Carolina Armagnague Thivant, Santiago Esteban, Analia J. Baum
1345 - 1346
By the implementation of the EMR in the Primary Care Centers of the City of Buenos Aires, it has been claimed that there is a need to obtain systematic and accurate information about the assessment that patients have about such incorporation. A qualitative research has been carried out in order to answer this query.
Personal Health Record (PHR) is not just the collection of personal health data but also a personal healthcare and disease management tool for the individual patient as well as a communication tool with the medical staff. Moreover, recently PHR has been considered an indispensable tool for patient engagement in the area of non-communicable diseases (NCDs) and has gained importance. Like many other developing countries, the growth of NCDs is very high in Bangladesh. Portable Health Clinic (PHC) system has been developed there with a focus on NCDs and PHR is there from the beginning. This study for the standardization of PHR system of PHC with the reference of the PHR proposed by Japanese Clinical Societies could be a reference work for the national PHR system development in the country.
Home rehabilitation after a hip operation can be daunting for the elderly. Lack of motivation to exercise and being insecure in the recovery process are common barriers. Personalized eHealth can help to ensure that the patient exercise efficiently, filling the gap between treatment in the practice with the physical therapist and practice at home.
The e-Prescription systems are modern and efficient prescribing tools which can affect the quality of the healthcare services. The aim of this study is to evaluate the e-Prescription systems in Greece based the users’ opinions. The survey was conducted in 2019 among 157 randomly selected healthcare profesionals through an on-line survey tool. The 51.2% of the sample were pharmacists and 48.8% physicians. 80.7% believe that the e-Prescription systems are reliable. More than the half of the professionals has the view that the e-Prescription systems are useful. Regarding to the ease of use, the e-Prescription systems, seem to can not fulfill sufficiently the participants’ requirements.
Anne Quesnel-Barbet, Julien Soula, Erik-André Sauleau, Pierre Parrend, Pierre Bazile, François Dufossez, Gilles Maignant, Pascal Staccini, Frédéric Albert, Arnaud Hansske
1353 - 1354
Since a French organization (2016) has defined “the territorial hospital groupings”, public hospitals must share medical-economic knowledge and decision-makers expect prospective analyses. PoleSat aims, quick hospital-catchment area modellings, completed by population analyses. Modellings are based on “diagnostic and interventional vascular catheterizations” acts and Nouvelle-Aquitaine, and they are carried out 3 times, through the graphical user interface’s main-setting values, coupled with 3 activity-scenarios. Scenario results cannot confirm the NA02-Atlantique’s H0. The experts have approved PoleSat’s method as a robust help-tool; therefore they project to repeat its usages.
Automated coding and classification systems play a role in healthcare for quality of care. Our objective was to predict diagnosis code from medication list of electronic medical record (EMR) using convolutional neural network (CNN). We collected the clinical note from outpatient department (OPD) of Wanfang hospital, Taiwan of 2016 and used three physicians from three departments. The dataset was split into two parts, 90% for training and 10% for test cases. We used medication list as input and International Statistical Classification of Diseases 10 (ICD 10) code as output. After data preprocess, we used word2vector CNN to predict ICD 10 code. This study shows all the three physicians from three departments achieved better performance. The best performance of model was a physician from cardiology department achieved precision 69%, recall 89% and F measure 78%. We need to include more component such as text data, lab report for evaluation.
Nan Liu, Andrew Fu Wah Ho, Pin Pin Pek, Tsung-Chien Lu, Pairoj Khruekarnchana, Kyoung Jun Song, Hideharu Tanaka, Ghulam Yasin Naroo, Han Nee Gan, Zhi Xiong Koh, Huei-Ming Ma, Marcus Ong
1357 - 1358
Out-of-hospital cardiac arrest (OHCA) is an important public health problem, with very low survival rate. In treating OHCA patients, the return of spontaneous circulation (ROSC) represents the success of early resuscitation efforts. In this study, we developed a machine learning model to predict ROSC and compared it with the ROSC after cardiac arrest (RACA) score. Results demonstrated the usefulness of machine learning in deriving predictive models.
Mads Nibe Stausholm, Pernille Heyckendorff Secher, Ole Kristian Hejlesen
1359 - 1360
The aim of this study was to identify predictors for hospital admissions in community-dwelling adults based on routinely collected community data. Univariate logistic regression analyses were performed to assess each variable’s ability to predict preventable and all cause hospital admissions.
David-Z. Issom, Jessica Rochat, Gunnar Hartvigsen, Christian Lovis
1361 - 1362
Adherence to the complex set of recommended self-care practices among people with Sickle-Cell Disease (SCD) positively impacts health outcomes. However, few patients possess the required skills (i.e. disease-specific knowledge, adequate levels of self-efficacy). Consequently, adherence rates remain low and only 1% of patients are empowered enough to master the self-care practices. Health coaching and therapeutic patient education have emerged as new approaches to enhance patients’ self-management and support health behavior changes. This preliminary feasibility study examined patients’ perceived usefulness of the information provided by a chatbot we developed following patient-important requirements collected during our preliminary studies. Participants tested the chatbot and completed a post-test survey. A total of 19 patients were enrolled and 2 withdrew. 15 respondents (15/17, 88%) gave a score of at least 3/4 to the question “The chatbot contains all the information I need”. Results suggest that mHealth coaching apps could be used to promote the knowledge acquisition of recommended health behaviors related to the prevention of SCD main symptoms.
Effective bed management is important for hospital management. Until now, bed allocation process is generally controlled by administrative staffs in centralized manner but it is not always effective. In the present study, we proposed and evaluated new method for bed allocation applying market mechanism via token. Evaluation was performed with newly-developed game-type simulation. Nurse managers as research participants played it and answered for survey. The result showed that the proposed method can be useful with appropriate operational design.
Rebecca Schnall, Lisa Kuhns, Cynthia Pearson, Josh Bruce, D. Scott Batey, Asa Radix, Uri Belkind, Marco A. Hidalgo, Sabina Hirshfield, Sarah Ganzhorn, Robert Garofalo
1365 - 1366
Our study team developed the MyPEEPS Mobile App for improving HIV prevention behaviors in diverse young men. We conducted a randomized controlled trial and evaluated the preliminary outcomes in the first half (N=350) of our intended study sample. Higher self-efficacy for HIV prevention behaviors (p=0.0042) and more recent HIV tests in the past 3 months (p=0.0156) were reported by the intervention group compared to control. Numbers of condomless anal sex acts were lower among the intervention group for both insertive anal sex acts (p=0.0283) and receptive anal sex acts (p=0.0001). Preliminary results indicate that some sexual risk behaviors were reduced among the intervention group in the preliminary analytic sample.
Ibrahim Habli, Charlotte Stockton-Powdrell, Matthew Machin, Paolo Fraccaro, Shon Lewis, Niels Peek
1367 - 1368
We discuss the preliminary safety analysis of a smartphone-based intervention for early detection of psychotic relapse. We briefly describe how we identified patient safety hazards associated with the system and how measures were defined to mitigate these hazards.
Agnieszka Lemanska, Sara Faithfull, Harshana Liyanage, Sophie Otter, Marina Romanchikova, Julian Sherlock, Nadia A.S. Smith, Spencer A. Thomas, Simon de Lusignan
1369 - 1370
Although routine healthcare data are not collected for research, they are increasingly used in epidemiology and are key real-world evidence for improving healthcare. This study presents a method to identify prostate cancer cases from a large English primary care database. 19,619 (1.3%) men had a code for prostate cancer diagnosis. Codes for medium and high Gleason grading enabled identification of additional 94 (0.5%) cases. Many studies do not report codes used to identify patients, and if published, the lists of codes differ from study to study. This can lead to poor research reproducibility and hinder validation. This work demonstrates that carefully developed comprehensive lists of clinical codes can be used to identify prostate cancer; and that approaches that do not solely rely on clinical codes such as ontologies or data linkage should also be considered.
Sara Mora, Sumit Madan, Stephan Gebel, Mauro Giacomini
1371 - 1372
Clinical and medical knowledge evolve and this causes changes in concepts and terms that describe them. The objective of this work is to formally present an ontology-based standard architecture that will be used in the scenario of neurodegeneration research to maintain terminologies and their relations updated and coherent over the time. The proposed structure is composed by three elements that will allow the user to do a list of operations on the terminology resources explicitly contemplated by the Common Terminology Service Release 2 (CTS2).
Su Min Kim, Suyoung Yoo, Won Chul Cha, Tae Rim Kim
1373 - 1374
We developed the service showing patient health record altogether which is managed by each hospital separately and recording the patient health information based on mobile application. We evaluated the effectiveness and satisfaction of the service. This study is aimed to reduce instances where patient’s medical records are unknown to the medical staff in emergencies and allow patients to use and utilize their health information.
Giuliana Colussi, Janine Sommer, Mariana Simón, Lucila Bruchanski, Daniel Luna
1375 - 1376
The aim of this research was to understand the needs of patients with psoriasis and the concerns of specialists in this pathology. Interviews with adults with psoriasis and dermatologists were conducted. We found 4 main dimensions: Frequently asked questions; Social stigma; Education to patients and Patient empowerment. The findings represent a first approach to understand the needs and perceptions of patients and dermatologists, for the design of a virtual community.
Emiliano Lopez, Maia Berlin, Romina Stein, Erica Cozzi, Andrea Bermudez, Humberto Mandirola Brieux, Martín Díaz Maffini, Roberto Moldes, Teodorico Bousquet, Patricia MacCulloch, Daniel A. Rizzato Lede, Cintia D. Speranza, Alejandro López Osornio
1377 - 1378
The Ministry of Health (MoH) set the National Digital Health Strategy 2018-2024 as a state policy. It included a National TeleHealth Plan to enhance access and quality of healthcare in a wide territory like Argentina, leveraging more than 20 years of national telemedicine experiences and coordinating it with the territorial integrated health service networks proposed by the Universal Health Coverage strategy. In collaboration with the Ministry of Modernisation, the MoH developed and implemented a new TeleHealth Web Platform to perform eReferrals and eConsultations nationwide. This poster describes the first 2 months of usage.
Oleg Metzker, Kirill Magoev, Stanislav Yanishevskiy, Alexey Yakovlev, Georgy Kopanitsa
1379 - 1380
Specific predictive models for diabetes polyneuropathy based on screening methods, for example Nerve conduction studies (NCS), can reach up to AUC 65.8–84.7 % for the conditional diagnosis of DPN in primary care. Prediction methods that utilize data from personal health records deal with large non-specific datasets with different prediction methods. It was demonstrated that the machine learning methods allow to achieve up to 0.7982 precision, 0.8152 recall, 0.8064 f1-score, 0.8261 accuracy, and 0.8988 AUC using the neural network classifier.
Using big data science we employ NLP and a novel interface the BMI Investigator to answer clinically meaninful questions. The use case presented is the association between Rosacea and Obstructive Sleep Apnea.
documentation of aspirin consumption is usually not complete and clear, probably because it’s a cheap drug that can be easily acquired.
To evaluate the quality of the record of aspirin consumption documented in the electronic medical records (EMRs) of a Private University Hospital of Argentina.
Qualitative and quantitative descriptive exploratory study.
principal findings were that 86 % of the notes mentioned aspirin as a chronic prescription. 12% mentioned its temporary suspension. Numerous EMRs mentioned the use of an “antiplatelet” drug without specifying which, and didn’t specify abbreviations, consumed dose or when to start or stop aspirin.
overall quality of aspirin related information registration in EMRs was poor. This is concerning since it’s a frequently prescribed drug, not exempt from adverse events.
Olli Korhonen, Vasiliki Mylonopoulou, Guido Giunti
1385 - 1386
This paper reports a case study on the spontaneous personalization discussions emerged from interviews with healthcare professionals when asked about their work practices and the role of information technology (IT) during consultations. We thematically analyzed the personalization elements using an existing personalization framework to provide insights on the service personalization. Our results contribute to the better design of IT solutions that can support health services’ personalization.
This poster presents some preliminary findings of the OpenWHO.org platform’s global use trends, in terms of the geographical distribution and occupational characteristics of its users. Assessment of user profiles is essential to measure the platform’s impact, most notably related to the attainment of its core mission: the provision of life-saving knowledge worldwide. A quantitative study was conducted on the global metrics of OpenWHO’s user statistics. Common user categories encompassed a wide range of professional bodies and occupations, both within public health and beyond, ranging from students and volunteers, to WHO staff, to members of international organizations and NGOs. Global tendencies in platform use confirm that that the mission of OpenWHO, to provide timely, up-to-date and easy-to-understand lifesaving knowledge to healthcare workers based in-country and responding to outbreaks at the front line, is being met.
The aim of this study was to investigate the validity and reliability of range of motion measurement via smartphone applications. This literature review included 26 articles after the selection process. The validity and reliability analysis showed good mean results (ICC or r >0.83). Thus, in clinical practice, photographic, goniometric and inclinometric smartphone applications can be used to measure joint angle, but with caution for cervical, hip and shoulder motions.
Alina Trifan, Dave Semeraro, Justin Drake, Radek Bukowski, José Luís Oliveira
1391 - 1392
This study investigated the feasibility of a postpartum depression predictor based on social media writings. The current broad use of social media networks generates a large amount of digital data, which, when coupled with artificial intelligence methods, have the potential to disclose significant health related insights. In this paper we explore the use of machine learning for prediction of postpartum depression on a corpus created from Reddit posts.
Due to the variety of different software systems and disparate observational databases, the need for a uniform data representation rises. Common data models (CDM) support the harmonisation of data. A powerful but compact software setup and a minimum vocabulary set has been composed via Docker to facilitate analysis of data across ten university hospitals. The presented approach also creates the possibility to use a concise database which is easy to deploy.