-
Journal of Clinical Nursing Jul 2023To describe the quality of information coming from previous care units to palliative care.
AIMS AND OBJECTIVES
To describe the quality of information coming from previous care units to palliative care.
BACKGROUND
Information quality is an interconnected concept that includes different dimensions and can be viewed from different perspectives. More knowledge is needed from a multi-professional perspective on the information quality coming to palliative care.
DESIGN
Descriptive qualitative study.
METHODS
Altogether 33 registered nurses, practical nurses, social workers and physicians working in palliative care were purposively selected to participate in thematic interviews. The research was carried out in six palliative care units in three hospital districts. The data were analysed by using deductive and inductive content analysis. The COREQ checklist was used.
RESULTS
Three main categories with thirteen categories were identified in connection with the deductive analysis based on the Clinical Information Quality framework: (1). Informativeness of information coming from previous care units to palliative care included accuracy, completeness, interpretability, plausibility, provenance and relevance. (2). Availability of information coming from previous care units to palliative care included accessibility, portability, security and timeliness. (3). Usability of information coming from previous care units to palliative care included conformance, consistency and maintainability. Each category is divided into sub-categories followed by narratives of their content.
CONCLUSIONS
This study provides new knowledge on the quality of information coming to palliative care from a multi-professional perspective. Professionals working in palliative care units highlight issues describing good information quality, but also point out quality issues and areas for improvement.
RELEVANCE TO CLINICAL PRACTICE
The results can guide the development of documentation practices and Health Information System development as well as be used in the generation of a new audit instrument of information quality.
Topics: Humans; Palliative Care; Hospice and Palliative Care Nursing; Qualitative Research; Physicians; Narration
PubMed: 35844084
DOI: 10.1111/jocn.16453 -
Animals : An Open Access Journal From... Jun 2023The illegal wildlife trade is a significant threat to global biodiversity, often targeting already threatened species. In combating the trade, it is critical to know the...
The illegal wildlife trade is a significant threat to global biodiversity, often targeting already threatened species. In combating the trade, it is critical to know the provenance of the traded animal or part to facilitate targeted conservation actions, such as education and enforcement. Here, we present and compare two methods, portable X-ray fluorescence (pXRF) and stable isotope analysis (SIA), to determine both the geographic and source provenance (captive or wild) of traded animals and their parts. Using three critically endangered, frequently illegally traded Philippine species, the Palawan forest turtle (), the Philippine cockatoo (), and the Philippine pangolin (), we demonstrate that using these methods, we can more accurately assign provenance using pXRF data (x¯ = 83%) than SIA data (x¯ = 47%). Our results indicate that these methods provide a valuable forensic tool that can be used in combating the illegal wildlife trade.
PubMed: 37443963
DOI: 10.3390/ani13132165 -
Nature Communications Jul 2023Significant challenges remain in the computational processing of data from liquid chomratography-mass spectrometry (LC-MS)-based metabolomic experiments into metabolite...
Significant challenges remain in the computational processing of data from liquid chomratography-mass spectrometry (LC-MS)-based metabolomic experiments into metabolite features. In this study, we examine the issues of provenance and reproducibility using the current software tools. Inconsistency among the tools examined is attributed to the deficiencies of mass alignment and controls of feature quality. To address these issues, we develop the open-source software tool asari for LC-MS metabolomics data processing. Asari is designed with a set of specific algorithmic framework and data structures, and all steps are explicitly trackable. Asari compares favorably to other tools in feature detection and quantification. It offers substantial improvement in computational performance over current tools, and it is highly scalable.
Topics: Chromatography, Liquid; Reproducibility of Results; Tandem Mass Spectrometry; Metabolomics
PubMed: 37433854
DOI: 10.1038/s41467-023-39889-1 -
Journal of Medical Internet Research Nov 2023In the context of the Medical Informatics Initiative, medical data integration centers (DICs) have implemented complex data flows to transfer routine health care data...
BACKGROUND
In the context of the Medical Informatics Initiative, medical data integration centers (DICs) have implemented complex data flows to transfer routine health care data into research data repositories for secondary use. Data management practices are of importance throughout these processes, and special attention should be given to provenance aspects. Insufficient knowledge can lead to validity risks and reduce the confidence and quality of the processed data. The need to implement maintainable data management practices is undisputed, but there is a great lack of clarity on the status.
OBJECTIVE
Our study examines the current data management practices throughout the data life cycle within the Medical Informatics in Research and Care in University Medicine (MIRACUM) consortium. We present a framework for the maturity status of data management practices and present recommendations to enable a trustful dissemination and reuse of routine health care data.
METHODS
In this mixed methods study, we conducted semistructured interviews with stakeholders from 10 DICs between July and September 2021. We used a self-designed questionnaire that we tailored to the MIRACUM DICs, to collect qualitative and quantitative data. Our study method is compliant with the Good Reporting of a Mixed Methods Study (GRAMMS) checklist.
RESULTS
Our study provides insights into the data management practices at the MIRACUM DICs. We identify several traceability issues that can be partially explained with a lack of contextual information within nonharmonized workflow steps, unclear responsibilities, missing or incomplete data elements, and incomplete information about the computational environment information. Based on the identified shortcomings, we suggest a data management maturity framework to reach more clarity and to help define enhanced data management strategies.
CONCLUSIONS
The data management maturity framework supports the production and dissemination of accurate and provenance-enriched data for secondary use. Our work serves as a catalyst for the derivation of an overarching data management strategy, abiding data integrity and provenance characteristics as key factors. We envision that this work will lead to the generation of fairer and maintained health research data of high quality.
Topics: Humans; Data Management; Delivery of Health Care; Medical Informatics; Surveys and Questionnaires
PubMed: 37938878
DOI: 10.2196/48809 -
ArXiv Aug 2023The prevalence of machine learning in biomedical research is rapidly growing, yet the trustworthiness of such research is often overlooked. While some previous works...
The prevalence of machine learning in biomedical research is rapidly growing, yet the trustworthiness of such research is often overlooked. While some previous works have investigated the ability of adversarial attacks to degrade model performance in medical imaging, the ability to falsely improve performance via recently-developed "enhancement attacks" may be a greater threat to biomedical machine learning. In the spirit of developing attacks to better understand trustworthiness, we developed two techniques to drastically enhance prediction performance of classifiers with minimal changes to features: 1) general enhancement of prediction performance, and 2) enhancement of a particular method over another. Our enhancement framework falsely improved classifiers' accuracy from 50% to almost 100% while maintaining high feature similarities between original and enhanced data (Pearson's ' > 0.99). Similarly, the method-specific enhancement framework was effective in falsely improving the performance of one method over another. For example, a simple neural network outperformed logistic regression by 17% on our enhanced dataset, although no performance differences were present in the original dataset. Crucially, the original and enhanced data were still similar ( = 0.99). Our results demonstrate the feasibility of minor data manipulations to achieve any desired prediction performance, which presents an interesting ethical challenge for the future of biomedical machine learning. These findings emphasize the need for more robust data provenance tracking and other precautionary measures to ensure the integrity of biomedical machine learning research. Code is available at https://github.com/mattrosenblatt7/enhancement_EPIMI.
PubMed: 36713237
DOI: No ID Found -
PloS One 2024This study, conducted in China in November 2020, was aimed at exploring the variations in growth traits among different provenances and families as well as to select...
This study, conducted in China in November 2020, was aimed at exploring the variations in growth traits among different provenances and families as well as to select elite materials of Juglans mandshurica. Thus, seeds of 44 families from six J. mandshurica provenances in Heilongjiang and Jilin provinces were sown in the nursery and then transplanted out in the field. At the age of 5 years, seven growth traits were assessed, and a comprehensive analysis was conducted as well as selection of provenance and families. Analysis of variance revealed statistically significant (P < 0.01) differences in seven growth traits among different provenances and families, thereby justifying the pursuit of further breeding endeavors. The genetic coefficient of variation (GCV) for all traits ranged from 5.44% (branch angle) to 21.95% (tree height) whereas the phenotypic coefficient of variation (PCV) ranged from 13.74% (tapering) to 38.50% (branch number per node), indicating considerable variability across the traits. Further, all the studied traits except stem straightness degree, branch angle and branch number per node, showed high heritability (Tree height, ground diameter, mean crown width and tapering, over 0.7±0.073), indicating that the variation in these traits is primarily driven by genetic factors. Correlation analysis revealed a strong positive correlation (r > 0.8) between tree height and ground diameter (r = 0.86), tree height and mean crown width (r = 0.82), and ground diameter and mean crown width (r = 0.83). This suggests that these relationships can be employed for more precise predictions of the growth and morphological characteristics of trees, as well as the selection of superior materials. There was a strong correlation between temperature factors and growth traits. Based on the comprehensive scores in this study, Sanchazi was selected as elite provenance. Using the top-percentile selection criteria, SC1, SC8, DJC15, and DQ18 were selected as elite families. These selected families exhibit genetic gains of over 10% in tree height, ground diameter and mean crown width, signifying their significant potential in forestry for enhancing timber production and reducing production cycles, thereby contributing to sustainable forest management. In this study, the growth traits of J. mandshurica were found to exhibit stable variation, and there were correlations between these traits. The selected elite provenance and families of J. mandshurica showed faster growth, which is advantageous for the subsequent breeding and promotion of improved J. mandshurica varieties.
Topics: Juglans; Plant Breeding; Trees; Forests; China
PubMed: 38451964
DOI: 10.1371/journal.pone.0298918 -
Archives of Orthopaedic and Trauma... Jul 2023In older people, hip fracture can lead to adverse outcomes. Frailty, capturing biological age and vulnerability to stressors, can indicate those at higher risk. We...
INTRODUCTION
In older people, hip fracture can lead to adverse outcomes. Frailty, capturing biological age and vulnerability to stressors, can indicate those at higher risk. We derived a frailty index (FI) in the Irish Hip Fracture Database (IHFD) and explored associations with prolonged length of hospital stay (LOS ≥ 30 days), delirium, inpatient mortality and new nursing home admission. We assessed whether the FI predicted those outcomes independently of age, sex and pre-operative American Society of Anaesthesiology (ASA) score.
MATERIALS AND METHODS
A 21-item FI was constructed with 17 dichotomous co-morbidities, three 4-level ordinal pre-morbid functional variables (difficulty with indoor mobility, outdoor mobility, and shopping) and nursing home provenance (yes/no). The FI was computed as the proportion of items present and divided into tertiles (low, medium, high risk). Independent associations between FI and outcomes were explored with logistic regression, from which we extracted adjusted Odds Ratios (aOR) and Areas Under the Curve (AUC).
RESULTS
From 2017 to 2020, the IHFD included 14,615 hip fracture admissions, mean (SD) age 80.4 (8.8), 68.9% women. Complete FI data were available for 12,502 (85.5%). By FI tertile (low to high risk), prolonged LOS proportions were 5.9%, 16.1% and 23.1%; delirium 5.5%, 13.5% and 17.6%; inpatient mortality 0.6%, 3.3% and 10.1%; and new nursing home admission 2.2%, 5.9% and 11.3%. All associations were statistically significant (p < 0.001) independently of age and sex. AUC analyses showed that the FI score, added to age, sex, and ASA score, significantly improved the prediction of delirium and new nursing home admission (p < 0.05), and especially prolonged LOS and inpatient mortality (p < 0.001).
CONCLUSIONS
A 21-item FI in the IHFD was a significant predictor of outcomes and added value to traditional risk markers. The utility of a routinely derived FI to more effectively direct limited orthogeriatric resources requires prospective investigation.
Topics: Humans; Female; Aged; Aged, 80 and over; Male; Frailty; Frail Elderly; Prospective Studies; Hospitalization; Hip Fractures; Risk Factors; Delirium; Geriatric Assessment
PubMed: 36210379
DOI: 10.1007/s00402-022-04644-6 -
Pragmatic and Observational Research 2023Real-world evidence (RWE) is being used to provide information on diverse groups of patients who may be highly impacted by disease but are not typically studied in... (Review)
Review
Real-world evidence (RWE) is being used to provide information on diverse groups of patients who may be highly impacted by disease but are not typically studied in traditional randomized clinical trials (RCT) and to obtain insights from everyday care settings and real-world adherence to inform clinical practice. RWE is derived from so-called real-world data (RWD), ie, information generated by clinicians in the course of everyday patient care, and is sometimes coupled with systematic input from patients in the form of patient-reported outcomes or from wearable biosensors. Studies using RWD are conducted to evaluate how well medical interventions, services, and diagnostics perform under conditions of real-world use, and may include long-term follow-up. Here, we describe the main types of studies used to generate RWE and offer pointers for clinicians interested in study design and execution. Our tactical guidance addresses (1) opportunistic study designs, (2) considerations about representativeness of study participants, (3) expectations for transparency about data provenance, handling and quality assessments, and (4) considerations for strengthening studies using record linkage and/or randomization in pragmatic clinical trials. We also discuss likely sources of bias and suggest mitigation strategies. We see a future where clinical records - patient-generated data and other RWD - are brought together and harnessed by robust study design with efficient data capture and strong data curation. Traditional RCT will remain the mainstay of drug development, but RWE will play a growing role in clinical, regulatory, and payer decision-making. The most meaningful RWE will come from collaboration with astute clinicians with deep practice experience and questioning minds working closely with patients and researchers experienced in the development of RWE.
PubMed: 37786592
DOI: 10.2147/POR.S396024 -
Blockchain in Healthcare Today 2023Blockchain technology is a radical innovation with the potential to disrupt and re-imagine more collaborative established business structures and processes. Significant... (Review)
Review
UNLABELLED
Blockchain technology is a radical innovation with the potential to disrupt and re-imagine more collaborative established business structures and processes. Significant advances, particularly in the payments space, include newer, faster, and less costly options for moving money. The underlying blockchain technology can be used for broader use cases spanning several verticals, including healthcare - although its adoption here is less than complete. Numerous proofs-of-concept and pilots have been executed and are increasing, although enterprise blockchain applications in healthcare at the production scale enabling transformative constituent processes are limited. In this article, the authors analyze the blockchain in healthcare literature for critical success factors and add practitioner views on crossing the chasm from proof-of-concept and pilots to a transformational scale. We explore 24 articles for key inflections for scale and highlight the need for a multifaceted execution framework to resolve the practical barriers to enabling reimagined network-based blockchain use cases for efficiencies, particularly in disparate health systems such as the U.S. In addition, we introduce the blockchain discovery framework to make this emerging technology meet the mainstream operations at scale systematically and in a stair-stepped and future-proofed manner, addressing practical stakeholder concerns. Finally, the authors present a reference case study discovered through the framework of one such healthcare administrative process for a scaled reimagined implementation. Healthcare executives and portfolio managers will benefit from these insights and help to increase the enterprise adoption of this inevitable technology of the future.
PLAN LANGUAGE SUMMARY
This article presents a practitioner's view of operating in emerging technology, exploring and advancing blockchain-based transformation in healthcare. Blockchain technology is maturing quickly, with financial technology (aka fintech) leading the way with efficient options for moving money, particularly in the public permissionless blockchain segment. The underlying technology allows for a broader set of capabilities, including provenance, data sharing, immutability, non-repudiation, and auditability, which provides for complete rethinking of existing business processes. These features can help to reimagine a more comprehensive set of use cases in many disciplines, including healthcare. However, enterprise adoption needs to catch up.
PubMed: 38187959
DOI: 10.30953/bhty.v6.280 -
Journal of Chemical Information and... Nov 2023Web ontologies are important tools in modern scientific research because they provide a standardized way to represent and manage web-scale amounts of complex data. In...
Web ontologies are important tools in modern scientific research because they provide a standardized way to represent and manage web-scale amounts of complex data. In chemistry, a semantic database for chemical species is indispensable for its ability to interrelate and infer relationships, enabling a more precise analysis and prediction of chemical behavior. This paper presents OntoSpecies, a web ontology designed to represent chemical species and their properties. The ontology serves as a core component of The World Avatar knowledge graph chemistry domain and includes a wide range of identifiers, chemical and physical properties, chemical classifications and applications, and spectral information associated with each species. The ontology includes provenance and attribution metadata, ensuring the reliability and traceability of data. Most of the information about chemical species are sourced from PubChem and ChEBI data on the respective compound Web pages using a software agent, making OntoSpecies a comprehensive semantic database of chemical species able to solve novel types of problems in the field. Access to this reliable source of chemical data is provided through a SPARQL end point. The paper presents example use cases to demonstrate the contribution of OntoSpecies in solving complex tasks that require integrated semantically searchable chemical data. The approach presented in this paper represents a significant advancement in the field of chemical data management, offering a powerful tool for representing, navigating, and analyzing chemical information to support scientific research.
Topics: Knowledge Discovery; Reproducibility of Results; Software; Databases, Factual; Semantics
PubMed: 37883649
DOI: 10.1021/acs.jcim.3c00820