What Determines the Use of Clinical Decision Support Systems in Nursing? Results of a Multiple Regression Analysis.

INTRODUCTION: In nursing, professionals are expected to base their practice on evidence-based knowledge, however the successful implementation of this knowledge into nursing practice is not always assured. Clinical Decision Support Systems (CDSS) are considered to bridge this evidence-practice gap. METHODS: This study examines the extent to which evidence-based nursing (EBN) practices influence the use of CDSS and identifies what additional factors from acceptance theories such as UTAUT play a role. RESULTS AND DISCUSSION: Our findings from three regression models revealed that nursing professionals and nursing students who employ evidence-based practices are not more likely to use an evidence-based CDSS. The relationship between an EBN composite score (model 1) or is individual dimensions (model 2) and CDSS use was not significant. However, a more comprehensive model (model 3), incorporating items from the UTAUT such as Social Influences, Facilitating Conditions, Performance Expectancy, and Effort Expectancy, supplemented by Satisfaction demonstrated a significant variance explained (R2 = 0.279). Performance Expectancy and Satisfaction were found to be significantly associated with CDSS utilization. CONCLUSION: This underscores the importance of user-friendliness and practical utility of a CDSS. Despite potential limitations in generalizability and a limited sample size, the results provide insights into that CDSS first and foremost underly the same mechanisms of use as other health IT systems.

Patient satisfaction and digital health in primary health care: a scoping review protocol.

Introduction: Using digital health in primary health care (PHC) contributes to reducing costs and travel time, achieving global development goals, improving access, quality and longitudinality of care, and managing health crises. Its evaluation must go beyond the technical-operational aspects to include patient satisfaction, a key element in assessing the quality of care. Objective: To identify and map patient satisfaction (expectations, desires, cultural values) about the adoption of digital health strategies and assess their impact on the quality of care in PHC. Methods: The review will follow the recommendations proposed by the Joanna's Briggs Institute (JBI) manual, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) and the methodology proposed by Arksey and O'Malley and Levac et al. and will be conducted in nine stages. The search will be conducted in health studies databases (MEDLINE via PubMed, EMBASE, CINAHL, Web of Science, and BVS), gray literature, and preprint repositories (Google Scholar and MedRxiv). Two reviewers will select the studies, and the third will analyze possible conflicts. The inclusion criteria comprise studies that have been made available in their entirety, whether they are primary studies or short communications, as well as the following materials extracted from the gray literature: preprints, manuals, government documents, books, guidelines, theses and dissertations. Exclusion criteria include literature reviews, abstracts, books, conference archives, letters to the editor, duplicates and opinion articles. Data will be analyzed by content analysis and inferential statistics. This protocol is registered on the Open Science Framework (OSF) under DOI 10.17605/OSF.IO/PUJDB. Results: The study aims to understand aspects related to the expectations, desires, and cultural values of patients from different countries, as well as the strengths and critical nodes of the use of digital health on the quality of care in PHC.

Needs-Assessment for an Artificial Intelligence-Based Chatbot for Pharmacists in HIV Care: Results from a Knowledge-Attitudes-Practices Survey.

BACKGROUND: Pharmacists need up-to-date knowledge and decision-making support in HIV care. We aim to develop MARVIN-Pharma, an adapted artificial intelligence-based chatbot initially for people with HIV, to assist pharmacists in considering evidence-based needs. METHODS: From December 2022 to December 2023, an online needs-assessment survey evaluated Québec pharmacists' knowledge, attitudes, involvement, and barriers relative to HIV care, alongside perceptions relevant to the usability of MARVIN-Pharma. Recruitment involved convenience and snowball sampling, targeting National HIV and Hepatitis Mentoring Program affiliates. RESULTS: Forty-one pharmacists (28 community, 13 hospital-based) across 15 Québec municipalities participated. Participants perceived their HIV knowledge as moderate (M = 3.74/6). They held largely favorable attitudes towards providing HIV care (M = 4.02/6). They reported a "little" involvement in the delivery of HIV care services (M = 2.08/5), most often ART adherence counseling, refilling, and monitoring. The most common barriers reported to HIV care delivery were a lack of time, staff resources, clinical tools, and HIV information/training, with pharmacists at least somewhat agreeing that they experienced each (M ≥ 4.00/6). On average, MARVIN-Pharma's acceptability and compatibility were in the 'undecided' range (M = 4.34, M = 4.13/7, respectively), while pharmacists agreed to their self-efficacy to use online health services (M = 5.6/7). CONCLUSION: MARVIN-Pharma might help address pharmacists' knowledge gaps and barriers to HIV treatment and care, but pharmacist engagement in the chatbot's development seems vital for its future uptake and usability.

The barriers and challenges of using health information technology in medication administration process for pediatrics and neonates: A qualitative study.

Background and Aims: Children and neonates are more susceptible to diseases and are a vulnerable group in medication administration (MA). Nurses interact directly with patients, ensuring safety and preventing unintended outcomes. Health Information Technology (HIT) has transformed health care, aiding nurses in decision-making and treatment responses. Despite its benefits, technology presents challenges that must be overcome to facilitate the nursing practice. Therefore, the present study aimed to explore the barriers to HIT use in the process of MA in children and neonates in a developing country. Methods: Semi-structured face-to-face interviews were conducted with 22 health care professionals across seven pediatric and neonatal settings. Also, observations were made of these settings for 3 weeks. A qualitative analysis was performed using the conventional content analysis method, recommended by Colaizzi's seven-step approach. Results: The results showed that the most significant barriers to adopting technology in MA process could be classified into two main categories: "inappropriate management approaches" with two sub-categories ("Managers' reluctance to adopt new technology", "lack of adequate budget for hardware resources"), and "resistance to change" with two sub-categories ("A desire to use conventional (traditional) approaches in care", "cultural issues and impracticality of providing some specialized technology services"). Conclusion: The findings revealed MA process complexities, which have been insufficiently examined in the current literature. We have highlighted the need for improved "effectiveness of HIT systems in administering medication processes, budget for hardware resources, and managers" interest in using new technology. The present findings can guide the development of more effective and user-friendly HIT systems in pediatric and neonatal care settings.

Translating Between Standardization and Local Fit in Health Information Technology.

The design of health information technology (HIT) requires balancing standardization and local adjustment. Preliminary study findings show that interactions between stakeholder shared attention and HIT translational 'boundary object' features ensure that HIT serves diverse stakeholders' purposes and needs. This can support subsequent implementation and patient safety.

Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review.

BACKGROUND: Chatbots, or conversational agents, have emerged as significant tools in health care, driven by advancements in artificial intelligence and digital technology. These programs are designed to simulate human conversations, addressing various health care needs. However, no comprehensive synthesis of health care chatbots' roles, users, benefits, and limitations is available to inform future research and application in the field. OBJECTIVE: This review aims to describe health care chatbots' characteristics, focusing on their diverse roles in the health care pathway, user groups, benefits, and limitations. METHODS: A rapid review of published literature from 2017 to 2023 was performed with a search strategy developed in collaboration with a health sciences librarian and implemented in the MEDLINE and Embase databases. Primary research studies reporting on chatbot roles or benefits in health care were included. Two reviewers dual-screened the search results. Extracted data on chatbot roles, users, benefits, and limitations were subjected to content analysis. RESULTS: The review categorized chatbot roles into 2 themes: delivery of remote health services, including patient support, care management, education, skills building, and health behavior promotion, and provision of administrative assistance to health care providers. User groups spanned across patients with chronic conditions as well as patients with cancer; individuals focused on lifestyle improvements; and various demographic groups such as women, families, and older adults. Professionals and students in health care also emerged as significant users, alongside groups seeking mental health support, behavioral change, and educational enhancement. The benefits of health care chatbots were also classified into 2 themes: improvement of health care quality and efficiency and cost-effectiveness in health care delivery. The identified limitations encompassed ethical challenges, medicolegal and safety concerns, technical difficulties, user experience issues, and societal and economic impacts. CONCLUSIONS: Health care chatbots offer a wide spectrum of applications, potentially impacting various aspects of health care. While they are promising tools for improving health care efficiency and quality, their integration into the health care system must be approached with consideration of their limitations to ensure optimal, safe, and equitable use.

Data quality and timeliness analysis for post-vaccination adverse event cases reported through healthcare data exchange to FDA BEST pilot platform.

Introduction: This study is part of the U.S. Food and Drug Administration (FDA)'s Biologics Effectiveness and Safety (BEST) initiative, which aims to improve the FDA's postmarket surveillance capabilities by using real-world data (RWD). In the United States, using RWD for postmarket surveillance has been hindered by the inability to exchange clinical data between healthcare providers and public health organizations in an interoperable format. However, the Office of the National Coordinator for Health Information Technology (ONC) has recently enacted regulation requiring all healthcare providers to support seamless access, exchange, and use of electronic health information through the interoperable HL7 Fast Healthcare Interoperability Resources (FHIR) standard. To leverage the recent ONC changes, BEST designed a pilot platform to query and receive the clinical information necessary to analyze suspected AEs. This study assessed the feasibility of using the RWD received through the data exchange of FHIR resources to study post-vaccination AE cases by evaluating the data volume, query response time, and data quality. Materials and methods: The study used RWD from 283 post-vaccination AE cases, which were received through the platform. We used descriptive statistics to report results and apply 322 data quality tests based on a data quality framework for EHR. Results: The volume analysis indicated the average clinical resources for a post-vaccination AE case was 983.9 for the median partner. The query response time analysis indicated that cases could be received by the platform at a median of 3 min and 30 s. The quality analysis indicated that most of the data elements and conformance requirements useful for postmarket surveillance were met. Discussion: This study describes the platform's data volume, data query response time, and data quality results from the queried postvaccination adverse event cases and identified updates to current standards to close data quality gaps.

Association between fitness technology use and physical activity mediated by communication behaviors on social media.

Objective: Fitness technologies, such as smartphone applications and wearable tracking devices, have gained widespread popularity. This study had two main objectives: 1) to examine whether fitness technology use is associated with increased physical activity (PA) levels and 2) to investigate whether communication behaviors on social media mediated the association between fitness technology use and PA. Methods: Data were from the U.S. Health Information National Trends Survey 2022 (N = 6,252, weighted N = 258,418,467). Weighted linear regressions were conducted to examine the associations between fitness technology usage, physical activities, and communication behaviors on social media. Mediations were tested using PROCESS macro, a path-analysis based tool. Results: Controlling for demographic and other known influences on PA, the findings revealed that users of fitness technology reported higher levels of both moderate PA (ß = .41, p < 0.001) and strength training (ß = .29, p < 0.001). Additionally, communication behaviors (i.e., sharing personal health information on social media and watching health-related videos on social media) mediated the relationship between fitness technology use and frequencies of strength training. Conclusion: The results underscored the potential of fitness technologies in enhancing PA levels through promoting communication behaviors on social media.

The application of health information technology for the elderly care in the emergency department: a conceptual model.

INTRODUCTION: In the emergency departments (EDs), usually the longest waiting time for treatment and discharge belongs to the elderly patients. Moreover, the number of the ED admissions for the elderly increases every year. It seems that the use of health information technology in geriatric emergency departments can help to reduce the burden of the healthcare services for this group of patients. This research aimed to develop a conceptual model for using health information technology in the geriatric emergency department. METHODS: This study was conducted in 2021. The initial conceptual model was designed based on the findings derived from the previous research phases (literature review and interview with the experts). Then, the model was examined by an expert panel (n = 7). Finally, using the Delphi technique (two rounds), the components of the conceptual model were reviewed and finalized. To collect data, a questionnaire was used, and data were analyzed using descriptive statistics. RESULTS: The common information technologies appropriate for the elderly care in the emergency departments included emergency department information system, clinical decision support system, electronic health records, telemedicine, personal health records, electronic questionnaires for screening, and other technologies such as picture archiving and communication systems (PACS), electronic vital sign monitoring systems, etc. The participants approved all of the proposed systems and their applications in the geriatric emergency departments. CONCLUSION: The proposed model can help to design and implement the most useful information systems in the geriatric emergency departments. As the application of technology accelerates care processes, investing in this field would help to support the care plans for the elderly and improve quality of care services. Further research is recommended to investigate the efficiency and effectiveness of using these technologies in the EDs.

Building Capacity of Community Health Centers to Improve the Provision of Postpartum Care Services Through Data-Driven Health Information Technology and Innovation.

Maternal morbidity and mortality remain significant challenges in the United States, with substantial burden during the postpartum period. The Centers for Disease Control and Prevention, in partnership with the National Association of Community Health Centers, began an initiative to build capacity in Federally Qualified Health Centers to (1) improve the infrastructure for perinatal care measures and (2) use perinatal care measures to identify and address gaps in postpartum care. Two partner health center-controlled networks implemented strategies to integrate evidence-based recommendations into the clinic workflow and used data-driven health information technology (HIT) systems to improve data standardization for quality improvement of postpartum care services. Ten measures were created to capture recommended care and services. To support measure capture, a data cleaning algorithm was created to prioritize defining pregnancy episodes and delivery dates and address data inconsistencies. Quality improvement activities targeted postpartum care delivery tailored to patients and care teams. Data limitations, including inconsistencies in electronic health record documentation and data extraction practices, underscored the complexity of integrating HIT solutions into postpartum care workflows. Despite challenges, the project demonstrated continuous quality improvement to support data quality for perinatal care measures. Future solutions emphasize the need for standardized data elements, collaborative care team engagement, and iterative HIT implementation strategies to enhance perinatal care quality. Our findings highlight the potential of HIT-driven interventions to improve postpartum care within health centers, with a focus on the importance of addressing data interoperability and documentation challenges to optimize and monitor initiatives to improve postpartum health outcomes.

Harnessing Health Information Technology in Domestic Violence in the United States: A Scoping Review.

Objectives: The following scoping review aims to identify and map the existing evidence for HIT interventions among women with DV experiences in the United States. And provide guidance for future research, and facilitate clinical and technical applications for healthcare professionals. Methods: Five databases, PubMed, EBSCOhost CINAHL, Ovid APA PsycINFO, Scopus and Google Scholar, were searched from date of inception to May 2023. Reviewers extracted classification of the intervention, descriptive details, and intervention outcomes, including physical safety, psychological, and technical outcomes, based on representations in the included studies. Results: A total of 24 studies were included, identifying seven web-based interventions and four types of abuse. A total of five studies reported safety outcomes related to physical health. Three studies reported depression, anxiety, and post-traumatic stress disorder as psychological health outcomes. The effectiveness of technology interventions was assessed in eight studies. Conclusion: Domestic violence is a major public health issue, and research has demonstrated the tremendous potential of health information technology, the use of which can support individuals, families, and communities of domestic violence survivors.

Health Information Technology Use among Foreign-Born Adults of Middle Eastern and North African Descent in the United States.

Health information technology (HIT) use among foreign-born adults of Middle Eastern and North African (MENA) descent is understudied. MENA Americans are currently categorized as "White" in the United States (US) on federal forms. Our purpose was to uncover the prevalence of HIT use among MENA immigrants compared to US- and foreign-born White adults before and after adjusting for covariates. The 2011-2018 National Health Interview Survey data (n = 161,613; ages 18 + years) were analyzed. HIT uses evaluated were searching for health information, filling prescriptions, scheduling appointments, and communicating with healthcare providers via email (last 12 months). Crude and multivariable logistic regression models were used to estimate the odds of each HIT use (searching for health information, filling prescriptions, scheduling appointments, and/or communicating with healthcare providers via email), and overall use of any HIT before and after adjustment. The most common HIT use was looking up health information (46.4% foreign-born MENA, 47.8% foreign-born White, 51.2% US-born White; p = .0079). Foreign-born adults of MENA descent had lower odds (OR = 0.64; 95% CI = 0.56-0.74) of reporting any HIT use, but no difference in reporting all HIT uses compared to US-born White adults. This is the first study to explore HIT use among MENA Americans. Results contribute to growing body of literature showing the health of MENA Americans differs from White Americans. A separate racial/ethnic identifier is needed to better capture HIT uses among populations of MENA descent.

Looking at the future of the medical certification of cause of death (MCCD) in England and Wales.

Internationally, the quality of death certification is poor although there are multiple efforts underway to improve the process. In England, a new medical certification system has been proposed to improve the quality of data. We surveyed general practitioners (n = 95) across the West Yorkshire area of England to appraise their views regarding whether further possible changes to the death certification system could promote their quality.

Exploring patient perspectives on Iran's Electronic Prescription System: a Qualitative Inquiry.

Background: Electronic prescriptions represent a fundamental shift in service delivery, healthcare management, and associated costs, offering numerous advantages. However, akin to other electronic systems, they also present challenges. This study aimed to investigate patients' understanding of the challenges associated with electronic prescriptions in Iran. Methods: This study used a qualitative research design, utilizing individual and semi-structured interviews with patients referred to selected pharmacies across all 11 districts of Shiraz City. The data were analyzed using MAXQDA software (version 10), and descriptive statistics for demographic data were calculated using SPSS version 19. Results: The study revealed that the participants generally demonstrated a certain level of familiarity with electronic prescribing systems. However, it was evident that many were unaware of the potential implications of such technology for their relationships with healthcare providers. This underscores the urgent need for patient understanding in the context of the electronic prescription system. While patients were relatively familiar with the functionality of electronic prescribing systems, they lacked a comprehensive understanding of how using these systems could affect their interactions with healthcare providers. Conclusion: Patients are significant beneficiaries of the electronic prescribing system. By addressing their needs and concerns, they can develop a positive attitude toward this system. Their active engagement can pave the way for the system's ease of use, increase its acceptance, and ultimately enhance the quality of healthcare services.

A Different View of Health Information Technology Workarounds in Critical Care.

When health information technology (HIT) was introduced into the hospital setting there was an obvious disruption to nursing workflow. In many cases it took a nurse extra steps or extra time to complete processes such as clinical documentation and medication administration. In response to HIT problems, nurses developed workarounds. Research on nursing workarounds has been hindered by a lack of variable definitions, measures and research models. This paper offers the results of an exploratory mixed methods study that proposes definitions for workarounds and describes the variable relationships with turbulence and patient safety in critical care.

A scoping review of rule-based clinical decision support malfunctions.

OBJECTIVE: Conduct a scoping review of research studies that describe rule-based clinical decision support (CDS) malfunctions. MATERIALS AND METHODS: In April 2022, we searched three bibliographic databases (MEDLINE, CINAHL, and Embase) for literature referencing CDS malfunctions. We coded the identified malfunctions according to an existing CDS malfunction taxonomy and added new categories for factors not already captured. We also extracted and summarized information related to the CDS system, such as architecture, data source, and data format. RESULTS: Twenty-eight articles met inclusion criteria, capturing 130 malfunctions. Architectures used included stand-alone systems (eg, web-based calculator), integrated systems (eg, best practices alerts), and service-oriented architectures (eg, distributed systems like SMART or CDS Hooks). No standards-based CDS malfunctions were identified. The "Cause" category of the original taxonomy includes three new types (organizational policy, hardware error, and data source) and two existing causes were expanded to include additional layers. Only 29 malfunctions (22%) described the potential impact of the malfunction on patient care. DISCUSSION: While a substantial amount of research on CDS exists, our review indicates there is a limited focus on CDS malfunctions, with even less attention on malfunctions associated with modern delivery architectures such as SMART and CDS Hooks. CONCLUSION: CDS malfunctions can and do occur across several different care delivery architectures. To account for advances in health information technology, existing taxonomies of CDS malfunctions must be continually updated. This will be especially important for service-oriented architectures, which connect several disparate systems, and are increasing in use.

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.

The Role of Health Information Technology During Hospital to Home Transitions.

The use of healthcare information technology (HIT) is vital for storing and exchanging health information during patient transitions, playing a significant role in care coordination for sepsis survivors. The critical role of HIT was evident during the pre-implementation phase of a study to implement an evidence-based protocol supporting the timely transition of sepsis survivors to home health and outpatient care. Through 61 semi-structured interviews involving 91 stakeholders, over half of the 33 identified themes were related to HIT. Notably, electronic health record (EHR) alert systems led to over-capture and alarm fatigue. Efficient information transfer during HHC referral highlighted the need for improved EHR access. The study underscores HIT's importance and potential while emphasizing the need for collaborative policy and interface development to promote effective transitions in care.

Evaluating ChatGPT's Performance in the EU*US eHealth Work Foundational Curriculum Using the HITCOMP Self-Assessment Quiz.

This study investigated the performance of OpenAI's Chat Generative Pre-trained Transformer (ChatGPT) in responding to the EU*US eHealth Work Foundational Curriculum. This curriculum, a collaborative effort between European and U.S. institutions, provides an extensive framework for eHealth learning. The assessment involved 321 questions from the online Health Information Technology Competencies (HITCOMP) self-assessment quiz. Using GPT-3.5 model, the study presented each question three times to assess ChatGPT's consistency. Findings revealed an accuracy of 70.7%, indicating a reasonable grasp of eHealth topics, although performance was uneven across the 21 modules. These results underscore ChatGPT's potential in health information technology education and highlight the need for further model enhancements to fully encompass eHealth competencies.