Subjects -> MEDICAL SCIENCES (Total: 8642 journals)
    - ALLERGOLOGY AND IMMUNOLOGY (218 journals)
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    - CHIROPRACTIC, HOMEOPATHY, OSTEOPATHY (21 journals)
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MEDICAL SCIENCES (2392 journals)            First | 3 4 5 6 7 8 9 10 | Last

Showing 1201 - 1400 of 3562 Journals sorted alphabetically
Journal of Forensic Science and Research     Open Access   (Followers: 2)
Journal of Gandaki Medical College-Nepal     Open Access  
Journal of Generic Medicines     Hybrid Journal   (Followers: 2)
Journal of Geographical Sciences     Hybrid Journal   (Followers: 1)
Journal of Global Antimicrobial Resistance     Hybrid Journal   (Followers: 3)
Journal of Hand Therapy     Hybrid Journal   (Followers: 18)
Journal of Head & Neck Physicians and Surgeons     Open Access   (Followers: 2)
Journal of Health & Medical Informatics     Open Access   (Followers: 59)
Journal of Health and Biological Sciences     Open Access   (Followers: 1)
Journal of Health Design     Open Access   (Followers: 1)
Journal of Health Economics and Outcomes Research     Open Access   (Followers: 1)
Journal of Health Promotion and Behavior     Open Access  
Journal of Health Research and Reviews     Open Access  
Journal of Health Science and Medical Research     Open Access  
Journal of Health Science Research     Open Access  
Journal of Health Sciences     Open Access   (Followers: 1)
Journal of health sciences     Open Access  
Journal of Health Sciences / Sağlık Bilimleri Dergisi     Open Access  
Journal of Health Sciences and Medicine     Open Access  
Journal of Health Sciences and Surveillance System     Open Access  
Journal of Health Sciences Scholarship     Open Access  
Journal of Health Specialties     Open Access  
Journal of Health Studies     Open Access  
Journal of Healthcare Informatics Research     Hybrid Journal   (Followers: 1)
Journal of Heavy Metal Toxicity and Diseases     Open Access  
Journal of Helminthology     Hybrid Journal   (Followers: 2)
Journal of Herbs Spices & Medicinal Plants     Hybrid Journal  
Journal of HIV for Clinical and Scientific Research     Open Access   (Followers: 2)
Journal of Hospital Medicine     Hybrid Journal   (Followers: 10)
Journal of Huazhong University of Science and Technology [Medical Sciences]     Hybrid Journal  
Journal of Human Hypertension     Hybrid Journal   (Followers: 3)
Journal of Human Rhythm     Open Access  
Journal of Human Transcriptome     Open Access  
Journal of Ideas in Health     Open Access  
Journal of Inflammation     Open Access   (Followers: 2)
Journal of Inflammation Research     Open Access  
Journal of Injury and Violence Research     Open Access   (Followers: 7)
Journal of Innovation in Health Informatics     Open Access   (Followers: 17)
Journal of Institute of Medicine     Open Access  
Journal of Insulin Resistance     Open Access   (Followers: 1)
Journal of Interactional Research in Communication Disorders     Hybrid Journal   (Followers: 5)
Journal of Interferon & Cytokine Research     Hybrid Journal   (Followers: 3)
Journal of International Medical Research     Open Access   (Followers: 4)
Journal of Interventional Medicine     Open Access   (Followers: 1)
Journal of Investigative Medicine     Hybrid Journal   (Followers: 3)
Journal of Islamabad Medical & Dental College     Open Access   (Followers: 1)
Journal of Istanbul Faculty of Medicine     Open Access  
Journal of Karnali Academy of Health Sciences     Open Access   (Followers: 1)
Journal of Kathmandu Medical College     Open Access   (Followers: 1)
Journal of King Abdulaziz University : Medical Sciences     Open Access   (Followers: 2)
Journal of Laboratory Medicine     Hybrid Journal   (Followers: 27)
Journal of Laryngology and Voice     Open Access   (Followers: 11)
Journal of Lasers in Medical Sciences     Open Access  
Journal of Law, Medicine & Ethics     Hybrid Journal   (Followers: 24)
Journal of Legal Medicine     Hybrid Journal   (Followers: 7)
Journal of Limb Lengthening & Reconstruction     Open Access  
Journal of Lumbini Medical College     Open Access   (Followers: 1)
Journal of Mahatma Gandhi Institute of Medical Sciences     Open Access  
Journal of Manipulative and Physiological Therapeutics     Hybrid Journal   (Followers: 6)
Journal of Manmohan Memorial Institute of Health Sciences     Open Access   (Followers: 1)
Journal of Marine Medical Society     Open Access  
Journal of Materials Science : Materials in Medicine     Hybrid Journal   (Followers: 4)
Journal of Maternal and Child Health     Open Access  
Journal of Mechanics in Medicine and Biology     Hybrid Journal  
Journal of Medical and Biological Engineering     Hybrid Journal   (Followers: 4)
Journal of Medical and Biomedical Sciences     Open Access   (Followers: 2)
Journal of Medical Case Reports     Open Access   (Followers: 1)
Journal of Medical Cases     Open Access   (Followers: 6)
Journal of Medical Colleges of PLA     Full-text available via subscription  
Journal of Medical Disorders     Open Access  
Journal of Medical Economics     Hybrid Journal   (Followers: 8)
Journal of Medical Education and Curricular Development     Open Access   (Followers: 6)
Journal of Medical Ethics     Partially Free   (Followers: 25)
Journal of Medical Ethics and History of Medicine     Open Access   (Followers: 15)
Journal of Medical Humanities     Hybrid Journal   (Followers: 21)
Journal of Medical Hypotheses and Ideas     Open Access  
Journal of Medical Imaging and Health Informatics     Full-text available via subscription   (Followers: 1)
Journal of Medical Investigation and Practice     Open Access  
Journal of Medical Laboratory and Diagnosis     Open Access  
Journal of Medical Law and Ethics     Full-text available via subscription   (Followers: 15)
Journal of Medical Microbiology     Full-text available via subscription   (Followers: 6)
Journal of Medical Sciences     Open Access  
Journal of Medical Sciences     Open Access  
Journal of Medical Screening     Hybrid Journal   (Followers: 6)
Journal of Medical Signals and Sensors     Open Access   (Followers: 3)
Journal of Medical Society     Open Access  
Journal of Medical Systems     Hybrid Journal  
Journal of Medical Toxicology     Hybrid Journal   (Followers: 6)
Journal of Medical Ultrasound     Open Access   (Followers: 2)
Journal of Medicinal Botany     Open Access  
Journal of Medicinal Chemistry     Hybrid Journal   (Followers: 200)
Journal of Medicine     Open Access   (Followers: 1)
Journal of Medicine and Biomedical Research     Open Access   (Followers: 1)
Journal of Medicine and Philosophy     Hybrid Journal   (Followers: 8)
Journal of Medicine and the Person     Hybrid Journal  
Journal of Medicine in Scientific Research     Open Access  
Journal of Medicine in the Tropics     Open Access  
Journal of Medicine Research and Development     Open Access   (Followers: 3)
Journal of Medicine, Physiology and Biophysics     Open Access   (Followers: 5)
Journal of Medicines Development Sciences     Open Access   (Followers: 1)
Journal of Metabolomics & Systems Biology     Open Access   (Followers: 1)
Journal of Mind and Medical Sciences     Open Access   (Followers: 1)
Journal of Molecular Medicine     Hybrid Journal   (Followers: 11)
Journal of Movement Disorders     Open Access   (Followers: 2)
Journal of Muscle Research and Cell Motility     Hybrid Journal   (Followers: 1)
Journal of Nanotechnology in Engineering and Medicine     Full-text available via subscription   (Followers: 6)
Journal of Nanotheranostics     Open Access   (Followers: 1)
Journal of Natural Medicines     Hybrid Journal  
Journal of Natural Science, Biology and Medicine     Open Access   (Followers: 3)
Journal of Nature and Science of Medicine     Open Access   (Followers: 4)
Journal of Negative and No Positive Results     Open Access  
Journal of Nepalgunj Medical College     Open Access  
Journal of Neurocritical Care     Open Access  
Journal of Neurodegenerative Diseases     Open Access   (Followers: 2)
Journal of Neurorestoratology     Open Access  
Journal of Neuroscience and Neurological Disorders     Open Access  
Journal of Nobel Medical College     Open Access  
Journal of Obesity and Bariatrics     Open Access   (Followers: 1)
Journal of Occupational Health     Open Access  
Journal of Occupational Therapy Education     Open Access   (Followers: 10)
Journal of Ocular Biology, Diseases, and Informatics     Hybrid Journal  
Journal of Oral Biology and Craniofacial Research     Full-text available via subscription  
Journal of Oral Health and Craniofacial Science     Open Access  
Journal of Orofacial Sciences     Open Access  
Journal of Otorhinolaryngology, Hearing and Balance Medicine     Open Access   (Followers: 1)
Journal of Ovarian Research     Open Access  
Journal of Ozone Therapy     Open Access  
Journal of Palliative Medicine     Hybrid Journal   (Followers: 47)
Journal of Paramedical Sciences & Rehabilitation     Open Access  
Journal of Parkinsonism and Restless Legs Syndrome     Open Access   (Followers: 2)
Journal of Parkinson’s Disease and Alzheimer’s Disease     Open Access   (Followers: 1)
Journal of Participatory Medicine     Open Access  
Journal of Patan Academy of Health Sciences     Open Access  
Journal of Pathogens     Open Access   (Followers: 1)
Journal of Patient Experience     Open Access  
Journal of Patient Safety and Risk Management     Hybrid Journal   (Followers: 2)
Journal of Patient-Centered Research and Reviews     Open Access  
Journal of Patient-Reported Outcomes     Open Access  
Journal of Periodontal Research     Hybrid Journal  
Journal of Personalized Medicine     Open Access   (Followers: 3)
Journal of Pest Science     Hybrid Journal   (Followers: 1)
Journal of Pharmaceutical Policy and Practice     Open Access   (Followers: 4)
Journal of Physiobiochemical Metabolism     Hybrid Journal   (Followers: 2)
Journal of Physiology-Paris     Hybrid Journal   (Followers: 2)
Journal of Pioneering Medical Sciences     Open Access  
Journal of Postgraduate Medicine     Open Access  
Journal of Pregnancy     Open Access   (Followers: 4)
Journal of Prevention & Intervention Community     Hybrid Journal   (Followers: 6)
Journal of Preventive Medicine and Public Health     Open Access  
Journal of Primary Prevention     Hybrid Journal   (Followers: 7)
Journal of Prosthodontic Research     Full-text available via subscription   (Followers: 1)
Journal of Prosthodontics     Hybrid Journal   (Followers: 2)
Journal of Receptor, Ligand and Channel Research     Open Access  
Journal of Regenerative Medicine     Partially Free   (Followers: 4)
Journal of Research in Medical Sciences     Open Access   (Followers: 2)
Journal of Science and Applications : Biomedicine     Open Access   (Followers: 1)
Journal of Science and Technology (Ghana)     Open Access   (Followers: 3)
Journal of Scientific Innovation in Medicine     Open Access  
Journal of Scientific Perspectives     Open Access   (Followers: 1)
Journal of Sensory Studies     Hybrid Journal   (Followers: 4)
Journal of Shaheed Suhrawardy Medical College     Open Access  
Journal of Shoulder and Elbow Arthroplasty     Open Access  
Journal of Sleep Disorders : Treatment & Care     Hybrid Journal   (Followers: 10)
Journal of South American Earth Sciences     Hybrid Journal   (Followers: 5)
Journal of Spinal Cord Medicine     Hybrid Journal   (Followers: 4)
Journal of Spinal Disorders & Techniques     Hybrid Journal   (Followers: 2)
Journal of Sports Medicine and Allied Health Sciences : Official Journal of the Ohio Athletic Trainers Association     Open Access   (Followers: 1)
Journal of Stem Cell Therapy and Transplantation     Open Access   (Followers: 1)
Journal of Stomal Therapy Australia     Full-text available via subscription  
Journal of Strength and Conditioning Research     Hybrid Journal   (Followers: 75)
Journal of Substance Use     Hybrid Journal   (Followers: 14)
Journal of Surgical Academia     Open Access   (Followers: 1)
Journal of Surgical and Clinical Research     Open Access  
Journal of Surgical Case Reports     Open Access  
Journal of Surgical Education     Full-text available via subscription   (Followers: 3)
Journal of Surgical Technique and Case Report     Open Access  
Journal of Systemic Therapies     Full-text available via subscription   (Followers: 3)
Journal of Taibah University Medical Sciences     Open Access  
Journal of Telemedicine and Telecare     Hybrid Journal   (Followers: 12)
Journal of The Academy of Clinical Microbiologists     Open Access  
Journal of the American Association for Laboratory Animal Science     Full-text available via subscription   (Followers: 7)
Journal of the American College of Certified Wound Specialists     Hybrid Journal   (Followers: 2)
Journal of the American College of Clinical Wound Specialists     Hybrid Journal   (Followers: 2)
Journal of the American Medical Directors Association     Hybrid Journal   (Followers: 5)
Journal of the American Medical Informatics Association : JAMIA     Hybrid Journal   (Followers: 35)
Journal of the American Podiatric Medical Association     Full-text available via subscription   (Followers: 7)
Journal of the Anatomical Society of India     Full-text available via subscription  
Journal of the Anus, Rectum and Colon     Open Access  
Journal of The Arab Society for Medical Research     Open Access  
Journal of the Australasian College of Nutritional and Environmental Medicine     Full-text available via subscription  
Journal of the Australasian Society of Aerospace Medicine     Open Access   (Followers: 1)
Journal of the Ceylon College of Physicians     Open Access  
Journal of the Chinese Medical Association     Open Access   (Followers: 2)
Journal of the College of Community Physicians of Sri Lanka     Open Access  
Journal of The Egyptian Public Health Association     Open Access   (Followers: 1)
Journal of the Formosan Medical Association     Open Access   (Followers: 2)
Journal of the Georgia Public Health Association     Open Access   (Followers: 1)
Journal of the Ghana Science Association     Full-text available via subscription   (Followers: 3)
Journal of the Grodno State Medical University     Open Access   (Followers: 1)
Journal of the History of Medicine and Allied Sciences     Hybrid Journal   (Followers: 17)

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Similar Journals
Journal Cover
Journal of the American Medical Informatics Association : JAMIA
Journal Prestige (SJR): 1.848
Citation Impact (citeScore): 4
Number of Followers: 35  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1067-5027 - ISSN (Online) 1527-974X
Published by Oxford University Press Homepage  [412 journals]
  • Celebrating the International Year of the Nurse and Midwife: A look at
           nursing in JAMIA
    • Authors: Bakken S; Alexander G.
      Pages: 665 - 666
      Abstract: In celebration of the 200th birthday of Florence Nightingale, widely acknowledged as the founder of modern nursing, the World Health Organization declared 2020 as the International Year of the Nurse and Midwife. Nursing informatics is a key component of the broader field of biomedical and health informatics as well as the Nursing Informatics Working Group, a large and vibrant working group within the American Medical Informatics Association community. The American Nurses Association (ANA) defined nursing informatics as a specialty and published the first standards for its practice more than 25 years ago.1,2 As described in Journal of the American Medical Informatics Association (JAMIA), the definition has evolved through the years.3 The most recent ANA definition is the following:
      PubDate: Sat, 02 May 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa046
      Issue No: Vol. 27, No. 5 (2020)
       
  • Self-monitoring diabetes with multiple mobile health devices
    • Authors: Shaw R; Yang Q, Barnes A, et al.
      Pages: 667 - 676
      Abstract: AbstractObjectiveThe purpose of this study was to examine the use of multiple mobile health technologies to generate and transmit data from diverse patients with type 2 diabetes mellitus (T2DM) in between clinic visits. We examined the data to identify patterns that describe characteristics of patients for clinical insights.MethodsWe enrolled 60 adults with T2DM from a US healthcare system to participate in a 6-month longitudinal feasibility trial. Patient weight, physical activity, and blood glucose were self-monitored via devices provided at baseline. Patients also responded to biweekly medication adherence text message surveys. Data were aggregated in near real-time. Measures of feasibility assessing total engagement in device submissions and survey completion over the 6 months of observation were calculated.ResultsIt was feasible for participants from different socioeconomic, educational, and racial backgrounds to use and track relevant diabetes-related data from multiple mobile health devices for at least 6 months. Both the transmission and engagement of the data revealed notable patterns and varied by patient characteristics.DiscussionUsing multiple mobile health tools allowed us to derive clinical insights from diverse patients with diabetes. The ubiquitous adoption of smartphones across racial, educational, and socioeconomic populations and the integration of data from mobile health devices into electronic health records present an opportunity to develop new models of care delivery for patients with T2DM that may promote equity as well.
      PubDate: Thu, 05 Mar 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa007
      Issue No: Vol. 27, No. 5 (2020)
       
  • Visual analogies, not graphs, increase patients' comprehension of changes
           in their health status
    • Authors: Reading Turchioe M; Grossman L, Myers A, et al.
      Pages: 677 - 689
      Abstract: Abstract ObjectivesPatients increasingly use patient-reported outcomes (PROs) to self-monitor their health status. Visualizing PROs longitudinally (over time) could help patients interpret and contextualize their PROs. The study sought to assess hospitalized patients' objective comprehension (primary outcome) of text-only, non-graph, and graph visualizations that display longitudinal PROs.Materials and MethodsWe conducted a clinical research study in 40 hospitalized patients comparing 4 visualization conditions: (1) text-only, (2) text plus visual analogy, (3) text plus number line, and (4) text plus line graph. Each participant viewed every condition, and we used counterbalancing (systematic randomization) to control for potential order effects. We assessed objective comprehension using the International Organization for Standardization protocol. Secondary outcomes included response times, preferences, risk perceptions, and behavioral intentions.ResultsOverall, 63% correctly comprehended the text-only condition and 60% comprehended the line graph condition, compared with 83% for the visual analogy and 70% for the number line (P = .05) conditions. Participants comprehended the visual analogy significantly better than the text-only (P = .02) and line graph (P = .02) conditions. Of participants who comprehended at least 1 condition, 14% preferred a condition that they did not comprehend. Low comprehension was associated with worse cognition (P < .001), lower education level (P = .02), and fewer financial resources (P = .03).ConclusionsThe results support using visual analogies rather than text to display longitudinal PROs but caution against relying on graphs, which is consistent with the known high prevalence of inadequate graph literacy. The discrepancies between comprehension and preferences suggest factors other than comprehension influence preferences, and that future researchers should assess comprehension rather than preferences to guide presentation decisions.
      PubDate: Thu, 30 Jan 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocz217
      Issue No: Vol. 27, No. 5 (2020)
       
  • Unmet information needs of clinical teams delivering care to complex
           patients and design strategies to address those needs
    • Authors: Cohen D; Wyte-Lake T, Dorr D, et al.
      Pages: 690 - 699
      Abstract: AbstractObjectivesTo identify the unmet information needs of clinical teams delivering care to patients with complex medical, social, and economic needs; and to propose principles for redesigning electronic health records (EHR) to address these needs.Materials and MethodsIn this observational study, we interviewed and observed care teams in 9 community health centers in Oregon and Washington to understand their use of the EHR when caring for patients with complex medical and socioeconomic needs. Data were analyzed using a comparative approach to identify EHR users’ information needs, which were then used to produce EHR design principles.ResultsAnalyses of > 300 hours of observations and 51 interviews identified 4 major categories of information needs related to: consistency of social determinants of health (SDH) documentation; SDH information prioritization and changes to this prioritization; initiation and follow-up of community resource referrals; and timely communication of SDH information. Within these categories were 10 unmet information needs to be addressed by EHR designers. We propose the following EHR design principles to address these needs: enhance the flexibility of EHR documentation workflows; expand the ability to exchange information within teams and between systems; balance innovation and standardization of health information technology systems; organize and simplify information displays; and prioritize and reduce information.ConclusionDeveloping EHR tools that are simple, accessible, easy to use, and able to be updated by a range of professionals is critical. The identified information needs and design principles should inform developers and implementers working in community health centers and other settings where complex patients receive care.
      PubDate: Thu, 05 Mar 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa010
      Issue No: Vol. 27, No. 5 (2020)
       
  • Accounting for data variability in multi-institutional distributed deep
           learning for medical imaging
    • Authors: Balachandar N; Chang K, Kalpathy-Cramer J, et al.
      Pages: 700 - 708
      Abstract: AbstractObjectivesSharing patient data across institutions to train generalizable deep learning models is challenging due to regulatory and technical hurdles. Distributed learning, where model weights are shared instead of patient data, presents an attractive alternative. Cyclical weight transfer (CWT) has recently been demonstrated as an effective distributed learning method for medical imaging with homogeneous data across institutions. In this study, we optimize CWT to overcome performance losses from variability in training sample sizes and label distributions across institutions.Materials and MethodsOptimizations included proportional local training iterations, cyclical learning rate, locally weighted minibatch sampling, and cyclically weighted loss. We evaluated our optimizations on simulated distributed diabetic retinopathy detection and chest radiograph classification.ResultsProportional local training iteration mitigated performance losses from sample size variability, achieving 98.6% of the accuracy attained by centrally hosting in the diabetic retinopathy dataset split with highest sample size variance across institutions. Locally weighted minibatch sampling and cyclically weighted loss both mitigated performance losses from label distribution variability, achieving 98.6% and 99.1%, respectively, of the accuracy attained by centrally hosting in the diabetic retinopathy dataset split with highest label distribution variability across institutions.DiscussionOur optimizations to CWT improve its capability of handling data variability across institutions. Compared to CWT without optimizations, CWT with optimizations achieved performance significantly closer to performance from centrally hosting.ConclusionOur work is the first to identify and address challenges of sample size and label distribution variability in simulated distributed deep learning for medical imaging. Future work is needed to address other sources of real-world data variability.
      PubDate: Fri, 20 Mar 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa017
      Issue No: Vol. 27, No. 5 (2020)
       
  • “How did you get to this number'” Stakeholder needs for
           
    • Authors: Benda N; Das L, Abramson E, et al.
      Pages: 709 - 716
      Abstract: AbstractObjectivePredictive analytics are potentially powerful tools, but to improve healthcare delivery, they must be carefully integrated into healthcare organizations. Our objective was to identify facilitators, challenges, and recommendations for implementing a novel predictive algorithm which aims to prospectively identify patients with high preventable utilization to proactively involve them in preventative interventions.Materials and MethodsIn preparation for implementing the predictive algorithm in 3 organizations, we interviewed 3 stakeholder groups: health systems operations (eg, chief medical officers, department chairs), informatics personnel, and potential end users (eg, physicians, nurses, social workers). We applied thematic analysis to derive key themes and categorize them into the dimensions of Sittig and Singh’s original sociotechnical model for studying health information technology in complex adaptive healthcare systems. Recruiting and analysis were conducted iteratively until thematic saturation was achieved.ResultsForty-nine interviews were conducted in 3 healthcare organizations. Technical components of the implementation (hardware and software) raised fewer concerns than alignment with sociotechnical factors. Stakeholders wanted decision support based on the algorithm to be clear and actionable and incorporated into current workflows. However, how to make this disease-independent classification tool actionable was perceived as a challenge, and appropriate patient interventions informed by the algorithm appeared likely to require substantial external and institutional resources. Stakeholders also described the criticality of trust, credibility, and interpretability of the predictive algorithm.ConclusionsAlthough predictive analytics can classify patients with high accuracy, they cannot advance healthcare processes and outcomes without careful implementation that takes into account the sociotechnical system. Key stakeholders have strong perceptions about facilitators and challenges to shape successful implementation.
      PubDate: Fri, 06 Mar 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa021
      Issue No: Vol. 27, No. 5 (2020)
       
  • Racial differences in patient consent policy preferences for electronic
           health information exchange
    • Authors: Turvey C; Klein D, Nazi K, et al.
      Pages: 717 - 725
      Abstract: AbstractObjectiveThis study aimed to explore the association between demographic variables, such as race and gender, and patient consent policy preferences for health information exchange as well as self-report by VHA enrollees of information continuity between Veterans Health Administration (VHA) and community non-VHA heath care providers.Materials and MethodsData were collected between March 25, 2016 and August 22, 2016 in an online survey of 19 567 veterans. Three questions from the 2016 Commonwealth Fund International Health Policy Survey, which addressed care continuity, were included. The survey also included questions about consent policy preference regarding opt-out, opt-in, and “break the glass” consent policies.ResultsVHA enrollees had comparable proportions of unnecessary laboratory testing and conflicting information from providers when compared with the United States sample in the Commonwealth Survey. However, they endorsed medical record information being unavailable between organizations more highly. Demographic variables were associated with gaps in care continuity as well as consent policy preferences, with 56.8% of Whites preferring an opt-out policy as compared with 40.3% of Blacks, 44.9% of Hispanic Latinos, 48.3% of Asian/Pacific Islanders, and 38.3% of Native Americans (P < .001).DiscussionObserved large differences by race and ethnicity in privacy preferences for electronic health information exchange should inform implementation of these programs to ensure cultural sensitivity. Veterans experienced care continuity comparable to a general United States sample, except for less effective exchange of health records between heath care organizations. VHA followed an opt-in consent policy at the time of this survey which may underlie this gap.
      PubDate: Mon, 09 Mar 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa012
      Issue No: Vol. 27, No. 5 (2020)
       
  • A system uptake analysis and GUIDES checklist evaluation of the Electronic
           Asthma Management System: A point-of-care computerized clinical decision
           support system
    • Authors: Lam Shin Cheung J; Paolucci N, Price C, et al.
      Pages: 726 - 737
      Abstract: AbstractObjectiveComputerized clinical decision support systems (CCDSSs) promise improvements in care quality; however, uptake is often suboptimal. We sought to characterize system use, its predictors, and user feedback for the Electronic Asthma Management System (eAMS)—an electronic medical record system–integrated, point-of-care CCDSS for asthma—and applied the GUIDES checklist as a framework to identify areas for improvement.Materials and MethodsThe eAMS was tested in a 1-year prospective cohort study across 3 Ontario primary care sites. We recorded system usage by clinicians and patient characteristics through system logs and chart reviews. We created multivariable models to identify predictors of (1) CCDSS opening and (2) creation of a self-management asthma action plan (AAP) (final CCDSS step). Electronic questionnaires captured user feedback.ResultsOver 1 year, 490 asthma patients saw 121 clinicians. The CCDSS was opened in 205 of 1033 (19.8%) visits and an AAP created in 121 of 1033 (11.7%) visits. Multivariable predictors of opening the CCDSS and producing an AAP included clinic site, having physician-diagnosed asthma, and presenting with an asthma- or respiratory-related complaint. The system usability scale score was 66.3 ± 16.5 (maximum 100). Reported usage barriers included time and system accessibility.DiscussionThe eAMS was used in a minority of asthma patient visits. Varying workflows and cultures across clinics, physician beliefs regarding asthma diagnosis, and relevance of the clinical complaint influenced uptake.ConclusionsConsidering our findings in the context of the GUIDES checklist helped to identify improvements to drive uptake and provides lessons relevant to CCDSS design across diseases.
      PubDate: Fri, 10 Apr 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa019
      Issue No: Vol. 27, No. 5 (2020)
       
  • The new International Classification of Diseases 11th edition: a
           comparative analysis with ICD-10 and ICD-10-CM
    • Authors: Fung K; Xu , , Bodenreider O.
      Pages: 738 - 746
      Abstract: AbstractObjectiveTo study the newly adopted International Classification of Diseases 11th revision (ICD-11) and compare it to the International Classification of Diseases 10th revision (ICD-10) and International Classification of Diseases 10th revision-Clinical Modification (ICD-10-CM).Materials and Methods: Data files and maps were downloaded from the World Health Organization (WHO) website and through the application programming interfaces. A round trip method based on the WHO maps was used to identify equivalent codes between ICD-10 and ICD-11, which were validated by limited manual review. ICD-11 terms were mapped to ICD-10-CM through normalized lexical mapping. ICD-10-CM codes in 6 disease areas were also manually recoded in ICD-11.ResultsExcluding the chapters for traditional medicine, functioning assessment, and extension codes for postcoordination, ICD-11 has 14 622 leaf codes (codes that can be used in coding) compared to ICD-10 and ICD-10-CM, which has 10 607 and 71 932 leaf codes, respectively. We identified 4037 pairs of ICD-10 and ICD-11 codes that were equivalent (estimated accuracy of 96%) by our round trip method. Lexical matching between ICD-11 and ICD-10-CM identified 4059 pairs of possibly equivalent codes. Manual recoding showed that 60% of a sample of 388 ICD-10-CM codes could be fully represented in ICD-11 by precoordinated codes or postcoordination.ConclusionIn ICD-11, there is a moderate increase in the number of codes over ICD-10. With postcoordination, it is possible to fully represent the meaning of a high proportion of ICD-10-CM codes, especially with the addition of a limited number of extension codes.
      PubDate: Sat, 02 May 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa030
      Issue No: Vol. 27, No. 5 (2020)
       
  • EXpectation Propagation LOgistic REgRession on permissioned blockCHAIN
           (ExplorerChain): decentralized online healthcare/genomics predictive model
           learning
    • Authors: Kuo T; Gabriel R, Cidambi K, et al.
      Pages: 747 - 756
      Abstract: AbstractObjectivePredicting patient outcomes using healthcare/genomics data is an increasingly popular/important area. However, some diseases are rare and require data from multiple institutions to construct generalizable models. To address institutional data protection policies, many distributed methods keep the data locally but rely on a central server for coordination, which introduces risks such as a single point of failure. We focus on providing an alternative based on a decentralized approach. We introduce the idea using blockchain technology for this purpose, with a brief description of its own potential advantages/disadvantages.Materials and MethodsWe explain how our proposed EXpectation Propagation LOgistic REgRession on Permissioned blockCHAIN (ExplorerChain) can achieve the same results when compared to a distributed model that uses a central server on 3 healthcare/genomic datasets, and what trade-offs need to be considered when using centralized/decentralized methods. We explain how the use of blockchain technology can help decrease some of the problems encountered in decentralized methods.ResultsWe showed that the discrimination power of ExplorerChain can be statistically similar to its counterpart central server-based algorithm. While ExplorerChain inherited some benefits of blockchain, it had a small increased running time.DiscussionExplorerChain has the same prerequisites as a distributed model with a centralized server for coordination. In a manner similar to secure multi-party computation strategies, it assumes that participating institutions are honest, but “curious.”ConclusionWhen evaluated on relatively small datasets, results suggest that ExplorerChain, which combines artificial intelligence and blockchain technologies, performs as well as a central server-based method, and may avoid some risks at the cost of efficiency.
      PubDate: Sat, 02 May 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa023
      Issue No: Vol. 27, No. 5 (2020)
       
  • Classifying non-small cell lung cancer types and transcriptomic subtypes
           using convolutional neural networks
    • Authors: Yu K; Wang F, Berry G, et al.
      Pages: 757 - 769
      Abstract: AbstractObjectiveNon-small cell lung cancer is a leading cause of cancer death worldwide, and histopathological evaluation plays the primary role in its diagnosis. However, the morphological patterns associated with the molecular subtypes have not been systematically studied. To bridge this gap, we developed a quantitative histopathology analytic framework to identify the types and gene expression subtypes of non-small cell lung cancer objectively.Materials and MethodsWe processed whole-slide histopathology images of lung adenocarcinoma (n = 427) and lung squamous cell carcinoma patients (n = 457) in the Cancer Genome Atlas. We built convolutional neural networks to classify histopathology images, evaluated their performance by the areas under the receiver-operating characteristic curves (AUCs), and validated the results in an independent cohort (n = 125).ResultsTo establish neural networks for quantitative image analyses, we first built convolutional neural network models to identify tumor regions from adjacent dense benign tissues (AUCs > 0.935) and recapitulated expert pathologists’ diagnosis (AUCs > 0.877), with the results validated in an independent cohort (AUCs = 0.726-0.864). We further demonstrated that quantitative histopathology morphology features identified the major transcriptomic subtypes of both adenocarcinoma and squamous cell carcinoma (P < .01).DiscussionOur study is the first to classify the transcriptomic subtypes of non-small cell lung cancer using fully automated machine learning methods. Our approach does not rely on prior pathology knowledge and can discover novel clinically relevant histopathology patterns objectively. The developed procedure is generalizable to other tumor types or diseases.
      PubDate: Sat, 02 May 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocz230
      Issue No: Vol. 27, No. 5 (2020)
       
  • How accurate is the medical record' A comparison of the physician’s
           note with a concealed audio recording in unannounced standardized patient
           encounters
    • Authors: Weiner S; Wang S, Kelly B, et al.
      Pages: 770 - 775
      Abstract: AbstractObjectivesAccurate documentation in the medical record is essential for quality care; extensive documentation is required for reimbursement. At times, these 2 imperatives conflict. We explored the concordance of information documented in the medical record with a gold standard measure.Materials and MethodsWe compared 105 encounter notes to audio recordings covertly collected by unannounced standardized patients from 36 physicians, to identify discrepancies and estimate the reimbursement implications of billing the visit based on the note vs the care actually delivered.ResultsThere were 636 documentation errors, including 181 charted findings that did not take place, and 455 findings that were not charted. Ninety percent of notes contained at least 1 error. In 21 instances, the note justified a higher billing level than the gold standard audio recording, and in 4, it underrepresented the level of service (P = .005), resulting in 40 level 4 notes instead of the 23 justified based on the audio, a 74% inflated misrepresentation.DiscussionWhile one cannot generalize about specific error rates based on a relatively small sample of physicians exclusively within the Department of Veterans Affairs Health System, the magnitude of the findings raise fundamental concerns about the integrity of the current medical record documentation process as an actual representation of care, with implications for determining both quality and resource utilization.ConclusionThe medical record should not be assumed to reflect care delivered. Furthermore, errors of commission—documentation of services not actually provided—may inflate estimates of resource utilization.
      PubDate: Fri, 24 Apr 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa027
      Issue No: Vol. 27, No. 5 (2020)
       
  • Assessment of the Nursing Quality Indicators for Reporting and Evaluation
           (NQuIRE) database using a data quality index
    • Authors: Naik S; Voong S, Bamford M, et al.
      Pages: 776 - 782
      Abstract: AbstractA comprehensive data quality assessment is necessary to expand a nursing database that is designed for evaluating the impact of implementing Best Practice Guidelines (BPG) developed by the Registered Nurses’ Association of Ontario (RNAO). This case report presents a method to standardize data quality assessments of the Nursing Quality Indicators for Reporting and Evaluation (NQuIRE) database by developing a data quality framework (DQF) and assessing key dimensions of the framework using a data quality index (DQI). The data quality index is a single key performance metric for assessing the quality of the database. The aims of sharing this case report are 2-fold: (1) to promote best practices for assessing data quality by developing and implementing a data quality framework and (2) to demonstrate an unprecedented method of assessing the data quality of a nursing database.
      PubDate: Sat, 02 May 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa031
      Issue No: Vol. 27, No. 5 (2020)
       
  • Identified themes of interactive visualizations overlayed onto EHR data:
           an example of improving birth center operating room efficiency
    • Authors: Stirling A; Tubb T, Reiff E, et al.
      Pages: 783 - 787
      Abstract: AbstractObjectiveWhile electronic health record (EHR) systems store copious amounts of patient data, aggregating those data across patients can be challenging. Visual analytic tools that integrate with EHR systems allow clinicians to gain better insight and understanding into clinical care and management. We report on our experience building Tableau-based visualizations and integrating them into our EHR system.Materials and MethodsVisual analytic tools were created as part of 12 clinician-initiated quality improvement projects. We built the visual analytic tools in Tableau and linked it within our EPIC environment. We identified 5 visual themes that spanned the various projects. To illustrate these themes, we choose 1 exemplary project which aimed to improve obstetric operating room efficiency.ResultsAcross our 12 projects, we identified 5 visual themes that are integral to project success: scheduling & optimization (in 11/12 projects); provider assessment (10/12); executive assessment (8/12); patient outcomes (7/12); and control and goal charts (2/12).DiscussionMany visualizations share common themes. Identification of these themes has allowed our internal team to be more efficient and directed in developing visualizations for future projects.ConclusionOrganizing visual analytics into themes can allow informatics teams to more efficiently provide visual products to clinical collaborators.
      PubDate: Tue, 17 Mar 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa016
      Issue No: Vol. 27, No. 5 (2020)
       
  • Early experiences with combined fellowship training in clinical
           informatics
    • Authors: Palma J; Hron J, Luberti A.
      Pages: 788 - 792
      Abstract: AbstractGiven the ubiquitous nature of information systems in modern health care, interest in the pursuit of formal training in clinical informatics is increasing. This interest is not restricted to generalists—informatics training is increasingly being sought by future subspecialists. The traditional structure of Accreditation Council on Graduate Medical Education subspecialty training requires completion of both clinical and clinical informatics fellowship programs, and understandably lacks appeal due to the time commitment required. One approach to encourage clinical informatics training is to integrate it with clinical fellowships in order to confer dual-board eligibility. In this perspective, we describe 3 successful petitions for combined training in clinical informatics in order to support other programs and the American Board of Preventive Medicine in establishing pathways for training subspecialists in clinical informatics.
      PubDate: Wed, 18 Mar 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa015
      Issue No: Vol. 27, No. 5 (2020)
       
  • Using and improving distributed data networks to generate actionable
           evidence: the case of real-world outcomes in the Food and Drug
           Administration’s Sentinel system
    • Authors: Brown J; Maro J, Nguyen M, et al.
      Pages: 793 - 797
      Abstract: AbstractThe US Food and Drug Administration (FDA) Sentinel System uses a distributed data network, a common data model, curated real-world data, and distributed analytic tools to generate evidence for FDA decision-making. Sentinel system needs include analytic flexibility, transparency, and reproducibility while protecting patient privacy. Based on over a decade of experience, a critical system limitation is the inability to identify enough medical conditions of interest in observational data to a satisfactory level of accuracy. Improving the system’s ability to use computable phenotypes will require an “all of the above” approach that improves use of electronic health data while incorporating the growing array of complementary electronic health record data sources. FDA recently funded a Sentinel System Innovation Center and a Community Building and Outreach Center that will provide a platform for collaboration across disciplines to promote better use of real-world data for decision-making.
      PubDate: Sat, 11 Apr 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa028
      Issue No: Vol. 27, No. 5 (2020)
       
  • A systematic review of the impact of health information technology on
           nurses’ time
    • Authors: Moore E; Tolley C, Bates D, et al.
      Pages: 798 - 807
      Abstract: ObjectiveNursing time represents one of the highest costs for most health services. We conducted a systematic review of the literature on the impact of health information technology on nurses’ time.Materials and MethodsWe followed PRISMA guidelines and searched 6 large databases for relevant articles published between Jan 2004 and December 2019. Two authors reviewed the titles, abstracts, and full texts. We included articles that included a comparison group in the design, measured the time taken to carry out documentation or medication administration, documented the quantitative estimates of time differences between the 2, had nurses as subjects, and was conducted in either a care home, hospital, or community clinic.ResultsWe identified a total of 1647 articles, of which 33 met our inclusion criteria. Twenty-one studies reported the impact of 12 different health information technology (HIT) implementations on nurses’ documentation time. Weighted averages were calculated for studies that implemented barcode medication administration (BCMA) and 2 weighted averages for those that implemented EHRs, as these studies used different sampling units; both showed an increase in the time spent in documentation (+22% and +46%). However, the time spent carrying out medication administration following BCMA implementation fell by 33% (P < .05). HIT also caused a redistribution of nurses’ time which, in some cases, was spent in more “value-adding” activities, such as delivering direct patient care as well as inter-professional communication.Discussion and ConclusionsMost of the HIT systems increased nursing documentation time, although time fell for medication administration following BCMA. Many HIT systems also resulted in nurses spending more time in direct care and “value-adding” activities.
      PubDate: Fri, 06 Mar 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocz231
      Issue No: Vol. 27, No. 5 (2020)
       
  • How does medical scribes’ work inform development of speech-based
           clinical documentation technologies' A systematic review
    • Authors: Tran B; Chen Y, Liu S, et al.
      Pages: 808 - 817
      Abstract: AbstractObjectiveUse of medical scribes reduces clinician burnout by sharing the burden of clinical documentation. However, medical scribes are cost-prohibitive for most settings, prompting a growing interest in developing ambient, speech-based technologies capable of automatically generating clinical documentation based on patient–provider conversation. Through a systematic review, we aimed to develop a thorough understanding of the work performed by medical scribes in order to inform the design of such technologies.Materials and MethodsRelevant articles retrieved by searching in multiple literature databases. We conducted the screening process following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) in guidelines, and then analyzed the data using qualitative methods to identify recurring themes.ResultsThe literature search returned 854 results, 65 of which met the inclusion criteria. We found that there is significant variation in scribe expectations and responsibilities across healthcare organizations; scribes also frequently adapt their work based on the provider’s style and preferences. Further, scribes’ job extends far beyond capturing conversation in the exam room; they also actively interact with patients and the care team and integrate data from other sources such as prior charts and lab test results.DiscussionThe results of this study provide several implications for designing technologies that can generate clinical documentation based on naturalistic conversations taking place in the exam room. First, a one-size-fits-all solution will be unlikely to work because of the significant variation in scribe work. Second, technology designers need to be aware of the limited role that their solution can fulfill. Third, to produce comprehensive clinical documentation, such technologies will likely have to incorporate information beyond the exam room conversation. Finally, issues of patient consent and privacy have yet to be adequately addressed, which could become paramount barriers to implementing such technologies in realistic clinical settings.ConclusionsMedical scribes perform complex and delicate work. Further research is needed to better understand their roles in a clinical setting in order to inform the development of speech-based clinical documentation technologies.
      PubDate: Tue, 17 Mar 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa020
      Issue No: Vol. 27, No. 5 (2020)
       
  • Serious games for smoking prevention and cessation: A systematic review of
           game elements and game effects
    • Authors: Derksen M; van Strijp S, Kunst A, et al.
      Pages: 818 - 833
      Abstract: AbstractObjectiveSerious health games might have the potential to prevent tobacco smoking and its health consequences, depending on the inclusion of specific game elements. This review aimed to assess the composition of serious games and their effects on smoking initiation prevention and cessation and behavioral determinants.Materials and MethodsWe systematically searched MEDLINE, Embase, PsycINFO, and Web of Science for publications that evaluated serious games aimed at changing smoking behavior or behavioral determinants. A taxonomy by King et al was used to classify game elements.ResultsWe identified 15 studies, evaluating 14 unique serious games. All games combined multiple game elements (mean 5.5; range, 3-10). Most frequently used were general and intermittent rewards, theme and genre features, and punishments. Six studies on smoking prevention together assessed 20 determinants and found statistically significant positive effects for 8 determinants (eg, attitude, knowledge, intention). Of 7 studies on smoking cessation, 5 found positive, statistically significant effects on smoking cessation or status. These studies found statistically significant positive effects for 6 of 12 determinants (eg, self-efficacy, attitude, intention). The majority of included studies had poor or fair methodological quality, lacked follow-up measures, and had fixed (as opposed to free, on-demand) play sessions.ConclusionsSerious games included multiple types of game elements. The evidence from a number of studies suggests that games may have positive effects on smoking-related outcomes, particularly smoking cessation. However, as most studies had important methodological limitations, stronger designs are needed to demonstrate, quantify, and understand the effects of serious games.
      PubDate: Tue, 28 Apr 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa013
      Issue No: Vol. 27, No. 5 (2020)
       
  • Patient characteristics associated with objective measures of digital
           health tool use in the United States: A literature review
    • Authors: Nouri S; Adler-Milstein J, Thao C, et al.
      Pages: 834 - 841
      Abstract: AbstractObjectiveThe study sought to determine which patient characteristics are associated with the use of patient-facing digital health tools in the United States.Materials and MethodsWe conducted a literature review of studies of patient-facing digital health tools that objectively evaluated use (eg, system/platform data representing frequency of use) by patient characteristics (eg, age, race or ethnicity, income, digital literacy). We included any type of patient-facing digital health tool except patient portals. We reran results using the subset of studies identified as having robust methodology to detect differences in patient characteristics.ResultsWe included 29 studies; 13 had robust methodology. Most studies examined smartphone apps and text messaging programs for chronic disease management and evaluated only 1-3 patient characteristics, primarily age and gender. Overall, the majority of studies found no association between patient characteristics and use. Among the subset with robust methodology, white race and poor health status appeared to be associated with higher use.DiscussionGiven the substantial investment in digital health tools, it is surprising how little is known about the types of patients who use them. Strategies that engage diverse populations in digital health tool use appear to be needed.ConclusionFew studies evaluate objective measures of digital health tool use by patient characteristics, and those that do include a narrow range of characteristics. Evidence suggests that resources and need drive use.
      PubDate: Sat, 02 May 2020 00:00:00 GMT
      DOI: 10.1093/jamia/ocaa024
      Issue No: Vol. 27, No. 5 (2020)
       
 
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