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Statistics in Medicine Nov 2021The world is becoming increasingly complex, both in terms of the rich sources of data we have access to and the statistical and computational methods we can use on data....
The world is becoming increasingly complex, both in terms of the rich sources of data we have access to and the statistical and computational methods we can use on data. These factors create an ever-increasing risk for errors in code and the sensitivity of findings to data preparation and the execution of complex statistical and computing methods. The consequences of coding and data mistakes can be substantial. In this paper, we describe the key steps for implementing a code quality assurance (QA) process that researchers can follow to improve their coding practices throughout a project to assure the quality of the final data, code, analyses, and results. These steps include: (i) adherence to principles for code writing and style that follow best practices; (ii) clear written documentation that describes code, workflow, and key analytic decisions; (iii) careful version control; (iv) good data management; and (v) regular testing and review. Following these steps will greatly improve the ability of a study to assure results are accurate and reproducible. The responsibility for code QA falls not only on individual researchers but institutions, journals, and funding agencies as well.
Topics: Humans; Mathematical Computing
PubMed: 34486156
DOI: 10.1002/sim.9169 -
AMIA ... Annual Symposium Proceedings.... 2021Working with scribes can reduce provider documentation time, but few studies have examined how scribes affect clinical notes. In this retrospective cross-sectional...
Working with scribes can reduce provider documentation time, but few studies have examined how scribes affect clinical notes. In this retrospective cross-sectional study, we examine over 50,000 outpatient progress notes written with and without scribe assistance by 70 providers across 27 specialties in 2017-2018. We find scribed notes were consistently longer than those written without scribe assistance, with most additional text coming from note templates. Scribed notes were also more likely to contain certain templated lists, such as the patient's medications or past medical history. However, there was significant variation in how working with scribes affected a provider's mix of typed, templated, and copied note text, suggesting providers adapt their documentation workflows to varying degrees when working with scribes. These results suggest working with scribes may contribute to note bloat, but that providers' individual documentation workflows, including their note templates, may have a large impact on scribed note contents.
Topics: Cross-Sectional Studies; Documentation; Electronic Health Records; Humans; Outpatients; Retrospective Studies
PubMed: 35309010
DOI: No ID Found -
Seminars in Oncology Nursing Apr 2023This article provides practical guidance on developing a comprehensible abstract, including those required for funding applications, conferences, and publication. In... (Review)
Review
OBJECTIVES
This article provides practical guidance on developing a comprehensible abstract, including those required for funding applications, conferences, and publication. In addition, we discuss and demonstrate the practicalities of editing and revising an abstract for conference or peer review and identify emerging formats that may be more relevant to nurses and researchers.
DATA SOURCES
This article has been informed by literature and the coauthors' respective experiences of preparing and reviewing abstracts for publication and conference presentation.
CONCLUSION
Abstracts are a valuable tool to communicate the most important elements of the methods and results of a research project for a conference, manuscript, or even a research funding application. However, abstracts may often be an overlooked part of the dissemination process. An abstract determines whether or not a piece of research is relevant for presentation at a conference or valuable enough to be considered for peer review and subsequent publication. A strong and clearly written abstract positively predisposes reviewers of grant applications.
IMPLICATIONS FOR NURSING PRACTICE
Writing an abstract is arguably the most challenging component of academic writing, summarizing the results of a substantive research project in three to five sentences and positioning them concisely within the background and implications for future practice, policy, and research. A well-written abstract is clear, concise, and critical and requires time and revision to ensure success.
Topics: Humans; Abstracting and Indexing; Writing; Peer Review; Language
PubMed: 36841679
DOI: 10.1016/j.soncn.2023.151395 -
JBJS Reviews Jul 2021In the United States, orthopaedic surgeons have a legal obligation to obtain informed consent from patients before performing surgery; it is a process that includes a...
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In the United States, orthopaedic surgeons have a legal obligation to obtain informed consent from patients before performing surgery; it is a process that includes a signed written document.
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There are specific legal requirements that vary somewhat by state but generally include disclosure and documentation of the diagnosis, an explanation of the recommended procedure, a conversation about the risks and benefits of the procedure, and a discussion about alternative treatments.
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Inadequate disclosure of risks and alternatives is associated with increased indemnity risk.
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Studies have shown that many consent processes and forms are suboptimal.
Topics: Disclosure; Humans; Informed Consent; Orthopedic Surgeons; United States
PubMed: 34270504
DOI: 10.2106/JBJS.RVW.21.00018 -
Journal of Pain and Symptom Management Nov 2023Advance care planning (ACP) discussions seek to guide future serious illness care. These discussions may be recorded in the electronic health record by documentation in... (Review)
Review
Advance care planning (ACP) discussions seek to guide future serious illness care. These discussions may be recorded in the electronic health record by documentation in clinical notes, structured forms and directives, and physician orders. Yet, most studies of ACP prevalence have only examined structured electronic health record elements and ignored data existing in notes. We sought to investigate the relative comprehensiveness and accuracy of ACP documentation from structured and unstructured electronic health record data sources. We evaluated structured and unstructured ACP documentation present in the electronic health records of 435 patients with cancer drawn from three separate healthcare systems. We extracted structured ACP documentation by manually annotating written documents and forms scanned into the electronic health record. We coded unstructured ACP documentation using a rule-based natural language processing software that identified ACP keywords within clinical notes and was subsequently reviewed for accuracy. The unstructured approach identified more instances of ACP documentation (238, 54.7% of patients) than the structured ACP approach (187, 42.9% of patients). Additionally, 16.6% of all patients with structured ACP documentation only had documents that were judged as misclassified, incomplete, blank, unavailable, or a duplicate of a previously entered erroneous document. ACP documents scanned into electronic health records represent a limited view of ACP activity. Research and measures of clinical practice with ACP should incorporate information from unstructured data.
PubMed: 37536523
DOI: 10.1016/j.jpainsymman.2023.07.016 -
Journal of Medical Internet Research Nov 2022Topic modeling approaches allow researchers to analyze and represent written texts. One of the commonly used approaches in psychology is latent Dirichlet allocation... (Review)
Review
BACKGROUND
Topic modeling approaches allow researchers to analyze and represent written texts. One of the commonly used approaches in psychology is latent Dirichlet allocation (LDA), which is used for rapidly synthesizing patterns of text within "big data," but outputs can be sensitive to decisions made during the analytic pipeline and may not be suitable for certain scenarios such as short texts, and we highlight resources for alternative approaches. This review focuses on the complex analytical practices specific to LDA, which existing practical guides for training LDA models have not addressed.
OBJECTIVE
This scoping review used key analytical steps (data selection, data preprocessing, and data analysis) as a framework to understand the methodological approaches being used in psychology research using LDA.
METHODS
A total of 4 psychology and health databases were searched. Studies were included if they used LDA to analyze written words and focused on a psychological construct or issue. The data charting processes were constructed and employed based on common data selection, preprocessing, and data analysis steps.
RESULTS
A total of 68 studies were included. These studies explored a range of research areas and mostly sourced their data from social media platforms. Although some studies reported on preprocessing and data analysis steps taken, most studies did not provide sufficient detail for reproducibility. Furthermore, the debate surrounding the necessity of certain preprocessing and data analysis steps is revealed.
CONCLUSIONS
Our findings highlight the growing use of LDA in psychological science. However, there is a need to improve analytical reporting standards and identify comprehensive and evidence-based best practice recommendations. To work toward this, we developed an LDA Preferred Reporting Checklist that will allow for consistent documentation of LDA analytic decisions and reproducible research outcomes.
Topics: Humans; Reproducibility of Results; Big Data; Documentation; Databases, Factual
PubMed: 36346659
DOI: 10.2196/33166 -
JCO Clinical Cancer Informatics Feb 2021Lack of interoperability is one of the greatest challenges facing healthcare informatics. Recent interoperability efforts have focused primarily on data transmission and...
Lack of interoperability is one of the greatest challenges facing healthcare informatics. Recent interoperability efforts have focused primarily on data transmission and generally ignore data capture standardization. Structured Data Capture (SDC) is an open-source technical framework that enables the capture and exchange of standardized and structured data in interoperable data entry forms (DEFs) at the point of care. Some of SDC's primary use cases concern complex oncology data such as anatomic pathology, biomarkers, and clinical oncology data collection and reporting. Its interoperability goals are the preservation of semantic, contextual, and structural integrity of the captured data throughout the data's lifespan. SDC documents are written in eXtensible Markup Language (XML) and are therefore computer readable, yet technology agnostic-SDC can be implemented by any EHR vendor or registry. Any SDC-capable system can render an SDC XML file into a DEF, receive and parse an SDC transmission, and regenerate the original SDC form as a DEF or synoptic report with the response data intact. SDC is therefore able to facilitate interoperable data capture and exchange for patient care, clinical trials, cancer surveillance and public health needs, clinical research, and computable care guidelines. The usability of SDC-captured oncology data is enhanced when the SDC data elements are mapped to standard terminologies. For example, an SDC map to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) enables aggregation of SDC data with other related data sets and permits advanced queries and groupings on the basis of SNOMED CT concept attributes and description logic. SDC supports terminology maps using separate map files or as terminology codes embedded in an SDC document.
Topics: Delivery of Health Care; Humans; Medical Oncology; Semantics; Systematized Nomenclature of Medicine
PubMed: 33591796
DOI: 10.1200/CCI.20.00103 -
Bioinformatics (Oxford, England) Oct 2022Transcriptome-based gene co-expression analysis has become a standard procedure for structured and contextualized understanding and comparison of different conditions...
MOTIVATION
Transcriptome-based gene co-expression analysis has become a standard procedure for structured and contextualized understanding and comparison of different conditions and phenotypes. Since large study designs with a broad variety of conditions are costly and laborious, extensive comparisons are hindered when utilizing only a single dataset. Thus, there is an increased need for tools that allow the integration of multiple transcriptomic datasets with subsequent joint analysis, which can provide a more systematic understanding of gene co-expression and co-functionality within and across conditions. To make such an integrative analysis accessible to a wide spectrum of users with differing levels of programming expertise it is essential to provide user-friendliness and customizability as well as thorough documentation.
RESULTS
This article introduces horizontal CoCena (hCoCena: horizontal construction of co-expression networks and analysis), an R-package for network-based co-expression analysis that allows the analysis of a single transcriptomic dataset as well as the joint analysis of multiple datasets. With hCoCena, we provide a freely available, user-friendly and adaptable tool for integrative multi-study or single-study transcriptomics analyses alongside extensive comparisons to other existing tools.
AVAILABILITY AND IMPLEMENTATION
The hCoCena R-package is provided together with R Markdowns that implement an exemplary analysis workflow including extensive documentation and detailed descriptions of data structures and objects. Such efforts not only make the tool easy to use but also enable the seamless integration of user-written scripts and functions into the workflow, creating a tool that provides a clear design while remaining flexible and highly customizable. The package and additional information including an extensive Wiki are freely available on GitHub: https://github.com/MarieOestreich/hCoCena. The version at the time of writing has been added to Zenodo under the following link: https://doi.org/10.5281/zenodo.6911782.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
Topics: Gene Expression Profiling; Phenotype; Software; Transcriptome; Workflow
PubMed: 36018233
DOI: 10.1093/bioinformatics/btac589 -
Journal of Immigrant and Minority Health Feb 2021The medical-legal partnership addresses social and political determinants of health. Yet, relatively little is known about best practices for these two service providers... (Review)
Review
The medical-legal partnership addresses social and political determinants of health. Yet, relatively little is known about best practices for these two service providers collaborating to deliver integrated services, particularly to im/migrant communities. To investigate evaluations of existing medical-legal partnerships in order to understand how they function together, what they provide, and how they define and deliver equitable, integrated care. We searched five databases (PubMed, Medline, Web of Science, HeinOnline, and Nexus Uni) using search terms related to "medical-legal partnerships", "migrants", and "United States". We systematically evaluated ten themes related to how medical and legal teams interacted, were situated, organized, and who they served. Articles were published in English between 2010 and 2019; required discussion about a direct partnership between medical and legal professionals; and focused on providing clinical care and legal services to im/migrant populations. Eighteen articles met our inclusion criteria. The most common form of partnership was a model in which legal clinics make regular referrals to medical clinics, although the reverse was also common. Most services were not co-located. Partnerships often engaged in advocacy work, provided translation services, and referred clients to non-medical providers and legal services. This review demonstrates the benefits of a legal-medical partnership, such as enhancing documentation and care for im/migrants and facilitating a greater attention to political determinants of health. Yet, this review demonstrates that, despite the increasing salience of such partnership, few have written up their lessons learned and best practices.
Topics: Delivery of Health Care; Emigrants and Immigrants; Humans; Legal Services; Transients and Migrants; United States
PubMed: 32978741
DOI: 10.1007/s10903-020-01088-1 -
HCA Healthcare Journal of Medicine 2023Quality improvement (QI) is a major focus of all departments and fields of health care, including emergency medical services. The chaotic and rapidly evolving atmosphere...
INTRODUCTION
Quality improvement (QI) is a major focus of all departments and fields of health care, including emergency medical services. The chaotic and rapidly evolving atmosphere in which paramedics must practice can lead to inconsistency between what is documented and the actual events. This leads to difficulty when trying to evaluate the practitioners and when implementing a QI program. In this study, we evaluated the prevalence of discrepancy between the video and written record for Rapid Sequence Intubation (RSI) performed in the field as a demonstration of the utility of video documentation in QI.
METHODS
We used a systematic retrospective chart review to compare written with video documentation in 100 consecutive prehospital RSI encounters in a single EMS agency.
RESULTS
Of the patient care records (PCRs), only 6% matched the video record for all quality measures tracked. The largest reason for the discrepancy was in the time required to intubate (58%) whether LEMON was evaluated (42%), total number of intubation attempts (36%), first attempt success (24%), BVM used (18%), and whether an airway introducer device was used (12%).
CONCLUSION
Written documentation is inaccurate compared to video documentation when used as a quality improvement process for EMS prehospital RSI encounters.
PubMed: 37753416
DOI: 10.36518/2689-0216.1183