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https://www.readbyqxmd.com/read/28817861/population-health-management-and-cancer-screening
#1
Bradley Kamstra, Mark K Huntington
Population health management (PHM) is a new health care model being implemented. It has been defined as "the health outcomes of a group of individuals, including the distribution of such outcomes within the group." This includes health outcomes and patterns of health determinants, and policies and interventions that link these two. Moving from a fee-for-service payment system to a quality- or value-based system, this model places on the clinician more responsibility for the costs of health care and its reimbursements...
2017: South Dakota Medicine: the Journal of the South Dakota State Medical Association
https://www.readbyqxmd.com/read/28817321/community-health-worker-impact-on-chronic-disease-outcomes-within-primary-care-examined-using-electronic-health-records
#2
Maia Ingram, Kevin Doubleday, Melanie L Bell, Abby Lohr, Lucy Murrieta, Maria Velasco, John Blackburn, Samantha Sabo, Jill Guernsey de Zapien, Scott C Carvajal
OBJECTIVES: To investigate community health worker (CHW) effects on chronic disease outcomes using electronic health records (EHRs). METHODS: We examined EHRs of 32 147 patients at risk for chronic disease during 2012 to 2015. Variables included contact with clinic-based CHWs, vitals, and laboratory tests. We estimated a mixed model for all outcomes. RESULTS: Within-group findings showed statistically significant improvements in chronic disease indicators after exposure to CHWs...
August 17, 2017: American Journal of Public Health
https://www.readbyqxmd.com/read/28815147/triangulating-methodologies-from-software-medicine-and-human-factors-industries-to-measure-usability-and-clinical-efficacy-of-medication-data-visualization-in-an-electronic-health-record-system
#3
Bora Chang, Manoj Kanagaraj, Ben Neely, Noa Segall, Erich Huang
Within the last decade, use of Electronic Health Record (EHR) systems has become intimately integrated into healthcare practice in the United States. However, large gaps remain in the study of clinical usability and require rigorous and innovative approaches for testing usability principles. In this study, validated tools from the core functions that EHRs serve-software, medicine and human factors-were combined to holistically understand and objectively measure usability of medication data displays. The first phase of this study included 132 medical trainee participants who were randomized to one of two simulated EHR environments with either a medication list or a medication timeline visualization...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815141/identifying-metastases-related-information-from-pathology-reports-of-lung-cancer-patients
#4
Ergin Soysal, Jeremy L Warner, Joshua C Denny, Hua Xu
Metastatic patterns of spread at the time of cancer recurrence are one of the most important prognostic factors in estimation of clinical course and survival of the patient. This information is not easily accessible since it's rarely recorded in a structured format. This paper describes a system for categorization of pathology reports by specimen site and the detection of metastatic status within the report. A clinical NLP pipeline was developed using sentence boundary detection, tokenization, section identification, part-of-speech tagger, and chunker with some rule based methods to extract metastasis site and status in combination with five types of information related to tumor metastases: histological type, grade, specimen site, metastatic status indicators and the procedure...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815133/correlating-lab-test-results-in-clinical-notes-with-structured-lab-data-a-case-study-in-hba1c-and-glucose
#5
Liu Sijia, Wang Liwei, Donna Ihrke, Vipin Chaudhary, Cui Tao, Chunhua Weng, Hongfang Liu
It is widely acknowledged that information extraction of unstructured clinical notes using natural language processing (NLP) and text mining is essential for secondary use of clinical data for clinical research and practice. Lab test results are currently structured in most of the electronic health record (EHR) systems. However, for referral patients or lab tests that can be done in non-clinical setting, the results can be captured in unstructured clinical notes. In this study, we proposed a rule-based information extraction system to extract the lab test results with temporal information from clinical notes...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815130/ground-truth-creation-for-complex-clinical-nlp-tasks-an-iterative-vetting-approach-and-lessons-learned
#6
Jennifer J Liang, Ching-Huei Tsou, Murthy V Devarakonda
Natural language processing (NLP) holds the promise of effectively analyzing patient record data to reduce cognitive load on physicians and clinicians in patient care, clinical research, and hospital operations management. A critical need in developing such methods is the "ground truth" dataset needed for training and testing the algorithms. Beyond localizable, relatively simple tasks, ground truth creation is a significant challenge because medical experts, just as physicians in patient care, have to assimilate vast amounts of data in EHR systems...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815128/a-comparative-study-of-different-methods-for-automatic-identification-of-clopidogrel-induced-bleedings-in-electronic-health-records
#7
Hee-Jin Lee, Min Jiang, Yonghui Wu, Christian M Shaffer, John H Cleator, Eitan A Friedman, Joshua P Lewis, Dan M Roden, Josh Denny, Hua Xu
Electronic health records (EHRs) linked with biobanks have been recognized as valuable data sources for pharmacogenomic studies, which require identification of patients with certain adverse drug reactions (ADRs) from a large population. Since manual chart review is costly and time-consuming, automatic methods to accurately identify patients with ADRs have been called for. In this study, we developed and compared different informatics approaches to identify ADRs from EHRs, using clopidogrel-induced bleeding as our case study...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815124/pheknow-cloud-a-tool-for-evaluating-high-throughput-phenotype-candidates-using-online-medical-literature
#8
Jette Henderson, Ryan Bridges, Joyce C Ho, Byron C Wallace, Joydeep Ghosh
As the adoption of Electronic Healthcare Records has grown, the need to transform manual processes that extract and characterize medical data into automatic and high-throughput processes has also grown. Recently, researchers have tackled the problem of automatically extracting candidate phenotypes from EHR data. Since these phenotypes are usually generated using unsupervised or semi-supervised methods, it is necessary to examine and validate the clinical relevance of the generated "candidate" phenotypes. We present PheKnow-Cloud, a framework that uses co-occurrence analysis on the publicly available, online repository ofjournal articles, PubMed, to build sets of evidence for user-supplied candidate phenotypes...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815121/enhancing-electronic-health-record-data-with-geospatial-information
#9
Sherrie Xie, Rebecca Greenblatt, Michael Z Levy, Blanca E Himes
Electronic Health Record (EHR)-derived data is a valuable resource for research, and efforts are underway to overcome some of its limitations by using data from external sources to gain a fuller picture of patient characteristics, symptoms, and exposures. Our goal was to assess the utility of augmenting EHR data with geocoded patient addresses to identify geospatial variation of disease that is not explained by EHR-derived demographic factors. Using 2011-2014 encounter data from 27,604 University of Pennsylvania Hospital System asthma patients, we identified factors associated with asthma exacerbations: risk was higher in female, black, middle aged to elderly, and obese patients, as well as those with positive smoking history and with Medicare or Medicaid vs...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815118/deep-learning-from-eeg-reports-for-inferring-underspecified-information
#10
Travis R Goodwin, Sanda M Harabagiu
Secondary use(1)of electronic health records (EHRs) often relies on the ability to automatically identify and extract information from EHRs. Unfortunately, EHRs are known to suffer from a variety of idiosyncrasies - most prevalently, they have been shown to often omit or underspecify information. Adapting traditional machine learning methods for inferring underspecified information relies on manually specifying features characterizing the specific information to recover (e.g. particular findings, test results, or physician's impressions)...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815117/systematic-analysis-of-free-text-family-history-in-electronic-health-record
#11
Yanshan Wang, Liwei Wang, Majid Rastegar-Mojarad, Sijia Liu, Feichen Shen, Hongfang Liu
Family history is an important component in modern clinical care especially in the era of precision medicine. Family history information in the Electronic Health Record (EHR) system is usually stored in structured format as well as in free-text format. In this study, we systematically analyzed a family history text corpus from 3 million clinical notes for the patients receiving their primary care at Mayo Clinic. Family members, medical problems, and their associations were analyzed and reported. Our findings showed a great agreement between positive/negated medical problems mentioned in the diagnosis report and the family history, as measured by observed agreement and random agreement...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815116/reducing-clinical-noise-for-body-mass-index-measures-due-to-unit-and-transcription-errors-in-the-electronic-health-record
#12
Robert Goodloe, Eric Farber-Eger, Jonathan Boston, Dana C Crawford, William S Bush
Body mass index (BMI) is an important outcome and covariate adjustment for many clinical association studies. Accurate assessment of BMI, therefore, is a critical part of many study designs. Electronic health records (EHRs) are a growing source of clinical data for research purposes, and have proven useful for identifying and replicating genetic associations. EHR-based data collected for clinical and billing purposes have several unique properties, including a high degree of heterogeneity or "clinical noise...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815105/extracting-country-of-origin-from-electronic-health-records-for-gene-environment-studies-as-part-of-the-epidemiologic-architecture-for-genes-linked-to-environment-eagle-study
#13
Eric Farber-Eger, Robert Goodloe, Jonathan Boston, William S Bush, Dana C Crawford
We describe here the extraction of country-of-origin, an acculturation variable relevant for gene-environment studies, in a biorepository linked to de-identified electronic health records (EHRs) assessed by the Epidemiologic Architecture for Genes Linked to Environment (EAGLE), a study site of the Population Architecture using Genomics and Epidemiology (PAGE) I study. We extracted country-of-origin from the unstructured clinical free text using regular expressions within the MySQL relational database system in a cohort of 15,863 subjects of mostly non-European descent (including 11,519 African Americans, 1,702 Hispanics, and 1,118 Asians)...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28815104/electronic-phenotyping-with-aphrodite-and-the-observational-health-sciences-and-informatics-ohdsi-data-network
#14
Juan M Banda, Yoni Halpern, David Sontag, Nigam H Shah
The widespread usage of electronic health records (EHRs) for clinical research has produced multiple electronic phenotyping approaches. Methods for electronic phenotyping range from those needing extensive specialized medical expert supervision to those based on semi-supervised learning techniques. We present Automated PHenotype Routine for Observational Definition, Identification, Training and Evaluation (APHRODITE), an R- package phenotyping framework that combines noisy labeling and anchor learning. APHRODITE makes these cutting-edge phenotyping approaches available for use with the Observational Health Data Sciences and Informatics (OHDSI) data model for standardized and scalable deployment...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28811769/significance-of-electronic-health-records-a-comparative-study-of-vaccination-rates-in-patients-with-sickle-cell-disease
#15
Asli Korur, Süheyl Asma, Cigdem Gereklioglu, Soner Solmaz, Can Boga, Akatlı Kürsat Ozsahin, Altug Kut
OBJECTIVE: In this study, we investigated the influence of electronic health records (EHR) and electronic vaccination schedule applications on the vaccination status of patients who were admitted to our Center for the treatment of sickle cell disease (SCD). METHODS: The vaccination status against influenza and pneumococcus infection was determined in 93 patients who were admitted to the hematology outpatient clinic, Baskent University Adana Hospital from April 2004 to March 2009...
May 2017: Pakistan Journal of Medical Sciences Quarterly
https://www.readbyqxmd.com/read/28809201/secondary-use-of-ehr-interpreting-clinician-inter-rater-reliability-through-qualitative-assessment
#16
Sarah Mullin, Edwin Anand, Shyamashree Sinha, Buer Song, Jane Zhao, Peter L Elkin
In a retrospective secondary-use EHR study identifying a cohort of Non-Valvular Atrial Fibrillation (NVAF) patients, chart abstraction was done by two sets of clinicians to create a gold standard for risk measures CHA2DS2-VASc and HAS-BLED. Inter-rater reliability between each set of clinicians for NVAF and the outcomes of interest were variable, ranging from extremely low agreement to high agreement. To assess the chart abstraction process, a focus group and a survey was conducted. Survey findings revealed patterns of difficulty in assessing certain items dealing with temporality and social data...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28808942/primary-care-providers-opening-of-time-sensitive-alerts-sent-to-commercial-electronic-health-record-inbaskets
#17
Sarah L Cutrona, Hassan Fouayzi, Laura Burns, Rajani S Sadasivam, Kathleen M Mazor, Jerry H Gurwitz, Lawrence Garber, Devi Sundaresan, Thomas K Houston, Terry S Field
BACKGROUND: Time-sensitive alerts are among the many types of clinical notifications delivered to physicians' secure InBaskets within commercial electronic health records (EHRs). A delayed alert review can impact patient safety and compromise care. OBJECTIVE: To characterize factors associated with opening of non-interruptive time-sensitive alerts delivered into primary care provider (PCP) InBaskets. DESIGN AND PARTICIPANTS: We analyzed data for 799 automated alerts...
August 14, 2017: Journal of General Internal Medicine
https://www.readbyqxmd.com/read/28808359/electronic-health-records-and-improved-patient-care-opportunities-for-applied-psychology
#18
Raj Ratwani
Healthcare is undergoing an unprecedented technology transition from paper medical records to electronic health records (EHRs). While the adoption of EHRs holds tremendous promise for improving efficiency, quality and safety, there have been numerous challenges that have been largely centered on the technology not meeting the cognitive needs of the clinical end-users. Clinicians are experiencing increased stress and frustration, and new safety hazards have been introduced. There is a significant opportunity for applied psychologists to address many of these challenges...
August 2017: Current Directions in Psychological Science
https://www.readbyqxmd.com/read/28807893/optimizing-the-use-of-electronic-health-records-to-identify-high-risk-psychosocial-determinants-of-health
#19
Nicolas Michel Oreskovic, Jennifer Maniates, Jeffrey Weilburg, Garry Choy
BACKGROUND: Care coordination programs have traditionally focused on medically complex patients, identifying patients that qualify by analyzing formatted clinical data and claims data. However, not all clinically relevant data reside in claims and formatted data. Recently, there has been increasing interest in including patients with complex psychosocial determinants of health in care coordination programs. Psychosocial risk factors, including social determinants of health, mental health disorders, and substance abuse disorders, are less amenable to rapid and systematic data analyses, as these data are often not collected or stored as formatted data, and due to US Health Insurance Portability and Accountability Act (HIPAA) regulations are often not available as claims data...
August 14, 2017: JMIR Medical Informatics
https://www.readbyqxmd.com/read/28807836/development-and-evaluation-of-the-automated-risk-assessment-system-for-multidrug-resistant-organisms-autoras-mdro
#20
Eun-Young Hur, Yinji Jin, Taixian Jin, Sun-Mi Lee
BACKGROUND: A high proportion of infections acquired in hospitals are caused by multidrug-resistant organisms (MDROs). The priority in MDRO prevention is to detect high-risk patients and implement preventive intervention as soon as possible. AIM: To develop an automated risk assessment system for MDROs (autoRAS-MDRO) to screen for patients at MDRO infection risk and evaluate the predictive validity of the autoRAS-MDRO. METHODS: Data for 4,200 variables were extracted from the electronic health records (EHRs) for constructing the MDRO risk-scoring algorithm, which was based on a logistic regression model...
August 11, 2017: Journal of Hospital Infection
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