our objective was to chronicle structural reorganizations within the NHS from 1973 to 2017, alongside concurrent national information technology (IT) strategies, as the basis for developing a conceptual model to aid understanding of the organizational factors involved.

Materials And Methods: We undertook an exploratory, retrospective longitudinal case study by reviewing strategic plans, legislation, and health policy documents, and constructed schemata for evolving structure and strategy. Read More

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http://dx.doi.org/10.1093/jamia/ocy162DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6351974PMC

An expandable approach for design and personalization of digital, just-in-time adaptive interventions.

J Am Med Inform Assoc 2019 Mar;26(3):198-210

Department of Computer Engineering, Middle East Technical University, Ankara, Turkey.

Objective: We aim to deliver a framework with 2 main objectives: 1) facilitating the design of theory-driven, adaptive, digital interventions addressing chronic illnesses or health problems and 2) producing personalized intervention delivery strategies to support self-management by optimizing various intervention components tailored to people's individual needs, momentary contexts, and psychosocial variables.

Materials And Methods: We propose a template-based digital intervention design mechanism enabling the configuration of evidence-based, just-in-time, adaptive intervention components. The design mechanism incorporates a rule definition language enabling experts to specify triggering conditions for interventions based on momentary and historical contextual/personal data. Read More

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http://dx.doi.org/10.1093/jamia/ocy160DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6351973PMC
March 2019
6 Reads

Enrichment sampling for a multi-site patient survey using electronic health records and census data.

J Am Med Inform Assoc 2019 Mar;26(3):219-227

Department of Biostatistics, Vanderbilt University, Nashville, Tennessee, USA.

Objective: We describe a stratified sampling design that combines electronic health records (EHRs) and United States Census (USC) data to construct the sampling frame and an algorithm to enrich the sample with individuals belonging to rarer strata.

Materials And Methods: This design was developed for a multi-site survey that sought to examine patient concerns about and barriers to participating in research studies, especially among under-studied populations (eg, minorities, low educational attainment). We defined sampling strata by cross-tabulating several socio-demographic variables obtained from EHR and augmented with census-block-level USC data. Read More

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https://academic.oup.com/jamia/advance-article/doi/10.1093/j
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http://dx.doi.org/10.1093/jamia/ocy164DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6351976PMC
March 2019
5 Reads

Classifying relations in clinical narratives using segment graph convolutional and recurrent neural networks (Seg-GCRNs).

J Am Med Inform Assoc 2019 Mar;26(3):262-268

Department of Preventive Medicine, Northwestern University, Chicago, Illinois, USA.

We propose to use segment graph convolutional and recurrent neural networks (Seg-GCRNs), which use only word embedding and sentence syntactic dependencies, to classify relations from clinical notes without manual feature engineering. In this study, the relations between 2 medical concepts are classified by simultaneously learning representations of text segments in the context of sentence syntactic dependency: preceding, concept1, middle, concept2, and succeeding segments. Seg-GCRN was systematically evaluated on the i2b2/VA relation classification challenge datasets. Read More

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http://dx.doi.org/10.1093/jamia/ocy157DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6351971PMC

Pharmacogenomic clinical decision support design and multi-site process outcomes analysis in the eMERGE Network.

J Am Med Inform Assoc 2019 Feb;26(2):143-148

Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.

To better understand the real-world effects of pharmacogenomic (PGx) alerts, this study aimed to characterize alert design within the eMERGE Network, and to establish a method for sharing PGx alert response data for aggregate analysis. Seven eMERGE sites submitted design details and established an alert logging data dictionary. Six sites participated in a pilot study, sharing alert response data from their electronic health record systems. Read More

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https://academic.oup.com/jamia/advance-article/doi/10.1093/j
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http://dx.doi.org/10.1093/jamia/ocy156DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339514PMC
February 2019
5 Reads

Cranky comments: detecting clinical decision support malfunctions through free-text override reasons.

J Am Med Inform Assoc 2019 Jan;26(1):37-43

Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, USA.

Background: Rule-base clinical decision support alerts are known to malfunction, but tools for discovering malfunctions are limited.

Objective: Investigate whether user override comments can be used to discover malfunctions.

Methods: We manually classified all rules in our database with at least 10 override comments into 3 categories based on a sample of override comments: "broken," "not broken, but could be improved," and "not broken. Read More

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http://dx.doi.org/10.1093/jamia/ocy139DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308015PMC
January 2019

Designing a medication timeline for patients and physicians.

J Am Med Inform Assoc 2019 Feb;26(2):95-105

Department of Family and Community Medicine, School of Medicine, University of Missouri, Columbia, Missouri, USA.

Objective: Most electronic health records display historical medication information only in a data table or clinician notes. We designed a medication timeline visualization intended to improve ease of use, speed, and accuracy in the ambulatory care of chronic disease.

Materials And Methods: We identified information needs for understanding a patient medication history, then applied human factors and interaction design principles to support that process. Read More

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http://dx.doi.org/10.1093/jamia/ocy143DOI Listing
February 2019

Doing what matters most.

Authors:
Suzanne Bakken

J Am Med Inform Assoc 2019 Jan;26(1):1-2

School of Nursing, Department of Biomedical Informatics, and Data Science Institute, Columbia University, New York, NY, USA.

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http://dx.doi.org/10.1093/jamia/ocy168DOI Listing
January 2019

Clinicians' reasoning as reflected in electronic clinical note-entry and reading/retrieval: a systematic review and qualitative synthesis.

J Am Med Inform Assoc 2019 Feb;26(2):172-184

Informatics Institute, University of Alabama at Birmingham, Birmingham, Alabama, USA.

Objective: To describe the literature exploring the use of electronic health record (EHR) systems to support creation and use of clinical documentation to guide future research.

Materials And Methods: We searched databases including MEDLINE, Scopus, and CINAHL from inception to April 20, 2018, for studies applying qualitative or mixed-methods examining EHR use to support creation and use of clinical documentation. A qualitative synthesis of included studies was undertaken. Read More

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http://dx.doi.org/10.1093/jamia/ocy155DOI Listing
February 2019
6 Reads

People-powered data collaboratives: fueling data science with the health-related experiences of individuals.

J Am Med Inform Assoc 2019 Feb;26(2):159-161

Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.

The creation of people-driven data collaboratives, with governance structures that enable participants to have a meaningful voice in issues surrounding the use of their own data, is a novel strategy to harness our growing capacity to develop and maintain immense data assets from the real health experiences of individuals. Read More

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http://dx.doi.org/10.1093/jamia/ocy159DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339513PMC
February 2019

Impact of document consolidation on healthcare providers' perceived workload and information reconciliation tasks: a mixed methods study.

J Am Med Inform Assoc 2019 Feb;26(2):134-142

Center for Biomedical Informatics, Regenstrief Institute, Inc., Indianapolis, Indiana, USA.

Background: Information reconciliation is a common yet complex and often time-consuming task performed by healthcare providers. While electronic health record systems can receive "outside information" about a patient in electronic documents, rarely does the computer automate reconciling information about a patient across all documents.

Materials And Methods: Using a mixed methods design, we evaluated an information system designed to reconcile information across multiple electronic documents containing health records for a patient received from a health information exchange (HIE) network. Read More

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http://dx.doi.org/10.1093/jamia/ocy158DOI Listing
February 2019

Electronic cigarette usage patterns: a case study combining survey and social media data.

J Am Med Inform Assoc 2019 Jan;26(1):9-18

Department of Management Information Systems, University of Arizona, Tucson, Arizona, USA.

Objective: To identify who were social media active e-cigarette users, to compare the use patterns from both survey and social media data for data triangulation, and to jointly use both datasets to conduct a comprehensive analysis on e-cigarette future use intentions.

Materials And Methods: We jointly used an e-cigarette use online survey (n = 5132) and a social media dataset. We conducted analysis from 3 different perspectives. Read More

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http://dx.doi.org/10.1093/jamia/ocy140DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308011PMC
January 2019

Reflections on the journey of editing a scientific journal.

J Am Med Inform Assoc 2018 Dec;25(12):1584-1585

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http://dx.doi.org/10.1093/jamia/ocy167DOI Listing
December 2018
1 Read

Detecting moderate or complex congenital heart defects in adults from an electronic health records system.

J Am Med Inform Assoc 2018 Dec;25(12):1634-1642

Emory University School of Medicine, Atlanta, GA, USA.

Background: The prevalence of moderate or complex (moderate-complex) congenital heart defects (CHDs) among adults is increasing due to improved survival, but many patients experience lapses in specialty care or their CHDs are undocumented in the medical system. There is, to date, no efficient approach to identify this population.

Objective: To develop and assess the performance of a risk score to identify adults aged 20-60 years with undocumented specific moderate-complex CHDs from electronic health records (EHR). Read More

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https://academic.oup.com/jamia/article/25/12/1634/5239000
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http://dx.doi.org/10.1093/jamia/ocy127DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6319253PMC
December 2018
7 Reads

Development and user evaluation of a rare disease gene prioritization workflow based on cognitive ergonomics.

J Am Med Inform Assoc 2019 Feb;26(2):124-133

Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada.

Objective: The clinical diagnosis of genetic disorders is undergoing transformation, driven by whole exome sequencing and whole genome sequencing (WES/WGS). However, such nucleotide-level resolution technologies create an interpretive challenge. Prior literature suggests that clinicians may employ characteristic cognitive processes during WES/WGS investigations to identify disruptions in genes causal for the observed disease. Read More

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https://academic.oup.com/jamia/advance-article/doi/10.1093/j
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http://dx.doi.org/10.1093/jamia/ocy153DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339516PMC
February 2019
2 Reads

Information visualizations of symptom information for patients and providers: a systematic review.

J Am Med Inform Assoc 2019 Feb;26(2):162-171

School of Nursing, Columbia University, New York City, New York USA.

Objective: To systematically synthesize the literature on information visualizations of symptoms included as National Institute of Nursing Research common data elements and designed for use by patients and/or healthcare providers.

Methods: We searched CINAHL, Engineering Village, PsycINFO, PubMed, ACM Digital Library, and IEEE Explore Digital Library to identify peer-reviewed studies published between 2007 and 2017. We evaluated the studies using the Mixed Methods Appraisal Tool (MMAT) and a visualization quality score, and organized evaluation findings according to the Health Information Technology Usability Evaluation Model. Read More

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http://fdslive.oup.com/www.oup.com/pdf/production_in_progres
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http://dx.doi.org/10.1093/jamia/ocy152DOI Listing
February 2019
14 Reads

Synthesizing electronic health records using improved generative adversarial networks.

J Am Med Inform Assoc 2019 Mar;26(3):228-241

Institute of Information Science, Academia Sinica, Taipei, Taiwan.

Objective: The aim of this study was to generate synthetic electronic health records (EHRs). The generated EHR data will be more realistic than those generated using the existing medical Generative Adversarial Network (medGAN) method.

Materials And Methods: We modified medGAN to obtain two synthetic data generation models-designated as medical Wasserstein GAN with gradient penalty (medWGAN) and medical boundary-seeking GAN (medBGAN)-and compared the results obtained using the three models. Read More

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https://academic.oup.com/jamia/advance-article/doi/10.1093/j
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http://dx.doi.org/10.1093/jamia/ocy142DOI Listing
March 2019
7 Reads

Engaging hospitalized patients with personalized health information: a randomized trial of an inpatient portal.

J Am Med Inform Assoc 2019 Feb;26(2):115-123

Department of Biomedical Informatics, Columbia University, New York, New York, USA.

Objective: To determine the effects of an inpatient portal intervention on patient activation, patient satisfaction, patient engagement with health information, and 30-day hospital readmissions.

Methods And Materials: From March 2014 to May 2017, we enrolled 426 English- or Spanish-speaking patients from 2 cardiac medical-surgical units at an urban academic medical center. Patients were randomized to 1 of 3 groups: 1) usual care, 2) tablet with general Internet access (tablet-only), and 3) tablet with an inpatient portal. Read More

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http://dx.doi.org/10.1093/jamia/ocy146DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339515PMC
February 2019

EARS to cyber incidents in health care.

J Am Med Inform Assoc 2019 Jan;26(1):81-90

Division of General Internal Medicine, Department of Medicine, Brigham & Women's Hospital, Boston, Massachusetts, USA.

Background: Connected medical devices and electronic health records have added important functionality to patient care, but have also introduced a range of cybersecurity concerns. When a healthcare organization suffers from a cybersecurity incident, its incident response strategies are critical to the success of its recovery.

Objective: In this article, we identify gaps in research concerning cybersecurity response plans in healthcare. Read More

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http://dx.doi.org/10.1093/jamia/ocy148DOI Listing
January 2019
10 Reads

Physician stress and burnout: the impact of health information technology.

J Am Med Inform Assoc 2019 Feb;26(2):106-114

Department of Medicine, Hennepin County Medical Center, Minneapolis, Minnesota, USA.

Objective: To quantify how stress related to use of health information technology (HIT) predicts burnout among physicians.

Methods: All 4197 practicing physicians in Rhode Island were surveyed in 2017 on their HIT use. Our main outcome was self-reported burnout. Read More

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http://dx.doi.org/10.1093/jamia/ocy145DOI Listing
February 2019
1 Read

Integrity of clinical information in computerized order requisitions for diagnostic imaging.

J Am Med Inform Assoc 2018 Dec;25(12):1651-1656

Department of Radiology, Brigham and Women's Hospital, Center for Evidence-Based Imaging, Boston, MA, USA.

Objective: Assess information integrity (concordance and completeness of documented exam indications from the electronic health record [EHR] imaging order requisition, compared to EHR provider notes), and assess potential impact of indication inaccuracies on exam planning and interpretation.

Methods: This retrospective study, approved by the Institutional Review Board, was conducted at a tertiary academic medical center. There were 139 MRI lumbar spine (LS-MRI) and 176 CT abdomen/pelvis orders performed 4/1/2016-5/31/2016 randomly selected and reviewed by 4 radiologists for concordance and completeness of relevant exam indications in order requisitions compared to provider notes, and potential impact of indication inaccuracies on exam planning and interpretation. Read More

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https://academic.oup.com/jamia/advance-article/doi/10.1093/j
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http://dx.doi.org/10.1093/jamia/ocy133DOI Listing
December 2018
8 Reads

Blockchain-based platforms for genomic data sharing: a de-centralized approach in response to the governance problems?

Authors:
Mahsa Shabani

J Am Med Inform Assoc 2019 Jan;26(1):76-80

Center for Biomedical Ethics and Law, Department of Public Health and Primary Care, University of Leuven, Leuven, Belgium.

Blockchain-based platforms are emerging to provide solutions for technical and governance challenges associated with genomic data sharing. Providing capabilities for distributed data stewardship and participatory access control along with effective ways for enforcement of the data access agreements and data ownership are among the major promises of these platforms. Read More

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http://dx.doi.org/10.1093/jamia/ocy149DOI Listing
January 2019

A population approach using cholesterol imputation to identify adults with high cardiovascular risk: a report from AHRQ's EvidenceNow initiative.

J Am Med Inform Assoc 2019 Feb;26(2):155-158

The Department of Biostatistics, The Gillings School of Global Public Health, the University of North Carolina, Chapel Hill, North Carolina, USA.

Objective: Large practice networks have access to EHR data that can be used to drive important improvements in population health. However, missing data often limit improvement efforts. Our goal was to determine the proportion of patients in a cohort of small primary care practices who lacked cholesterol data to calculate ASCVD risk scores and then gauge the extent that imputation can accurately identify individuals already at high risk. Read More

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http://dx.doi.org/10.1093/jamia/ocy151DOI Listing
February 2019

Automated and flexible identification of complex disease: building a model for systemic lupus erythematosus using noisy labeling.

J Am Med Inform Assoc 2019 Jan;26(1):61-65

Department of Medicine, University of California, San Francisco, California, USA.

Accurate and efficient identification of complex chronic conditions in the electronic health record (EHR) is an important but challenging task that has historically relied on tedious clinician review and oversimplification of the disease. Here we adapt methods that allow for automated "noisy labeling" of positive and negative controls to create a "silver standard" for machine learning to automate identification of systemic lupus erythematosus (SLE). Our final model, which includes both structured data as well as text processing of clinical notes, outperformed all existing algorithms for SLE (AUC 0. Read More

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https://academic.oup.com/jamia/advance-article/doi/10.1093/j
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http://dx.doi.org/10.1093/jamia/ocy154DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308013PMC
January 2019
7 Reads

Inpatient portal clusters: identifying user groups based on portal features.

J Am Med Inform Assoc 2019 Jan;26(1):28-36

Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, USA.

Objective: Conduct a cluster analysis of inpatient portal (IPP) users from an academic medical center to improve understanding of who uses these portals and how.

Methods: We used 18 months of data from audit log files, which recorded IPP user actions, of 2815 patient admissions. A hierarchical clustering algorithm was executed to group patient admissions on the basis of proportion of use for each of 10 IPP features. Read More

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https://academic.oup.com/jamia/advance-article/doi/10.1093/j
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http://dx.doi.org/10.1093/jamia/ocy147DOI Listing
January 2019
7 Reads

The other office.

Authors:
Elizabeth T Toll

J Am Med Inform Assoc 2019 Jan;26(1):71-75

The Medicine-Pediatrics Primary Care Center, Providence, Rhode Island, USA.

Across recent decades, profound changes in the practice of medicine have been accompanied by parallel developments in the daily mental efforts of medical professionals. Using visual metaphors and hand-drawn illustrations, the author explores the evolution of one physician's brain over the past 25 years. At the completion of training, the patient-practitioner relationship, medical knowledge, and care decisions dominated clinician thought, time, and effort. Read More

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https://academic.oup.com/jamia/advance-article/doi/10.1093/j
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http://dx.doi.org/10.1093/jamia/ocy144DOI Listing
January 2019
9 Reads

Impacts of a web-based educational program for veterans who read their mental health notes online.

J Am Med Inform Assoc 2019 Jan;26(1):3-8

Center to Improve Veteran Involvement in Care (CIVIC), VA Portland Health Care System, Portland, Oregon, USA.

Objective: This study evaluates whether a web-based educational program for patients who read their mental health notes online improves patient-clinician communication and increases patient activation.

Methods: The web-based educational program, developed with end-user input, was designed to educate patients on the content of mental health notes, provide guidance on communicating with clinicians about notes, and facilitate patients' safe and purposeful use of their health information. Eligible patients were engaged in mental health treatment (≥1 visit in the prior 6 months) and had logged into the Veterans Health Administration (VHA) patient portal at least twice. Read More

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http://fdslive.oup.com/www.oup.com/pdf/production_in_progres
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http://dx.doi.org/10.1093/jamia/ocy134DOI Listing
January 2019
11 Reads

Recruiting for a pragmatic trial using the electronic health record and patient portal: successes and lessons learned.

J Am Med Inform Assoc 2019 Jan;26(1):44-49

Division of General Medicine and Clinical Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Objective: Querying electronic health records (EHRs) to find patients meeting study criteria is an efficient method of identifying potential study participants. We aimed to measure the effectiveness of EHR-driven recruitment in the context of ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness)-a pragmatic trial aiming to recruit 15 000 patients.

Materials And Methods: We compared the participant yield of 4 recruitment methods: in-clinic recruitment by a research coordinator, letters, direct email, and patient portal messages. Read More

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https://academic.oup.com/jamia/advance-article/doi/10.1093/j
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http://dx.doi.org/10.1093/jamia/ocy138DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308009PMC
January 2019
5 Reads

Planning and implementing sexual orientation and gender identity data collection in electronic health records.

J Am Med Inform Assoc 2019 Jan;26(1):66-70

Massachusetts General Hospital, Boston, Massachusetts, USA.

Lesbian, gay, bisexual, transgender, and queer (LGBTQ) people experience significant health disparities across the life course and require health care that addresses their unique needs. Collecting information on the sexual orientation and gender identity (SO/GI) of patients and entering SO/GI data in electronic health records has been recommended by the Institute of Medicine, the Joint Commission, and the Health Resources and Services Administration as fundamental to improving access to and quality of care for LGBTQ people. Most healthcare organizations, however, have yet to implement a system to collect SO/GI data due to multiple barriers. Read More

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http://dx.doi.org/10.1093/jamia/ocy137DOI Listing
January 2019
9 Reads

Expert-level sleep scoring with deep neural networks.

J Am Med Inform Assoc 2018 Dec;25(12):1643-1650

Neurology Department, Massachusetts General Hospital, Wang 720, Boston, MA, USA.

Objectives: Scoring laboratory polysomnography (PSG) data remains a manual task of visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb movements. Attempts to automate this process have been hampered by the complexity of PSG signals and physiological heterogeneity between patients. Deep neural networks, which have recently achieved expert-level performance for other complex medical tasks, are ideally suited to PSG scoring, given sufficient training data. Read More

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http://dx.doi.org/10.1093/jamia/ocy131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6289549PMC
December 2018
24 Reads

Mapping of HIE CT terms to LOINC®: analysis of content-dependent coverage and coverage improvement through new term creation.

J Am Med Inform Assoc 2019 Jan;26(1):19-27

Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Objective: We describe and evaluate the mapping of computerized tomography (CT) terms from 40 hospitals participating in a health information exchange (HIE) to a standard terminology.

Methods: Proprietary CT exam terms and corresponding exam frequency data were obtained from 40 participant HIE sites that transmitted radiology data to the HIE from January 2013 through October 2015. These terms were mapped to the Logical Observations Identifiers Names and Codes (LOINC®) terminology using the Regenstrief LOINC mapping assistant (RELMA) beginning in January 2016. Read More

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http://dx.doi.org/10.1093/jamia/ocy135DOI Listing
January 2019

Algorithm to detect pediatric provider attention to high BMI and associated medical risk.

J Am Med Inform Assoc 2019 Jan;26(1):55-60

Department of Pediatrics, University of Texas Southwestern Medical Center and Children's Health, Dallas, TX, USA.

We developed and validated an algorithm that uses combinations of extractable electronic-health-record (EHR) indicators (diagnosis codes, orders for laboratories, medications, and referrals) that denote widely-recommended clinician practice behaviors: attention to overweight/obesity/body mass index alone (BMI Alone), with attention to hypertension/other comorbidities (BMI/Medical Risk), or neither (No Attention). Data inputs used for each EHR indicator were refined through iterative chart review to identify and resolve modifiable coding errors. Validation was performed through manual review of randomly selected visit encounters (n = 308) coded by the refined algorithm. Read More

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http://dx.doi.org/10.1093/jamia/ocy126DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308014PMC
January 2019
12 Reads

Leveraging mobile health applications for biomedical research and citizen science: a scoping review.

J Am Med Inform Assoc 2018 Dec;25(12):1685-1695

Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona, USA.

Objective: This systematic review aims to analyze current capabilities, challenges, and impact of self-directed mobile health (mHealth) research applications such as those based on the ResearchKit platform.

Materials And Methods: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. English publications were included if: 1) mobile applications were used in the context of large-scale collection of data for biomedical research, and not as medical or behavioral intervention of any kind, and 2) all activities related to participating in research and data collection methods were executed remotely without any face-to-face interaction between researchers and study participants. Read More

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http://fdslive.oup.com/www.oup.com/pdf/production_in_progres
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http://dx.doi.org/10.1093/jamia/ocy130DOI Listing
December 2018
8 Reads

Effect of vocabulary mapping for conditions on phenotype cohorts.

J Am Med Inform Assoc 2018 Dec;25(12):1618-1625

Department of Biomedical Informatics, Columbia University, New York, New York, USA.

Objective: To study the effect on patient cohorts of mapping condition (diagnosis) codes from source billing vocabularies to a clinical vocabulary.

Materials And Methods: Nine International Classification of Diseases, Ninth Revision, Clinical Modification (ICD9-CM) concept sets were extracted from eMERGE network phenotypes, translated to Systematized Nomenclature of Medicine - Clinical Terms concept sets, and applied to patient data that were mapped from source ICD9-CM and ICD10-CM codes to Systematized Nomenclature of Medicine - Clinical Terms codes using Observational Health Data Sciences and Informatics (OHDSI) Observational Medical Outcomes Partnership (OMOP) vocabulary mappings. The original ICD9-CM concept set and a concept set extended to ICD10-CM were used to create patient cohorts that served as gold standards. Read More

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https://academic.oup.com/jamia/advance-article/doi/10.1093/j
Publisher Site
http://dx.doi.org/10.1093/jamia/ocy124DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6289550PMC
December 2018
8 Reads

The therapy is making me sick: how online portal communications between breast cancer patients and physicians indicate medication discontinuation.

J Am Med Inform Assoc 2018 Nov;25(11):1444-1451

Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.

Objective: Online platforms have created a variety of opportunities for breast patients to discuss their hormonal therapy, a long-term adjuvant treatment to reduce the chance of breast cancer occurrence and mortality. The goal of this investigation is to ascertain the extent to which the messages breast cancer patients communicated through an online portal can indicate their potential for discontinuing hormonal therapy.

Materials And Methods: We studied the de-identified electronic medical records of 1106 breast cancer patients who were prescribed hormonal therapy at Vanderbilt University Medical Center over a 12-year period. Read More

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http://dx.doi.org/10.1093/jamia/ocy118DOI Listing
November 2018
6 Reads