Healthcare Information Research Articles

Implementation of the Observational Medical Outcomes Partnership Model in Electronic Medical Record Systems: Evaluation Study Using Factor Analysis and Decision-Making Trial and Evaluation Laboratory-Best-Worst Methods.

Electronic medical record (EMR) systems are essential in health care for collecting and storing patient medical data. They provide critical information to doctors and caregivers, facilitating improved decision-making and patient care. Despite their significance, optimizing EMR systems is crucial for enhancing health care quality. Implementing the Observational Medical Outcomes Partnership (OMOP) shared data model represents a promising approach to improve EMR performance and overall health care outcomes. This study aims to evaluate the effects of implementing the OMOP shared data model in EMR systems and to assess its impact on enhancing health care quality. In this study, 3 distinct methodologies are used to explore various aspects of health care information systems. First, factor analysis is utilized to investigate the correlations between EMR systems and attitudes toward OMOP. Second, the best-worst method (BWM) is applied to determine the weights of criteria and subcriteria. Lastly, the decision-making trial and evaluation laboratory technique is used to illustrate the interactions and interdependencies among the identified criteria. In this research, we evaluated the AliHealth EMR system by surveying 98 users and practitioners to assess its effectiveness and user satisfaction. The study reveals that among all components, "EMR resolution" holds the highest importance with a weight of 0.31007783, highlighting its significant role in the evaluation. Conversely, "EMR ease of use" has the lowest weight of 0.1860467, indicating that stakeholders prioritize the resolution aspect over ease of use in their assessment of EMR systems. The findings highlight that stakeholders prioritize certain aspects of EMR systems, with "EMR resolution" being the most valued component.

The temporal trend and disparity in short-term health impacts of fine particulate matter in California (2006–2019)

Most epidemiological studies assume that the relationship between short-term air pollution exposure and health outcomes is constant over time, which ignores potential changes in population composition and particulate matter emission sources. Limited studies have assessed changes in the relationship between fine particulate matter (PM2.5) and adverse health outcomes over time, with mixed results. Additionally, there is a need to identify which subgroups are disproportionately impacted over time by PM2.5-related health consequences. Therefore, we aimed to examine whether temporal trends exist in the relationships between daily PM2.5 exposure and circulatory and respiratory acute care utilization in California from 2006 to 2019. We further assessed whether certain subpopulations are more susceptible to PM2.5 exposure by demographic characteristics and extreme wildfire frequency. Daily PM2.5 concentrations estimated from a stacked ensemble model and daily cause-specific acute care utilization and demographic data from the California Department of Health Care Access and Information. We analyzed this relationship using modified two-stage Bayesian hierarchical models, where we first did not consider temporal trends, then stratified by two periods, and finally flexibly considered non-linear changes over time. Increases in circulatory (0.56 %; 95 % credible interval (CI): 0.17 %, 0.96 %) and respiratory acute care utilization risk (2.61 %; 95%CI: 2.29 %, 2.94 %) were found with every 10 μg/m3 increase in PM2.5 on the same day and previous two days. These risks were found to increase over time, where 0.13 % (95%CI: 0.02 %, 0.22 %) and 1.40 % (95%CI: 1.24 %, 1.54 %) increases were identified for circulatory and respiratory acute care utilizations, respectively, from the first (2006–2012) to second period (2013–2019). Differences by age, sex, race/ethnicity, and extreme wildfire frequency were noted. These findings confirm that air pollution guidelines should consider the dynamic nature of epidemiological dose-response and can provide insight for targeted air pollution control and adaptation policies designed to reduce PM2.5 exposure, particularly for the most susceptible subpopulations.

User involvement in the design and development of medical devices in epilepsy: A systematic review.

This systematic review aims to describe the involvement of persons with epilepsy (PWE), healthcare professionals (HP) and caregivers (CG) in the design and development of medical devices is epilepsy. A systematic review was conducted, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eligibility criteria included peer-reviewed research focusing on medical devices for epilepsy management, involving users (PWE, CG, and HP) during the MDD process. Searches were performed on PubMed, Web of Science, and Scopus, and a total of 55 relevant articles were identified and reviewed. From 1999 to 2023, there was a gradual increase in the number of publications related to user involvement in epilepsy medical device development (MDD), highlighting the growing interest in this field. The medical devices involved in these studies encompassed a range of seizure detection tools, healthcare information systems, vagus nerve stimulation (VNS) and electroencephalogram (EEG) technologies reflecting the emphasis on seizure detection, prediction, and prevention. PWE and CG were the primary users involved, underscoring the importance of their perspectives. Surveys, usability testing, interviews, and focus groups were the methods used for capturing user perspectives. User involvement occurs in four out of the five stages of MDD, with production being the exception. User involvement in the MDD process for epilepsy management is an emerging area of interest holding a significant promise for improving device quality and patient outcomes. This review highlights the need for broader and more effective user involvement, as it currently lags in the development of commercially available medical devices for epilepsy management. Future research should explore the benefits and barriers of user involvement to enhance medical device technologies for epilepsy. This review covers studies that have involved users in the development process of medical devices for epilepsy. The studies reported here have focused on getting input from people with epilepsy, their caregivers, and healthcare providers. These devices include tools for detecting seizures, stimulating nerves, and tracking brain activity. Most user feedback was gathered through surveys, usability tests, interviews, and focus groups. Users were involved in nearly every stage of device development except production. The review highlights that involving users can improve device quality and patient outcomes, but more effective involvement is needed in commercial device development. Future research should focus on the benefits and challenges of user involvement.

Is Information About Musculoskeletal Malignancies From Large Language Models or Web Resources at a Suitable Reading Level for Patients?

Patients and caregivers may experience immense distress when receiving the diagnosis of a primary musculoskeletal malignancy and subsequently turn to internet resources for more information. It is not clear whether these resources, including Google and ChatGPT, offer patients information that is readable, a measure of how easy text is to understand. Since many patients turn to Google and artificial intelligence resources for healthcare information, we thought it was important to ascertain whether the information they find is readable and easy to understand. The objective of this study was to compare readability of Google search results and ChatGPT answers to frequently asked questions and assess whether these sources meet NIH recommendations for readability. (1) What is the readability of ChatGPT-3.5 as a source of patient information for the three most common primary bone malignancies compared with top online resources from Google search? (2) Do ChatGPT-3.5 responses and online resources meet NIH readability guidelines for patient education materials? This was a cross-sectional analysis of the 12 most common online questions about osteosarcoma, chondrosarcoma, and Ewing sarcoma. To be consistent with other studies of similar design that utilized national society frequently asked questions lists, questions were selected from the American Cancer Society and categorized based on content, including diagnosis, treatment, and recovery and prognosis. Google was queried using all 36 questions, and top responses were recorded. Author types, such as hospital systems, national health organizations, or independent researchers, were recorded. ChatGPT-3.5 was provided each question in independent queries without further prompting. Responses were assessed with validated reading indices to determine readability by grade level. An independent t-test was performed with significance set at p < 0.05. Google (n = 36) and ChatGPT-3.5 (n = 36) answers were recorded, 12 for each of the three cancer types. Reading grade levels based on mean readability scores were 11.0 ± 2.9 and 16.1 ± 3.6, respectively. This corresponds to the eleventh grade reading level for Google and a fourth-year undergraduate student level for ChatGPT-3.5. Google answers were more readable across all individual indices, without differences in word count. No difference in readability was present across author type, question category, or cancer type. Of 72 total responses across both search modalities, none met NIH readability criteria at the sixth-grade level. Google material was presented at a high school reading level, whereas ChatGPT-3.5 was at an undergraduate reading level. The readability of both resources was inadequate based on NIH recommendations. Improving readability is crucial for better patient understanding during cancer treatment. Physicians should assess patients' needs, offer them tailored materials, and guide them to reliable resources to prevent reliance on online information that is hard to understand. Level III, prognostic study.

Сравнительный анализ развития Eдиных Информационных Систем Здравоохранения (ЕИСЗ) в странах Африки, Северной Америки и Европы: проблемы и перспективы.

This study presents a comparative analysis of the development of unified healthcare information systems (UHIS) in North America, Europe, and Africa. The research examines key aspects of UHIS implementation, including population coverage by electronic health records, telemedicine development, system interoperability, and regulatory frameworks. The analysis revealed significant regional differences in approaches to healthcare digitalization and UHIS implementation levels. North America is characterized by high digital technology adoption but faces challenges in integrating disparate systems. The European region shows heterogeneity, with Northern European countries leading, while Southern and Eastern Europe lag in UHIS development. The African continent presents the most contrasting picture, with a small group of leading countries and most states in the early stages of digitalization. The study identified common challenges across all regions, including ensuring interoperability, protecting personal data, and overcoming healthcare professionals' resistance to change. Special attention is given to innovative approaches, such as the use of mobile technologies in Africa to overcome infrastructure limitations. The research results emphasize the need for a comprehensive approach to UHIS implementation, considering not only technological but also socio-economic factors. The study concludes that successful UHIS development requires a clear national strategy, adequate funding, and active involvement of all stakeholders.

Data quality in hospital information systems: Lessons learned from analyzing 30 years of patient data in a regional German hospital

Background: The integration of Hospital Information Systems (HIS) into healthcare delivery has significantly enhanced patient care and operational efficiency. Nonetheless, the rapid acceleration of digital transformation has led to a substantial increase in the volume of data managed by these systems. This emphasizes the need for robust mechanisms for data management and quality assurance.Objective: This study addresses data quality issues related to patient identifiers within the Hospital Information System (HIS) of a regional German hospital, focusing on improving the accuracy and consistency of these administrative data entries.Methods: Employing a combination of data analysis and expert interviews, this study reviews and programmatically cleanses a dataset with over 2,000,000 patient data entries extracted from the HIS. The areas of investigation are patient admissions, discharges, and geographical data.Results: The analysis revealed that roughly 25% of the dataset was rendered unusable by errors and inconsistencies. By implementing a thorough data cleansing process, we significantly enhanced the utility of the dataset. In doing so, we identified the primary issues affecting data quality, including ambiguities among similar variables and a gap between the intended and actual use of the system.Conclusion: The findings highlight the critical importance of enhancing data quality in healthcare information systems. This study shows the necessity of a careful review of data extracted from the HIS before it can be reliably utilized for machine learning tasks, thereby rendering the data more usable for both clinical and analytical purposes.

Determininants of Diarrhea-Related Health Care Seeking Behavior among Indonesian Mothers with Under-five Children during the COVID-19 Pandemic

This study investigated factors influencing healthcare-seeking behaviours of Indonesian mothers during the COVID-19 pandemic when their children had diarrhea. The 117 participants completed a self-report which measured the socio-demographic condition, knowledge about diarrhea, illness perception, anxiety, and health care seeking behavior for diarrhea. The data were analyzed with the descriptive statistics, Chi-square, and logistic multinomial regression analysis. Analysis revealed critical determinants including child age, maternal occupation, education, transportation, knowledge of diarrhea, and illness perception. The model accurately predicted 84.6% of healthcare-seeking behaviours, with mothers favoring formal care for younger children and education positively influencing formal healthcare utilization. The type of public transportation significantly influenced healthcare-seeking behavior. While accurate knowledge of diarrhea increased professional care seeking, the model explained only 5.61% of behavior variation, suggesting unexplored factors. Addressing these factors could improve child health outcomes during pandemics. Policy enhancements and cultural sensitivity in health education are vital for efficacy. Deepening understanding and developing effective interventions amidst pandemics require further research.

Abstract A144: Insight into cervical cancer screening and HPV self-sampling among Vietnamese immigrants in Southern California

Abstract Background: Screening can effectively identify precancerous lesions for early treatment to prevent cervical cancer. However, only 69% of Vietnamese immigrants in the U.S. reported screening in the past 3 years compared to 84% of non-Hispanic White women. Human papillomavirus (HPV) self-sampling is a novel cervical cancer screening approach that does not require women to visit healthcare providers and has been shown to increase screening uptake in several minority populations. Understanding the attitudes towards cervical cancer screening, including HPV self-sampling, among Vietnamese immigrants could inform strategies to improve their screening rates. Methods: We conducted two online semi-structured focus groups with a total of nine Vietnam-born women aged 50-65 living in Southern California, which has the largest Vietnamese community outside of Vietnam, to understand their awareness of, attitudes towards, and experiences with cervical cancer screening. Participants also watched two short videos on two cervical cancer screening methods (Papanicolaou "Pap" test and HPV self-sampling) and shared their thoughts on each method. Each focus group was recorded, transcribed, translated into English, and coded and analyzed using NVivo 14. Results: Three main themes emerged from the focus groups. First, participants showed a strong acceptance of cervical cancer screening despite poor knowledge of the disease and its prevention as well as logistic and psychosocial barriers associated with visiting healthcare providers for screening. Second, participants found HPV self-sampling to be highly acceptable, mentioning advantages like its convenience and the lack of embarrassment compared to visiting healthcare providers. However, there were some concerns regarding the mailing of the self-collected samples and the cost of the test. Third, participants described circumstances that may be immigrant-specific, such as a shift from making gynecologic appointments themselves in Vietnam to relying on family doctors as gatekeepers for such appointments in the U.S., a strong preference for Vietnamese- speaking providers, and the use of English as a Second Language (ESL) centers, community organizations, radio stations, and newspapers targeting Vietnamese communities to obtain healthcare information. Conclusions: HPV self-sampling has the potential to improve cervical cancer screening uptake in Vietnamese immigrants since it can overcome barriers associated with visiting healthcare providers for a Pap test. Education campaigns are needed to increase awareness of cervical cancer screening and address concerns related to HPV self-sampling. Engagement with healthcare providers, organizations, and media channels that serve Vietnamese communities may be effective since Vietnamese immigrants often receive health-related information from these sources. It is necessary to explore the perceptions of younger immigrants and U.S.-born Vietnamese women to inform efforts that can improve screening uptake in all Vietnamese women; focus groups and interviews of these women are underway. Citation Format: Minh T. Phung, Ivy Nguyen, Bethany Nguyen, Hailey Nguyen, Becky Nguyen, Dung Hua, Celeste L. Pearce, Alice W. Lee. Insight into cervical cancer screening and HPV self-sampling among Vietnamese immigrants in Southern California [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A144.

Healthcare Service Delivery and Patients’ Satisfaction in Public Hospitals in Akwa Ibom State

This study is centred on healthcare service delivery and patients’ satisfaction in public hospitals in Akwa Ibom State. We formulated two specific objectives and hypotheses to guide this investigation. We also adopted a cross-sectional research approach and selected the respondents using simple random sampling. Given the study's infinite population, we used the Topman formula to determine the sample size. The data assembled from the participants was analysed using the simple linear regression technique. Findings from the study demonstrated that patient waiting time (PWT) and healthcare provider-patient communication (HCP-PC) have positive and significant effects on patient satisfaction in selected public hospitals in Akwa Ibom State, Nigeria. The researcher’s conclusion is that healthcare service delivery has a significant positive effect on patients’ healthcare satisfaction in the studied public hospitals in Akwa Ibom State. Based on these findings, public hospitals should prioritise the proper management of patient administrative concerns, as this could potentially reduce patient waiting times. Given that patients place their trust in healthcare workers, it is important for healthcare providers in the studied public hospitals to respect their private healthcare information.

The use of medicine retailers by people of Goma as an alternative healthcare provider: a risky but rational practice

BackgroundMedicine retailers, considered here as any person or setting dedicated to the sale of retail medicines, fill an important gap in terms of access to healthcare in areas where population are not covered by universal healthcare schemes. In Goma in the Democratic Republic of the Congo, such retailers have proliferated and are consulted as the first port of call by more than half of the population, playing therefore a key role as an alternative source of healthcare for any type of health condition. The objective of this study is to understand people of Goma’s rationale for using the medicine retailers over the formal healthcare system.MethodsTwelve focus groups, gathering 147 participants in total, were conducted in four worship communities, covering the most common faiths practised in Goma. Three focus group discussions were organised per worship community: one with fathers, another with mothers, and another with chronic patients and/or highly vulnerable people. We used a qualitative and inductive approach to analyse the participants’ practices and perceptions in terms of their use of medicine retailers. We identified central categories explaining the reasons for using medicine retailers and the choice of a specific medicine retailer.ResultsWhen facing a health problem, most of the participants in our study tended to first buy medicines at medicine retailers because it was cheap, quick, and easily accessible. Most were aware of the risks and limitations of such practices and had developed a number of mitigation strategies in order to reduce those risks: evaluating medicine retailers’ expertise; developing a “medical expertise”; and seeking proactively out empathetic care.ConclusionsPeople in Goma make a conscious and rational choice when resorting to medicine retailers as it is seen as the least-worst option in a complex situation. In order to reduce the risks, they have developed a number of mitigation strategies. Future research should focus on the organisation of medicine retailers as a professional group to improve their supervision in a sensitive context such as Goma and on modalities to articulate them to the formal health system to guarantee a financial accessibility to healthcare for all.

Use of Digital Technologies for the Conduct of Work in the Government System Based on the Demans of the Current Times

This article deals with the issues of ensuring the safety of the population in the residences of citizens. It is planned to implement an electronic platform that allows for quick collection and analysis of information on the technical and social condition of residential areas. These strategies focus on digital transformation in the national economy, industry, and society. In Uzbekistan, significant steps have been taken to implement modern information and communication technologies (ICT) in public administration, education, healthcare, and agriculture. One notable challenge addressed in this study is the management of carbon monoxide poisoning, fire hazards, and explosions during the heating season. The research highlights the limitations of manual data collection, including the risk of data loss, difficulty in locating information, and inefficiencies in processing critical safety data. The program processes data in less than a minute, facilitating more efficient emergency management and preventive measures. This system exemplifies the role of digital technology in enhancing public safety and optimizing government operations.

Use of Creative Frameworks in Health Care to Solve Data and Information Problems: Scoping Review.

Digitization is vital for data management, especially in health care. However, problems still hinder health care stakeholders in their daily work while collecting, processing, and providing health data or information. Data are missing, incorrect, cannot be collected, or information is inadequately presented. These problems can be seen as data or information problems. A proven way to elicit requirements for (software) systems is by using creative frameworks (eg, user-centered design, design thinking, lean UX [user experience], or service design) or creative methods (eg, mind mapping, storyboarding, 6 thinking hats, or interaction room). However, to what extent they are used to solve data or information-related problems in health care is unclear. The primary objective of this scoping review is to investigate the use of creative frameworks in addressing data and information problems in health care. Following JBI guidelines and the PRISMA-ScR framework, this paper analyzes selected papers, answering whether creative frameworks addressed health care data or information problems. Focusing on data problems (elicitation or collection, processing) and information problems (provision or visualization), the review examined German and English papers published between 2018 and 2022 using keywords related to "data," "design," and "user-centered." The database SCOPUS was used. Of the 898 query results, only 23 papers described a data or information problem and a creative method to solve it. These were included in the follow-up analysis and divided into different problem categories: data collection (n=7), data processing (n=1), information visualization (n=11), and mixed problems meaning data and information problem present (n=4). The analysis showed that most identified problems fall into the information visualization category. This could indicate that creative frameworks are particularly suitable for solving information or visualization problems and less for other, more abstract areas such as data problems. The results also showed that most researchers applied a creative framework after they knew what specific (data or information) problem they had (n=21). Only a minority chose a creative framework to identify a problem and realize it was a data or information problem (n=2). In response to these findings, the paper discusses the need for a new approach that addresses health care data and information challenges by promoting collaboration, iterative feedback, and user-centered development. Although the potential of creative frameworks is undisputed, applying these in solving data and information problems is a minority. To harness this potential, a suitable method needs to be developed to support health care system stakeholders. This method could be the User-Centered Data Approach.

The critical need for expert oversight of ChatGPT: Prompt engineering for safeguarding child healthcare information.

ChatGPT and other large language models have the potential to transform the health information landscape online. However, lack of domain-specific expertise and known errors in large language models raise concerns about the widespread adoption of content generated by these tools for parents making healthcare decisions for their children. The aim of this study is to determine if health-related text generated by ChatGPT under the supervision of an expert is comparable to that generated by an expert regarding persuasiveness and credibility from the perspective of a parent. In a cross-sectional study 116 parents aged 18-65 years (M = 45.02, SD = 10.92) were asked to complete a baseline assessment of their behavioral intentions regarding pediatric healthcare topics. Subsequently, participants were asked to rate text generated by either an expert or by ChatGPT under supervision of an expert. Results indicate that prompt engineered ChatGPT is capable of impacting behavioral intentions for medication, sleep, and diet decision-making. Additionally, there was little distinction between prompt engineered ChatGPT and content experts on perceived morality, trustworthiness, expertise, accuracy, and reliance. Notably, when differences were present, prompt engineered ChatGPT was rated as higher in trustworthiness and accuracy, and participants indicated they would be more likely to rely on the information presented by prompt engineered ChatGPT compared to the expert. Given that parents will trust and rely on information generated by ChatGPT, it is critically important that human domain-specific expertise be applied to healthcare information that will ultimately be presented to consumers (e.g., parents).

A trial of a chat service for patients and their family members in an emergency department

BackgroundEffective communication between patients and healthcare providers in the emergency department (ED) is challenging due to the dynamic nature of the ED environment. This study aimed to trial a chat service enabling patients in the ED and their family members to ask questions freely, exploring the service’s feasibility and user experience.ObjectivesTo identify the types of needs and inquiries from patients and family members in the ED that could be addressed through the chat service and to assess the user experience of the service.MethodsWe enrolled patients and family members aged over 19 years in the ED, providing the chat service for up to 4 h per ED visit. Trained research nurses followed specific guidelines to respond to messages from the participants. After participation, participants were required to complete a survey. Those who agreed also participated in interviews to provide insights on their experiences with the ED chat service.ResultsA total of 40 participants (20 patients and 20 family members) sent 305 messages (72 by patients and 233 by family members), with patients sending an average of 3.6 messages and family members 11.7. Research nurses resolved 41.4% of patient inquiries and 70.9% of family member inquiries without further healthcare provider involvement. High usability was reported, with positive feedback on communication with healthcare workers, information accessibility, and emotional support.ConclusionsThe ED chat service was found to be feasible and led to positive user experiences for both patients and their family members.

Exploring women’s knowledge of abortion legality and association with source of abortion care using population-based survey data in Côte d’Ivoire and Ghana

BackgroundKnowledge of the conditions under which abortion is legal is important so that people can advocate for their right to abortion care. Yet minimal research has explored the association between women’s knowledge of abortion legality and the induced abortion care they receive, particularly using population-based survey data.MethodsUsing national survey data collected by Performance Monitoring for Action (PMA) in Côte d’Ivoire and Ghana, we aimed to compare the prevalence of accurate knowledge of abortion legality, factors associated with knowledge of the law, and the association between knowledge of abortion legality and the source of women’s induced abortion care in these two settings. We ran bivariate and multivariable logistic regressions to assess the relationships of interest.ResultsWe found that awareness and knowledge of the abortion law were low in both Côte d’Ivoire and Ghana. In Cote d’Ivoire, women who were older, more educated, and with past abortion experience were more likely to be aware of the law. In Ghana, knowledge of the law did not vary significantly by demographic characteristics. However, in Ghana, knowledge of the law was correlated with women’s use of the formal healthcare system for abortion care, with greater use of clinical sources in rural areas.ConclusionsIt is possible that for populations with reduced access to abortion services, such as those in rural areas, knowledge of the law is advantageous for those seeking facility-based abortion care, particularly in settings where abortion is legal for a range of indications. Interventions seeking to improve access to facility-based abortion care in settings where abortion is legal on various grounds should incorporate education on the legal grounds for abortion.

CUREMA project: a further step towards malaria elimination among hard-to-reach and mobile populations

BackgroundIn most countries engaged on the last mile towards malaria elimination, residual transmission mainly persists among vulnerable populations represented by isolated and mobile (often cross-border) communities. These populations are sometimes involved in informal or even illegal activities. In regions with Plasmodium vivax transmission, the specific biology of this parasite poses additional difficulties related to the need for a radical treatment against hypnozoites to prevent relapses. Among hard-to-reach communities, case management, a pillar of elimination strategy, is deficient: acute malaria attacks often occur in remote areas, where there is limited access to care, and drugs acquired outside formal healthcare are often inadequately used for treatment, which typically does not include radical treatment against P. vivax. For these reasons, P. vivax circulation among these communities represents one of the main challenges for malaria elimination in many non-African countries. The objective of this article is to describe the protocol of the CUREMA study, which aims to meet the challenge of targeting malaria in hard-to-reach populations with a focus on P. vivax.ResultsCUREMA is a multi-centre, international public health intervention research project. The study population is represented by persons involved in artisanal and small-scale gold mining who are active and mobile in the Guiana Shield, deep inside the Amazon Forest. The CUREMA project includes a complex intervention composed of a package of actions: (1) health education activities; (2) targeted administration of treatment against P. vivax after screening against G6PD deficiency to asymptomatic persons considered at risk of silently carrying the parasite; (3) distribution of a self-testing and self-treatment kit (malakit) associated with user training for self-management of malaria symptoms occurring while in extreme isolation. These actions are offered by community health workers at settlements and neighbourhoods (often cross-border) that represent transit and logistic bases of gold miners. The study relies on hybrid design, aiming to evaluate both the effectiveness of the intervention on malaria transmission with a pre/post quasi-experimental design, and its implementation with a mixed methods approach.ConclusionsThe purpose of this study is to experiment an intervention that addresses both Plasmodium falciparum and P. vivax malaria elimination in a mobile and isolated population and to produce results that can be transferred to many contexts facing the same challenges around the world.

Outcomes of the Health Data Research Network (HDRN) Canada and Canadian Longitudinal Study on Aging (CLSA) Partnership

Objective and ApproachThe Canadian Longitudinal Study on Aging (CLSA) is the largest national longitudinal cohort study, following ~50,000 adults across 10 provinces for at least 20 years. Health Data Research Network (HDRN) Canada is a distributed pan-Canadian network including members in all 13 provinces and territories. In February 2021, the organizations partnered with the objective to provide researchers with efficient access to multi-regional CLSA data linked to other health/health-related data through HDRN Canada’s data centres. A Steering Committee was convened including representatives from all parties to oversee the process from data sharing agreements (DSAs), negotiating terms of access, through to data transfer and linkage. ResultsIn Spring 2024, linkage was complete at four data centres (Ontario, New Brunswick, British Columbia, and Nova Scotia), with a DSA also in place for Newfoundland and Labrador. DSAs are nearing approval at three others (Manitoba, Prince Edward Island, and Quebec), and in progress in Alberta. Saskatchewan is working towards participation. ConclusionsThe HDRN Canada-CLSA partnership is on the way to making linked provincial CLSA cohort data available in all participating jurisdictions, facilitated by streamlined agreements and processes. ImplicationsCollaborative efforts of organizations such as HDRN Canada and CLSA to foster data linkages and streamline data access at a multi-regional level offers an unparalleled opportunity to explore the intersection between aging and health care utilization. Research enabled by this initiative will inform health care decision making and evidence-based policy development at multiple levels, from the individual to multiple levels of government.

HARNESSING BIG DATA AND MACHINE LEARNING FOR TRANSFORMATIVE HEALTHCARE INFORMATION MANAGEMENT

This study explores the transformative impact of big data and machine learning (ML) on healthcare information management, drawing insights from a comprehensive review of 50 peer-reviewed articles published between 2010 and 2023. The analysis highlights significant advancements in predictive analytics, with ML models improving disease prediction accuracy by up to 40% compared to traditional methods, as demonstrated in multiple studies. Personalized medicine has also benefited, with ML-driven treatment plans showing a 25% improvement in chronic disease management and a 15% reduction in treatment failures, as reported in several case studies. Additionally, integrating big data and ML into healthcare operations has led to a 35% reduction in patient wait times and a 20% decrease in hospital readmissions. However, challenges such as data fragmentation, privacy concerns, and algorithmic bias were identified in over 60% of the reviewed studies, indicating the need for stronger regulatory frameworks. This review underscores the potential of big data and ML to revolutionize healthcare while also calling attention to the ethical and practical challenges that must be addressed to ensure equitable and transparent healthcare solutions.

Online Patient Education in Obstructive Sleep Apnea: ChatGPT versus Google Search.

The widespread implementation of artificial intelligence technologies provides an appealing alternative to traditional search engines for online patient healthcare education. This study assessed ChatGPT-3.5's capabilities as a source of obstructive sleep apnea (OSA) information, using Google Search as a comparison. Ten frequently searched questions related to OSA were entered into Google Search and ChatGPT-3.5. The responses were assessed by two independent researchers using the Global Quality Score (GQS), Patient Education Materials Assessment Tool (PEMAT), DISCERN instrument, CLEAR tool, and readability scores (Flesch Reading Ease and Flesch-Kincaid Grade Level). ChatGPT-3.5 significantly outperformed Google Search in terms of GQS (5.00 vs. 2.50, p < 0.0001), DISCERN reliability (35.00 vs. 29.50, p = 0.001), and quality (11.50 vs. 7.00, p = 0.02). The CLEAR tool scores indicated that ChatGPT-3.5 provided excellent content (25.00 vs. 15.50, p < 0.001). PEMAT scores showed higher understandability (60-91% vs. 44-80%) and actionability for ChatGPT-3.5 (0-40% vs. 0%). Readability analysis revealed that Google Search responses were easier to read (FRE: 56.05 vs. 22.00; FKGL: 9.00 vs. 14.00, p < 0.0001). ChatGPT-3.5 delivers higher quality and more comprehensive OSA information compared to Google Search, although its responses are less readable. This suggests that while ChatGPT-3.5 can be a valuable tool for patient education, efforts to improve readability are necessary to ensure accessibility and utility for all patients. Healthcare providers should be aware of the strengths and weaknesses of various healthcare information resources and emphasize the importance of critically evaluating online health information, advising patients on its reliability and relevance.

Unbiased care, unequal outcomes: a nursing telehealth intervention reveals systematic inequities in COVID-19 care delivery

BackgroundThe Covid Connected Care Center (C4), a low-barrier telephone nurse hotline, was developed at an academic medical center to increase access to healthcare information and services across the state of Oregon, including to those without a usual source of care. Other studies have demonstrated that telephone triage services can positively influence health behaviors, but it is not known how this effect is maintained across racial/ethnic groups. The objective of this study was to show that the C4 reached throughout the state of Oregon, was valuable to callers, and that recommendations given affected callers’ subsequent health-related behaviors.MethodsThis mixed-methods study, informed by the RE-AIM (Reach, Effectiveness, Addoption, Implementation and Maintenance) framework, assessed caller demographics and clinical care from March 30 2020 until September 8, 2021. Descriptive statistics, multivariable risk models and Zou’s modified Poisson modeling were applied to electronic health record and call system data; An inductive approach was used for patient and staff experience surveys and semi-structured interviews. Approval was obtained from the OHSU Institutional Review Board (Study 00021413).Results145,537 telephone calls and 92,100 text-based contacts (61% and 39%, respectively) were included. Callers tended to not have a usual source of primary care and utilized recommended services. Emergency department utilization was minimal (1.5%). Racial or ethnic disparities were not detected in the recommendations, but Black (RR 0.92, CI 0.86–0.98) and Multiracial (RR 0.90 CI 0.81–0.99) callers were less likely than non-Hispanic white callers to receive a COVID-19 test. Participants in the post-call survey (n = 50) would recommend this service to friends or family. Interviews with callers (n = 9) revealed this was because they valued assistance translating general recommendations into a personalized care plan. C4 staff interviewed (n = 9) valued the opportunity to serve the public. The C4 was a trusted resource to the public and reached the intended audiences. However, disparities in access to COVID-19 testing persisted.ConclusionsNursing triage hotlines can guide caller behavior and be an effective part of a robust public health information infrastructure.