Rapid increases in e-cigarette use and potential exposure to harmful byproducts have shifted public health focus to e-cigarettes as a possible drug of abuse. Effective surveillance of use and prevalence would allow appropriate regulatory responses. An ideal surveillance system would collect usage data in real time, focus on populations of interest, include populations unable to take the survey, allow a breadth of questions to answer, and enable geo-location analysis. Social media streams may provide this ideal system. To realize this use case, a foundational question is whether we can detect ecigarette use at all. This work reports two pilot tasks using text classification to identify automatically Tweets that indicate e-cigarette use and/or e-cigarette use for smoking cessation. We build and define both datasets and compare performance of 4 state of the art classifiers and a keyword search for each task. Our results demonstrate excellent classifier performance of up to 0.90 and 0.94 area under the curve in each category. These promising initial results form the foundation for further studies to realize the ideal surveillance solution.

Our systematic assessment of end-users' perceptions of VHA CCRs suggests that CCRs need to be developed and implemented with a continual focus on improvement based on end-user feedback. Potential target areas include better integration into the primary care clinic workflow/workload.

While many aspects of patient care have transitioned to digital technology, the patient registration process often is still paper based. Several studies have examined the effects of changes in clinic workflows and appointment scheduling on patient satisfaction, but few have investigated changes from a paper-based to a paperless registration process. The authors measured patient and staff satisfaction before and after implementation of a new, tablet-based registration process at NYU Langone Health's Center for Women's Health in New York City. Mean preimplementation patient satisfaction scores on the six questions related to the registration process (1-5 scale, with 5 being the highest score) ranged from 4.0 to 4.5. Postimplementation satisfaction scores on the nine questions (six premeasure questions and three additional questions related to the tablet-based process) ranged from 4.4 to 4.6, with four of the six premeasures showing statistically significant improvement in patient satisfaction. Staff satisfaction was generally lower (2.8-3.6 preimplementation and 2.8-4 postimplementation), with no statistically significant difference between time frames. Patient satisfaction was relatively high under the paper registration process, and it improved significantly in some respects under the paperless process, while staff satisfaction did not change. The convenience and ease of use of a paperless registration system can help maintain or increase patient and staff satisfaction while introducing new workflows and improving the efficiency of the outpatient registration process. In adopting technology that can lead to changing workflows, organizations should train staff members and support them during the process.