Community stakeholder-driven technology solutions towards rural health equity: A concept mapping study in Western Canada.

BACKGROUND: Technology holds great potential for promoting health equity for rural populations, who have more chronic illnesses than their urban counterparts but less access to services. Yet, more participatory research approaches are needed to gather community-driven health technology solutions. The purpose was to collaboratively identify and prioritize action strategies for using technology to promote rural health equity through community stakeholder engagement. METHODS: Concept mapping, a quantitative statistical technique, embedded within a qualitative approach, was used to identify and integrate technological solutions towards rural health equity from community stakeholders in three steps: (1) idea generation; (2) sorting and rating feasibility/importance and (3) group interpretation. Purposeful recruitment strategies were used to recruit key stakeholders and organizational representatives from targeted rural communities. RESULTS: Overall, 34 rural community stakeholders from western Canada (76% female, mean age = 55.4 years) participated in the concept mapping process. In Step 1, 84 ideas were generated that were reduced to a pool of 30. Multidimensional scaling and cluster analysis resulted in a six-cluster map representing how technological solutions can contribute toward rural health equity. The clusters of ideas included technological solutions and applications, but also ideas to make health care more accessible regardless of location, training and support in the use of technology, ensuring digital tools are simplified for ease of use, technologies to support collaboration among healthcare professionals and ideas for overcoming challenges to data sharing across health systems/networks. Each cluster included ideas that were rated as equally important and feasible. Key themes included organizational and individual-level solutions and connecting patients to newly developed technologies. CONCLUSIONS: Overall, the grouping of solutions revealed that technological applications require not only access but also support and collaboration. Concept mapping is a tool that can engage rural community stakeholders in the identification of technological solutions for promoting rural health equity. PATIENT OR PUBLIC CONTRIBUTION: Rural community stakeholders were involved in the generation and interpretation of technological solutions towards rural health equity in a three-step process: (1) individual brainstorming of ideas, (2) sorting and rating all ideas generated and (3) collective interpretation and group consensus on final results.

Internet access is a necessity: a latent class analysis of COVID-19 related challenges and the role of technology use among rural community residents.

BACKGROUND: Rural and remote communities faced unique access challenges to essential services such as healthcare and highspeed infrastructure pre-COVID, which have been amplified by the pandemic. This study examined patterns of COVID-related challenges and the use of technology among rural-living individuals during the first wave of the COVID-19 pandemic. METHODS: A sample of 279 rural residents completed an online survey about the impact of COVID-related challenges and the role of technology use. Latent class analysis was used to generate subgroups reflecting the patterns of COVID-related challenges. Differences in group membership were examined based on age, gender, education, race/ethnicity, and living situation. Finally, thematic analysis of open-ended qualitative responses was conducted to further contextualize the challenges experienced by rural-living residents. RESULTS: Four distinct COVID challenge impact subgroups were identified: 1) Social challenges (35%), 2) Social and Health challenges (31%), 3) Social and Financial challenges (14%), and 4) Social, Health, Financial, and Daily Living challenges (19%). Older adults were more likely to be in the Social challenges or Social and Health challenges groups as compared to young adults who were more likely to be in the Social, Health, Financial, and Daily Living challenges group. Additionally, although participants were using technology more frequently during the COVID-19 pandemic to address challenges, they were also reporting issues with quality and connectivity as a significant barrier. CONCLUSIONS: These analyses found four different patterns of impact related to social, health, financial, and daily living challenges in the context of COVID. Social needs were evident across the four groups; however, we also found nearly 1 in 5 rural-living individuals were impacted by an array of challenges. Access to reliable internet and devices has the potential to support individuals to manage these challenges.

Exploring prevalence of wound infections and related patient characteristics in homecare using natural language processing.

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.

Use of Asynchronous Virtual Mental Health Resources for COVID-19 Pandemic-Related Stress Among the General Population in Canada: Cross-Sectional Survey Study.

BACKGROUND: The COVID-19 pandemic has resulted in profound mental health impacts among the general population worldwide. As many in-person mental health support services have been suspended or transitioned online to facilitate physical distancing, there have been numerous calls for the rapid expansion of asynchronous virtual mental health (AVMH) resources. These AVMH resources have great potential to provide support for people coping with negative mental health impacts associated with the pandemic; however, literature examining use prior to COVID-19 illustrates that the uptake of these resources is consistently low. OBJECTIVE: The aim of this paper is to examine the use of AVMH resources in Canada during the COVID-19 pandemic among the general population and among a participant subgroup classified as experiencing an adverse mental health impact related to the pandemic. METHODS: Data from this study were drawn from the first wave of a large multiwave cross-sectional monitoring survey, distributed from May 14 to 29, 2020. Participants (N=3000) were adults living in Canada. Descriptive statistics were used to characterize the sample, and bivariate cross-tabulations were used to examine the relationships between the use of AVMH resources and self-reported indicators of mental health that included a range of emotional and coping-related responses to the pandemic. Univariate and fully adjusted multivariate logistic regression models were used to examine associations between sociodemographic and health-related characteristics and use of AVMH resources in the subgroup of participants who reported experiencing one or more adverse mental health impacts identified in the set of self-reported mental health indicators. RESULTS: Among the total sample, 2.0% (n=59) of participants reported accessing AVMH resources in the prior 2 weeks to cope with stress related to the COVID-19 pandemic, with the highest rates of use among individuals who reported self-harm (n=5, 10.4%) and those who reported coping "not well" with COVID-19-related stress (n=22, 5.5%). Within the subgroup of 1954 participants (65.1% of the total sample) who reported an adverse mental health impact related to COVID-19, 54 (2.8%) reported use of AVMH resources. Individuals were more likely to have used AVMH resources if they had reported receiving in-person mental health supports, were connecting virtually with a mental health worker or counselor, or belonged to a visible minority group. CONCLUSIONS: Despite substantial government investment into AVMH resources, uptake is low among both the general population and individuals who may benefit from the use of these resources as a means of coping with the adverse mental health impacts of the COVID-19 pandemic. Further research is needed to improve our understanding of the barriers to use.

Leveraging Nurses to Improve Care for Patients with Concurrent Disorders in Inpatient Mental Health Settings: A Scoping Review.

Objective: Several challenges have been identified for patients with concurrent disorders and the providers that care for them, contributing to a pressing need for interventions to improve outcomes, particularly within inpatient mental health settings. Methods: A systematic search of peer-reviewed literature was conducted using four online databases: CINAHL, MEDLINE (Ovid), PsycInfo and Web of Science. Articles were selected based on inclusion criteria and additional articles were identified through hand searches. Study details were charted and qualitative synthesis was conducted. Results: Thirty two articles met inclusion criteria. A substantial focus within the literature was education, with higher levels of education shown to improve healthcare provider attitudes and practices. Within this overarching focus, four themes were identified: 1) education as an intervention to improve attitudes and increase confidence and knowledge; 2) strategies to support practice change, including interventions aimed at clinical leaders and methods to address substance use among inpatients; 3) frameworks to guide care; and 4) opportunities to expand nursing scope of practice. Conclusions: Given the substantial evidence indicating that education improves nurses' knowledge, attitudes and practices, there is great promise in expanding educational intervention opportunities for nurses to improve care and outcomes for patients with concurrent disorders-a priority patient population.

Visibility of Community Nursing Within an Administrative Health Classification System: Evaluation of Content Coverage.

BACKGROUND: The World Health Organization is in the process of developing an international administrative classification for health called the International Classification of Health Interventions (ICHI). The purpose of ICHI is to provide a tool for supporting intervention reporting and analysis at a global level for policy development and beyond. Nurses represent the largest resource carrying out clinical interventions in any health system. With the shift in nursing care from hospital to community settings in many countries, it is important to ensure that community nursing interventions are present in any international health information system. Thus, an investigation into the extent to which community nursing interventions were covered in ICHI was needed. OBJECTIVE: The objectives of this study were to examine the extent to which International Classification for Nursing Practice (ICNP) community nursing interventions were represented in the ICHI administrative classification system, to identify themes related to gaps in coverage, and to support continued advancements in understanding the complexities of knowledge representation in standardized clinical terminologies and classifications. METHODS: This descriptive study used a content mapping approach in 2 phases in 2018. A total of 187 nursing intervention codes were extracted from the ICNP Community Nursing Catalogue and mapped to ICHI. In phase 1, 2 coders completed independent mapping activities. In phase 2, the 2 coders compared each list and discussed concept matches until consensus on ICNP-ICHI match and on mapping relationship was reached. RESULTS: The initial percentage agreement between the 2 coders was 47% (n=88), but reached 100% with consensus processes. After consensus was reached, 151 (81%) of the community nursing interventions resulted in an ICHI match. A total of 36 (19%) of community nursing interventions had no match to ICHI content. A total of 100 (53%) community nursing interventions resulted in a broader ICHI code, 9 (5%) resulted in a narrower ICHI code, and 42 (23%) were considered equivalent. ICNP concepts that were not represented in ICHI were thematically grouped into the categories family and caregivers, death and dying, and case management. CONCLUSIONS: Overall, the content mapping yielded similar results to other content mapping studies in nursing. However, it also found areas of missing concept coverage, difficulties with interterminology mapping, and further need to develop mapping methods.

Nurses "Seeing Forest for the Trees" in the Age of Machine Learning: Using Nursing Knowledge to Improve Relevance and Performance.

Although machine learning is increasingly being applied to support clinical decision making, there is a significant gap in understanding what it is and how nurses should adopt it in practice. The purpose of this case study is to show how one application of machine learning may support nursing work and to discuss how nurses can contribute to improving its relevance and performance. Using data from 130 specialized hospitals with 101 766 patients with diabetes, we applied various advanced statistical methods (known as machine learning algorithms) to predict early readmission. The best-performing machine learning algorithm showed modest predictive ability with opportunities for improvement. Nurses can contribute to machine learning algorithms by (1) filling data gaps with nursing-relevant data that provide personalized context about the patient, (2) improving data preprocessing techniques, and (3) evaluating potential value in practice. These findings suggest that nurses need to further process the information provided by machine learning and apply "Wisdom-in-Action" to make appropriate clinical decisions. Nurses play a pivotal role in ensuring that machine learning algorithms are shaped by their unique knowledge of each patient's personalized context. By combining machine learning with unique nursing knowledge, nurses can provide more visibility to nursing work, advance nursing science, and better individualize patient care. Therefore, to successfully integrate and maximize the benefits of machine learning, nurses must fully participate in its development, implementation, and evaluation.

A tailored online safety and health intervention for women experiencing intimate partner violence: the iCAN Plan 4 Safety randomized controlled trial protocol.

BACKGROUND: Intimate partner violence (IPV) threatens the safety and health of women worldwide. Safety planning is a widely recommended, evidence-based intervention for women experiencing IPV, yet fewer than 1 in 5 Canadian women access safety planning through domestic violence services. Rural, Indigenous, racialized, and immigrant women, those who prioritize their privacy, and/or women who have partners other than men, face unique safety risks and access barriers. Online IPV interventions tailored to the unique features of women's lives, and to maximize choice and control, have potential to reduce access barriers, and improve fit and inclusiveness, maximizing effectiveness of these interventions for diverse groups. METHODS/DESIGN: In this double blind randomized controlled trial, 450 Canadian women who have experienced IPV in the previous 6 months will be randomized to either a tailored, interactive online safety and health intervention (iCAN Plan 4 Safety) or general online safety information (usual care). iCAN engages women in activities designed to increase their awareness of safety risks, reflect on their plans for their relationships and priorities, and create a personalize action plan of strategies and resources for addressing their safety and health concerns. Self-reported outcome measures will be collected at baseline and 3, 6, and 12 months post-baseline. Primary outcomes are depressive symptoms (Center for Epidemiological Studies Depression Scale, Revised) and PTSD Symptoms (PTSD Checklist, Civilian Version). Secondary outcomes include helpful safety actions, safety planning self-efficacy, mastery, and decisional conflict. In-depth qualitative interviews with approximately 60 women who have completed the trial and website utilization data will be used to explore women's engagement with the intervention and processes of change. DISCUSSION: This trial will contribute timely evidence about the effectiveness of online safety and health interventions appropriate for diverse life contexts. If effective, iCAN could be readily adopted by health and social services and/or accessed by women to work through options independently. This study will produce contextualized knowledge about how women engage with the intervention; its strengths and weaknesses; whether specific groups benefit more than others; and the processes explaining any positive outcomes. Such information is critical for effective scale up of any complex intervention. TRIAL REGISTRATION: Clinicaltrials.gov ID NCT02258841 (Registered on Oct 2, 2014).

Evaluation of QuitNow Men: An Online, Men-Centered Smoking Cessation Intervention.

BACKGROUND: Men continue to smoke cigarettes in greater numbers than women. There is growing evidence for the value of developing targeted, men-centered health promotion programs. However, few smoking cessation interventions have been designed for men. A gender-specific website, QuitNow Men, was developed based on focus group interview findings, stakeholder feedback, and evidence-based cessation strategies. The website was designed to incorporate a masculine look and feel through the use of images, direct language, and interactive content. Usability experts and end-users provided feedback on navigation and functionality of the website prior to pilot testing. OBJECTIVES: The objectives of the pilot study were to describe (1) men's use and evaluations of the interactive resources and information on the QuitNow Men website, and (2) the potential of QuitNow Men to engage men in reducing and quitting smoking. METHODS: A one-group, pretest-posttest study design was used. Men who were interested in quitting were recruited and invited to use the website over a 6-month period. Data were collected via online questionnaires at baseline, 3-month, and 6-month follow-up. A total of 117 men completed the baseline survey. Over half of those (67/117, 57.3%) completed both follow-up surveys. RESULTS: At baseline, participants (N=117) had been smoking for an average of 24 years (SD 12.1) and smoked on average 15 cigarettes a day (SD 7.4). The majority had not previously used a quit smoking website (103/117, 88.0%) or websites focused on men's health (105/117, 89.7%). At the 6-month follow-up, the majority of men used the QuitNow Men website at least once (64/67, 96%). Among the 64 users, 29 (43%) reported using the website more than 6 times. The men using QuitNow Men agreed or strongly agreed that the website was easy to use (51/64, 80%), the design and images were appealing (42/64, 66%), they intended to continue to use the website (42/64, 66%), and that they would recommend QuitNow Men to others who wanted to quit (46/64, 72%). Participants reported using an average of 8.76 (SD 4.08) of the 15 resources available on the website. At 6-month follow-up, 16 of the 67 participants (24%) had quit, 27 (40%) had reduced their smoking and 24 (36%) had not changed their smoking habits. Repeated measures general linear model showed a significant decrease in the number of cigarettes smoked between the 3-month and 6-month follow-up (F1,63=6.41, P=.01, eta squared=0.09). Number of resources used on the website, quit confidence, nicotine dependence and age significantly predicted number of quit attempts by those still smoking at 6 months (F4,45=2.73, P=.04), with number of resources used being the strongest predictor (P=.02). CONCLUSIONS: The results of this research support efforts to integrate gender-sensitive approaches in smoking cessation interventions and indicate that this novel Web-based resource has potential in supporting men's smoking cessation efforts.

Personas to Guide Understanding Traditions of Gay Men Living With HIV Who Smoke.

Gay men living with HIV (GMLWH) who smoke are less responsive to generalized smoking reduction and cessation (SRC) programs than heterosexual persons. This study explored perspectives of GMLWH during the design of a web-based SRC intervention. Participatory design techniques were used to guide the creation of personas that are composite representations of a person who would use the web-based SRC intervention. Researcher-participants (n = 13) created all data. Data analysis involved thematic coding drawing from an ethnographic perspective. Thematic analysis revealed seven intersecting themes related to SRC among participants, and an overarching theme navigating life. Concepts drawn from our ethnographic approach highlight cultural differences between GMLWH and mainstream society. Personas offer a mechanism for interpreting experiences and traditions of GMLWH. SRC interventions with GMLWH must address their social realities that include tools for navigating life, disease, and social identity.

Integrating Justice, Equity, Diversity, Inclusion & Indigeneity into an Informatics Curriculum.

In this case study, we present the inclusion of justice, equity, diversity, inclusion, and Indigeneity (JEDI-I) principles into a graduate certificate in clinical informatics. We specifically focus on two assignments that were created for the program: 1) journal club, 2) usability evaluation. We found that there was limited description of JEDI-I principles in journal club articles. New criteria for authentic resource evaluation were somewhat met in the usability evaluation of a sexual health website. Incorporating JEDI-I principles into the assignments supported fulsome conversations about end-user of technology in healthcare. Identifying examples of including JEDI-I would strengthen students' experiences in clinical informatics programs.

Nurse Involvement in Health Information Technology Design for Computerized Nursing Practice: A Scoping Review.

This scoping review assesses evidence regarding nurse involvement in health information technology (health IT) design, focusing on the method(s), frequency, capacity, and levels of involvement. The JBI methodology for scoping reviews was used to search seven multidisciplinary databases, yielding 2948 articles. After screening, 98 articles were included for data abstraction. Textual data summary is ongoing. Preliminary findings highlight that nurses are often involved in the late stages of health IT design, with less frequency in the early and pre-programming design phases. Most studies used a user-centered design approach to elicit nurses' views about health IT tools after the tools had been developed, with nearly half being point of care nurses. Increasing nurse involvement in health IT design may help to improve nurses' perceptions of health IT that nurses use.

Development and Testing of an Instrument to Measure the Impact of EHR Use on Quality of Care.

There is an increased adoption of electronic health records (EHR) motivated by many purported benefits, yet limited research has explored their impact on quality of care. We developed and tested a multidimensional measure of quality of care in relation to EHR use. 234 nurses completed a cross-sectional survey. The score of the quality of care construct reached 0.92. Four subdimensions were identified: technology impact on nursing practice, learning and improvement capability, transition accountability, and fault responsibility. The instrument has potential to advance our understanding of the impact of EHR use on quality of care.

Association Between EHR Compatibility and Nurses' Emotional Exhaustion.

In this study we explored the relationship between nurses' emotional exhaustion and three EHR compatibility subdimensions (nurses' preferred work style, existing clinical practice, and values). We found higher emotional exhaustion with lower EHR compatibility for both preferred work style and existing clinical practice, but no relationship between emotional exhaustion and nurses' values. Efforts to improve EHR compatibility are recommended to mitigate nurses' burnout.

Technology-Related Safety Events in Primary and Community Care Settings: A Scoping Review.

This scoping review assesses the current knowledge on technology-related safety events in primary and community care settings, focusing on patient safety and harm. Utilizing Arksey and O'Malley's methodological framework, a comprehensive literature search was conducted across various databases, yielding 17 relevant articles. The review highlighted predominant safety event issues, such as technology limitations, incorrect data, and software malfunctions, and identified essential risk mitigation strategies. Consultation with healthcare leaders reinforced these findings and revealed additional organizational challenges, emphasizing the need for continuous monitoring, reporting, and analyzing of HIT-related safety concerns. The findings suggest that while safety events in non-acute settings share similarities with those in acute care, they require specific attention and further research.

Speech Recognition Technology for Nursing Charting: A Literature Review.

This literature review explores the impact of Speech Recognition Technology (SRT) on nursing documentation within electronic health records (EHR). A search across PubMed, CINAHL, and Google Scholar identified 156 studies, with seven meeting the inclusion criteria. These studies investigated the impact of SRT on documentation time, accuracy, and user satisfaction. Findings suggest SRT, particularly when integrated with artificial intelligence can speed up documentation by up to 15%. However, challenges remain in its implementation in real-world clinical settings and existing EHR workflows. Future studies should focus on developing SRT systems that process conversational nursing assessments and integrate into current EHRs.

Integration of Equity, Diversity, Inclusivity, and Indigeneity Principles into Usability Heuristic Evaluations.

Cognitive walkthrough is a form of usability testing that considers the perspective of the end users to identify issues related to user experience and web design. This project aims to enhance traditional heuristic evaluation methods with consideration of equity, diversity, inclusivity, and indigeneity (EDI-I) principles. The authors provide suggestions that align with modern informatics advancements, aiming for inclusive design systems and the elimination of systemic barriers.

Clinical Informatics Team Members' Perspectives on Health Information Technology Safety After Experiential Learning and Safety Process Development: Qualitative Descriptive Study.

BACKGROUND: Although intended to support improvement, the rapid adoption and evolution of technologies in health care can also bring about unintended consequences related to safety. In this project, an embedded researcher with expertise in patient safety and clinical education worked with a clinical informatics team to examine safety and harm related to health information technologies (HITs) in primary and community care settings. The clinical informatics team participated in learning activities around relevant topics (eg, human factors, high reliability organizations, and sociotechnical systems) and cocreated a process to address safety events related to technology (ie, safety huddles and sociotechnical analysis of safety events). OBJECTIVE: This study aimed to explore clinical informaticians' experiences of incorporating safety practices into their work. METHODS: We used a qualitative descriptive design and conducted web-based focus groups with clinical informaticians. Thematic analysis was used to analyze the data. RESULTS: A total of 10 informants participated. Barriers to addressing safety and harm in their context included limited prior knowledge of HIT safety, previous assumptions and perspectives, competing priorities and organizational barriers, difficulty with the reporting system and processes, and a limited number of reports for learning. Enablers to promoting safety and mitigating harm included participating in learning sessions, gaining experience analyzing reported events, participating in safety huddles, and role modeling and leadership from the embedded researcher. Individual outcomes included increased ownership and interest in HIT safety, the development of a sociotechnical systems perspective, thinking differently about safety, and increased consideration for user perspectives. Team outcomes included enhanced communication within the team, using safety events to inform future work and strategic planning, and an overall promotion of a culture of safety. CONCLUSIONS: As HITs are integrated into care delivery, it is important for clinical informaticians to recognize the risks related to safety. Experiential learning activities, including reviewing safety event reports and participating in safety huddles, were identified as particularly impactful. An HIT safety learning initiative is a feasible approach for clinical informaticians to become more knowledgeable and engaged in HIT safety issues in their work.

Fairness in Classifying and Grouping Health Equity Information.

This paper explores the balance between fairness and performance in machine learning classification, predicting the likelihood of a patient receiving anti-microbial treatment using structured data in community nursing wound care electronic health records. The data includes two important predictors (gender and language) of the social determinants of health, which we used to evaluate the fairness of the classifiers. At the same time, the impact of various groupings of language codes on classifiers' performance and fairness is analyzed. Most common statistical learning-based classifiers are evaluated. The findings indicate that while K-Nearest Neighbors offers the best fairness metrics among different grouping settings, the performance of all classifiers is generally consistent across different language code groupings. Also, grouping more variables tends to improve the fairness metrics over all classifiers while maintaining their performance.

Technology-Related Safety Event Analysis in Community Clinical Informatics: A Case Study.

This case study presents a process that was iteratively developed for clinical informaticians to identify, analyse, and respond to safety events related to health information technologies (HIT) in community care settings (This research was supported by the CIHR Health Systems Impact Fellowship Program. We would also like to thank Vancouver Coastal Health for their valuable contributions.). The goal was to build capacity within a clinical informatics team to integrate patient safety into their work and to help them recognize and respond to HIT-related safety events. The technology-related safety event analysis process that was ultimately developed included three key components: 1) an internal workflow to analyse voluntarily reported HIT-related safety events using a sociotechnical model, 2) safety huddles to amplify learnings from reviewed events, and 3) a cumulative analysis of all events over time to identify and respond to patterns. A systematic approach to quickly identify and understand HIT safety concerns enables informatics teams to proactively reduce risks and prevent harm.