Online journal of public health informatics最新文献

{"title":"Facilitators, Barriers, and Potential Impacts of Implementation of e-Pharmacy in India and its Potential Impact on Cost, Quality, and Access to Medicines: Scoping Review.","authors":"Aditi Apte, Heber Rew Bright, Sandeep Kadam, Thambu David Sundarsanam, Sujith J Chandy","doi":"10.2196/51080","DOIUrl":"10.2196/51080","url":null,"abstract":"<p><strong>Background: </strong>e-Pharmacy can potentially solve problems related to the quality of services and products, cost, and access to medicines in low- and middle-income countries. This review aims to understand the facilitators and barriers to the implementation of e-pharmacy in India.</p><p><strong>Objective: </strong>This scoping review aimed (1) to understand the facilitators and barriers to the use of e-pharmacy in India and (2) to estimate the potential for e-pharmacy in India for improving access to medication, improving the quality of services and medicines, and decreasing costs of medications.</p><p><strong>Methods: </strong>All published and gray literature from July 1, 2011, to June 30, 2021, relating to e-pharmacy, was searched from MEDLINE, Scopus, ProQuest, and Google using a systematic search strategy.</p><p><strong>Results: </strong>In total, 1464 titles and abstracts were screened, of which 47 full-texts were included in the review. e-Pharmacy can potentially improve access to medications for remote areas, and old and debilitated individuals. e-Pharmacies can enable lean supply chain management, lower cost, and allow easy tracking of dispensed medicines. There is potential for integration of e-pharmacy services into the national program of Bhartiya Jan Aushadhi Pariyojana. However, the country is not adequately regulated to prevent the growth of illicit e-pharmacies. Lack of global accreditation and internet coverage, digital literacy, and transnational access are other challenges.</p><p><strong>Conclusions: </strong>E-pharmacy has the potential to improve universal health coverage in India by improving access to medicines and lowering the overall cost of health care. However, future growth will need specific regulations and accreditation mechanisms.</p><p><strong>Trial registration: </strong>Open Science Forum; https://doi.org/10.17605/OSF.IO/6R9YQ.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"16 ","pages":"e51080"},"PeriodicalIF":0.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11499724/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142395785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mobile Apps for Vaccination Services: Content Analysis and Quality Assessment.","authors":"Chenchen Zhang, Xing Guo, Rui Zhu, Wenjie Hou, Lingmeng Wang, Fuzhi Wang, Li Zhang, Dan Luo","doi":"10.2196/50364","DOIUrl":"10.2196/50364","url":null,"abstract":"<p><strong>Background: </strong>Vaccination services are increasingly in demand by the public, and mobile apps are an effective tool to meet that demand. However, the characteristics and quality of these apps are unknown.</p><p><strong>Objective: </strong>Commonly used vaccination service apps on the market were surveyed with regard to quality, service content, and user experience to evaluate and guide users.</p><p><strong>Methods: </strong>The Qimai Data mobile app data analytics platform was used to search for common vaccination service apps by keyword, and the WeChat and Alipay platforms were searched for apps. The apps included in the study were independently evaluated by two reviewers using the Mobile Application Rating Scale, and the service content and user experience of the apps were analyzed. The intragroup correlation coefficient between raters was used to measure interrater reliability.</p><p><strong>Results: </strong>In the app stores of the four major Android platforms and the iOS app store, 1092 and 207 apps were found, respectively; 189 WeChat applets and 30 Alipay applets were also found. A total of 29 apps was ultimately included in this study according to the inclusion criteria, including 21 independent apps, 4 WeChat applets, and 4 Alipay applets. Significant differences were found between independent apps and applets in terms of the quality score (t_449.57=-5.301; P<.001) and the subjective quality score (z=-4.753; P<.001). No significant differences were found between iOS and Android platforms in terms of the quality score (t₁₄₀₄=-2.55; P=.80) and the subjective quality score (z=-0.137; P=.89). There was good intragroup consistency among the raters.</p><p><strong>Conclusions: </strong>In this study, independent apps and nonindependent apps that rely on social and payment platforms for implementation were included in the vaccination services category. The overall quality of these apps was acceptable. Nonindependent running apps were found to have slightly lower scores and showed room for improvement, and scores for the participatory apps were found to be generally low overall.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"16 ","pages":"e50364"},"PeriodicalIF":0.0,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11487208/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142367755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing Generalizable Real-World Ophthalmic Big Data: Descriptive Analysis of the Bodhya Eye Consortium Model for Collaborative Research.","authors":"Ishaana Sood, Shalinder Sabherwal, Umang Mathur, Elesh Jain, Madhu Bhadauria, Deepshikha Agrawal, Ashi Khurana, Vikas Mittal, Avinash Mahindrakar, Vishal Govindahari, Sucheta Kulkarni, Ken K Nischal","doi":"10.2196/53370","DOIUrl":"10.2196/53370","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Eye care organizations and professionals worldwide are increasingly focusing on bridging the gap between population health and medical practice. Recent advances in genomics and anthropology have revealed that most Indian groups trace their ancestry to a blend of 2 genetically distinct populations: Ancestral North Indians, who share genetic affinities with Central Asians, Middle Easterners, Caucasians, and Europeans; and Ancestral South Indians, genetically distinct from groups outside the Indian subcontinent. Studies conducted among North Indian populations can therefore offer insights that are potentially applicable to these diverse global populations, underscoring significant implications for global health.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The Bodhya Eye Consortium is a collaboration among 8 high-volume nonprofit eyecare organizations from across North India. The consortium aims to harness real-world data consistently and with assured quality for collaborative research. This paper outlines the formation of the consortium as a proposed model for controlled collaborative research among the leading eyecare organizations of North India.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We detail the creation and effective implementation of a consortium following a structured road map that included planning and assessment, establishing an exploratory task force, defining specialty areas, setting objectives and priorities, and conducting a SWOT (strengths, weaknesses, opportunities, and threats) analysis. Central to this process was a comprehensive data audit aimed at standardizing data collection across all participating organizations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The consortium currently comprises 9 organizations, each represented in the governance structure by the Governing Council. Scientific standards for published research are established and overseen by the Scientific Committee, while the Conflict Resolution Committee manages any unresolved disputes. The consortium's working groups, organized by various eyecare specialties, collaborate on research projects through virtual interactions. A foundational step in this process was the organizationwide data audit, which revealed that most organizations complied with accurate and standardized data collection practices. Organizations with deficiencies in data completeness developed action plans to address them. Subsequently, the consortium adopted data collection proformas, contributing to the publication of high-quality manuscripts characterized by low dropout rates.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The collaborative research conducted by the Bodhya Eye Consortium-a group of high-volume eyecare organizations primarily from North India-offers a unique opportunity to contribute to scientific knowledge across various domains of eyecare. By leveraging the established heterogeneity of anthropological and genomic origins within the population, the findings can be generalizable, to some ","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"16 ","pages":"e53370"},"PeriodicalIF":0.0,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11474137/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142333958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Drug and Herbal Medicinal Promotions on Social Media During the COVID-19 Pandemic in Relation to World Health Organization Ethical Criteria and South African Health Products Regulatory Authority Guidelines in South Africa: Cross-Sectional Content Analysis.","authors":"Rujeko Samanthia Chimukuche, Julia Ndlazi, Lucky Thembani Mtolo, Kristien Bird, Janet Seeley","doi":"10.2196/58378","DOIUrl":"10.2196/58378","url":null,"abstract":"<p><strong>Background: </strong>Consideration of ethics in the promotion of medications is essential to safeguard the health of consumers, particularly during health crises. The World Health Organization (WHO) and the South African Health Products Regulatory Authority (SAHPRA) have established stringent standards to ensure the integrity of pharmaceutical promotions and safeguard public health, including advertisements on the internet and social media platforms. However, the dynamic nature of online advertising poses challenges for monitoring and enforcing ethical standards.</p><p><strong>Objective: </strong>The study aimed (1) to examine the COVID-19 drug and medicinal promotions across online platforms and social media from 2020 to 2022 in South Africa and (2) to ensure that drug promotions adhere to ethical guidelines outlined by the WHO and SAPHRA.</p><p><strong>Methods: </strong>A cross-sectional content analysis was conducted to assess drug and medicinal advertisements across various internet and social media platforms. A systematic approach was used to identify and analyze promotional content, focusing on adherence to ethical guidelines outlined by WHO and SAPHRA. Data were collected and analyzed to determine the extent of compliance and identify any potential violations or areas for improvement.</p><p><strong>Results: </strong>A total of 14 online drug advertisements were included in this analysis. Our findings show that most of the drugs advertised did not meet the regulations and guidelines provided by WHO and SAHPRA. There were omissions about active ingredients, proprietary names, adverse drug responses, precautions, and overdosage and adverse drug reactions. Traditional medicines were not fully consistent with the approved WHO ethical criteria data sheet.</p><p><strong>Conclusions: </strong>Our analysis highlights the critical importance of ensuring compliance with ethical guidelines in drug promotions on the internet and social media platforms. There is a need for continued vigilance and enforcement efforts to uphold ethical standards and protect the health of the public. Ongoing monitoring and collaboration between national drug regulatory agencies, pharmaceutical companies, and online platforms will be essential for promoting responsible advertising. In addition, safety monitoring and pharmacovigilance systems for herbal medicinal products are yet to be established.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"16 ","pages":"e58378"},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11447434/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142302826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population Digital Health: Continuous Health Monitoring and Profiling at Scale.","authors":"Naser Hossein Motlagh, Agustin Zuniga, Ngoc Thi Nguyen, Huber Flores, Jiangtao Wang, Sasu Tarkoma, Mattia Prosperi, Sumi Helal, Petteri Nurmi","doi":"10.2196/60261","DOIUrl":"10.2196/60261","url":null,"abstract":"<p><strong>Unstructured: </strong>Our article provides a viewpoint on population digital health - the use of digital health information sourced from Health IoT and wearable devices for population health modeling - as an emerging research initiative for offering an integrated approach for continuous monitoring and profiling of diseases and health conditions at multiple spatial resolutions. Global healthcare systems are increasingly challenged by rising costs as life expectancy and the average age of people increases. Population digital health looks at how wearables, IoT, and AI can offer an alternative approach for understanding health issues within the population, significantly reducing cost and improving the completeness of information collection by current practices, such as electronic health records - including integration with mhealth personal health records - or survey instruments. This significantly improves our collective understanding of public health priorities, including factors affecting disease prevalence, occurrence and risk factors, ultimately helping to design targeted programmatic interventions apt at reducing the cost of healthcare provision and leading to better life quality, also reducing disparities. Realizing this vision requires overcoming several unique challenges, including data quality, availability, sparsity, and social and technical barriers in the use of health technologies. Our article highlights these challenges and offers solutions and empirical evidence to demonstrate how these challenges can be addressed. As population digital health addresses the impact large-scale sensor data collection and AI can have on improving healthcare delivery and society, we sincerely believe the topic is well within the journal's scope and would be highly interesting to its readership. Our experiments using a combination of real-world health IoT data and electronic health records also highlight the potential cross-disciplinary benefits of population digital health and challenge the research community to address the vision and challenges. Therefore, our article serves the dual purpose of challenging the research community and offering insights into the use of AI and sensor data, and how population digital health can serve as a catalyst for further research by the broader research community.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142302827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Public Perceptions of Treating Opioid Use Disorder With Deep Brain Stimulation: Comment Analysis Study.","authors":"Patricia Henegan, Jack Koczara, Robyn Bluhm, Laura Y Cabrera","doi":"10.2196/49924","DOIUrl":"10.2196/49924","url":null,"abstract":"<p><strong>Background: </strong>The number of opioid-related deaths in the United States has more than tripled over the past 7 years, with a steep increase beginning at the same time as the COVID-19 pandemic. There is an urgent need for novel treatment options that can help alleviate the individual and social effects of refractory opioid use disorder (OUD). Deep brain stimulation (DBS), an intervention that involves implanting electrodes in the brain to deliver electrical impulses, is one potential treatment. Currently in clinical trials for many psychiatric conditions, including OUD, DBS's use for psychiatric indications is not without controversy. Several studies have examined ethical issues raised by using DBS to counter treatment-resistant depression, obsessive-compulsive disorder, and eating disorders. In contrast, there has been limited literature regarding the use of DBS for OUD.</p><p><strong>Objective: </strong>This study aims to gain empirical neuroethical insights into public perceptions regarding the use of DBS for OUD, specifically via the analysis of web-based comments on news media stories about the topic.</p><p><strong>Methods: </strong>Qualitative thematic content analysis was performed on 2 Washington Post newspaper stories that described a case of DBS being used to treat OUD. A total of 292 comments were included in the analysis, 146 comments from each story, to identify predominant themes raised by commenters.</p><p><strong>Results: </strong>Predominant themes raised by commenters across the 2 samples included the hopes and expectations with treatment outcomes, whether addiction is a mental health disorder, and issues related to resource allocation. Controversial comments regarding DBS as a treatment method for OUD seemingly decreased when comparing the first printed newspaper story to the second. In comparison, the number of comments relating to therapeutic need increased over time.</p><p><strong>Conclusions: </strong>The general public's perspectives on DBS as a treatment method for OUD elucidated themes via this qualitative thematic content analysis that include overarching sociopolitical issues, positions on the use of technology, and technological and scientific issues. A better understanding of the public perceptions around the use of DBS for OUD can help address misinformation and misperceptions about the use of DBS for OUD, and identify similarities and differences regarding ethical concerns when DBS is used specifically for OUD compared to other psychiatric disorders.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"16 ","pages":"e49924"},"PeriodicalIF":0.0,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364942/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141992544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Vaccine Hesitancy in Taiwan: Temporal, Multilayer Network Study of Echo Chambers Shaped by Influential Users.","authors":"Jason Dean-Chen Yin","doi":"10.2196/65413","DOIUrl":"10.2196/65413","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.2196/55104.].</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"16 ","pages":"e65413"},"PeriodicalIF":0.0,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11362701/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141989673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Making Metadata Machine-Readable as the First Step to Providing Findable, Accessible, Interoperable, and Reusable Population Health Data: Framework Development and Implementation Study.","authors":"David Amadi, Sylvia Kiwuwa-Muyingo, Tathagata Bhattacharjee, Amelia Taylor, Agnes Kiragga, Michael Ochola, Chifundo Kanjala, Arofan Gregory, Keith Tomlin, Jim Todd, Jay Greenfield","doi":"10.2196/65249","DOIUrl":"10.2196/65249","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.2196/56237.].</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"16 ","pages":"e65249"},"PeriodicalIF":0.0,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11358657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141984143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vaccine Hesitancy in Taiwan: Temporal, Multilayer Network Study of Echo Chambers Shaped by Influential Users.","authors":"Jason Dean-Chen Yin","doi":"10.2196/55104","DOIUrl":"10.2196/55104","url":null,"abstract":"<p><strong>Background: </strong>Vaccine hesitancy is a growing global health threat that is increasingly studied through the monitoring and analysis of social media platforms. One understudied area is the impact of echo chambers and influential users on disseminating vaccine information in social networks. Assessing the temporal development of echo chambers and the influence of key users on their growth provides valuable insights into effective communication strategies to prevent increases in vaccine hesitancy. This also aligns with the World Health Organization's (WHO) infodemiology research agenda, which aims to propose new methods for social listening.</p><p><strong>Objective: </strong>Using data from a Taiwanese forum, this study aims to examine how engagement patterns of influential users, both within and across different COVID-19 stances, contribute to the formation of echo chambers over time.</p><p><strong>Methods: </strong>Data for this study come from a Taiwanese forum called PTT. All vaccine-related posts on the \"Gossiping\" subforum were scraped from January 2021 to December 2022 using the keyword \"vaccine.\" A multilayer network model was constructed to assess the existence of echo chambers. Each layer represents either provaccination, vaccine hesitant, or antivaccination posts based on specific criteria. Layer-level metrics, such as average diversity and Spearman rank correlations, were used to measure chambering. To understand the behavior of influential users-or key nodes-in the network, the activity of high-diversity and hardliner nodes was analyzed.</p><p><strong>Results: </strong>Overall, the provaccination and antivaccination layers are strongly polarized. This trend is temporal and becomes more apparent after November 2021. Diverse nodes primarily participate in discussions related to provaccination topics, both receiving comments and contributing to them. Interactions with the antivaccination layer are comparatively minimal, likely due to its smaller size, suggesting that the forum is a \"healthy community.\" Overall, diverse nodes exhibit cross-cutting engagement. By contrast, hardliners in the vaccine hesitant and antivaccination layers are more active in commenting within their own communities. This trend is temporal, showing an increase during the Omicron outbreak. Hardliner activity potentially reinforces their stances over time. Thus, there are opposing forces of chambering and cross-cutting.</p><p><strong>Conclusions: </strong>Efforts should be made to moderate hardliner and influential nodes in the antivaccination layer and to support provaccination users engaged in cross-cutting exchanges. There are several limitations to this study. One is the bias of the platform used, and another is the lack of a comprehensive definition of \"influence.\" To address these issues, comparative studies across different platforms can be conducted, and various metrics of influence should be explored. Additionally, examining the impact of inf","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"16 ","pages":"e55104"},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11344187/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141910198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive Data Analytics in Telecare and Telehealth: Systematic Scoping Review.","authors":"Euan Anderson, Marilyn Lennon, Kimberley Kavanagh, Natalie Weir, David Kernaghan, Marc Roper, Emma Dunlop, Linda Lapp","doi":"10.2196/57618","DOIUrl":"10.2196/57618","url":null,"abstract":"<p><strong>Background: </strong>Telecare and telehealth are important care-at-home services used to support individuals to live more independently at home. Historically, these technologies have reactively responded to issues. However, there has been a recent drive to make better use of the data from these services to facilitate more proactive and predictive care.</p><p><strong>Objective: </strong>This review seeks to explore the ways in which predictive data analytics techniques have been applied in telecare and telehealth in at-home settings.</p><p><strong>Methods: </strong>The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist was adhered to alongside Arksey and O'Malley's methodological framework. English language papers published in MEDLINE, Embase, and Social Science Premium Collection between 2012 and 2022 were considered and results were screened against inclusion or exclusion criteria.</p><p><strong>Results: </strong>In total, 86 papers were included in this review. The types of analytics featuring in this review can be categorized as anomaly detection (n=21), diagnosis (n=32), prediction (n=22), and activity recognition (n=11). The most common health conditions represented were Parkinson disease (n=12) and cardiovascular conditions (n=11). The main findings include: a lack of use of routinely collected data; a dominance of diagnostic tools; and barriers and opportunities that exist, such as including patient-reported outcomes, for future predictive analytics in telecare and telehealth.</p><p><strong>Conclusions: </strong>All papers in this review were small-scale pilots and, as such, future research should seek to apply these predictive techniques into larger trials. Additionally, further integration of routinely collected care data and patient-reported outcomes into predictive models in telecare and telehealth offer significant opportunities to improve the analytics being performed and should be explored further. Data sets used must be of suitable size and diversity, ensuring that models are generalizable to a wider population and can be appropriately trained, validated, and tested.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"16 ","pages":"e57618"},"PeriodicalIF":0.0,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11339581/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141899119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}