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AMIA ... Annual Symposium Proceedings

Jane Wang, Shannon Wongvibulsin, Katharine Henry, Saki Fujita
Medication adherence is a critical component for recovery following acute myocardial infarction (AMI). Currently, numerous smartphone applications are capable of tracking medication adherence through patient-generated data (PGD), but few are integrated with the electronic health record (EHR). Integration of medication adherence PGD into the EHR can give both healthcare providers and patients increased insight into patterns of missed doses, effects on vital signs, and correlation with side effect symptomology to inform healthcare decisions...
2017: AMIA ... Annual Symposium Proceedings
Angela Smith, Ada Ng, Eleanor R Burgess, Noah Weingarten, Jennifer A Pacheco
We present Sensi-steps, an application using patient-generated data (PGD) to prevent falls for geriatric and especially poststroke patients. The Sensi-steps tool incorporates a wearable wrist device, pedometer, pressure and proximity sensors, and tablet. PGD collection occurs through Timed Up and Go (TUG) tests and collection of physiological data, which is integrated into the EHR. Fall risk factor active tracking encourages new ways of shared decision-making between patients, caregivers, and practitioners...
2017: AMIA ... Annual Symposium Proceedings
Lisa V Grossman, Elliot G Mitchell
Congruent with the nationwide movement toward patient-centered healthcare, an increasing number of organizations collect and assess patient-reported outcomes (PROs). The standardized NIH PROMIS measures represent one of the most widely used PRO questionnaires, but organizations still face challenges with conveying PROMIS outcomes to clinicians in clinically relevant ways. Our proposed solution, the ProVis application, uses visualizations to engage heart failure patients with PROMIS questionnaires in the waiting room, and conveys PROMIS data to clinicians through longitudinal visualizations in iNYP, our institution's electronic health record (EHR) interface...
2017: AMIA ... Annual Symposium Proceedings
Gabrielle Choonoo, Mitzi Boardman
Cardiovascular disease and diabetes are epidemic in the United States, and efforts to shift this trend have been largely ineffective. The greatest challenge that health care practitioners face is inspiring the lifestyle changes necessary to prevent or reverse these conditions. New evidence suggests that minimal activity, such as simply standing up periodically and moving around can reduce biomarkers of cardiovascular disease and diabetes. Given the challenge and temporary nature of inspiring habitually sedentary individuals to take on intensive exercise routines, this is an exciting prospect...
2017: AMIA ... Annual Symposium Proceedings
Regina A Casanova-Perez, Pierre G Padilla-Huamantinco, Catharine I De Freitas-Vidal, Yong K Choi
No abstract text is available yet for this article.
2017: AMIA ... Annual Symposium Proceedings
Kevin Blansit, Rebecca Marmor, Beiqun Zhao, Dan Tien
Unplanned surgical readmissions pose a challenging problem for the American healthcare system. We propose to combine consumer electronic voice recognition technology with the FHIR standard to create a post-surgical discharge monitoring app to identify and alert physicians to a patient's deteriorating status.
2017: AMIA ... Annual Symposium Proceedings
Timothy Bergquist, Ronald W Buie, Kevin Li, Pascal Brandt
No abstract text is available yet for this article.
2017: AMIA ... Annual Symposium Proceedings
Zhu Wei, Cui Licong, Zhang Guo-Qiang
The completeness of a medical terminology system consists of two parts: complete content coverage and complete semantics. In this paper, we focus on semantic completeness and present a scalable approach, called Spark-MCA, for evaluating the semantic completeness of SNOMED CT. We formulate the SNOMED CT contents into an FCA-based formal context, in which SNOMED CT concepts are used for extents, while their attributes are used as intents. We applied Spark-MCA to the 201403 US edition of SNOMED CT to exhaustively compute all the formal concepts and sub concept relationships in about 2 hours with 96 processors using an Amazon Web Service cluster...
2017: AMIA ... Annual Symposium Proceedings
Vivienne J Zhu, Tina D Walker, Robert W Warren, Peggy B Jenny, Stephane Meystre, Leslie A Lenert
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...
2017: AMIA ... Annual Symposium Proceedings
Jane Y Zhao, Buer Song, Edwin Anand, Diane Schwartz, Mandip Panesar, Gretchen P Jackson, Peter L Elkin
Patient portal and personal health record adoption and usage rates have been suboptimal. A systematic review of the literature was performed to capture all published studies that specifically addressed barriers, facilitators, and solutions to optimal patient portal and personal health record enrollment and use. Consistent themes emerged from the review. Patient attitudes were critical as either barrier or facilitator. Institutional buy-in, information technology support, and aggressive tailored marketing were important facilitators...
2017: AMIA ... Annual Symposium Proceedings
Zhang Guo-Qiang, Huang Yan, Cui Licong
We introduce RGT, Retrospective Ground-Truthing, as a surrogate reference standard for evaluating the performance of automated Ontology Quality Assurance (OQA) methods. The key idea of RGT is to use cumulative SNOMED CT changes derived from its regular longitudinal distributions by the official SNOMED CT editorial board as a partial, surrogate reference standard. The contributions of this paper are twofold: (1) to construct an RGT reference set for SNOMED CT relational changes; and (2) to perform a comparative evaluation of the performances of lattice, non-lattice, and randomized relational error detection methods using the standard precision, recall, and geometric measures...
2017: AMIA ... Annual Symposium Proceedings
Jing Zhang, Rebecca Marmor, Jina Huh
As of 2014, 29.1 million people in the US have diabetes. Patients with diabetes have evolving information needs around complex lifestyle and medical decisions. As their conditions progress, patients need to sporadically make decisions by understanding alternatives and comparing options. These moments along the decision-making process present a valuable opportunity to support their information needs. An increasing number of patients visit online diabetes communities to fulfill their information needs. To understand how patients attempt to fulfill the information needs around decision-making in online communities, we reviewed 801 posts from an online diabetes community and included 79 posts for in-depth content analysis...
2017: AMIA ... Annual Symposium Proceedings
Zexian Zeng, Xiaoyu Li, Sasa Espino, Ankita Roy, Kristen Kitsch, Susan Clare, Seema Khan, Yuan Luo
To facilitate the identification of contralateral breast cancer events for large cohort study, we proposed and implemented a new method based on features extracted from narrative text in progress notes and features from numbers of pathology reports for each side of breast cancer. Our method collects medical concepts and their combinations to detect contralateral events in progress notes. In addition, the numbers of pathology reports generated for either left or right side of breast cancer were derived as additional features...
2017: AMIA ... Annual Symposium Proceedings
Mengru Yuan, Guido Powell, Maxime Lavigne, Anya Okhmatovskaia, David L Buckeridge
We report the baseline usability of a novel web-based application, the Population Health Record (PopHR), designed to facilitate the effective use of population health information by public health professionals and to support evidence-based decision-making. The usability test was conducted with ten potential users who each completed eight tasks using the PopHR system. Participant responses were recorded, including timestamps for each data entry. Overall, the task completion rate was 96% while the success rate was 88%...
2017: AMIA ... Annual Symposium Proceedings
Zhijun Yin, Wei Xie, Bradley A Malin
Hormonal therapy adherence is challenging for many patients with hormone-receptor-positive breast cancer. Gaining intuition into their adherence behavior would assist in improving outcomes by pinpointing, and eventually addressing, why patients fail to adhere. While traditional adherence studies rely on survey-based methods or electronic medical records, online health communities provide a supplemental data source to learn about such behavior and often on a much larger scale. In this paper, we focus on an online breast cancer discussion forum and propose a framework to automatically extract hormonal therapy adherence behavior (HTAB) mentions...
2017: AMIA ... Annual Symposium Proceedings
Wen-Wai Yim, Sharon W Kwan, Guy Johnson, Meliha Yetisgen
Cancer stage information is important for clinical research. However, they are not always explicitly noted in electronic medical records. In this paper, we present our work on automatic classification of hepatocellular carcinoma (HCC) stages from free-text clinical and radiology notes. To accomplish this, we defined 11 stage parameters used in the three HCC staging systems, American Joint Committee on Cancer (AJCC), Barcelona Clinic Liver Cancer (BCLC), and Cancer of the Liver Italian Program (CLIP). After aggregating stage parameters to the patient-level, the final stage classifications were achieved using an expert-created decision logic...
2017: AMIA ... Annual Symposium Proceedings
Chengliang Yang, Chris Delcher, Elizabeth Shenkman, Sanjay Ranka
We propose an approach to identify high health care utilizers using residuals from a regression-based health care utilization adjustment model to analyze the variations in health care expenditures. Using a large administrative claims dataset from a state public insurance program, we show that the residuals can identify a group of patients with high residuals whose demographics and categorization of comorbidities are similar to other patients but who have a significant amount of unexplained health care utilization...
2017: AMIA ... Annual Symposium Proceedings
Yanbo Xu, Mohammad Taha Bahadori, Elizabeth Searles, Michael Thompson, Tejedor-Sojo Javier, Jimeng Sun
Medically complex patients consume a disproportionate amount of care resources in hospitals but still often end up with sub-optimal clinical outcomes. Predicting dynamics of complexity in such patients can potentially help improve the quality of care and reduce utilization of hospital resources. In this work, we model the change prediction of medical complexity using a large dataset of 226K pediatric patients over 5 years from Children's Healthcare of Atlanta (CHOA). We compare different classification methods including logistic regression, random forest, gradient boosting trees, and multilayer perceptron in predicting whether patients will change their complexity status in the last year based on the data from previous years...
2017: AMIA ... Annual Symposium Proceedings
Eryu Xia, Jing Mei, Guotong Xie, Xuejun Li, Zhibin Li, Meilin Xu
Increasing learning ability from massive medical data and building learning methods robust to data quality issues are key factors toward building data-driven clinical decision support systems for medicine prescription decision support. Here, we attempted accordingly to address the factors using a multi-task neural network approach, benefiting from multi-task learning's advantage in modeling commonalities to increase learning performance and neural network's robustness to imprecise data. By mining electronic health record data, we learned medicine prescription patterns of multiple correlated antidiabetic agents in blood glucose control and antihypertensive drugs in blood pressure control scenarios...
2017: AMIA ... Annual Symposium Proceedings
Danny T Y Wu, Nikolas Smart, Elizabeth L Ciemins, Holly J Lanham, Curt Lindberg, Kai Zheng
To develop a workflow-supported clinical documentation system, it is a critical first step to understand clinical workflow. While Time and Motion studies has been regarded as the gold standard of workflow analysis, this method can be resource consuming and its data may be biased due to the cognitive limitation of human observers. In this study, we aimed to evaluate the feasibility and validity of using EHR audit trail logs to analyze clinical workflow. Specifically, we compared three known workflow changes from our previous study with the corresponding EHR audit trail logs of the study participants...
2017: AMIA ... Annual Symposium Proceedings
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