Online journal of public health informatics最新文献

{"title":"Evaluating multi-purpose syndromic surveillance systems - a complex problem.","authors":"Roger Morbey,&nbsp;Gillian Smith,&nbsp;Isabel Oliver,&nbsp;Obaghe Edeghere,&nbsp;Iain Lake,&nbsp;Richard Pebody,&nbsp;Dan Todkill,&nbsp;Noel McCarthy,&nbsp;Alex J Elliot","doi":"10.5210/ojphi.v13i3.10818","DOIUrl":"https://doi.org/10.5210/ojphi.v13i3.10818","url":null,"abstract":"<p><p>Surveillance systems need to be evaluated to understand what the system can or cannot detect. The measures commonly used to quantify detection capabilities are sensitivity, positive predictive value and timeliness. However, the practical application of these measures to multi-purpose syndromic surveillance services is complex. Specifically, it is very difficult to link definitive lists of what the service is intended to detect and what was detected. First, we discuss issues arising from a multi-purpose system, which is designed to detect a wide range of health threats, and where individual indicators, e.g. 'fever', are also multi-purpose. Secondly, we discuss different methods of defining what can be detected, including historical events and simulations. Finally, we consider the additional complexity of evaluating a service which incorporates human decision-making alongside an automated detection algorithm. Understanding the complexities involved in evaluating multi-purpose systems helps design appropriate methods to describe their detection capabilities.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"13 3","pages":"E15"},"PeriodicalIF":0.0,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8765799/pdf/ojphi-13-3-e15.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39862554","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":"Syndromic Surveillance Data for Accidental Fall Injury.","authors":"Donald E Brannen,&nbsp;Melissa Howell,&nbsp;Ashley Steveley,&nbsp;Jeff Webb,&nbsp;Deidre Owsley","doi":"10.5210/ojphi.v13i3.10264","DOIUrl":"https://doi.org/10.5210/ojphi.v13i3.10264","url":null,"abstract":"<p><strong>Background: </strong>Fall injuries (FI) are a priority for public health planning. Syndromic surveillance (SS) is used to detect outbreaks, environmental exposures, and bioterrorism in real time. Since information is gathered on patients, the utility of using this system for FI should be evaluated.</p><p><strong>Methods: </strong>Strategies to integrate FI medical and SS data were compared using a cohort versus case control (CC) study design.</p><p><strong>Results: </strong>The CC study was accurate 77.7% (57.7-91.3) of the time versus 100% for a cohort design. The CC study design found FI increased for older age groups, female gender, November, and December months. Dates with any freezing temperature had a higher case fatality rate. Repeat acute care visits increased the risk of FI diagnosis by over 6% and trended upward with each visit (R=.333, p<.001).</p><p><strong>Conclusions: </strong>The CC diagnostic quality of FI were better for age and gender than for area. The CC study found the indicators of increased risk of FI including freezing temperature, repeat acute care visits, older age groups, female gender, November, and December months. A gradient of increasing odds of FI with the number of acute care visits provides proof that community fall prevention programs should focus on those most likely to fall. A CC design of SS data can quickly identify indicators of FI with a lower accuracy but with less cost than a full cohort study, thus providing a method to focus local public health interventions.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"13 3","pages":"e18"},"PeriodicalIF":0.0,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769255/pdf/ojphi-13-3-e18.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39859245","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":"A Virtual Data Repository Stimulates Data Sharing in a Consortium.","authors":"Suzanne Siminski,&nbsp;Soyeon Kim,&nbsp;Adel Ahmed,&nbsp;Jake Currie,&nbsp;Alex Benns,&nbsp;Amy Ragsdale,&nbsp;Marjan Javanbakht,&nbsp;Pamina M Gorbach","doi":"10.5210/ojphi.v13i3.10878","DOIUrl":"https://doi.org/10.5210/ojphi.v13i3.10878","url":null,"abstract":"<p><p>Research data may have substantial impact beyond the original study objectives. The Collaborating Consortium of Cohorts Producing NIDA Opportunities (C3PNO) facilitates the combination of data and access to specimens from nine NIDA-funded cohorts in a virtual data repository (VDR). Unique challenges were addressed to create the VDR. An initial set of common data elements was agreed upon, selected based on their importance for a wide range of research proposals. Data were mapped to a common set of values. Bioethics consultations resulted in the development of various controls and procedures to protect against inadvertent disclosure of personally identifiable information. Standard operating procedures govern the evaluation of proposed concepts, and specimen and data use agreements ensure proper data handling and storage. Data from eight cohorts have been loaded into a relational database with tables capturing substance use, available specimens, and other participant data. A total of 6,177 participants were seen at a study visit within the past six months and are considered under active follow-up for C3PNO cohort participation as of the third data transfer, which occurred in January 2020. A total of 70,391 biospecimens of various types are available for these participants to test approved scientific hypotheses. Sociodemographic and clinical data accompany these samples. The VDR is a web-based interactive, searchable database available in the public domain, accessed at www.c3pno.org. The VDR are available to inform both consortium and external investigators interested in submitting concept sheets to address novel scientific questions to address high priority research on HIV/AIDS in the context of substance use.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"13 3","pages":"e19"},"PeriodicalIF":0.0,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769254/pdf/ojphi-13-3-e19.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39859246","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":"Leveraging Data and Digital Health Technologies to Assess and Impact Social Determinants of Health (SDoH): a State-of-the-Art Literature Review.","authors":"Kelly J Thomas Craig,&nbsp;Nicole Fusco,&nbsp;Thrudur Gunnarsdottir,&nbsp;Luc Chamberland,&nbsp;Jane L Snowdon,&nbsp;William J Kassler","doi":"10.5210/ojphi.v13i3.11081","DOIUrl":"https://doi.org/10.5210/ojphi.v13i3.11081","url":null,"abstract":"<p><strong>Objective: </strong>Identify how novel datasets and digital health technology, including both analytics-based and artificial intelligence (AI)-based tools, can be used to assess non-clinical, social determinants of health (SDoH) for population health improvement.</p><p><strong>Methods: </strong>A state-of-the-art literature review with systematic methods was performed on MEDLINE, Embase, and the Cochrane Library databases and the grey literature to identify recently published articles (2013-2018) for evidence-based qualitative synthesis. Following single review of titles and abstracts, two independent reviewers assessed eligibility of full-texts using predefined criteria and extracted data into predefined templates.</p><p><strong>Results: </strong>The search yielded 2,714 unique database records of which 65 met inclusion criteria. Most studies were conducted retrospectively in a United States community setting. Identity, behavioral, and economic factors were frequently identified social determinants, due to reliance on administrative data. Three main themes were identified: 1) improve access to data and technology with policy - advance the standardization and interoperability of data, and expand consumer access to digital health technologies; 2) leverage data aggregation - enrich SDoH insights using multiple data sources, and use analytics-based and AI-based methods to aggregate data; and 3) use analytics-based and AI-based methods to assess and address SDoH - retrieve SDoH in unstructured and structured data, and provide contextual care management sights and community-level interventions.</p><p><strong>Conclusions: </strong>If multiple datasets and advanced analytical technologies can be effectively integrated, and consumers have access to and literacy of technology, more SDoH insights can be identified and targeted to improve public health. This study identified examples of AI-based use cases in public health informatics, and this literature is very limited.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"13 3","pages":"E14"},"PeriodicalIF":0.0,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8765800/pdf/ojphi-13-3-e14.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39862553","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":"Commentary: Does Twitter have a role in improving Family Planning messages and services in Low-and-Middle-Income Countries (LMICs)?","authors":"Denise Harrison,&nbsp;Saumya RamaRao,&nbsp;Dinesh Vijeyakumar,&nbsp;James McKinnon,&nbsp;Kristina Brown,&nbsp;Stanley Mierzwa","doi":"10.5210/ojphi.v13i2.11094","DOIUrl":"https://doi.org/10.5210/ojphi.v13i2.11094","url":null,"abstract":"<p><p>Stakeholders are coming together to develop a vision for increasing access to family planning (FP) by 2030. Of the 923 million women in the developing world who wish to avoid a pregnancy, 218 million women are not using a modern contraceptive (Guttmacher Institute, 2020). In 2016, over 3.4 billion people were using the internet (https://ourworldindata.org/internet 2016). Moreover, internet users in the developing world use social media more frequently than Internet users in the U.S. and Europe. Of the many proposed actions to accelerate progress in family planning, the use of Twitter should be a key component. In this commentary, we describe the use of Twitter in a select group of low-and-middle-income countries that have made commitments to the family planning 2020 initiative (FP2020 countries and have the potential to leverage Twitter with current and potential family planning users. We examine Twitter feeds in eight key FP2020 countries, and we look at the content of Tweets issued by the ministries of health in most of these same countries. Our view is that it is feasible and easy to access Twitter feeds in low-and -middle income countries. We base our view on the types of reproductive health and family planning terms discussed in a public forum such as Twitter by current and potential users and their partners and ministries of health. We highlight two broad considerations that merit discussion among interested stakeholders, including policy makers, program designers, and health advocates. The first relates to the use of Twitter within family planning programs, and the second relates to themes that require more significant research. Data coupled with analytical capacity will help policy makers and program designers to effectively leverage Twitter for expanding the reach of family planning services and influencing social media policy. Our aim is to not only to contribute to the body of knowledge but also to spur greater engagement by program personnel, researchers, health advocates and contraceptive users.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"13 2","pages":"e11"},"PeriodicalIF":0.0,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8500783/pdf/ojphi-13-2-e11.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39527842","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":"Visual Analytics of Tuberculosis Detection Rat Performance.","authors":"Joan Jonathan,&nbsp;Camilius Sanga,&nbsp;Magesa Mwita,&nbsp;Georgies Mgode","doi":"10.5210/ojphi.v13i2.11465","DOIUrl":"https://doi.org/10.5210/ojphi.v13i2.11465","url":null,"abstract":"<p><p>The diagnosis of tuberculosis (TB) disease remains a global challenge, and the need for innovative diagnostic approaches is inevitable. Trained African giant pouched rats are the scent TB detection technology for operational research. The adoption of this technology is beneficial to countries with a high TB burden due to its cost-effectiveness and speed than microscopy. However, rats with some factors perform better. Thus, more insights on factors that may affect performance is important to increase rats' TB detection performance. This paper intends to provide understanding on the factors that influence rats TB detection performance using visual analytics approach. Visual analytics provide insight of data through the combination of computational predictive models and interactive visualizations. Three algorithms such as Decision tree, Random Forest and Naive Bayes were used to predict the factors that influence rats TB detection performance. Hence, our study found that age is the most significant factor, and rats of ages between 3.1 to 6 years portrayed potentiality. The algorithms were validated using the same test data to check their prediction accuracy. The accuracy check showed that the random forest outperforms with an accuracy of 78.82% than the two. However, their accuracies difference is small. The study findings may help rats TB trainers, researchers in rats TB and Information systems, and decision makers to improve detection performance. This study recommends further research that incorporates gender factors and a large sample size.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"13 2","pages":"e12"},"PeriodicalIF":0.0,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8500793/pdf/ojphi-13-2-e12.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39527843","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":"Developing Evidence-based Population Health Informatics curriculum: Integrating competency based model and job analysis.","authors":"Ashish Joshi,&nbsp;Irene Bruce,&nbsp;Chioma Amadi,&nbsp;Jaya Amatya","doi":"10.5210/ojphi.v13i1.11517","DOIUrl":"https://doi.org/10.5210/ojphi.v13i1.11517","url":null,"abstract":"<p><p>With the rapid pace of technological advancements, public health professions require a core set of informatics skills. The objective of the study is to integrate informatics competencies and job analysis to guide development of an evidence-based curriculum framework and apply it towards creation of a population health informatics program. We conducted content analysis of the Population Health Informatics related job postings in the state of New York between June and July 2019 using the Indeed job board. The search terms included \"health informatics\" and \"population health informatics.\" The initial search yielded 496 job postings. After removal of duplicates, inactive postings and that did not include details of the positions' responsibilities resulted in 306 jobs. Information recorded from the publicly available job postings included job categories, type of hiring organization, educational degree preferred and required, work experience preferred and required, salary information, job type, job location, associated knowledge, skills and expertise and software skills. Most common job title was that of an analyst (21%, n=65) while more than one-third of the hiring organizations were health systems (35%, n=106). 95% (n=291) of the jobs were fulltime and nearly half of these jobs were in New York City (47%, n=143). Data/statistical analysis (68%, n=207), working in multidisciplinary teams (35%, n=108), and biomedical/clinical experience (30%, n=93) were the common skills needed. Structured query language (SQL), Python, and R language were common programming language skills. A broad framework of integrating informatics competencies, combined with analysis of the skills the jobs needed, and knowledge acquisition based on global health informatics projects guided the development of an online population health informatics curriculum in a rapidly changing technological environment.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"13 1","pages":"e10"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8238051/pdf/ojphi-13-e10.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39149553","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":"Design Thinking to Create a Remote Patient Monitoring Platform for Older Adults' Homes.","authors":"H A Kolnick,&nbsp;Jennifer E Miller,&nbsp;Olivia Dupree,&nbsp;Lisa Gualtieri","doi":"10.5210/ojphi.v13i1.11582","DOIUrl":"https://doi.org/10.5210/ojphi.v13i1.11582","url":null,"abstract":"<p><p>How might clinicians collect the vitals needed for effective scheduled video visits for older adults? This challenge was presented by AARP to graduate students in a Digital Health course at Tufts University School of Medicine. The design thinking process was used to create a product that would meet this need, keeping the needs and constraints of older adults, especially those with chronic conditions or other barriers to health, central to the solution. The initial steps involved understanding and empathizing with the target audience through interviews and by developing personas and scenarios that identified barriers and opportunities. The later steps were to ideate potential solutions, design a prototype, and define product success. The design thinking process led to the design of Home Health Hub, a remote patient monitoring (RPM) platform designed to meet the unique needs of older adults. Additionally, Home Health Hub can conceivably benefit all users of telehealth, regardless of health status-an important need during the COVID-19 pandemic, and in general due to increased use of virtual visits. Home Health Hub is one example of what can be achieved with the dedicated use of design thinking. The design thinking process can benefit public health practice as a whole by encouraging practitioners to delve into a problem to find the root causes and empathize with the needs and constraints of stakeholders to design innovative, human-centered solutions.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"13 1","pages":"e9"},"PeriodicalIF":0.0,"publicationDate":"2021-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8216651/pdf/ojphi-13-1-e9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39113814","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":"WA Notify: the planning and implementation of a Bluetooth exposure notification tool for COVID-19 pandemic response in Washington State.","authors":"Tiffany Chen,&nbsp;Janet Baseman,&nbsp;William B Lober,&nbsp;Debra Revere,&nbsp;Rebecca Hills,&nbsp;Nola Klemfuss,&nbsp;Bryant T Karras","doi":"10.5210/ojphi.v13i1.11694","DOIUrl":"https://doi.org/10.5210/ojphi.v13i1.11694","url":null,"abstract":"<p><p>Bluetooth exposure notification tools for mobile phones have emerged as one way to support public health contact tracing and mitigate the spread of COVID-19. Many states have launched their own versions of these tools. Washington State's exposure notification tool, WA Notify, became available on November 30, 2020, following a one-month Seattle campus pilot at the University of Washington. By the end of April 2021, 25% of the state's population had activated WA Notify, one of the highest adoption rates in the country. Washington State's formation of an Exposure Notification Advisory Committee, early pilot testing, and use of the EN Express system framework were all important factors in its adoption. Continuous monitoring and willingness to make early adjustments such as switching to automated texting of verification codes have also been important for improving the tool's value. Evaluation work is ongoing to determine and quantify WA Notify's effectiveness, timeliness, and accessibility.</p>","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"13 1","pages":"e8"},"PeriodicalIF":0.0,"publicationDate":"2021-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8216404/pdf/ojphi-13-1-e8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39113813","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":"COVID-19: an Alarm to Move Faster towards \"Smart Hospitals\".","authors":"Seyyed Mohammad Tabatabaei,&nbsp;Marjan Rasoulian Kasrineh,&nbsp;Nahid Sharifzadeh,&nbsp;Moslem Taheri Soodejani","doi":"10.5210/ojphi.v13i1.11515","DOIUrl":"https://doi.org/10.5210/ojphi.v13i1.11515","url":null,"abstract":"While our lifestyle is now influenced by novel technologies, we are challenged by the burden of a mysterious disease called COVID-19. It began from Wuhan, China, in late 2019 and spread rapidly around the world and has caused unprecedented health, social and economic challenges worldwide so far [1]. This virus is mostly transmitted through person-to-person contact; due to the fact that it is mostly transmitted through respiration, it is very contagious and can spread quickly in society [2]. This is why all researchers around the world are trying to find an appropriate solution to control this pandemic and reduce the losses and damages caused by it until a suitable therapeutic solution is reached.","PeriodicalId":74345,"journal":{"name":"Online journal of public health informatics","volume":"13 1","pages":"e7"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8177960/pdf/ojphi-13-1-e7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39014999","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}