We aimed to create and validate a natural language processing algorithm to extract wound infection-related information from nursing notes. We also estimated wound infection prevalence in homecare settings and described related patient characteristics. In this retrospective cohort study, a natural language processing algorithm was developed and validated against a gold standard testing set. Cases with wound infection were identified using the algorithm and linked to Outcome and Assessment Information Set data to identify related patient characteristics. The final version of the natural language processing vocabulary contained 3914 terms and expressions related to the presence of wound infection. The natural language processing algorithm achieved overall good performance (F-measure = 0.88). The presence of wound infection was documented for 1.03% (n = 602) of patients without wounds, for 5.95% (n = 3232) of patients with wounds, and 19.19% (n = 152) of patients with wound-related hospitalisation or emergency department visits. Diabetes, peripheral vascular disease, and skin ulcer were significantly associated with wound infection among homecare patients. Our findings suggest that nurses frequently document wound infection-related information. The use of natural language processing demonstrated that valuable information can be extracted from nursing notes which can be used to improve our understanding of the care needs of people receiving homecare. By linking findings from clinical nursing notes with additional structured data, we can analyse related patients' characteristics and use them to develop a tailored intervention that may potentially lead to reduced wound infection-related hospitalizations.
Wound infection is prevalent in home healthcare (HHC) and often leads to hospitalizations. However, none of the previous studies of wounds in HHC have used data from clinical notes. Therefore, the authors created a more accurate description of a patient's condition by extracting risk factors from clinical notes to build predictive models to identify a patient's risk of wound infection in HHC.The structured data (eg, standardized assessments) and unstructured information (eg, narrative-free text charting) were retrospectively reviewed for HHC patients with wounds who were served by a large HHC agency in 2014. Wound infection risk factors were identified through bivariate analysis and stepwise variable selection. Risk predictive performance of three machine learning models (logistic regression, random forest, and artificial neural network) was compared.A total of 754 of 54,316 patients (1.39%) had a hospitalization or ED visit related to wound infection. In the bivariate logistic regression, language describing wound type in the patient's clinical notes was strongly associated with risk (odds ratio, 9.94; P < .05). The areas under the curve were 0.82 in logistic regression, 0.75 in random forest, and 0.78 in artificial neural network. Risk prediction performance of the models improved (by up to 13.2%) after adding risk factors extracted from clinical notes.Logistic regression showed the best risk prediction performance in prediction of wound infection-related hospitalization or ED visits in HHC. The use of data extracted from clinical notes can improve the performance of risk prediction models.
Abstract Purpose The study purpose was to compare dissemination of PhD dissertation research by dissertation format: traditional (five‐chapter document providing a complete and systematic account of the PhD research) versus an alternate (substudy [document containing three smaller studies but not written as stand‐alone manuscripts] or publication [document containing three or more related manuscripts intended for submission or published in a peer‐reviewed journal]) format. Design A retrospective study of all PhD dissertations (1999–2019) from one research intensive school of nursing. Methods Following identification of graduates via the school's PhD database, we searched ProQuest and PubMed databases for the dissertation and first authored peer‐reviewed publications of each graduate to determine dissertation format, study design, timing and number of dissertation research publications, and inclusion of dissertation sponsor in authorship. Data were analyzed using descriptive statistics and Wilcoxon rank sum tests. Findings Of 113 graduates, 80 (70.8%) employed a traditional format, with the remaining graduates structuring dissertations using an alternate (substudy [ n = 12], publication [ n = 21]) format. Of those using the traditional format, 33 graduates (41.3%) never published dissertation research findings in a peer‐reviewed journal. For those who published their dissertation research in a peer‐reviewed journal, time to first publication was 1.4 ± 2.1 years (median 1.6 years) following degree conferral. In contrast, all graduates who utilized alternate formats published one or more components of their dissertation research with shorter time to first published manuscript (‐0.6 ± 1.1 years; median ‐0.5 years; p < .001). Number of peer‐reviewed publications was higher for those who utilized an alternate format compared to the traditional format (2.9 ± 1.5 [median 3.0] vs. 1.8 ± 1.1 [median 1.0], p = .001). Acknowledgment of the sponsor's contribution via publication authorship was higher for those using an alternate format compared to the traditional format (100% vs. 70.2%). Conclusions Number and timeliness of peer‐reviewed publications stemming from dissertation research was higher for PhD graduates who utilized an alternate dissertation format. Alternate dissertation formats should be encouraged by PhD programs as one means to improve dissemination of PhD nursing research. Clinical Relevance Dissemination of PhD research through peer‐reviewed publications promotes the continued development of nursing science to inform nursing practice and advances the career trajectory of PhD graduates.
Objectives: This study is a descriptive research study to identify factors affecting the proficiency of core basic nursing skills of 3rd and 4th year nursing students. This study was conducted to use as evidence data for an intervention study to increase the proficiency of core basic nursing skills of nursing students. Methods: The subjects of this study were 184 people in the 3rd and 4th years of the nursing department at a university located in K city. They voluntarily agreed to participate in this study and filled a structured questionnaire provided. The questionnaire includes general characteristics, problem-solving ability, and proficiency in core basic nursing skills. The collected data were analyzed using descriptive statistics, t-test, one-way ANOVA, Schéffe test, Pearson's correlation coefficients, and multiple regression using the SPSS WIN 18.0 program. Results: It was found that the higher the grade, the higher the problem-solving ability, the higher the mastery of core basic nursing skills. Conclusion: In order to improve the proficiency of core basic nursing skills of nursing students, it is necessary to continuously provide opportunities for education and practice of core basic nursing skills and the application of educational content to continuously improve problem-solving skills from the lower grades.
ABSTRACT Background Improving care quality while reducing cost has always been a focus of nursing homes. Certified nursing assistants comprise the largest proportion of the workforce in nursing homes and have the potential to contribute to the quality of care provided. Quality improvement (QI) initiatives using certified nursing assistants as champions have the potential to improve job satisfaction, which has been associated with care quality. Aims To identify the role, use and preparation of champions in a nursing home setting as a way of informing future QI strategies in nursing homes. Methods A systematic literature review. Medical Subject Headings and text words for “quality improvement” were combined with those for “champion*” to search Medline, CINAHL, Joanna Briggs Institute, MedLine In‐Process, and other Nonindexed Citations. After duplicates were removed, a total of 337 potential articles were identified for further review. After full text review, seven articles from five original studies met inclusion criteria and were included in the synthesis. Results Various types of QI initiatives and implementation strategies were used together with champions. Champions were identified by study authors as one of the single most effective strategies employed in all studies. The majority of studies described the champion role as that of a leader, who fosters and reinforces changes for improvement. Although all the included studies suggested that implementing nurse or aid champions in their QI initiatives were important facilitators of success, how the champions were selected and trained in their role is either missing or not described in any detail in the studies included in the review. Linking Evidence to Action Utilizing certified nursing assistants as QI champions can increase participation in QI projects and has the potential to improve job satisfaction and contribute to improve quality of care and improved patient outcomes in nursing homes.
Abstract Background In most of developed societies, the prevalence of informal care is on the rise due to rapid population ageing. This study investigates longitudinal associations between informal caregiving and health among caregivers and potential gender differences in this relationship. Moreover, drawing on the Health Promotion Model, this study examines the mediating role of health promoting behaviors in the link between informal caregiving and caregiver’s health. Methods Seven waves of a large-scale ( N = 9,608), a nationally representative longitudinal study of middle- and old-aged adults in Korea between 2006 and 2018, were used. To address the possibility of omitted variable bias, this study employed ordinary least squares models with lagged dependent variables (OLS-LDV) as well as fixed effects (FE) models. Univariate Sobel-Goodman mediation tests were used. Results Findings from OLS-LDV models showed that transition into informal caregiving is negatively associated with health satisfaction and self-rated health. FE results also suggest that our results are robust to controlling for unobserved heterogeneity. In the model where informal caregiving is interacted with gender, we found that these associations were largely driven by women caregivers. Results from Sobel-Goodman tests revealed that a decrease in regular exercise partially explains the observed association between informal caregiving and subjective health outcomes (11% for health satisfaction and 8% for self-rated health). Conclusions Although informal caregiving can be a rewarding role, it poses a threat to caregiver’s subjective health. Findings of this hold important implications and provide evidence in support of a gender-conscious approach to improve the health and well-being of informal caregivers.
Telehealth has been reported to be effective in helping patients with heart failure manage their symptoms at home. Despite this, the adoption rate for telehealth among home care patients with heart failure is low, and there is limited research on reasons for this. This study was undertaken to explore factors associated with patients' decisions to adopt telehealth at home. A qualitative descriptive study underpinned by the Unified Theory of Acceptance Use of Technology model was conducted using semi-structured telephone interviews with patients with heart failure (N = 20) referred for telehealth. Interviews were analyzed using a mixture of deductive and inductive coding. Among the theoretical model elements, the perceived usefulness of the technology (performance expectancy), the availability of clinical/technical support (facilitating conditions), and the opinion of other individuals important to the patient (social influence) were associated with telehealth initiation. However, the ease of use (effort expectancy) was not an associated factor. Other factors such as experience, knowledge, confidence, satisfaction, and attitudes were also associated with the decision. Identification of factors related to higher telehealth initiation rates can be used to inform individualized care planning by nurses. Knowledge of such associations can inform referral process to improve the efficiency and utilization of telehealth.
Although the potential of natural language processing and an increase in its application in nursing research is evident, there is a lack of understanding of the research trends. This study conducts text network analysis and topic modeling to uncover the underlying knowledge structures, research trends, and emergent research themes within nursing literature related to natural language processing. In addition, this study aims to provide a foundation for future scholarly inquiries and enhance the integration of natural language processing in the analysis of nursing research. We analyzed 443 literature abstracts and performed core keyword analysis and topic modeling based on frequency and centrality. The following topics emerged: (1) Term Identification and Communication; (2) Application of Machine Learning; (3) Exploration of Health Outcome Factors; (4) Intervention and Participant Experience; and (5) Disease-Related Algorithms. Nursing meta-paradigm elements were identified within the core keyword analysis, which led to understanding and expanding the meta-paradigm. Although still in its infancy in nursing research with limited topics and research volumes, natural language processing can potentially enhance research efficiency and nursing quality. The findings emphasize the possibility of integrating natural language processing in nursing-related subjects, validating nursing value, and fostering the exploration of essential paradigms in nursing science.
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