In an effort to understand how results of human clinical trials are made public, we analyze a large set of clinical trials registered at ClinicalTrials.gov, the world's largest clinical trial ...registry.
We considered two trial result artifacts: (1) existence of a trial result journal article that is formally linked to a registered trial or (2) the deposition of a trial's basic summary results within the registry.
The study sample consisted of 8907 completed, interventional, phase 2-or-higher clinical trials that were completed in 2006-2009. The majority of trials (72.2%) had no structured trial-article link present. A total of 2367 trials (26.6%) deposited basic summary results within the registry. Of those, 969 trials (10.9%) were classified as trials with extended results and 1398 trials (15.7%) were classified as trials with only required basic results. The majority of the trials (54.8%) had no evidence of results, based on either linked result articles or basic summary results (silent trials), while a minimal number (9.2%) report results through both registry deposition and publication.
Our study analyzes the body of linked knowledge around clinical trials (which we refer to as the "trialome"). Our results show that most trials do not report results and, for those that do, there is minimal overlap in the types of reporting. We identify several mechanisms by which the linkages between trials and their published results can be increased.
Our study shows that even when combining publications and registry results, and despite availability of several information channels, trial sponsors do not sufficiently meet the mandate to inform the public either via a linked result publication or basic results submission.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Complaints about electronic health records, including information overload, note bloat, and alert fatigue, are frequent topics of discussion. Despite substantial effort by researchers and ...industry, complaints continue noting serious adverse effects on patient safety and clinician quality of life. I believe solutions are possible if we can add information to the record that explains the “why” of a patient’s care, such as relationships between symptoms, physical findings, diagnostic results, differential diagnoses, therapeutic plans, and goals. While this information may be present in clinical notes, I propose that we modify electronic health records to support explicit representation of this information using formal structure and controlled vocabularies. Such information could foster development of more situation-aware tools for data retrieval and synthesis. Informatics research is needed to understand what should be represented, how to capture it, and how to benefit those providing the information so that their workload is reduced.
The article discusses some of the advantages offered for clinicians by the introduction of electronic health records (EHRs). However, some of the areas in which EHRs are lacking and need improvement ...are highlighted.
The US health system has recently achieved widespread adoption of electronic health record (EHR) systems, primarily driven by financial incentives provided by the Meaningful Use (MU) program. ...Although successful in promoting EHR adoption and use, the program, and other contributing factors, also produced important unintended consequences (UCs) with far-reaching implications for the US health system. Based on our own experiences from large health information technology (HIT) adoption projects and a collection of key studies in HIT evaluation, we discuss the most prominent UCs of MU: failed expectations, EHR market saturation, innovation vacuum, physician burnout, and data obfuscation. We identify challenges resulting from these UCs and provide recommendations for future research to empower the broader medical and informatics communities to realize the full potential of a now digitized health system. We believe that fixing these unanticipated effects will demand efforts from diverse players such as health care providers, administrators, HIT vendors, policy makers, informatics researchers, funding agencies, and outside developers; promotion of new business models; collaboration between academic medical centers and informatics research departments; and improved methods for evaluations of HIT.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Physicians intuitively apply pattern recognition when evaluating a patient. Rational diagnosis making requires that clinical patterns be put in the context of disease prior probability, yet ...physicians often exhibit flawed probabilistic reasoning. Difficulties in making a diagnosis are reflected in the high rates of deadly and costly diagnostic errors. Introduced 6 decades ago, computerized diagnosis support systems are still not widely used by internists. These systems cannot efficiently recognize patterns and are unable to consider the base rate of potential diagnoses. We review the limitations of current computer-aided diagnosis support systems. We then portray future diagnosis support systems and provide a conceptual framework for their development. We argue for capturing physician knowledge using a novel knowledge representation model of the clinical picture. This model (based on structured patient presentation patterns) holds not only symptoms and signs but also their temporal and semantic interrelations. We call for the collection of crowdsourced, automatically deidentified, structured patient patterns as means to support distributed knowledge accumulation and maintenance. In this approach, each structured patient pattern adds to a self-growing and -maintaining knowledge base, sharing the experience of physicians worldwide. Besides supporting diagnosis by relating the symptoms and signs with the final diagnosis recorded, the collective pattern map can also provide disease base-rate estimates and real-time surveillance for early detection of outbreaks. We explain how health care in resource-limited settings can benefit from using this approach and how it can be applied to provide feedback-rich medical education for both students and practitioners.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
To determine whether two specific criteria in Uniform Requirements for Manuscripts (URM) created by the International Committee of Medical Journal Editors (ICMJE)--namely, including the trial ID ...registration within manuscripts and timely registration of trials, are being followed.
Observational study using computerized analysis of publicly available Medline article data and clinical trial registry data. We analyzed a purposive set of five ICMJE founding journals looking at all trial articles published in those journals during 2010-2011, and data from the ClinicalTrials.gov (CTG) trial registry. We measured adherence to trial ID inclusion policy as the percentage of trial journal articles that contained a valid trial ID within the article (journal-based sample). Adherence to timely registration was measured as the percentage of trials that registered the trial before enrolling the first participant within a 60-day grace period. We also examined timely registration rates by year of all phase II and higher interventional trials in CTG (registry-based sample).
To determine trial ID inclusion, we analyzed 698 clinical trial articles in five journals. A total of 95.8% (661/690) of trial journal articles included the trial ID. In 88.3% the trial-article link is stored within a structured Medline field. To evaluate timely registration, we analyzed trials referenced by 451 articles from the selected five journals. A total of 60% (272/451) of articles were registered in a timely manner with an improving trend for trials initiated in later years (eg, 89% of trials that began in 2008 were registered in a timely manner). In the registry-based sample, the timely registration rates ranged from 56% for trials registered in 2006 to 72% for trials registered in 2011.
Adherence to URM requirements for registration and trial ID inclusion increases the utility of PubMed and links it in an important way to clinical trial repositories. This new integrated knowledge source can facilitate research prioritization, clinical guidelines creation, and precision medicine.
The five selected journals adhere well to the policy of mandatory trial registration and also outperform the registry in adherence to timely registration. ICMJE's URM policy represents a unique international mandate that may be providing a powerful incentive for sponsors and investigators to document clinical trials and trial result publications and thus fulfill important obligations to trial participants and society.
Abstract
Objective
The study sought to describe the literature describing clinical reasoning ontology (CRO)–based clinical decision support systems (CDSSs) and identify and classify the medical ...knowledge and reasoning concepts and their properties within these ontologies to guide future research.
Methods
MEDLINE, Scopus, and Google Scholar were searched through January 30, 2019, for studies describing CRO-based CDSSs. Articles that explored the development or application of CROs or terminology were selected. Eligible articles were assessed for quality features of both CDSSs and CROs to determine the current practices. We then compiled concepts and properties used within the articles.
Results
We included 38 CRO-based CDSSs for the analysis. Diversity of the purpose and scope of their ontologies was seen, with a variety of knowledge sources were used for ontology development. We found 126 unique medical knowledge concepts, 38 unique reasoning concepts, and 240 unique properties (137 relationships and 103 attributes). Although there is a great diversity among the terms used across CROs, there is a significant overlap based on their descriptions. Only 5 studies described high quality assessment.
Conclusion
We identified current practices used in CRO development and provided lists of medical knowledge concepts, reasoning concepts, and properties (relationships and attributes) used by CRO-based CDSSs. CRO developers reason that the inclusion of concepts used by clinicians’ during medical decision making has the potential to improve CDSS performance. However, at present, few CROs have been used for CDSSs, and high-quality studies describing CROs are sparse. Further research is required in developing high-quality CDSSs based on CROs.
Abstract
Objective
To describe the literature exploring the use of electronic health record (EHR) systems to support creation and use of clinical documentation to guide future research.
Materials and ...Methods
We searched databases including MEDLINE, Scopus, and CINAHL from inception to April 20, 2018, for studies applying qualitative or mixed-methods examining EHR use to support creation and use of clinical documentation. A qualitative synthesis of included studies was undertaken.
Results
Twenty-three studies met the inclusion criteria and were reviewed in detail. We briefly reviewed 9 studies that did not meet the inclusion criteria but provided recommendations for EHR design. We identified 4 key themes: purposes of electronic clinical notes, clinicians’ reasoning for note-entry and reading/retrieval, clinicians’ strategies for note-entry, and clinicians’ strategies for note-retrieval/reading. Five studies investigated note purposes and found that although patient care is the primary note purpose, non-clinical purposes have become more common. Clinicians’ reasoning studies (n = 3) explored clinicians’ judgement about what to document and represented clinicians’ thought process in cognitive pathways. Note-entry studies (n = 6) revealed that what clinicians document is affected by EHR interfaces. Lastly, note-retrieval studies (n = 12) found that “assessment and plan” is the most read note section and what clinicians read is affected by external stimuli, care/information goals, and what they know about the patient.
Conclusion
Despite the widespread adoption of EHRs, their use to support note-entry and reading/retrieval is still understudied. Further research is needed to investigate approaches to capture and represent clinicians’ reasoning and improve note-entry and retrieval/reading.
The growing amount of data in operational electronic health record systems provides unprecedented opportunity for its reuse for many tasks, including comparative effectiveness research. However, ...there are many caveats to the use of such data. Electronic health record data from clinical settings may be inaccurate, incomplete, transformed in ways that undermine their meaning, unrecoverable for research, of unknown provenance, of insufficient granularity, and incompatible with research protocols. However, the quantity and real-world nature of these data provide impetus for their use, and we develop a list of caveats to inform would-be users of such data as well as provide an informatics roadmap that aims to insure this opportunity to augment comparative effectiveness research can be best leveraged.
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