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Researchers across the translational research continuum have emphasized the importance of integrating genomics into their research program. To date capacity and resources for genomics research have been limited; however, a recent population-wide genomic screening initiative launched at the Medical University of South Carolina in partnership with Helix has rapidly advanced the need to develop appropriate infrastructure for genomics research at our institution. We conducted a survey with researchers from across our institution (n = 36) to assess current knowledge about genomics health, barriers, and facilitators to uptake, and next steps to support translational research using genomics. We also completed 30-minute qualitative interviews with providers and researchers from diverse specialties (n = 8). Quantitative data were analyzed using descriptive analyses. A rapid assessment process was used to develop a preliminary understanding of each interviewee's perspective. These interviews were transcribed and coded to extract themes. The codes included types of research, alignment with precision health, opportunities to incorporate precision health, examples of researchers in the field, barriers, and facilitators to uptake, educational activity suggestions, questions to be answered, and other observations. Themes from the surveys and interviews inform implementation strategies that are applicable not only to our institution, but also to other organizations interested in making genomic data available to researchers to support genomics-informed translational research., (© Society of Behavioral Medicine 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Objectives: Stressful life events, such as going through divorce, can have an important impact on human health. However, there are challenges in capturing these events in electronic health records (EHR). We conducted a scoping review aimed to answer 2 major questions: how stressful life events are documented in EHR and how they are utilized in research and clinical care., Materials and Methods: Three online databases (EBSCOhost platform, PubMed, and Scopus) were searched to identify papers that included information on stressful life events in EHR; paper titles and abstracts were reviewed for relevance by 2 independent reviewers., Results: Five hundred fifty-seven unique papers were retrieved, and of these 70 were eligible for data extraction. Most articles (n = 36, 51.4%) were focused on the statistical association between one or several stressful life events and health outcomes, followed by clinical utility (n = 15, 21.4%), extraction of events from free-text notes (n = 12, 17.1%), discussing privacy and other issues of storing life events (n = 5, 7.1%), and new EHR features related to life events (n = 4, 5.7%). The most frequently mentioned stressful life events in the publications were child abuse/neglect, arrest/legal issues, and divorce/relationship breakup. Almost half of the papers (n = 7, 46.7%) that analyzed clinical utility of stressful events were focused on decision support systems for child abuse, while others (n = 7, 46.7%) were discussing interventions related to social determinants of health in general., Discussion and Conclusions: Few citations are available on the prevalence and use of stressful life events in EHR reflecting challenges in screening and storing of stressful life events., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Introduction: This study aimed to identify barriers and facilitators to the implementation of family cancer history (FCH) collection tools in clinical practices and community settings by assessing clinicians' perceptions of implementing a chatbot interface to collect FCH information and provide personalized results to patients and providers., Objectives: By identifying design and implementation features that facilitate tool adoption and integration into clinical workflows, this study can inform future FCH tool development and adoption in healthcare settings., Materials and Methods: Quantitative data were collected using survey to evaluate the implementation outcomes of acceptability, adoption, appropriateness, feasibility, and sustainability of the chatbot tool for collecting FCH. Semistructured interviews were conducted to gather qualitative data on respondents' experiences using the tool and recommendations for enhancements., Results: We completed data collection with 19 providers (n = 9, 47%), clinical staff (n = 5, 26%), administrators (n = 4, 21%), and other staff (n = 1, 5%) affiliated with the NCI Community Oncology Research Program. FCH was systematically collected using a wide range of tools at sites, with information being inserted into the patient's medical record. Participants found the chatbot tool to be highly acceptable, with the tool aligning with existing workflows, and were open to adopting the tool into their practice., Discussion and Conclusions: We further the evidence base about the appropriateness of scripted chatbots to support FCH collection. Although the tool had strong support, the varying clinical workflows across clinic sites necessitate that future FCH tool development accommodates customizable implementation strategies. Implementation support is necessary to overcome technical and logistical barriers to enhance the uptake of FCH tools in clinical practices and community settings., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

In 2021, the Medical University of South Carolina (MUSC) launched In Our DNA SC. This large-scale initiative will screen 100,000 individuals in South Carolina for three preventable hereditary conditions that impact approximately two million people in the USA but often go undetected. In anticipation of inevitable changes to the delivery of this complex initiative, we developed an approach to track and assess the impact of evaluate adaptations made during the pilot phase of program implementation. We used a modified version of the Framework for Reporting Adaptations and Modification-Enhanced (FRAME) and Adaptations to code adaptations made during the 3-month pilot phase of In Our DNA SC. Adaptations were documented in real-time using a REDCap database. We used segmented linear regression models to independently test three hypotheses about the impact of adaptations on program reach (rate of enrollment in the program, rate of messages viewed) and implementation (rate of samples collected) 7 days pre- and post-adaptation. Effectiveness was assessed using qualitative observations. Ten adaptations occurred during the pilot phase of program implementation. Most adaptations (60%) were designed to increase the number and type of patient contacted (reach). Adaptations were primarily made based on knowledge and experience (40%) or from quality improvement data (30%). Of the three adaptations designed to increase reach, shortening the recruitment message potential patients received significantly increased the average rate of invitations viewed by 7.3% (p = 0.0106). There was no effect of adaptations on implementation (number of DNA samples collected). Qualitative findings support improvement in effectiveness of the intervention after shortening the consent form and short-term positive impact on uptake of the intervention as measured by team member's participation. Our approach to tracking adaptations of In Our DNA SC allowed our team to quantify the utility of modifications, make decisions about pursuing the adaptation, and understand consequences of the change. Streamlining tools for tracking and responding to adaptations can help monitor the incremental impact of interventions to support continued learning and problem solving for complex interventions being delivered in health systems based on real-time data., (© Society of Behavioral Medicine 2023. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: The annual American College of Medical Informatics (ACMI) symposium focused discussion on the national public health information systems (PHIS) infrastructure to support public health goals. The objective of this article is to present the strengths, weaknesses, threats, and opportunities (SWOT) identified by public health and informatics leaders in attendance., Materials and Methods: The Symposium provided a venue for experts in biomedical informatics and public health to brainstorm, identify, and discuss top PHIS challenges. Two conceptual frameworks, SWOT and the Informatics Stack, guided discussion and were used to organize factors and themes identified through a qualitative approach., Results: A total of 57 unique factors related to the current PHIS were identified, including 9 strengths, 22 weaknesses, 14 opportunities, and 14 threats, which were consolidated into 22 themes according to the Stack. Most themes (68%) clustered at the top of the Stack. Three overarching opportunities were especially prominent: (1) addressing the needs for sustainable funding, (2) leveraging existing infrastructure and processes for information exchange and system development that meets public health goals, and (3) preparing the public health workforce to benefit from available resources., Discussion: The PHIS is unarguably overdue for a strategically designed, technology-enabled, information infrastructure for delivering day-to-day essential public health services and to respond effectively to public health emergencies., Conclusion: Most of the themes identified concerned context, people, and processes rather than technical elements. We recommend that public health leadership consider the possible actions and leverage informatics expertise as we collectively prepare for the future., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Prior authorization (PA) may be a necessary evil within the healthcare system, contributing to physician burnout and delaying necessary care, but also allowing payers to prevent wasting resources on redundant, expensive, and/or ineffective care. PA has become an "informatics issue" with the rise of automated methods for PA review, championed in the Health Level 7 International's (HL7's) DaVinci Project. DaVinci proposes using rule-based methods to automate PA, a time-tested strategy with known limitations. This article proposes an alternative that may be more human-centric, using artificial intelligence (AI) methods for the computation of authorization decisions. We believe that by combining modern approaches for accessing and exchanging existing electronic health data with AI methods tailored to reflect the judgments of expert panels that include patient representatives, and refined with "few shot" learning approaches to prevent bias, we could create a just and efficient process that serves the interests of society as a whole. Efficient simulation of human appropriateness assessments from existing data using AI methods could eliminate burdens and bottlenecks while preserving PA's benefits as a tool to limit inappropriate care., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

The COVID-19 pandemic exposed multiple weaknesses in the nation's public health system. Therefore, the American College of Medical Informatics selected "Rebuilding the Nation's Public Health Informatics Infrastructure" as the theme for its annual symposium. Experts in biomedical informatics and public health discussed strategies to strengthen the US public health information infrastructure through policy, education, research, and development. This article summarizes policy recommendations for the biomedical informatics community postpandemic. First, the nation must perceive the health data infrastructure to be a matter of national security. The nation must further invest significantly more in its health data infrastructure. Investments should include the education and training of the public health workforce as informaticians in this domain are currently limited. Finally, investments should strengthen and expand health data utilities that increasingly play a critical role in exchanging information across public health and healthcare organizations., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: Opioid-related overdose (OD) deaths continue to increase. Take-home naloxone (THN), after treatment for an OD in an emergency department (ED), is a recommended but under-utilized practice. To promote THN prescription, we developed a noninterruptive decision support intervention that combined a detailed OD documentation template with a reminder to use the template that is automatically inserted into a provider's note by decision rules. We studied the impact of the combined intervention on THN prescribing in a longitudinal observational study., Methods: ED encounters involving an OD were reviewed before and after implementation of the reminder embedded in the physicians' note to use an advanced OD documentation template for changes in: (1) use of the template and (2) prescription of THN. Chi square tests and interrupted time series analyses were used to assess the impact. Usability and satisfaction were measured using the System Usability Scale (SUS) and the Net Promoter Score., Results: In 736 OD cases defined by International Classification of Disease version 10 diagnosis codes (247 prereminder and 489 postreminder), the documentation template was used in 0.0% and 21.3%, respectively (P < .0001). The sensitivity and specificity of the reminder for OD cases were 95.9% and 99.8%, respectively. Use of the documentation template led to twice the rate of prescribing of THN (25.7% vs 50.0%, P < .001). Of 19 providers responding to the survey, 74% of SUS responses were in the good-to-excellent range and 53% of providers were Net Promoters., Conclusions: A noninterruptive decision support intervention was associated with higher THN prescribing in a pre-post study across a multiinstitution health system., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

COVID-19 vaccination uptake has been suboptimal, even in high-risk populations. New approaches are needed to bring vaccination data to the groups leading outreach efforts. This article describes work to make state-level vaccination data more accessible by extending the Bulk Fast Healthcare Interoperability Resource (FHIR) standard to better support the repeated retrieval of vaccination data for coordinated outreach efforts. We also describe a corresponding low-foot-print software for population outreach that automates repeated checks of state-level immunization data and prioritizes outreach by social determinants of health. Together this software offers an integrated approach to addressing vaccination gaps. Several extensions to the Bulk FHIR protocol were needed to support bulk query of immunization records. These are described in detail. The results of a pilot study, using the outreach tool to target a population of 1500 patients are also described. The results confirmed the limitations of current patient-by-patient approach for querying state immunizations systems for population data and the feasibility of a Bulk FHIR approach., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Public health faces unprecedented challenges in its efforts to control COVID-19 through a national vaccination campaign. Addressing these challenges will require fundamental changes to public health data systems. For example, of the core data systems for immunization campaigns is the immunization information system (IIS); however, IISs were designed for tracking the vaccinated, not finding the patients who are high risk and need to be vaccinated. Health systems have this data in their electronic health records (EHR) systems and often have a greater capacity for outreach. Clearly, a partnership is needed. However, successful collaborations will require public health to change from its historical hierarchical information supply chain model to an ecosystem model with a peer-to-peer exchange with population health providers. Examples of the types of informatics innovations necessary to support such an ecosystem include a national patient identifier, population-level data exchange for immunization data, and computable electronic quality measures. Rather than think of these components individually, a comprehensive approach to rapidly adaptable tools for collaboration is needed., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Objective: The rapidly evolving COVID-19 pandemic has created a need for timely data from the healthcare systems for research. To meet this need, several large new data consortia have been developed that require frequent updating and sharing of electronic health record (EHR) data in different common data models (CDMs) to create multi-institutional databases for research. Traditionally, each CDM has had a custom pipeline for extract, transform, and load operations for production and incremental updates of data feeds to the networks from raw EHR data. However, the demands of COVID-19 research for timely data are far higher, and the requirements for updating faster than previous collaborative research using national data networks have increased. New approaches need to be developed to address these demands., Methods: In this article, we describe the use of the Fast Healthcare Interoperability Resource (FHIR) data model as a canonical data model and the automated transformation of clinical data to the Patient-Centered Outcomes Research Network (PCORnet) and Observational Medical Outcomes Partnership (OMOP) CDMs for data sharing and research collaboration on COVID-19., Results: FHIR data resources could be transformed to operational PCORnet and OMOP CDMs with minimal production delays through a combination of real-time and postprocessing steps, leveraging the FHIR data subscription feature., Conclusions: The approach leverages evolving standards for the availability of EHR data developed to facilitate data exchange under the 21st Century Cures Act and could greatly enhance the availability of standardized datasets for research., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Objective: Integrated, real-time data are crucial to evaluate translational efforts to accelerate innovation into care. Too often, however, needed data are fragmented in disparate systems. The South Carolina Clinical & Translational Research Institute at the Medical University of South Carolina (MUSC) developed and implemented a universal study identifier-the Research Master Identifier (RMID)-for tracking research studies across disparate systems and a data warehouse-inspired model-the Research Integrated Network of Systems (RINS)-for integrating data from those systems., Materials and Methods: In 2017, MUSC began requiring the use of RMIDs in informatics systems that support human subject studies. We developed a web-based tool to create RMIDs and application programming interfaces to synchronize research records and visualize linkages to protocols across systems. Selected data from these disparate systems were extracted and merged nightly into an enterprise data mart, and performance dashboards were created to monitor key translational processes., Results: Within 4 years, 5513 RMIDs were created. Among these were 726 (13%) bridged systems needed to evaluate research study performance, and 982 (18%) linked to the electronic health records, enabling patient-level reporting., Discussion: Barriers posed by data fragmentation to assessment of program impact have largely been eliminated at MUSC through the requirement for an RMID, its distribution via RINS to disparate systems, and mapping of system-level data to a single integrated data mart., Conclusion: By applying data warehousing principles to federate data at the "study" level, the RINS project reduced data fragmentation and promoted research systems integration., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

The ability to analyze human specimens is the pillar of modern-day translational research. To enhance the research availability of relevant clinical specimens, we developed the Living BioBank (LBB) solution, which allows for just-in-time capture and delivery of phenotyped surplus laboratory medicine specimens. The LBB is a system-of-systems integrating research feasibility databases in i2b2, a real-time clinical data warehouse, and an informatics system for institutional research services management (SPARC). LBB delivers deidentified clinical data and laboratory specimens. We further present an extension to our solution, the Living µBiome Bank, that allows the user to request and receive phenotyped specimen microbiome data. We discuss the details of the implementation of the LBB system and the necessary regulatory oversight for this solution. The conducted institutional focus group of translational investigators indicates an overall positive sentiment towards potential scientific results generated with the use of LBB. Reference implementation of LBB is available at https://LivingBioBank.musc.edu., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Objectives: We describe our approach in using health information technology to provide a continuum of services during the coronavirus disease 2019 (COVID-19) pandemic. COVID-19 challenges and needs required health systems to rapidly redesign the delivery of care., Materials and Methods: Our health system deployed 4 COVID-19 telehealth programs and 4 biomedical informatics innovations to screen and care for COVID-19 patients. Using programmatic and electronic health record data, we describe the implementation and initial utilization., Results: Through collaboration across multidisciplinary teams and strategic planning, 4 telehealth program initiatives have been deployed in response to COVID-19: virtual urgent care screening, remote patient monitoring for COVID-19-positive patients, continuous virtual monitoring to reduce workforce risk and utilization of personal protective equipment, and the transition of outpatient care to telehealth. Biomedical informatics was integral to our institutional response in supporting clinical care through new and reconfigured technologies. Through linking the telehealth systems and the electronic health record, we have the ability to monitor and track patients through a continuum of COVID-19 services., Discussion: COVID-19 has facilitated the rapid expansion and utilization of telehealth and health informatics services. We anticipate that patients and providers will view enhanced telehealth services as an essential aspect of the healthcare system. Continuation of telehealth payment models at the federal and private levels will be a key factor in whether this new uptake is sustained., Conclusions: There are substantial benefits in utilizing telehealth during the COVID-19, including the ability to rapidly scale the number of patients being screened and providing continuity of care., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Objective: In an effort to improve the efficiency of computer algorithms applied to screening for coronavirus disease 2019 (COVID-19) testing, we used natural language processing and artificial intelligence-based methods with unstructured patient data collected through telehealth visits., Materials and Methods: After segmenting and parsing documents, we conducted analysis of overrepresented words in patient symptoms. We then developed a word embedding-based convolutional neural network for predicting COVID-19 test results based on patients' self-reported symptoms., Results: Text analytics revealed that concepts such as smell and taste were more prevalent than expected in patients testing positive. As a result, screening algorithms were adapted to include these symptoms. The deep learning model yielded an area under the receiver-operating characteristic curve of 0.729 for predicting positive results and was subsequently applied to prioritize testing appointment scheduling., Conclusions: Informatics tools such as natural language processing and artificial intelligence methods can have significant clinical impacts when applied to data streams early in the development of clinical systems for outbreak response., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Public health needs up-to-date information for surveillance and response. As healthcare application programming interfaces become widely available, a novel data gathering mechanism could provide public health with critical information in a timely fashion to respond to a fast-moving epidemic. In this article, we extrapolate from our experiences using a Fast Healthcare Interoperability Resource-based architecture for infectious disease surveillance for sexually transmitted diseases to its application to gather case information for an outbreak. One of the challenges with a fast-moving outbreak is to accurately assess its demand on healthcare resources, since information specific to comorbidities is often not available. These comorbidities are often associated with poor prognosis and higher resource utilization. If the comorbidity data and other clinical information were readily available to public health workers, they could better address community disruption and manage healthcare resources. The use of FHIR resources available through application programming and filtered through tools such as described herein will give public health the flexibility needed to investigate rapidly emerging disease while protecting patient privacy., (Published by Oxford University Press on behalf of the American Medical Informatics Association 2020. This work is written by US Government employees and is in the public domain in the US.)

The novel coronavirus disease 2019 infection poses serious challenges to the healthcare system that are being addressed through the creation of new unique and advanced systems of care with disjointed care processes (eg, telehealth screening, drive-through specimen collection, remote testing, telehealth management). However, our current regulations on the flows of information for clinical care and research are antiquated and often conflict at the state and federal levels. We discuss proposed changes to privacy regulations such as the Health Insurance Portability and Accountability Act designed to let health information seamlessly and frictionlessly flow among the health entities that need to collaborate on treatment of patients and, also, allow it to flow to researchers trying to understand how to limit its impacts., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: The effects of electronic health records (EHRs) on doctor-patient communication are unclear., Objective: To evaluate the effects of EHR use compared with paper chart use, on novice physicians' communication skills., Design: Within-subjects randomized controlled trial using observed structured clinical examination methods to assess the impact of use of an EHR on communication., Setting: A large academic internal medicine training program., Population: First-year internal medicine residents., Intervention: Residents interviewed, diagnosed, and initiated treatment of simulated patients using a paper chart or an EHR on a laptop computer. Video recordings of interviews were rated by three trained observers using the Four Habits scale., Results: Thirty-two residents completed the study and had data available for review (61.5% of those enrolled in the residency program). In most skill areas in the Four Habits model, residents performed at least as well using the EHR and were statistically better in six of 23 skills areas (p<0.05). The overall average communication score was better when using an EHR: mean difference 0.254 (95% CI 0.05 to 0.45), p = 0.012, Cohen's d of 0.47 (a moderate effect). Residents scoring poorly (>3 average score) with paper methods (n = 8) had clinically important improvement when using the EHR., Limitations: This study was conducted in first-year residents in a training environment using simulated patients at a single institution., Conclusions: Use of an EHR on a laptop computer appears to improve the ability of first-year residents to communicate with patients relative to using a paper chart., (© The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

The Office of the National Coordinator will be defining the architecture of the Nationwide Health Information Network (NWHIN) together with the proposed HealtheWay public/private partnership as a development and funding strategy. There are a number of open questions--for example, what is the best way to realize the benefits of health information exchange? How valuable are regional health information organizations in comparison with a more direct approach? What is the role of the carriers in delivering this service? The NWHIN is to exist for the public good, and thus shares many traits of the common law notion of 'common carriage' or 'public calling,' the modern term for which is network neutrality. Recent policy debates in Congress and resulting potential regulation have implications for key stakeholders within healthcare that use or provide services, and for those who exchange information. To date, there has been little policy debate or discussion about the implications of a neutral NWHIN. This paper frames the discussion for future policy debate in healthcare by providing a brief education and summary of the modern version of common carriage, of the key stakeholder positions in healthcare, and of the potential implications of the network neutrality debate within healthcare.

The AMIA biomedical informatics (BMI) core competencies have been designed to support and guide graduate education in BMI, the core scientific discipline underlying the breadth of the field's research, practice, and education. The core definition of BMI adopted by AMIA specifies that BMI is 'the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health.' Application areas range from bioinformatics to clinical and public health informatics and span the spectrum from the molecular to population levels of health and biomedicine. The shared core informatics competencies of BMI draw on the practical experience of many specific informatics sub-disciplines. The AMIA BMI analysis highlights the central shared set of competencies that should guide curriculum design and that graduate students should be expected to master.

In the midst of a US $30 billion USD investment in the Nationwide Health Information Network (NwHIN) and electronic health records systems, a significant change in the architecture of the NwHIN is taking place. Prior to 2010, the focus of information exchange in the NwHIN was the Regional Health Information Organization (RHIO). Since 2010, the Office of the National Coordinator (ONC) has been sponsoring policies that promote an internet-like architecture that encourages point to-point information exchange and private health information exchange networks. The net effect of these activities is to undercut the limited business model for RHIOs, decreasing the likelihood of their success, while making the NwHIN dependent on nascent technologies for community level functions such as record locator services. These changes may impact the health of patients and communities. Independent, scientifically focused debate is needed on the wisdom of ONC's proposed changes in its strategy for the NwHIN.

Health care providers are legally obliged to report cases of specified diseases to public health authorities, but existing manual, provider-initiated reporting systems generally result in incomplete, error-prone, and tardy information flow. Automated laboratory-based reports are more likely accurate and timely, but lack clinical information and treatment details. Here, we describe the Electronic Support for Public Health (ESP) application, a robust, automated, secure, portable public health detection and messaging system for cases of notifiable diseases. The ESP application applies disease specific logic to any complete source of electronic medical data in a fully automated process, and supports an optional case management workflow system for case notification control. All relevant clinical, laboratory and demographic details are securely transferred to the local health authority as an HL7 message. The ESP application has operated continuously in production mode since January 2007, applying rigorously validated case identification logic to ambulatory EMR data from more than 600,000 patients. Source code for this highly interoperable application is freely available under an approved open-source license at http://esphealth.org.

The Internet provides a medium to administer and evaluate evidence-based interventions for highly prevalent public health problems worldwide. The authors report a series of four Internet smoking cessation studies conducted in English and Spanish. These studies examined both outcome (self-reported 7-day abstinence) and mechanisms related to outcome (the impact of major depressive episodes [MDEs] on the likelihood of quitting). Over 4,000 smokers from 74 countries entered the studies. Studies 1 and 2 evaluated a standard smoking cessation guide (the "Guía"). Studies 3 and 4 were randomized trials comparing the Guía+ITEMs (individually timed educational messages) to the Guía+ITEMs+a mood management course. ITEMs were E-mails inviting participants back to the site at specific times. Online follow-up assessments resulted in completion rates of 44%-54% at 1 month and 26%-30% at 6 months in studies 1 and 2. Incentives and follow-up phone calls increased these rates to 70%, 66%, 65%, and 62% at 1, 3, 6, and 12 months in study 4. At 6 months, self-reported 7-day abstinence rates using missing = smoking data were 6% in studies 1 and 2, 10%-14% in study 3, and 20%-26% in study 4. The Guía+ITEMs condition tended to have higher quit rates, which reached significance at the 12-month follow-up in study 3 and at the 3-month follow-up in study 4. Smokers with past (but not current) MDEs tended to be the most likely to abstain and those with current MDEs the least likely. This trend reached significance in studies 1 and 4.

Objective: The aim of this study was to determine whether an automated e-mail messaging system that sent individually timed educational messages (ITEMs) increased the effectiveness of an Internet smoking cessation intervention., Design: Using two consecutive series of participants, the authors compared two Web-based self-help style smoking cessation interventions: a single-point-in-time educational intervention and an enhanced intervention that also sent ITEMs timed to participants' quit efforts. Outcomes were compared in 199 participants receiving the one-time intervention and 286 receiving ITEMs., Measurements: Demographic factors, number of cigarettes smoked, nicotine addiction, depressive symptoms, and confidence in ability to quit were measured at entry. Twenty-four-hour quit attempts and seven-day point-prevalence of abstinence (nonrespondents assumed to smoke) were measured 30 days after each subject's self-selected quit date., Results: The one-time and ITEMs groups differed in some demographics and some relapse risk factors but not in factors associated with 30-day quit rates. ITEMs appeared to increase the rate at which individuals set quit dates (97% vs. 91%, p = 0.005) and, among the respondents to follow-up questionnaires (n = 145), the rate of reported 24-hour quit efforts (83% vs. 54%, p = 0.001). The 30-day intent-to-treat quit rates were higher in the ITEMs group: 7.5% vs. 13.6%, p = 0.035. In multivariate analyses controlling for differences between groups, receiving ITEMs was associated with an increase in the odds ratio for quitting of 2.6 (95% confidence interval = 1.3-5.3)., Conclusion: ITEMs sent on strategic days in smokers' quit efforts enhanced early success with smoking cessation relative to a single-point-in-time Web intervention. The effect appears to be mediated by ITEMs' causing smokers to plan and undertake quit efforts more frequently.

Relatively little is known about how to use the Internet to promote health behavioral change. This article describes a multiple-contact Internet smoking cessation program with an 8-week web-based course, online tools for self-monitoring of behaviors, and computer-tailored e-mail messages timed to enrollees' quit efforts. In a pilot study in 49 smokers, we found that enrollees returned to the website a median of 2 times and completed an average of 2 of 8 educational modules. In follow-up, respondents (n = 26) rated e-mail and web components of the intervention as equally valuable (5.9 vs. 5.5 of 10, p = 0.44). While site had potentially important effects on smoking behaviors (34% of enrollees either quit smoking or had a 50% reduction in cigarette use), we were not able hold the interest of the majority of enrollees over the intervention period. Problems with the design of the site are discussed.

The Internet is a rich multimodal communication environment where researchers can often recruit large numbers of participants for survey studies at low cost; however, there are many unanswered questions about the use of this technology in medical research. An important question is whether the results obtained in such surveys are generalizable to other populations. In this article, we describe different approaches for recruitment of participants on the Internet and how specific approaches may limit generalizability. Another issue clouding use of the Web in research is the essential anonymity of participants. We discuss the risk and benefits of anonymous surveys and technical methods that minimize the risks while preserving anonymity and confidentiality. A related problem may be accidental or deliberate enrollment of unqualified individuals in studies. Researchers can use survey design and statistical methods described herein to partially address threats to validity arising from such individuals; however, in some situations, confirmation of eligibility, by manual review of medical records, may be necessary.