3,020 results match your criteria Journal of the American Medical Informatics Association [Journal]


Data, capacity-building, and training needs to address rural health inequities in the Northwest United States: a qualitative study.

J Am Med Inform Assoc 2019 Apr 16. Epub 2019 Apr 16.

Northwest Center for Public Health Practice, University of Washington,Seattle, Washington, USA.

Objective: Rural public health system leaders struggle to access and use data for understanding local health inequities and to effectively allocate scarce resources to populations in need. This study sought to determine these rural public health system leaders' data access, capacity, and training needs.

Materials And Methods: We conducted qualitative interviews across Alaska, Idaho, Oregon, and Washington with individuals expected to use population data for analysis or decision-making in rural communities. Read More

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http://dx.doi.org/10.1093/jamia/ocz037DOI Listing

Assessing the collective utility of multiple analyses on clinical alcohol use disorder data.

J Am Med Inform Assoc 2019 Apr 16. Epub 2019 Apr 16.

University of Minnesota - Department of Psychiatry, Minneapolis, Minnesota, USA.

Objective: The objective of this study was to assess the potential of combining graph learning methods with latent variable estimation methods for mining clinically useful information from observational clinical data sets.

Materials And Methods: The data set contained self-reported measures of psychopathology symptoms from a clinical sample receiving treatment for alcohol use disorder. We used the traditional graph learning methods: Graphical Least Absolute Shrinkage and Selection Operator, and Friedman's hill climbing algorithm; traditional latent variable estimation method factor analysis; recently developed graph learning method Greedy Fast Causal Inference; and recently developed latent variable estimation method Find One Factor Clusters. 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/ocz034DOI Listing
April 2019
2 Reads

A review of measurement practice in studies of clinical decision support systems 1998-2017.

J Am Med Inform Assoc 2019 Apr 16. Epub 2019 Apr 16.

Schools of Medicine, Information and Public Health, University of Michigan, Ann Arbor, Michigan, USA.

Objective: To assess measurement practice in clinical decision support evaluation studies.

Materials And Methods: We identified empirical studies evaluating clinical decision support systems published from 1998 to 2017. We reviewed titles, abstracts, and full paper contents for evidence of attention to measurement validity, reliability, or reuse. Read More

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http://dx.doi.org/10.1093/jamia/ocz035DOI Listing
April 2019
1 Read

Successful deployment of drug-disease interaction clinical decision support across multiple Kaiser Permanente regions.

J Am Med Inform Assoc 2019 Apr 15. Epub 2019 Apr 15.

Technology Leadership, The Permanente Medical Group, Oakland, California, USA.

Objective: The study sought to develop a criteria-based scoring tool for assessing drug-disease knowledge base content and creation of a subset and to implement the subset across multiple Kaiser Permanente (KP) regions.

Materials And Methods: In Phase I, the scoring tool was developed, used to create a drug-disease alert subset, and validated by surveying physicians and pharmacists from KP Northern California. In Phase II, KP enabled the alert subset in July 2015 in silent mode to collect alert firing rates and confirmed that alert burden was adequately reduced. Read More

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http://dx.doi.org/10.1093/jamia/ocz020DOI Listing

Reply to comment on: "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts".

J Am Med Inform Assoc 2019 Apr 13. Epub 2019 Apr 13.

Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.

We appreciate the detailed review provided by Magge et al1 of our article, "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts." 2 In their letter, they present a subjective criticism that rests on concerns about our dataset composition and potential misinterpretation of comparisons to existing methods. Our article underwent two rounds of extensive peer review and has been cited 28 times1 in the nearly 2 years since it was published online (February 2017). Read More

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http://dx.doi.org/10.1093/jamia/ocy192DOI Listing

A new approach and gold standard toward author disambiguation in MEDLINE.

J Am Med Inform Assoc 2019 Apr 8. Epub 2019 Apr 8.

Institute of Computational Linguistics, University of Zurich, Switzerland.

Objective: Author-centric analyses of fast-growing biomedical reference databases are challenging due to author ambiguity. This problem has been mainly addressed through author disambiguation using supervised machine-learning algorithms. Such algorithms, however, require adequately designed gold standards that reflect the reference database properly. Read More

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http://dx.doi.org/10.1093/jamia/ocz028DOI Listing

Interventions to increase patient portal use in vulnerable populations: a systematic review.

J Am Med Inform Assoc 2019 Apr 8. Epub 2019 Apr 8.

Department of Healthcare Policy & Research, Weill Cornell Medicine, New York, New York, USA.

Background: More than 100 studies document disparities in patient portal use among vulnerable populations. Developing and testing strategies to reduce disparities in use is essential to ensure portals benefit all populations.

Objective: To systematically review the impact of interventions designed to: (1) increase portal use or predictors of use in vulnerable patient populations, or (2) reduce disparities in use. Read More

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http://dx.doi.org/10.1093/jamia/ocz023DOI Listing

Patient portal utilization: before and after stage 2 electronic health record meaningful use.

J Am Med Inform Assoc 2019 Apr 4. Epub 2019 Apr 4.

Department of Health Services Research, Management and Policy, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, USA.

Objective: Patient portal functionalities, such as patient-physician e-communication, can benefit patients by improving clinical outcomes. Utilization has historically been low but may have increased in recent years due to the implementation of Stage 2 Meaningful Use for electronic health records. This study has 2 objectives: 1) to compare patient portal utilization rates before Stage 2 (2011-2013) and after Stage 2 (2014-2017), and 2) to examine whether disparities in patient portal utilization attenuate after Stage 2. Read More

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http://dx.doi.org/10.1093/jamia/ocz030DOI Listing
April 2019
5 Reads

Can menstrual health apps selected based on users' needs change health-related factors? A double-blind randomized controlled trial.

J Am Med Inform Assoc 2019 Apr 4. Epub 2019 Apr 4.

Interdisciplinary Program of Medical Informatics, Seoul National University, Seoul, Korea.

Objective: Most healthcare providers are reluctant to use health apps for healthcare because there is no rigorous way of choosing the best app for their patient or consumer. Accordingly, we developed a new method of app selection that fully considers target users' needs. This study verified whether health apps selected based on target users' needs can influence health-related factors. Read More

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http://dx.doi.org/10.1093/jamia/ocz019DOI Listing
April 2019
4 Reads

Clinical impact of intraoperative electronic health record downtime on surgical patients.

J Am Med Inform Assoc 2019 Apr 4. Epub 2019 Apr 4.

Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota, USA.

Objective: Despite increased use of electronic health records (EHRs), the clinical impact of system downtime is unknown.

Materials And Methods: This retrospective matched cohort study evaluated the impact of EHR downtime episodes lasting more than 60 minutes over a 6-year study period. Patients age 18 years or older who underwent surgical procedures at least 60 minutes in duration with an inpatient stay exceeding 24 hours within the study period were eligible for inclusion. Read More

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http://dx.doi.org/10.1093/jamia/ocz029DOI Listing
April 2019
2 Reads
3.504 Impact Factor

Patient experience with family history tool: analysis of patients' experience sharing their family health history through patient-computer dialogue in a patient portal.

J Am Med Inform Assoc 2019 Apr 4. Epub 2019 Apr 4.

Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.

Objective: The collection and use of a family health history are important for assessing the patient's risk of disease, but history taking is often impeded by practical barriers in the office. Provision for patient-computer dialogue, linked with the electronic health record, may enable patients to contribute their history while bypassing these barriers. We sought to assess the patient experience using such a tool. Read More

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http://dx.doi.org/10.1093/jamia/ocz008DOI Listing

An investigation of single-domain and multidomain medication and adverse drug event relation extraction from electronic health record notes using advanced deep learning models.

Authors:
Fei Li Hong Yu

J Am Med Inform Assoc 2019 Apr 2. Epub 2019 Apr 2.

Department of Computer Science, University of Massachusetts Lowell, Lowell, Massachusetts, USA.

Objective: We aim to evaluate the effectiveness of advanced deep learning models (eg, capsule network [CapNet], adversarial training [ADV]) for single-domain and multidomain relation extraction from electronic health record (EHR) notes.

Materials And Methods: We built multiple deep learning models with increased complexity, namely a multilayer perceptron (MLP) model and a CapNet model for single-domain relation extraction and fully shared (FS), shared-private (SP), and adversarial training (ADV) modes for multidomain relation extraction. Our models were evaluated in 2 ways: first, we compared our models using our expert-annotated cancer (the MADE1. Read More

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http://dx.doi.org/10.1093/jamia/ocz018DOI Listing
April 2019
4 Reads

Data linkages between patient-powered research networks and health plans: a foundation for collaborative research.

J Am Med Inform Assoc 2019 Apr 2. Epub 2019 Apr 2.

HealthCore, Wilmington, Delaware, USA.

Objective: Patient-powered research networks (PPRNs) are a valuable source of patient-generated information. Diagnosis code-based algorithms developed by PPRNs can be used to query health plans' claims data to identify patients for research opportunities. Our objective was to implement privacy-preserving record linkage processes between PPRN members' and health plan enrollees' data, compare linked and nonlinked members, and measure disease-specific confirmation rates for specific health conditions. Read More

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http://dx.doi.org/10.1093/jamia/ocz012DOI Listing
April 2019
2 Reads
3.504 Impact Factor

Disposition toward privacy and information disclosure in the context of emerging health technologies.

J Am Med Inform Assoc 2019 Apr 2. Epub 2019 Apr 2.

Department of Psychiatry, School of Medicine, University of California, San Diego, San Diego, La Jolla, California, USA.

Objective: We sought to present a model of privacy disposition and its development based on qualitative research on privacy considerations in the context of emerging health technologies.

Materials And Methods: We spoke to 108 participants across 44 interviews and 9 focus groups to understand the range of ways in which individuals value (or do not value) control over their health information. Transcripts of interviews and focus groups were systematically coded and analyzed in ATLAS. Read More

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http://dx.doi.org/10.1093/jamia/ocz010DOI Listing
April 2019
2 Reads

The complex case of EHRs: examining the factors impacting the EHR user experience.

J Am Med Inform Assoc 2019 Apr 2. Epub 2019 Apr 2.

Professional Satisfaction and Practice Sustainability, American Medical Association, Chicago, USA.

Physicians can spend more time completing administrative tasks in their electronic health record (EHR) than engaging in direct face time with patients. Increasing rates of burnout associated with EHR use necessitate improvements in how EHRs are developed and used. Although EHR design often bears the brunt of the blame for frustrations expressed by physicians, the EHR user experience is influenced by a variety of factors, including decisions made by entities other than the developers and end users, such as regulators, policymakers, and administrators. 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/ocz021DOI Listing
April 2019
2 Reads

Does an interactive trust-enhanced electronic consent improve patient experiences when asked to share their health records for research? A randomized trial.

J Am Med Inform Assoc 2019 Apr 2. Epub 2019 Apr 2.

Department of Community Health and Family Medicine, University of Florida, Gainesville, Florida, USA.

Objective: In the context of patient broad consent for future research uses of their identifiable health record data, we compare the effectiveness of interactive trust-enhanced e-consent, interactive-only e-consent, and standard e-consent (no interactivity, no trust enhancement).

Materials And Methods: A randomized trial was conducted involving adult participants making a scheduled primary care visit. Participants were randomized into 1 of the 3 e-consent conditions. Read More

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http://dx.doi.org/10.1093/jamia/ocz015DOI Listing

Estimating the impact of deploying an electronic clinical decision support tool as part of a national practice improvement project.

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

Department of Pediatrics, University of Nebraska Medical Center, Omaha, Nebraska, USA.

Objective: Estimate the impact on clinical practice of using a mobile device-based electronic clinical decision support (mECDS) tool within a national standardization project.

Materials And Methods: An mECDS tool (app) was released as part of a change package to provide febrile infant management guidance to clinicians. App usage was analyzed using 2 measures: metric hits per case (metric-related screen view count divided by site-reported febrile infant cases in each designated market area [DMA] monthly) and cumulative prior metric hits per site (DMA metric hits summed from study month 1 until the month preceding the index, divided by sites in the DMA). Read More

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http://dx.doi.org/10.1093/jamia/ocz011DOI Listing
March 2019
3 Reads

A federated EHR network data completeness tracking system.

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

Laboratory of Computer Science, Massachusetts General Hospital, Boston, Massachusetts, USA.

Objective: The study sought to design, pilot, and evaluate a federated data completeness tracking system (CTX) for assessing completeness in research data extracted from electronic health record data across the Accessible Research Commons for Health (ARCH) Clinical Data Research Network.

Materials And Methods: The CTX applies a systems-based approach to design workflow and technology for assessing completeness across distributed electronic health record data repositories participating in a queryable, federated network. The CTX invokes 2 positive feedback loops that utilize open source tools (DQe-c and Vue) to integrate technology and human actors in a system geared for increasing capacity and taking action. Read More

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http://dx.doi.org/10.1093/jamia/ocz014DOI Listing
March 2019
2 Reads

Role of provider encouragement on patient engagement via online portals.

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

Department of Health Care Administration, California State University, Long Beach, Long Beach, California, USA.

Objective: The study sought to examine whether provider encouragement is associated with improvements in engaging patients with their healthcare processes using online portals.

Materials And Methods: Using the Health Information National Trends Survey 2017 (N = 2, 670), we conducted an exploratory factor analysis with varimax orthogonal rotation and derived 3 outcome variables on patient engagement: (1) information access score, (2) care convenience score, and (3) patient engagement score. Multivariable linear regression on each outcome variable was conducted with provider encouragement as the main predictor, controlling for patient demographics. Read More

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http://dx.doi.org/10.1093/jamia/ocz026DOI Listing
March 2019
4 Reads

Racial and ethnic disparities in use of a personal health record by veterans living with HIV.

J Am Med Inform Assoc 2019 Mar 28. Epub 2019 Mar 28.

Center for Innovation to Implementation (Ci2i), VA Palo Alto Health Care System, Menlo Park, California, USA.

Objective: To examine sociodemographic characteristics associated with use of My HealtheVet (MHV) by veterans living with HIV.

Materials And Methods: Veterans Health Administration administrative data were used to identify a cohort of veterans living with HIV in fiscal years 2011-2017. Descriptive analyses were conducted to examine demographic characteristics and racial/ethnic differences in MHV registration and tool use. Read More

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http://dx.doi.org/10.1093/jamia/ocz024DOI Listing

Not the medical informatics of our founding mothers and fathers, or is it?

Authors:
Suzanne Bakken

J Am Med Inform Assoc 2019 May;26(5):381-382

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http://dx.doi.org/10.1093/jamia/ocz027DOI Listing

A systematic literature review of machine learning in online personal health data.

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

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

Objective: User-generated content (UGC) in online environments provides opportunities to learn an individual's health status outside of clinical settings. However, the nature of UGC brings challenges in both data collecting and processing. The purpose of this study is to systematically review the effectiveness of applying machine learning (ML) methodologies to UGC for personal health investigations. 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/ocz009DOI Listing
March 2019
8 Reads

Comparison of blockchain platforms: a systematic review and healthcare examples.

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

UCSD Health Department of Biomedical Informatics, University of California San Diego, La Jolla, California, USA.

Objectives: To introduce healthcare or biomedical blockchain applications and their underlying blockchain platforms, compare popular blockchain platforms using a systematic review method, and provide a reference for selection of a suitable blockchain platform given requirements and technical features that are common in healthcare and biomedical research applications.

Target Audience: Healthcare or clinical informatics researchers and software engineers who would like to learn about the important technical features of different blockchain platforms to design and implement blockchain-based health informatics applications.

Scope: Covered topics include (1) a brief introduction to healthcare or biomedical blockchain applications and the benefits to adopt blockchain; (2) a description of key features of underlying blockchain platforms in healthcare applications; (3) development of a method for systematic review of technology, based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement, to investigate blockchain platforms for healthcare and medicine applications; (4) a review of 21 healthcare-related technical features of 10 popular blockchain platforms; and (5) a discussion of findings and limitations of the review. Read More

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http://dx.doi.org/10.1093/jamia/ocy185DOI Listing
March 2019
2 Reads

Systems engineering and human factors support of a system of novel EHR-integrated tools to prevent harm in the hospital.

J Am Med Inform Assoc 2019 Mar 22. Epub 2019 Mar 22.

Healthcare Systems Engineering Institute, Northeastern University, Boston, Massachusetts, USA.

We established a Patient Safety Learning Laboratory comprising 2 core and 3 individual project teams to introduce a suite of digital health tools integrated with our electronic health record to identify, assess, and mitigate threats to patient safety in real time. One of the core teams employed systems engineering (SE) and human factors (HF) methods to analyze problems, design and develop improvements to intervention components, support implementation, and evaluate the system of systems as an integrated whole. Of the 29 participants, 19 and 16 participated in surveys and focus groups, respectively, about their perception of SE and HF. Read More

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http://dx.doi.org/10.1093/jamia/ocz002DOI Listing
March 2019
1 Read

Fair compute loads enabled by blockchain: sharing models by alternating client and server roles.

J Am Med Inform Assoc 2019 May;26(5):392-403

UCSD Health Department of Biomedical Informatics, University of California, San Diego, La Jolla, California, USA.

Objective: Decentralized privacy-preserving predictive modeling enables multiple institutions to learn a more generalizable model on healthcare or genomic data by sharing the partially trained models instead of patient-level data, while avoiding risks such as single point of control. State-of-the-art blockchain-based methods remove the "server" role but can be less accurate than models that rely on a server. Therefore, we aim at developing a general model sharing framework to preserve predictive correctness, mitigate the risks of a centralized architecture, and compute the models in a fair way. Read More

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http://dx.doi.org/10.1093/jamia/ocy180DOI Listing

Building consensus toward a national nursing home information technology maturity model.

J Am Med Inform Assoc 2019 Mar 19. Epub 2019 Mar 19.

Research Triangle Institute, Research Triangle Park, North Carolina, USA.

Objectives: We describe the development of a nursing home information technology (IT) maturity model designed to capture stages of IT maturity.

Materials And Methods: This study had 2 phases. The purpose of phase I was to develop a preliminary nursing home IT maturity model. 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/ocz006DOI Listing
March 2019
4 Reads

Evaluation of multidisciplinary collaboration in pediatric trauma care using EHR data.

J Am Med Inform Assoc 2019 Mar 19. Epub 2019 Mar 19.

Division of Health Sciences Informatics, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Objectives: The study sought to identify collaborative electronic health record (EHR) usage patterns for pediatric trauma patients and determine how the usage patterns are related to patient outcomes.

Materials And Methods: A process mining-based network analysis was applied to EHR metadata and trauma registry data for a cohort of pediatric trauma patients with minor injuries at a Level I pediatric trauma center. The EHR metadata were processed into an event log that was segmented based on gaps in the temporal continuity of events. Read More

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http://dx.doi.org/10.1093/jamia/ocy184DOI Listing
March 2019
3.504 Impact Factor

An outcome model approach to transporting a randomized controlled trial results to a target population.

J Am Med Inform Assoc 2019 May;26(5):429-437

Department of Biostatistics John Hopkins University, Baltimore, Maryland, USA.

Objective: Participants enrolled into randomized controlled trials (RCTs) often do not reflect real-world populations. Previous research in how best to transport RCT results to target populations has focused on weighting RCT data to look like the target data. Simulation work, however, has suggested that an outcome model approach may be preferable. Read More

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http://dx.doi.org/10.1093/jamia/ocy188DOI Listing
May 2019
1 Read

Evaluating and sharing global genetic ancestry in biomedical datasets.

J Am Med Inform Assoc 2019 May;26(5):457-461

Health Department of Biomedical Informatics, University of California, San Diego, La Jolla, California, USA.

Genetic ancestry is a critical co-factor to study phenotype-genotype associations using cohorts of human subjects. Most publicly available molecular datasets are, however, missing this information or only share self-reported race and ethnicity, representing a limitation to identify and repurpose datasets to investigate the contribution of ancestry to diseases and traits. We propose an analytical framework to enrich the metadata from publicly available cohorts with genetic ancestry information and a resulting diversity score at continental resolution, calculated directly from the 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/ocy194DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6433181PMC
May 2019
4 Reads

Disconnected: a survey of users and nonusers of telehealth and their use of primary care.

J Am Med Inform Assoc 2019 May;26(5):420-428

Robert Graham Center, Washington, DC, USA.

Objective: The study sought to assess awareness, perceptions, and value of telehealth in primary care from the perspective of patients.

Materials And Methods: We conducted a cross-sectional, Web-based survey of adults with access to telehealth services who visited healthcare providers for any of the 20 most-commonly seen diagnoses during telehealth visits. Three groups were studied: registered users (RUs) of telehealth had completed a LiveHealth Online (a health plan telehealth service provider) visit, registered nonusers (RNUs) registered for LiveHealth Online but had not conducted a visit, and nonregistered nonusers (NRNUs) completed neither step. Read More

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http://dx.doi.org/10.1093/jamia/ocy182DOI Listing

Novel displays of patient information in critical care settings: a systematic review.

J Am Med Inform Assoc 2019 May;26(5):479-489

Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA.

Objective: Clinician information overload is prevalent in critical care settings. Improved visualization of patient information may help clinicians cope with information overload, increase efficiency, and improve quality. We compared the effect of information display interventions with usual care on patient care outcomes. Read More

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http://dx.doi.org/10.1093/jamia/ocy193DOI Listing
May 2019
2 Reads

Investigating data accessibility of personal health apps.

J Am Med Inform Assoc 2019 May;26(5):412-419

College of Information Studies, University of Maryland, College Park, Maryland, USA.

Objective: Despite the potential values self-tracking data could offer, we have little understanding of how much access people have to "their" data. Our goal of this article is to unveil the current state of the data accessibility-the degree to which people can access their data-of personal health apps in the market.

Materials And Methods: We reviewed 240 personal health apps from the App Store and selected 45 apps that support semi-automated tracking. Read More

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http://dx.doi.org/10.1093/jamia/ocz003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6433179PMC
May 2019
1 Read

Evaluation of a mandatory phishing training program for high-risk employees at a US healthcare system.

J Am Med Inform Assoc 2019 Mar 12. Epub 2019 Mar 12.

Harvard Medical School, Boston, Massachusetts, USA.

Objective: The study sought to understand the impact of a phishing training program on phishing click rates for employees at a single, anonymous US healthcare institution.

Materials And Methods: We stratified our population into 2 groups: offenders and nonoffenders. Offenders were defined as those that had clicked on at least 5 simulated phishing emails and nonoffenders were those that had not. Read More

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http://dx.doi.org/10.1093/jamia/ocz005DOI Listing
March 2019
5 Reads

Can laypeople identify a drug-induced QT interval prolongation? A psychophysical and eye-tracking experiment examining the ability of nonexperts to interpret an ECG.

J Am Med Inform Assoc 2019 May;26(5):404-411

University of Manchester, School of Computer Science, Manchester, UK.

Objective: The study sought to quantify a layperson's ability to detect drug-induced QT interval prolongation on an electrocardiogram (ECG) and determine whether the presentation of the trace affects such detection.

Materials And Methods: Thirty layperson participants took part in a psychophysical and eye-tracking experiment. Following training, participants completed 21 experimental trials, in which each trial consisted of 2 ECGs (a baseline and a comparison stimulus, both with a heart rate of 60 beats/min). Read More

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http://dx.doi.org/10.1093/jamia/ocy183DOI Listing
May 2019
1 Read

Evaluating the effect of data standardization and validation on patient matching accuracy.

J Am Med Inform Assoc 2019 May;26(5):447-456

The Pew Charitable Trusts, Washington DC, USA.

Objective: This study evaluated the degree to which recommendations for demographic data standardization improve patient matching accuracy using real-world datasets.

Materials And Methods: We used 4 manually reviewed datasets, containing a random selection of matches and nonmatches. Matching datasets included health information exchange (HIE) records, public health registry records, Social Security Death Master File records, and newborn screening records. Read More

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http://dx.doi.org/10.1093/jamia/ocy191DOI Listing

Evaluating visual analytics for health informatics applications: a systematic review from the American Medical Informatics Association Visual Analytics Working Group Task Force on Evaluation.

J Am Med Inform Assoc 2019 Apr;26(4):314-323

Carolina Health Informatics Program, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Objective: This article reports results from a systematic literature review related to the evaluation of data visualizations and visual analytics technologies within the health informatics domain. The review aims to (1) characterize the variety of evaluation methods used within the health informatics community and (2) identify best practices.

Methods: A systematic literature review was conducted following PRISMA guidelines. Read More

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http://dx.doi.org/10.1093/jamia/ocy190DOI Listing
April 2019
2 Reads
3.504 Impact Factor

Patient free text reporting of symptomatic adverse events in cancer clinical research using the National Cancer Institute's Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE).

J Am Med Inform Assoc 2019 Apr;26(4):276-285

Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.

Objective: The study sought to describe patient-entered supplemental information on symptomatic adverse events (AEs) in cancer clinical research reported via a National Cancer Institute software system and examine the feasibility of mapping these entries to established terminologies.

Materials And Methods: Patients in 3 multicenter trials electronically completed surveys during cancer treatment. Each survey included a prespecified subset of items from the National Cancer Institute's Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). Read More

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http://dx.doi.org/10.1093/jamia/ocy169DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402312PMC
April 2019
3.504 Impact Factor

Advancing biomedical and health informatics knowledge through reviews of existing research.

Authors:
Suzanne Bakken

J Am Med Inform Assoc 2019 Apr;26(4):273-275

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http://dx.doi.org/10.1093/jamia/ocz016DOI Listing
April 2019
1 Read

Quantifying risk factors in medical reports with a context-aware linear model.

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

National Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, United Kingdom.

Objective: We seek to quantify the mortality risk associated with mentions of medical concepts in textual electronic health records (EHRs). Recognizing mentions of named entities of relevant types (eg, conditions, symptoms, laboratory tests or behaviors) in text is a well-researched task. However, determining the level of risk associated with them is partly dependent on the textual context in which they appear, which may describe severity, temporal aspects, quantity, etc. Read More

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http://dx.doi.org/10.1093/jamia/ocz004DOI Listing
March 2019
12 Reads

Identifying translational science through embeddings of controlled vocabularies.

Authors:
Qing Ke

J Am Med Inform Assoc 2019 Mar 1. Epub 2019 Mar 1.

Center for Complex Network Research, Department of Physics, Northeastern University, Boston, Massachusetts, USA.

Objective: Translational science aims at "translating" basic scientific discoveries into clinical applications. The identification of translational science has practicality such as evaluating the effectiveness of investments made into large programs like the Clinical and Translational Science Awards. Despite several proposed methods that group publications-the primary unit of research output-into some categories, we still lack a quantitative way to place articles onto the full, continuous spectrum from basic research to clinical medicine. Read More

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http://dx.doi.org/10.1093/jamia/ocy177DOI Listing

Healthcare data scientist qualifications, skills, and job focus: a content analysis of job postings.

Authors:
Melanie A Meyer

J Am Med Inform Assoc 2019 May;26(5):383-391

Health Informatics and Management, College of Health Sciences, University of Massachusetts Lowell, Lowell, Massachusetts, USA.

Objective: Growth in big data and its potential impact on the healthcare industry have driven the need for more data scientists. In health care, big data can be used to improve care quality, increase efficiency, lower costs, and drive innovation. Given the importance of data scientists to U. Read More

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http://dx.doi.org/10.1093/jamia/ocy181DOI Listing
May 2019
1 Read

deepBioWSD: effective deep neural word sense disambiguation of biomedical text data.

J Am Med Inform Assoc 2019 May;26(5):438-446

School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N 6N5, Canada.

Objective: In biomedicine, there is a wealth of information hidden in unstructured narratives such as research articles and clinical reports. To exploit these data properly, a word sense disambiguation (WSD) algorithm prevents downstream difficulties in the natural language processing applications pipeline. Supervised WSD algorithms largely outperform un- or semisupervised and knowledge-based methods; however, they train 1 separate classifier for each ambiguous term, necessitating a large number of expert-labeled training data, an unattainable goal in medical informatics. Read More

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http://dx.doi.org/10.1093/jamia/ocy189DOI Listing

A systematic review of the effects of implementing clinical pathways supported by health information technologies.

J Am Med Inform Assoc 2019 Apr;26(4):356-363

Department of Women's and Children's Health, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom.

Objective: Health information technology (HIT) interventions include electronic patient records, prescribing, and ordering systems. Clinical pathways are multidisciplinary plans of care that enable the delivery of evidence-based healthcare. Our objective was to systematically review the effects of implementing HIT-supported clinical pathways. Read More

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http://dx.doi.org/10.1093/jamia/ocy176DOI Listing

An ancillary genomics system to support the return of pharmacogenomic results.

J Am Med Inform Assoc 2019 Apr;26(4):306-310

Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.

Existing approaches to managing genetic and genomic test results from external laboratories typically include filing of text reports within the electronic health record, making them unavailable in many cases for clinical decision support. Even when structured computable results are available, the lack of adopted standards requires considerations for processing the results into actionable knowledge, in addition to storage and management of the data. Here, we describe the design and implementation of an ancillary genomics system used to receive and process heterogeneous results from external laboratories, which returns a descriptive phenotype to the electronic health record in support of pharmacogenetic clinical decision support. Read More

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http://dx.doi.org/10.1093/jamia/ocy187DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402311PMC

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

J Am Med Inform Assoc 2019 Apr;26(4):324-338

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
April 2019
2 Reads

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

J Am Med Inform Assoc 2019 Apr;26(4):294-305

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
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402359PMC
April 2019
10 Reads

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

J Am Med Inform Assoc 2019 Apr;26(4):364-379

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
April 2019
4 Reads

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

J Am Med Inform Assoc 2019 Apr;26(4):286-293

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
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402306PMC
April 2019
6 Reads