Hospitalization as an opportunity to improve lung cancer screening in high-risk patients.

BACKGROUND: Lung cancer screening with annual low-dose computed tomography (LDCT) in high-risk patients with exposure to smoking reduces lung cancer-related mortality, yet the screening rate of eligible adults is low. As hospitalization is an opportune moment to engage patients in their overall health, it may be an opportunity to improve rates of lung cancer screening. Prior to implementing a hospital-based lung cancer screening referral program, this study assesses the association between hospitalization and completion of lung cancer screening. METHODS: A retrospective cohort study of evaluated completion of at least one LDCT from 2014 to 2021 using electronic health record data using hospitalization as the primary exposure. Patients aged 55-80 who received care from a university-based internal medicine clinic and reported cigarette use were included. Univariate analysis and logistic regression evaluated the association of hospitalization and completion of LDCT. Cox proportional hazard model examined the time relationship between hospitalization and LDCT. RESULTS: Of the 1935 current smokers identified, 47% had at least one hospitalization, and 21% completed a LDCT during the study period. While a higher proportion of patients with a hospitalization had a LDCT (24%) compared to patients without a hospitalization (18%, p<0.001), there was no association between hospitalization and completion of a LDCT after adjusting for potentially confounding covariates (95%CI 0.680 - 1.149). There was an association between hospitalization time to event and LDCT completion, with hospitalized patients having a lower probability of competing LDCT compared to non-hospitalized patients (HR 0.747; 95% CI 0.611 - 0.914). CONCLUSIONS: In a cohort of patients at risk for lung cancer and established within a primary care clinic, only 1 in 4 patients who had been hospitalized completed lung cancer screening with LDCT. Hospitalization events were associated with a lower probability of LDCT completion. Hospitalization is a missed opportunity to refer at-risk patients to lung cancer screening.

Using implementation science to evaluate a population-wide genomic screening program: Findings from the first 20,000 In Our DNA SC participants.

We use the implementation science framework RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) to describe outcomes of In Our DNA SC, a population-wide genomic screening (PWGS) program. In Our DNA SC involves participation through clinical appointments, community events, or at home collection. Participants provide a saliva sample that is sequenced by Helix, and those with a pathogenic variant or likely pathogenic variant for CDC Tier 1 conditions are offered free genetic counseling. We assessed key outcomes among the first cohort of individuals recruited. Over 14 months, 20,478 participants enrolled, and 14,053 samples were collected. The majority selected at-home sample collection followed by clinical sample collection and collection at community events. Participants were predominately female, White (self-identified), non-Hispanic, and between the ages of 40-49. Participants enrolled through community events were the most racially diverse and the youngest. Half of those enrolled completed the program. We identified 137 individuals with pathogenic or likely pathogenic variants for CDC Tier 1 conditions. The majority (77.4%) agreed to genetic counseling, and of those that agreed, 80.2% completed counseling. Twelve clinics participated, and we conducted 108 collection events. Participants enrolled at home were most likely to return their sample for sequencing. Through this evaluation, we identified facilitators and barriers to implementation of our state-wide PWGS program. Standardized reporting using implementation science frameworks can help generalize strategies and improve the impact of PWGS.

Barriers and facilitators to the implementation of family cancer history collection tools in oncology clinical practices.

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.

Is hospitalization a missed opportunity to intervene on tobacco cessation?

BACKGROUND: Although tobacco use is associated with elevated morbidity and mortality, its use remains widespread among adults within the United States. Nicotine Replacement Therapy (NRT) products are effective aids that improve rates of tobacco cessation. Many smokers interact with the medical system, such as during hospitalization, without their tobacco use addressed. Hospitalization is a teachable moment for patients to make health-related changes, including tobacco cessation. METHODS: Retrospective cohort study of adult patients in a university-based patient-centered medical home from 2012 to 2021 evaluating the proportion of adults who smoke who received at least one prescription for NRT. Logistic regression models were used to analyze the association of being hospitalized and receipt of a NRT prescription. RESULTS: Of the 4,072 current smokers identified, 1,182 (29%) received at least one prescription for NRT during the study period. Hospitalization was associated with increased odds of receiving a NRT prescription (OR 1.68). Of 1,844 current smokers with a hospitalization during the study period, 1,078 (58%) never received a prescription for NRT at any point. Only 87 (5%) of the smokers received a prescription for NRT during hospitalization or at the time of hospital discharge. CONCLUSIONS: Despite hospitalization being associated with NRT prescribing, most patients who use tobacco and are hospitalized are not prescribed NRT. Hospitalization is an underutilized opportunity for both hospitalists and primary care physicians to intervene on smoking cessation through education and prescription of tobacco cessation aids.

Predicting Mammogram Screening Follow Through with Electronic Health Record and Geographically Linked Data.

Cancer is the second leading cause of death in the United States, and breast cancer is the fourth leading cause of cancer-related death, with 42,275 women dying of breast cancer in the United States in 2020. Screening is a key strategy for reducing mortality from breast cancer and is recommended by various national guidelines. This study applies machine learning classification methods to the task of predicting which patients will fail to complete a mammogram screening after having one ordered, as well as understanding the underlying features that influence predictions. The results show that a small group of patients can be identified that are very unlikely to complete mammogram screening, enabling care managers to focus resources. SIGNIFICANCE: The motivation behind this study is to create an automated system that can identify a small group of individuals that are at elevated risk for not following through completing a mammogram screening. This will enable interventions to boost screening to be focused on patients least likely to complete screening.

Lessons Learned from the Pilot Phase of a Population-Wide Genomic Screening Program: Building the Base to Reach a Diverse Cohort of 100,000 Participants.

Background and Objectives: Genomic information is increasingly relevant for disease prevention and risk management at the individual and population levels. Screening healthy adults for Tier 1 conditions of hereditary breast and ovarian cancer, Lynch syndrome, and familial hypercholesterolemia using a population-based approach can help identify the 1−2% of the US population at increased risk of developing diseases associated with these conditions and tailor prevention strategies. Our objective is to report findings from an implementation science study that evaluates multi-level facilitators and barriers to implementation of the In Our DNA SC population-wide genomic screening initiative. Methods: We established an IMPACTeam (IMPlementAtion sCience for In Our DNA SC Team) to evaluate the pilot phase using principles of implementation science. We used a parallel convergent mixed methods approach to assess the Reach, Implementation, and Effectiveness outcomes from the RE-AIM implementation science framework during the pilot phase of In Our DNA SC. Quantitative assessment included the examination of frequencies and response rates across demographic categories using chi-square tests. Qualitative data were audio-recorded and transcribed, with codes developed by the study team based on the semi-structured interview guide. Results: The pilot phase (8 November 2021, to 7 March 2022) included recruitment from ten clinics throughout South Carolina. Reach indicators included enrollment rate and representativeness. A total of 23,269 potential participants were contacted via Epic's MyChart patient portal with 1976 (8.49%) enrolled. Black individuals were the least likely to view the program invitation (28.9%) and take study-related action. As a result, there were significantly higher enrollment rates among White (10.5%) participants than Asian (8.71%) and Black (3.46%) individuals (p < 0.0001). Common concerns limiting reach and participation included privacy and security of results and the impact participation would have on health or life insurance. Facilitators included family or personal history of a Tier 1 condition, prior involvement in genetic testing, self-interest, and altruism. Assessment of implementation (i.e., adherence to protocols/fidelity to protocols) included sample collection rate (n = 1104, 55.9%) and proportion of samples needing recollection (n = 19, 1.7%). There were no significant differences in sample collection based on demographic characteristics. Implementation facilitators included efficient collection processes and enthusiastic clinical staff. Finally, we assessed the effectiveness of the program, finding low dropout rates (n = 7, 0.35%), the identification of eight individuals with Tier 1 conditions (0.72% positive), and high rates of follow-up genetic counseling (87.5% completion). Conclusion: Overall, Asian and Black individuals were less engaged, with few taking any study-related actions. Strategies to identify barriers and promoters for the engagement of diverse populations are needed to support participation. Once enrolled, individuals had high rates of completing the study and follow-up engagement with genetic counselors. Findings from the pilot phase of In Our DNA SC offer opportunities for improvement as we expand the program and can provide guidance to organizations seeking to begin efforts to integrate population-wide genomic screening.

Automatically identifying opioid use disorder in non-cancer patients on chronic opioid therapy.

Background: Using the International Classification of Diseases (ICD) codes alone to record opioid use disorder (OUD) may not completely document OUD in the electronic health record (EHR). We developed and evaluated natural language processing (NLP) approaches to identify OUD from the clinal note. We explored the concordance between ICD-coded and NLP-identified OUD.Methods: We studied EHRs from 13,654 (female: 8223; male: 5431) adult non-cancer patients who received chronic opioid therapy (COT) and had at least one clinical note between 2013 and 2018. Of eligible patients, we randomly selected 10,218 (75%) patients as the training set and the remaining 3436 patients (25%) as the test dataset for NLP approaches.Results: We generated 539 terms representing OUD mentions in clinical notes (e.g., "opioid use disorder," "opioid abuse," "opioid dependence," "opioid overdose") and 73 terms representing OUD medication treatments. By domain expert manual review for the test dataset, our NLP approach yielded high performance: 98.5% for precision, 100% for recall, and 99.2% for F-measure. The concordance of these NLP and ICD identified OUD was modest (Kappa = 0.63).Conclusions: Our NLP approach can accurately identify OUD patients from clinical notes. The combined use of ICD diagnostic code and NLP approach can improve OUD identification.

A pragmatic implementation research study for In Our DNA SC: a protocol to identify multi-level factors that support the implementation of a population-wide genomic screening initiative in diverse populations.

BACKGROUND: In 2021, the Medical University of South Carolina (MUSC) partnered with Helix, a population genetic testing company, to offer population-wide genomic screening for Centers for Disease Control and Preventions' Tier 1 conditions of hereditary breast and ovarian cancer, Lynch syndrome, and familial hypercholesterolemia to 100,000 individuals in South Carolina. We developed an implementation science protocol to study the multi-level factors that influence the successful implementation of the In Our DNA SC initiative. METHODS: We will use a convergent parallel mixed-methods study design to evaluate the implementation of planned strategies and associated outcomes for In Our DNA SC. Aims focus on monitoring participation to ensure engagement of diverse populations, assessing contextual factors that influence implementation in community and clinical settings, describing the implementation team's facilitators and barriers, and tracking program adaptations. We report details about each data collection tool and analyses planned, including surveys, interview guides, and tracking logs to capture and code work group meetings, adaptations, and technical assistance needs. DISCUSSION: The goal of In Our DNA SC is to provide population-level screening for actionable genetic conditions and to foster ongoing translational research. The use of implementation science can help better understand how to support the success of In Our DNA SC, identify barriers and facilitators to program implementation, and can ensure the sustainability of population-level genetic testing. The model-based components of our implementation science protocol can support the identification of best practices to streamline the expansion of similar population genomics programs at other institutions.

Leveraging health system telehealth and informatics infrastructure to create a continuum of services for COVID-19 screening, testing, and treatment.

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.

Correction to: Automatically identifying social isolation from clinical narratives for patients with prostate Cancer.

Following publication of the original article [1], the authors reported an error in one of the authors' names.

Automatically identifying social isolation from clinical narratives for patients with prostate Cancer.

BACKGROUND: Social isolation is an important social determinant that impacts health outcomes and mortality among patients. The National Academy of Medicine recently recommended that social isolation be documented in electronic health records (EHR). However, social isolation usually is not recorded or obtained as coded data but rather collected from patient self-report or documented in clinical narratives. This study explores the feasibility and effectiveness of natural language processing (NLP) strategy for identifying patients who are socially isolated from clinical narratives. METHOD: We used data from the Medical University of South Carolina (MUSC) Research Data Warehouse. Patients 18 years-of-age or older who were diagnosed with prostate cancer between January 1, 2014 and May 31, 2017 were eligible for this study. NLP pipelines identifying social isolation were developed via extraction of notes on progress, history and physical, consult, emergency department provider, telephone encounter, discharge summary, plan of care, and radiation oncology. Of 4195 eligible prostate cancer patients, we randomly sampled 3138 patients (75%) as a training dataset. The remaining 1057 patients (25%) were used as a test dataset to evaluate NLP algorithm performance. Standard performance measures for the NLP algorithm, including precision, recall, and F-measure, were assessed by expert manual review using the test dataset. RESULTS: A total of 55,516 clinical notes from 3138 patients were included to develop the lexicon and NLP pipelines for social isolation. Of those, 35 unique patients (1.2%) had social isolation mention(s) in 217 notes. Among 24 terms relevant to social isolation, the most prevalent were "lack of social support," "lonely," "social isolation," "no friends," and "loneliness". Among 1057 patients in the test dataset, 17 patients (1.6%) were identified as having social isolation mention(s) in 40 clinical notes. Manual review identified four false positive mentions of social isolation and one false negatives in 154 notes from randomly selected 52 controls. The NLP pipeline demonstrated 90% precision, 97% recall, and 93% F-measure. The major reasons for a false positive included the ambiguities of the experiencer of social isolation, negation, and alternate meaning of words. CONCLUSIONS: Our NLP algorithms demonstrate a highly accurate approach to identify social isolation.

Identifying Falls Risk Screenings Not Documented with Administrative Codes Using Natural Language Processing.

Quality reporting that relies on coded administrative data alone may not completely and accurately depict providers' performance. To assess this concern with a test case, we developed and evaluated a natural language processing (NLP) approach to identify falls risk screenings documented in clinical notes of patients without coded falls risk screening data. Extracting information from 1,558 clinical notes (mainly progress notes) from 144 eligible patients, we generated a lexicon of 38 keywords relevant to falls risk screening, 26 terms for pre-negation, and 35 terms for post-negation. The NLP algorithm identified 62 (out of the 144) patients who falls risk screening documented only in clinical notes and not coded. Manual review confirmed 59 patients as true positives and 77 patients as true negatives. Our NLP approach scored 0.92 for precision, 0.95 for recall, and 0.93 for F-measure. These results support the concept of utilizing NLP to enhance healthcare quality reporting.

Shifts in the architecture of the Nationwide Health Information Network.

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.

Evaluation of an internet-based disease trajectory decision tool for prostate cancer screening.

OBJECTIVE: To evaluate the application of a chronic disease model (CDM) for prostate cancer to visual analog scale (VAS) and time trade-off (TTO) decision tools. METHODS: A total of 138 men (mean age 58 years) viewed a CDM module for prostate cancer with and without prostate specific antigen (PSA) screening. Participants rated their hypothetical quality of life with potential prostate cancer treatment complications using a CDM-based VAS decision tool. They were then asked to estimate how many years they would be willing to trade to be free of treatment complications using a CDM-based TTO decision tool. The consistency between VAS and TTO scores and the relationship between scores and preferences for PSA screening test and hypothetical treatment choice for prostate cancer were then evaluated. RESULTS: There was a significant relationship between the VAS and TTO ratings (regression P < 0.001). The TTO tool was sensitive to age. Mean scores with standard deviations for those less than 58 years compared to those 58 years and more were 7.78 (1.75) and 8.41 (1.52), respectively (P = 0.04). Using the VAS tool, men who chose PSA screening had higher quality of life ratings compared to men who did not choose PSA screening: 7.73 (1.78) and 6.59 (2.39), respectively (P = 0.01). Similar results were found with the TTO decision tool: 8.33 (1.45) and 7.04 (2.00), respectively (P = 0.005). Men who would hypothetically prefer treatment for moderately differentiated prostate cancer also had higher TTO scores compared to men who preferred watchful waiting: 8.54 (1.39) and 7.85 (1.73), respectively (P = 0.04). CONCLUSION: CDM-based for prostate cancer, VAS and TTO ratings were consistent and were concordant with patient preferences for screening; TTO ratings were also concordant with treatment choice. The use of the CDM-based TTO ratings to adjust for quality of life in decision analytic modeling needs to be explored.

Epilepsy surgery for pharmacoresistant temporal lobe epilepsy: a decision analysis.

CONTEXT: Patients with pharmacoresistant epilepsy have increased mortality compared with the general population, but patients with pharmacoresistant temporal lobe epilepsy who meet criteria for surgery and who become seizure-free after anterior temporal lobe resection have reduced excess mortality vs those with persistent seizures. OBJECTIVE: To quantify the potential survival benefit of anterior temporal lobe resection for patients with pharmacoresistant temporal lobe epilepsy vs continued medical management. DESIGN: Monte Carlo simulation model that incorporates possible surgical complications and seizure status, with 10,000 runs. The model was populated with health-related quality-of-life data obtained directly from patients and data from the medical literature. Insufficient data were available to assess gamma-knife radiosurgery or vagal nerve stimulation. MAIN OUTCOME MEASURES: Life expectancy and quality-adjusted life expectancy. RESULTS: Compared with medical management, anterior temporal lobe resection for a 35-year-old patient with an epileptogenic zone identified in the anterior temporal lobe would increase survival by 5.0 years (95% CI, 2.1-9.2) with surgery preferred in 100% of the simulations. Anterior temporal lobe resection would increase quality-adjusted life expectancy by 7.5 quality-adjusted life-years (95%, CI, -0.8 to 17.4) with surgery preferred in 96.5% of the simulations, primarily due to increased years spent without disabling seizures, thereby reducing seizure-related excess mortality and improving quality of life. The results were robust to sensitivity analyses. CONCLUSION: The decision analysis model suggests that on average anterior temporal lobe resection should provide substantial gains in life expectancy and quality-adjusted life expectancy for surgically eligible patients with pharmacoresistant temporal lobe epilepsy compared with medical management.

Toward evidence-based Internet interventions: A Spanish/English Web site for international smoking cessation trials.

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.

Utilities for prostate cancer health states in men aged 60 and older.

PURPOSE: We sought to measure utilities for prostate cancer health states in older men. METHODS: A total of 162 men aged 60 years or older (52% of whom had been diagnosed with prostate cancer) provided standard gamble utilities for 19 health states associated with prostate cancer or its treatment using an interactive, computer-based utility assessment program. Demographics and experience with specific health states were examined as predictors of ratings using ordinary least squares regression analysis. RESULTS: Mean utilities ranged from 0.67 to 0.84 for living with symptom-free cancer under conservative management ("watchful waiting") and from 0.71 to 0.89 for symptoms occurring with treatment (prostatectomy, radiation, and hormone ablation). For long-term treatment complications, bowel problems (0.71) were rated as significantly worse than impotence (0.89), urinary difficulty (0.88), or urinary incontinence (0.83). Combinations of these conditions were rated as significantly worse than individual component states. Men who had experienced impotence or urinary incontinence rated these states as slightly better than men who had not experienced the specific problems. CONCLUSIONS: Both "watchful waiting" and treatment complications from prostate cancer treatments can have large impacts on quality of life. Mean ratings are important for use in policy-making and cost-effectiveness analyses. Variation in ratings across patients suggests that mean scores do not reflect individual preferences and that shared decision-making may be best for clinical decisions.

Smoking cessation research via the internet: a feasibility study.

To reverse the present stagnation in progress toward reduced smoking rates, new widely accessible treatment methods for smoking cessation must be developed and evaluated with large groups of smokers. We tested the feasibility of conducting a smoking cessation study over the Internet using a brief, self-help educational intervention. Through a direct e-mail sent from a large health information web site (WebMD), and with our presence on the Internet, we recruited 538 adult smokers to the study. Most participants (90.5%) completed all baseline questionnaires. Questionnaires showed acceptable to good reliability and were comparable with studies using paper-and-pencil methods. Participants appeared to be highly dependent on nicotine. Forty-two percent indicated being ready to quit smoking at baseline. At 1-month follow-up, 42.8% of baseline participants returned a complete follow-up questionnaire, 40% of whom indicated having made a serious quit attempt, and 8.3% of whom indicated 7-day abstinence. Most follow-up participants rated the site as at least somewhat helpful to quitting (74.9%) and reported at least a slight increased intention to quit smoking over baseline (67.3%). While Internet-enabled self-help interventions for smoking cessation are able to reach large numbers of smokers interested in quitting smoking, additional procedures are needed to retain these users for treatment and follow-up assessments.

Automated e-mail messaging as a tool for improving quit rates in an internet smoking cessation intervention.

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.

Design and pilot evaluation of an internet smoking cessation program.

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.