METHODS FOR CLUSTERING TIME SERIES DATA ACQUIRED FROM MOBILE HEALTH APPS.

In our recent Asthma Mobile Health Study (AMHS), thousands of asthma patients across the country contributed medical data through the iPhone Asthma Health App on a daily basis for an extended period of time. The collected data included daily self-reported asthma symptoms, symptom triggers, and real time geographic location information. The AMHS is just one of many studies occurring in the context of now many thousands of mobile health apps aimed at improving wellness and better managing chronic disease conditions, leveraging the passive and active collection of data from mobile, handheld smart devices. The ability to identify patient groups or patterns of symptoms that might predict adverse outcomes such as asthma exacerbations or hospitalizations from these types of large, prospectively collected data sets, would be of significant general interest. However, conventional clustering methods cannot be applied to these types of longitudinally collected data, especially survey data actively collected from app users, given heterogeneous patterns of missing values due to: 1) varying survey response rates among different users, 2) varying survey response rates over time of each user, and 3) non-overlapping periods of enrollment among different users. To handle such complicated missing data structure, we proposed a probability imputation model to infer missing data. We also employed a consensus clustering strategy in tandem with the multiple imputation procedure. Through simulation studies under a range of scenarios reflecting real data conditions, we identified favorable performance of the proposed method over other strategies that impute the missing value through low-rank matrix completion. When applying the proposed new method to study asthma triggers and symptoms collected as part of the AMHS, we identified several patient groups with distinct phenotype patterns. Further validation of the methods described in this paper might be used to identify clinically important patterns in large data sets with complicated missing data structure, improving the ability to use such data sets to identify at-risk populations for potential intervention.

The Use of Smartphones for Health Research.

Because of their growing popularity and functionality, smartphones are increasingly valuable potential tools for health and medical research. Using ResearchKit, Apple's open-source platform to build applications ("apps") for smartphone research, collaborators have developed apps for researching asthma, breast cancer, cardiovascular disease, type 2 diabetes, and Parkinson disease. These research apps enhance widespread participation by removing geographical barriers to participation, provide novel ways to motivate healthy behaviors, facilitate high-frequency assessments, and enable more objective data collection. Although the studies have great potential, they also have notable limitations. These include selection bias, identity uncertainty, design limitations, retention, and privacy. As smartphone technology becomes increasingly available, researchers must recognize these factors to ensure that medical research is conducted appropriately. Despite these limitations, the future of smartphones in health research is bright. Their convenience grants unprecedented geographic freedom to researchers and participants alike and transforms the way clinical research can be conducted.

Medical utilization of kiosks in the delivery of patient education: a systematic review.

BACKGROUND: The utilization of kiosks has previously been shown to be effective for collecting information, delivering educational modules, and providing access to health information. We discuss a review of current literature for the utilization of kiosks for the delivery of patient education. METHODS: The criteria for inclusion in this literature review were: (1) study discusses the utilization of kiosks for patient health education; (2) study discusses the use of touch screens for patient health information; (3) published in English. Our review includes searches via MEDLINE databases and Google Scholar for the years 1996-2014. RESULTS: Overall, 167 articles were screened for final eligibility, and after discarding duplicates and non-eligible studies with abstract. Full-text review of 28 articles was included in the final analysis. CONCLUSION: The review of available literature demonstrates the effectiveness of touch screen kiosks to educate patients and to improve healthcare, both at a performance and cost advantage over other modes of patient education.

Effectiveness of stroke education in the emergency department waiting room.

OBJECTIVE: The purpose of this study was to evaluate the effectiveness of stroke education provided to patients and their significant others in the emergency department (ED) waiting area. Our focus was on the 4 main aspects of stroke: signs and symptoms, risk factors, behavior modification, and the urgency to seek medical attention. We hypothesized that showing educational videos, providing one-on-one counseling, and distributing literature would result in greater stroke knowledge and positive behavioral modification. METHODS: In this pilot, randomized controlled trial, our research team enrolled patients and visitors in the fast-track waiting area of the ED. After obtaining informed written consent, participants were randomly assigned to the control group or to the intervention group. The intervention group received an educational video program, one-on-one counseling, and stroke education materials, and completed a 13-question test after receiving the education. The control group completed the same test without receiving any education. Both groups completed the same test again at 1 and 3 months to assess stroke knowledge retention. RESULTS: There were a total of 329 participants: 151 in the control group and 178 in the intervention group. Gender, age, and educational level of participants did not differ between groups. At all time points of the study, participants receiving stroke education demonstrated better test scores than those in the control group. However, knowledge retention in the intervention group gradually declined during the follow-up. Individuals enrolled in the intervention group appeared to be more motivated to reduce their smoking habits, compared with control subjects; however, the number of cigarettes they smoked per day did not dramatically decrease in comparison with their own baseline. Receiving the education session did not result in positive diet or physical activity changes. CONCLUSIONS: ED stroke education, which includes video program, one-on-one counseling, and written educational materials, is able to significantly increase stroke knowledge. Modification and reinforcement of education is needed to achieve better knowledge retention and favorable lifestyle modifications.