General Characteristics and Design Taxonomy of Chatbots for COVID-19: Systematic Review.

BACKGROUND: A conversational agent powered by artificial intelligence, commonly known as a chatbot, is one of the most recent innovations used to provide information and services during the COVID-19 pandemic. However, the multitude of conversational agents explicitly designed during the COVID-19 pandemic calls for characterization and analysis using rigorous technological frameworks and extensive systematic reviews. OBJECTIVE: This study aims to describe the general characteristics of COVID-19 chatbots and examine their system designs using a modified adapted design taxonomy framework. METHODS: We conducted a systematic review of the general characteristics and design taxonomy of COVID-19 chatbots, with 56 studies included in the final analysis. This review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to select papers published between March 2020 and April 2022 from various databases and search engines. RESULTS: Results showed that most studies on COVID-19 chatbot design and development worldwide are implemented in Asia and Europe. Most chatbots are also accessible on websites, internet messaging apps, and Android devices. The COVID-19 chatbots are further classified according to their temporal profiles, appearance, intelligence, interaction, and context for system design trends. From the temporal profile perspective, almost half of the COVID-19 chatbots interact with users for several weeks for >1 time and can remember information from previous user interactions. From the appearance perspective, most COVID-19 chatbots assume the expert role, are task oriented, and have no visual or avatar representation. From the intelligence perspective, almost half of the COVID-19 chatbots are artificially intelligent and can respond to textual inputs and a set of rules. In addition, more than half of these chatbots operate on a structured flow and do not portray any socioemotional behavior. Most chatbots can also process external data and broadcast resources. Regarding their interaction with users, most COVID-19 chatbots are adaptive, can communicate through text, can react to user input, are not gamified, and do not require additional human support. From the context perspective, all COVID-19 chatbots are goal oriented, although most fall under the health care application domain and are designed to provide information to the user. CONCLUSIONS: The conceptualization, development, implementation, and use of COVID-19 chatbots emerged to mitigate the effects of a global pandemic in societies worldwide. This study summarized the current system design trends of COVID-19 chatbots based on 5 design perspectives, which may help developers conveniently choose a future-proof chatbot archetype that will meet the needs of the public in the face of growing demand for a better pandemic response.

Occupational traumatic injuries among workers in health care facilities - United States, 2012-2014.

In 2013, one in five reported nonfatal occupational injuries occurred among workers in the health care and social assistance industry, the highest number of such injuries reported for all private industries. In 2011, U.S. health care personnel experienced seven times the national rate of musculoskeletal disorders compared with all other private sector workers. To reduce the number of preventable injuries among health care personnel, CDC's National Institute for Occupational Safety and Health (NIOSH), with collaborating partners, created the Occupational Health Safety Network (OHSN) to collect detailed injury data to help target prevention efforts. OHSN, a free, voluntary surveillance system for health care facilities, enables prompt and secure tracking of occupational injuries by type, occupation, location, and risk factors. This report describes OHSN and reports on current findings for three types of injuries. A total of 112 U.S. facilities reported 10,680 OSHA-recordable* patient handling and movement (4,674 injuries); slips, trips, and falls (3,972 injuries); and workplace violence (2,034 injuries) injuries occurring from January 1, 2012-September 30, 2014. Incidence rates for patient handling; slips, trips, and falls; and workplace violence were 11.3, 9.6, and 4.9 incidents per 10,000 worker-months,† respectively. Nurse assistants and nurses had the highest injury rates of all occupations examined. Focused interventions could mitigate some injuries. Data analyzed through OHSN identify where resources, such as lifting equipment and training, can be directed to potentially reduce patient handling injuries. Using OHSN can guide institutional and national interventions to protect health care personnel from common, disabling, preventable injuries.

Centering Digital Health Equity During Technology Innovation: Protocol for a Comprehensive Scoping Review of Evidence-Based Tools and Approaches.

BACKGROUND: In the rush to develop health technologies for the COVID-19 pandemic, the unintended consequence of digital health inequity or the inability of priority communities to access, use, and receive equal benefits from digital health technologies was not well examined. OBJECTIVE: This scoping review will examine tools and approaches that can be used during digital technology innovation to improve equitable inclusion of priority communities in the development of digital health technologies. The results from this study will provide actionable insights for professionals in health care, health informatics, digital health, and technology development to proactively center equity during innovation. METHODS: Based on the Arksey and O'Malley framework, this scoping review will consider priority communities' equitable involvement in digital technology innovation. Bibliographic databases in health, medicine, computing, and information sciences will be searched. Retrieved citations will be double screened against the inclusion and exclusion criteria using Covidence (Veritas Health Innovation). Data will be charted using a tailored extraction tool and mapped to a digital health innovation pathway defined by the Centre for eHealth Research roadmap for eHealth technologies. An accompanying narrative synthesis will describe the outcomes in relation to the review's objectives. RESULTS: This scoping review is currently in progress. The search of databases and other sources returned a total of 4868 records. After the initial screening of titles and abstracts, 426 studies are undergoing dual full-text review. We are aiming to complete the full-text review stage by May 30, 2024, data extraction in October 2024, and subsequent synthesis in December 2024. Funding was received on October 1, 2023, from the Centre for Health Equity Incubator Grant Scheme, University of Melbourne, Australia. CONCLUSIONS: This paper will identify and recommend a series of validated tools and approaches that can be used by health care stakeholders and IT developers to produce equitable digital health technology across the Centre for eHealth Research roadmap. Identified evidence gaps, possible implications, and further research will be discussed. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/53855.

Comparing data accuracy between structured abstracts and full-text journal articles: implications in their use for informing clinical decisions.

BACKGROUND: The abstract is the most frequently read section of a research article. The use of 'Consensus Abstracts', a clinician-oriented web application formatted for mobile devices to search MEDLINE/PubMed, for informing clinical decisions was proposed recently; however, inaccuracies between abstracts and the full-text article have been shown. Efforts have been made to improve quality. METHODS: We compared data in 60 recent-structured abstracts and full-text articles from six highly read medical journals. RESULTS: Data inaccuracies were identified and then classified as either clinically significant or not significant. Data inaccuracies were observed in 53.33% of articles ranging from 3.33% to 45% based on the IMRAD format sections. The Results section showed the highest discrepancies (45%) although these were deemed to be mostly not significant clinically except in one. The two most common discrepancies were mismatched numbers or percentages (11.67%) and numerical data or calculations found in structured abstracts but not mentioned in the full text (40%). There was no significant relationship between journals and the presence of discrepancies (Fisher's exact p value =0.3405). Although we found a high percentage of inaccuracy between structured abstracts and full-text articles, these were not significant clinically. CONCLUSIONS: The inaccuracies do not seem to affect the conclusion and interpretation overall. Structured abstracts appear to be informative and may be useful to practitioners as a resource for guiding clinical decisions.

Five-year (2015-2019) follow-up study of 6,526 cases of medical repatriation of Filipino seafarers.

BACKGROUND: There is a limited number of studies on the medical repatriation of seafarers. The aim of the study was to follow up on the previous 2010-2014 study using data from 2015-2019 to evaluate the epidemiology of medical repatriation among Filipino seafarers. MATERIALS AND METHODS: Data from medical repatriation records of Filipino seafarers from January 2015 to December 2019 were collected from various claims departments of different manning agencies in Manila, Philippines. RESULTS: Data from a total of 6,526 medical repatriation cases and 464,418 deployments in a 5-year period resulted in a medical repatriation rate calculated at 1.4%. We used the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) to determine the most common causes of repatriation. We found that these were musculoskeletal disorders, gastrointestinal problems, and traumatic injuries. The distribution of the specific illnesses per organ system is presented. CONCLUSIONS: Filipinos continue to represent the most numerous group of seafarers in the world. The continued profiling of health issues should lead to better health protocols and controlling medical costs. It should also lead to better prioritisation of health protection and care on board ships. Within the present 10-year database of medical repatriations coinciding with the implementation of Maritime Convention Labour Convention 2006, there is a compelling need to compare the two data sets to have an objective evaluation of the convention's projected goals.

Usability testing of the Philippine Electronic National Newborn Hearing Screening Registry (ENNHSR).

PURPOSE AND OBJECTIVES: The study determined the usability of the online and offline versions of the Philippine Electronic National Newborn Hearing Screening Registry (ENNHSR) as well as user perspectives and satisfaction on the training modules and the online and offline systems. The steps in creating the systems, training modules, and evaluation of the user training manual and video training modules, accuracy and time and motion studies on data entry as well as determination of user perspectives and satisfaction were the specific objectives. METHODOLOGY: With the combined efforts of the staff of Newborn Hearing Screening Reference Center (NHSRC), Philippine National Ear Institute (PNEI) and the National Telehealth Center (NTHC) of the National Institutes of Health UP Manila, the development of the online and offline versions of the ENNHSR took six (6) months from January 2021 to June 2021 to complete. Creation of the user manual and training modules took three (3) months from July 2021 to September 2021. The pilot of the systems was carried out in 2 Zoom Conferencing sessions with the participation of 28 existing certified newborn hearing center users with different roles, backgrounds, demographics from all over the Philippines. Written evaluation as well as focused group discussions on the training modules and the database were conducted during the sessions. Effectivity of the training modules was determined using a 10-point learning check. The time and accuracies in encoding each data field per user were also determined. RESULTS: All 28 participants were able to attend and actively participate in the required Zoom Conferencing sessions as well as submit the 2 evaluation surveys for the training modules and the ENNHSR. During the learning check 93% or 26 out of 28 passed. The surgical intervention module took the longest time to encode while the fastest module to complete was for speech therapy. The average mean time to complete all modules was 3382 s or around 57 min while the time range was between 32 and 104 min. A screener would need 18 min while an implant programmer who is a clinical audiologist would need 52 min to enter data. The accuracy in encoding patient data was 92% while hearing screening results was 88.64%. The system usability scale (SUS) score of ENNHSR was computed at 75.5 which was the average of individual SUS scores, falling within grade B or 74.1 to 77.1 as its corresponding numerical score range in percentile. Most of the participants noted that it was easy to find patient data, results and that it was streamlined with easy to track information. CONCLUSIONS AND RECOMMENDATIONS: Data gathering and analysis both play important roles in health management, policy implementation and quality assurance. We were able to uncover areas where the system performed well - effectively, efficiently, and with satisfaction. We realize that all the possible problems cannot be detected with a small number of participants and variety in information. This testing will serve as both a means to record or benchmark current usability, but also to identify areas where improvements must be made.

Policy-driven mathematical modeling for COVID-19 pandemic response in the Philippines.

Around the world, disease surveillance and mathematical modeling have been vital tools for government responses to the COVID-19 pandemic. In the face of a volatile crisis, modeling efforts have had to evolve over time in proposing policies for pandemic interventions. In this paper, we document how mathematical modeling contributed to guiding the trajectory of pandemic policies in the Philippines. We present the mathematical specifications of the FASSSTER COVID-19 compartmental model at the core of the FASSSTER platform, the scenario-based disease modeling and analytics toolkit used in the Philippines. We trace how evolving epidemiological analysis at the national, regional, and provincial levels guided government actions; and conversely, how emergent policy questions prompted subsequent model development and analysis. At various stages of the pandemic, simulated outputs of the FASSSTER model strongly correlated with empirically observed case trajectories (r=94%-99%, p<.001). Model simulations were subsequently utilized to predict the outcomes of proposed interventions, including the calibration of community quarantine levels alongside improvements to healthcare system capacity. This study shows how the FASSSTER model enabled the implementation of a phased approach toward gradually expanding economic activity while limiting the spread of COVID-19. This work points to the importance of locally contextualized, flexible, and responsive mathematical modeling, as applied to pandemic intelligence and for data-driven policy-making in general.

Understanding COVID-19 dynamics and the effects of interventions in the Philippines: A mathematical modelling study.

BACKGROUND: COVID-19 initially caused less severe outbreaks in many low- and middle-income countries (LMIC) compared with many high-income countries, possibly because of differing demographics, socioeconomics, surveillance, and policy responses. Here, we investigate the role of multiple factors on COVID-19 dynamics in the Philippines, a LMIC that has had a relatively severe COVID-19 outbreak. METHODS: We applied an age-structured compartmental model that incorporated time-varying mobility, testing, and personal protective behaviors (through a "Minimum Health Standards" policy, MHS) to represent the first wave of the Philippines COVID-19 epidemic nationally and for three highly affected regions (Calabarzon, Central Visayas, and the National Capital Region). We estimated effects of control measures, key epidemiological parameters, and interventions. FINDINGS: Population age structure, contact rates, mobility, testing, and MHS were sufficient to explain the Philippines epidemic based on the good fit between modelled and reported cases, hospitalisations, and deaths. The model indicated that MHS reduced the probability of transmission per contact by 13-27%. The February 2021 case detection rate was estimated at ~8%, population recovered at ~9%, and scenario projections indicated high sensitivity to MHS adherence. INTERPRETATION: COVID-19 dynamics in the Philippines are driven by age, contact structure, mobility, and MHS adherence. Continued compliance with low-cost MHS should help the Philippines control the epidemic until vaccines are widely distributed, but disease resurgence may be occurring due to a combination of low population immunity and detection rates and new variants of concern.

Nursing Informatics Research Trends: Findings from an International Survey.

This follow-up survey on trends in Nursing Informatics (NI) was conducted by the International Medical Informatics Association (IMIA) Student and Emerging Professionals (SEP) group as a cross-sectional study in 2019. There were 455 responses from 24 countries. Based on the findings NI research is evolving rapidly. Current ten most common trends include: clinical quality measures, clinical decision support, big data, artificial intelligence, care coordination, education and competencies, patient safety, mobile health, description of nursing practices and evaluation of patient outcomes. The findings help support the efforts to efficiently use resources in the promotion of health care activities, to support the development of informatics education and to grow NI as a profession.

Advancing Nursing Informatics in the Next Decade: Recommendations from an International Survey.

In the summer of 2015, the International Medical Informatics Association Nursing Informatics Special Interest Group (IMIA NISIG) Student Working Group developed and distributed an international survey of current and future trends in nursing informatics. The survey was developed based on current literature on nursing informatics trends and translated into six languages. Respondents were from 31 different countries in Asia, Africa, North and Central America, South America, Europe, and Australia. This paper presents the results of responses to the survey question: "What should be done (at a country or organizational level) to advance nursing informatics in the next 5-10 years?" (n responders = 272). Using thematic qualitative analysis, responses were grouped into five key themes: 1) Education and training; 2) Research; 3) Practice; 4) Visibility; and 5) Collaboration and integration. We also provide actionable recommendations for advancing nursing informatics in the next decade.

Nursing Informatics Research Priorities for the Future: Recommendations from an International Survey.

We present one part of the results of an international survey exploring current and future nursing informatics (NI) research trends. The study was conducted by the International Medical Informatics Association Nursing Informatics Special Interest Group (IMIA-NISIG) Student Working Group. Based on findings from this cross-sectional study, we identified future NI research priorities. We used snowball sampling technique to reach respondents from academia and practice. Data were collected between August and September 2015. Altogether, 373 responses from 44 countries were analyzed. The identified top ten NI trends were big data science, standardized terminologies (clinical evaluation/implementation), education and competencies, clinical decision support, mobile health, usability, patient safety, data exchange and interoperability, patient engagement, and clinical quality measures. Acknowledging these research priorities can enhance successful future development of NI to better support clinicians and promote health internationally.

Current Trends in Nursing Informatics: Results of an International Survey.

Nursing informatics (NI) can help provide effective and safe healthcare. This study aimed to describe current research trends in NI. In the summer 2015, the IMIA-NI Students Working Group created and distributed an online international survey of the current NI trends. A total of 402 responses were submitted from 44 countries. We identified a top five NI research areas: standardized terminologies, mobile health, clinical decision support, patient safety and big data research. NI research funding was considered to be difficult to acquire by the respondents. Overall, current NI research on education, clinical practice, administration and theory is still scarce, with theory being the least common. Further research is needed to explain the impact of these trends and the needs from clinical practice.

Nurse Informaticians Report Low Satisfaction and Multi-level Concerns with Electronic Health Records: Results from an International Survey.

This study presents a qualitative content analysis of nurses' satisfaction and issues with current electronic health record (EHR) systems, as reflected in one of the largest international surveys of nursing informatics. Study participants from 45 countries (n=469) ranked their satisfaction with the current state of nursing functionality in EHRs as relatively low. Two-thirds of the participants (n=283) provided disconcerting comments when explaining their low satisfaction rankings. More than one half of the comments identified issues at the system level (e.g., poor system usability; non-integrated systems and poor interoperability; lack of standards; and limited functionality/missing components), followed by user-task issues (e.g., failure of systems to meet nursing clinical needs; non nursing-specific systems) and environment issues (e.g., low prevalence of EHRs; lack of user training). The study results call for the attention of international stakeholders (educators, managers, policy makers) to improve the current issues with EHRs from a nursing perspective.

Repatriation rates in Filipino seafarers: a five-year study of 6,759 cases.

BACKGROUND: Studies on medical repatriation of seafarers due to illnesses and injuries have been limited. The aim of the study was to describe the epidemiology of medical repatriation among Filipino seafarers. MATERIALS AND METHODS: We performed a retrospective analysis of records from January 2010 to December 2014 of medical repatriations of Filipino seafarers from the claims and legal departments of different manning agencies in Manila, Philippines. RESULTS: We analysed data from a total of 6,759 medical repatriation cases in a 5-year period, representing 174 shipping companies and 2,256 vessels. The total number of seafarers deployed from the manning agencies where we obtained data was 388,963 with the rate of medical repatriations calculated at 1.7%. We used the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) to determine the most common causes of repatriation. We found that these were injuries (trauma), musculoskeletal disorders, gastrointestinal problems, and genitourinary illnesses. We also conducted an analysis of the most common clinical problems per organ system. CONCLUSIONS: Filipinos represent the most numerous group of seafarers in the world. Profiling their health issues may help in optimising current protocols, implementing health surveillance programs, and formulating health policies for seafaring personnel. In addition, our study results may help physicians performing pre-employment medical examinations to identify and manage conditions that are at a high risk of medical repatriation.

Confidence and Information Access in Clinical Decision-Making: An Examination of the Cognitive Processes that affect the Information-seeking Behavior of Physicians.

Clinical decision-making involves the interplay between cognitive processes and physicians' perceptions of confidence in the context of their information-seeking behavior. The objectives of the study are: to examine how these concepts interact, to determine whether physician confidence, defined in relation to information need, affects clinical decision-making, and if information access improves decision accuracy. We analyzed previously collected data about resident physicians' perceptions of information need from a study comparing abstracts and full-text articles in clinical decision accuracy. We found that there is a significant relation between confidence and accuracy (φ=0.164, p<0.01). We also found various differences in the alignment of confidence and accuracy, demonstrating the concepts of underconfidence and overconfidence across years of clinical experience. Access to online literature also has a significant effect on accuracy (p<0.001). These results highlight possible CDSS strategies to reduce medical errors.

Optimizing the txt2MEDLINE search portal for low-resource clinical decision support.

txt2MEDLINE provides access to high-quality medical evidence via text-messaging in settings with inadequate Internet access. We optimized the txt2MEDLINE search technique by parsing queries for MeSH (Medical Subject Heading) terms and searching MEDLINE for articles containing these terms in their titles or abstracts. We compared our results to the existing txt2MEDLINE tool by compiling benchmark queries from low-income and low-middle-income countries, and asking doctors and nurses with practice experience in low-resource areas to evaluate them. The median scores on a 5-point Likert scale were 2.9 for the existing txt2MEDLINE vs. 3.8 for the modified version (p=0.015). This reached our predefined criterion for clinical significance, a difference of 0.5 standard deviations. Improving this technology could improve clinical information resources in the world's most medically underserved communities.