journal
MENU ▼
Read by QxMD icon Read
search

Health Informatics Journal

journal
https://www.readbyqxmd.com/read/30596321/patient-reported-data-and-the-politics-of-meaningful-data-work
#1
Henriette Langstrup
Patient-reported outcome data have moved from the realm of research to center stage in efforts to provide patient-centered care. In a Danish context, health authorities are seeking to promote and standardize the use of patient-reported outcome data. This involves normative articulations of what counts as meaningful data work in a healthcare system characterized by intensified data-sourcing. Based on ethnographic material, I suggest that an assemblage of actors, both human and technological, has accomplished the articulation of meaningful data work, with patient-reported outcome as being dependent on the active application of data in clinical trajectories-in contrast to supplying data "passively" for secondary use for research or governance...
December 31, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30596318/a-transparent-cancer-classifier
#2
Pitoyo Hartono
Recently, many neural network models have been successfully applied for histopathological analysis, including for cancer classifications. While some of them reach human-expert level accuracy in classifying cancers, most of them have to be treated as black box, in which they do not offer explanation on how they arrived at their decisions. This lack of transparency may hinder the further applications of neural networks in realistic clinical settings where not only decision but also explainability is important...
December 31, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30554546/corrigendum
#3
(no author information available yet)
No abstract text is available yet for this article.
December 17, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30537881/current-challenges-in-health-information-technology-related-patient-safety
#4
Dean F Sittig, Adam Wright, Enrico Coiera, Farah Magrabi, Raj Ratwani, David W Bates, Hardeep Singh
We identify and describe nine key, short-term, challenges to help healthcare organizations, health information technology developers, researchers, policymakers, and funders focus their efforts on health information technology-related patient safety. Categorized according to the stage of the health information technology lifecycle where they appear, these challenges relate to (1) developing models, methods, and tools to enable risk assessment; (2) developing standard user interface design features and functions; (3) ensuring the safety of software in an interfaced, network-enabled clinical environment; (4) implementing a method for unambiguous patient identification (1-4 Design and Development stage); (5) developing and implementing decision support which improves safety; (6) identifying practices to safely manage information technology system transitions (5 and 6 Implementation and Use stage); (7) developing real-time methods to enable automated surveillance and monitoring of system performance and safety; (8) establishing the cultural and legal framework/safe harbor to allow sharing information about hazards and adverse events; and (9) developing models and methods for consumers/patients to improve health information technology safety (7-9 Monitoring, Evaluation, and Optimization stage)...
December 11, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30526246/use-of-electronic-health-record-data-from-diverse-primary-care-practices-to-identify-and-characterize-patients-prescribed-common-medications
#5
Allison M Cole, Kari A Stephens, Imara West, Gina A Keppel, Ken Thummel, Laura-Mae Baldwin
We use prescription of statin medications and prescription of warfarin to explore the capacity of electronic health record data to (1) describe cohorts of patients prescribed these medications and (2) identify cohorts of patients with evidence of adverse events related to prescription of these medications. This study was conducted in the WWAMI region Practice and Research Network (WPRN)., a network of primary care practices across Washington, Wyoming, Alaska, Montana and Idaho DataQUEST, an electronic data-sharing infrastructure...
December 10, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30518275/machine-learning-for-identification-of-surgeries-with-high-risks-of-cancellation
#6
Li Luo, Fengyi Zhang, Yao Yao, RenRong Gong, Martina Fu, Jin Xiao
Surgery cancellations waste scarce operative resources and hinder patients' access to operative services. In this study, the Wilcoxon and chi-square tests were used for predictor selection, and three machine learning models - random forest, support vector machine, and XGBoost - were used for the identification of surgeries with high risks of cancellation. The optimal performances of the identification models were as follows: sensitivity - 0.615; specificity - 0.957; positive predictive value - 0.454; negative predictive value - 0...
December 5, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30518264/a-layered-computer-interpretable-guideline-model-for-easing-the-update-of-locally-adapted-clinical-guidelines
#7
Adi Fux, Pnina Soffer, Mor Peleg
Maintenance of computer-interpretable guidelines is complicated by evolving medical knowledge and by the requirement to customize content to local practice settings. We developed a framework to support knowledge engineers in customization and maintenance of computer-interpretable guidelines specified in the PROforma formalism. In our layered approach, the computer-interpretable guidelines containing the original clinical guideline serves as the primary layer and local customizations form secondary layers that adhere to its schema while augmenting it...
December 5, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30516095/implementation-and-early-adaptation-of-patient-reported-outcome-measures-into-an-electronic-health-record-a-technical-report
#8
Heather Taffet Gold, Raj J Karia, Alissa Link, Rachel Lebwohl, Joseph D Zuckerman, Thomas J Errico, James D Slover, Aaron J Buckland, Devin M Mann, Michael N Cantor
We integrated and optimized patient-reported outcome measures into the electronic health record to provide quantitative, objective data regarding patients' health status, which is important for patient care, payer contracts, and research. With a multidisciplinary team from information technology, clinical informatics, population health, and physician champions, we used formal human-computer interaction techniques and user-centered design to integrate several technology platforms and computerized adaptive testing for the National Institutes of Health Patient-Reported Outcomes Measurement Information System...
December 5, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30516092/assessing-the-relation-of-the-coded-nursing-care-and-nursing-intensity-data-towards-the-exploitation-of-clinical-data-for-administrative-use-and-the-design-of-nursing-workload
#9
Pia Liljamo, Ulla-Mari Kinnunen, Kaija Saranto
Patient-care data from the electronic health record systems are increasingly in demand for re-use in administration and resource planning. Nursing documentation with coded concepts is expected to produce more reliable data, fulfilling better requirements for re-use. The aim was to ascertain what kind of relation exist between coded nursing diagnoses, nursing interventions, and nursing intensity and to discuss the possibilities for re-using nursing data for workload design. We analysed the retrospective nursing records of 794 patients documented by the Finnish Care Classification and nursing intensity data assessed by the Oulu Patient Classification over a 15-day period in nine inpatient units at a university hospital...
December 5, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30501370/too-much-or-too-little-investigating-the-usability-of-high-and-low-data-displays-of-the-same-electronic-medical-record
#10
Maher Al Ghalayini, Jumana Antoun, Nadine Marie Moacdieh
The high data density on electronic medical record screens is touted as a major usability issue. However, it may not be a problem if the data is relevant and well-organized. Our objective was to test this assumption using a comprehensive set of measures that assess the three pillars of usability: efficiency (both physical and cognitive), effectiveness, and satisfaction. Physicians were asked to go through a series of tasks using two versions of the same electronic medical record: one where all the display items were separated into tabs (the original display), and one where important display items were grouped logically in one tab (the redesigned display)...
November 30, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30501364/an-evaluation-of-behaviour-change-techniques-in-health-and-lifestyle-mobile-applications
#11
Gaston Antezana, Anthony Venning, Victoria Blake, David Smith, Megan Winsall, Simone Orlowski, Niranjan Bidargaddi
Despite the current popularity and potential use of mobile applications (apps) in the area of behaviour change, health promotion, and well-being for young people, it is unclear whether their design is underpinned by theory-based behaviour change techniques. Understanding the design of these apps may improve the way they can be used to support young people's well-being.The objectives of this study were to investigate what behaviour change techniques are included in the content of health and lifestyle apps, and determine which of these are prominent in app design...
November 30, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30497336/usability-aspects-of-medication-related-decision-support-systems-in-the-outpatient-setting-a-systematic-literature-review
#12
Alec Xander Hardenbol, Bram Knols, Mathijs Louws, Marjan Askari, Michiel Meulendijk
In this study, we evaluated the usability aspects of medication-related clinical decision support systems in the outpatient setting. Articles published between 2000 and 2016 in Scopus, PubMed and EMBASE were searched and classified into three usability aspects: Effectiveness, Efficiency and Satisfaction. Using Van Welie et al.'s usability model, we categorized usability aspects in terms of usage indicators and means. Out of the 1999 articles, 24 articles met the selection criteria of which the main focus was on reducing inappropriate medication, prescription rate and prescription errors...
November 30, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30497317/drivers-of-intentions-to-use-healthcare-information-systems-among-health-and-care-professionals
#13
Vladimir Ljubicic, Panayiotis H Ketikidis, Lambros Lazuras
Although investment in healthcare technology is rapidly increasing, the readiness to use emerging technologies among healthcare professionals is still low. The present study relies on an integrated model derived from the unified theory of acceptance and use of technology and the diffusion of innovation model to assess the factors that predicted healthcare professionals' intentions to use healthcare information systems. Using a cross-sectional correlational design, 105 healthcare professionals (M age = 41...
November 30, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30488755/a-comparison-of-logistic-regression-models-with-alternative-machine-learning-methods-to-predict-the-risk-of-in-hospital-mortality-in-emergency-medical-admissions-via-external-validation
#14
Muhammad Faisal, Andy Scally, Robin Howes, Kevin Beatson, Donald Richardson, Mohammed A Mohammed
We compare the performance of logistic regression with several alternative machine learning methods to estimate the risk of death for patients following an emergency admission to hospital based on the patients' first blood test results and physiological measurements using an external validation approach. We trained and tested each model using data from one hospital ( n = 24,696) and compared the performance of these models in data from another hospital ( n = 13,477). We used two performance measures - the calibration slope and area under the receiver operating characteristic curve...
November 29, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30488754/estimating-disease-burden-using-internet-data
#15
Riyi Qiu, Mirsad Hadzikadic, Sha Yu, Lixia Yao
Data on disease burden are often used for assessing population health, evaluating the effectiveness of interventions, formulating health policies, and planning future resource allocation. We investigated whether Internet usage and social media data, specifically the search volume on Google, page view count on Wikipedia, and disease mentioning frequency on Twitter, correlated with the disease burden, measured by prevalence and treatment cost, for 1633 diseases over an 11-year period. We also applied least absolute shrinkage and selection operator to predict the burden of diseases...
November 29, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30488752/are-youtube-videos-useful-for-patient-self-education-in-type-2-diabetes
#16
Gabriel Gimenez-Perez, Neus Robert-Vila, Marta Tomé-Guerreiro, Ignasi Castells, Didac Mauricio
OBJECTIVE: To evaluate the usefulness of YouTube videos as an educative tool for type 2 diabetes self-management. DESIGN: Search terms were "diabetes diet" and "diabetes treatment." Videos were jointly assessed by two reviewers. A third investigator evaluated a random sample to check for agreement. MAIN MEASURES: Usefulness defined as making reference to AAD7 Self-Care Behaviors™ and presence of misleading information...
November 29, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30488750/the-assessment-of-data-quality-issues-for-process-mining-in-healthcare-using-medical-information-mart-for-intensive-care-iii-a-freely-available-e-health-record-database
#17
Angelina Prima Kurniati, Eric Rojas, David Hogg, Geoff Hall, Owen A Johnson
There is a growing body of literature on process mining in healthcare. Process mining of electronic health record systems could give benefit into better understanding of the actual processes happened in the patient treatment, from the event log of the hospital information system. Researchers report issues of data access approval, anonymisation constraints, and data quality. One solution to progress methodology development is to use a high-quality, freely available research dataset such as Medical Information Mart for Intensive Care III, a critical care database which contains the records of 46,520 intensive care unit patients over 12 years...
November 29, 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30376769/a-soft-computing-approach-for-diabetes-disease-classification
#18
Mehrbakhsh Nilashi, Othman Bin Ibrahim, Abbas Mardani, Ali Ahani, Ahmad Jusoh
As a chronic disease, diabetes mellitus has emerged as a worldwide epidemic. The aim of this study is to classify diabetes disease by developing an intelligence system using machine learning techniques. Our method is developed through clustering, noise removal and classification approaches. Accordingly, we use expectation maximization, principal component analysis and support vector machine for clustering, noise removal and classification tasks, respectively. We also develop the proposed method for incremental situation by applying the incremental principal component analysis and incremental support vector machine for incremental learning of data...
December 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/30376768/medical-informatics-research-trend-analysis-a-text-mining-approach
#19
Yong-Mi Kim, Dursun Delen
The objective of this research is to identify major subject areas of medical informatics and explore the time-variant changes therein. As such it can inform the field about where medical informatics research has been and where it is heading. Furthermore, by identifying subject areas, this study identifies the development trends and the boundaries of medical informatics as an academic field. To conduct the study, first we identified 26,307 articles in PubMed archives which were published in the top medical informatics journals within the timeframe of 2002 to 2013...
December 2018: Health Informatics Journal
https://www.readbyqxmd.com/read/28050920/elderly-fall-risk-prediction-based-on-a-physiological-profile-approach-using-artificial-neural-networks
#20
Jafar Razmara, Mohammad Hassan Zaboli, Hadi Hassankhani
Falls play a critical role in older people's life as it is an important source of morbidity and mortality in elders. In this article, elders fall risk is predicted based on a physiological profile approach using a multilayer neural network with back-propagation learning algorithm. The personal physiological profile of 200 elders was collected through a questionnaire and used as the experimental data for learning and testing the neural network. The profile contains a series of simple factors putting elders at risk for falls such as vision abilities, muscle forces, and some other daily activities and grouped into two sets: psychological factors and public factors...
December 2018: Health Informatics Journal
journal
journal
34601
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"