Medical informatics is increasingly central to the effective and efficient delivery of healthcare today.
This book presents the proceedings of the European Federation for Medical Informatics Special Topic Conference (EFMI STC 2017), held in Tel Aviv, Israel, in October 2017. The theme and title of the 2017 edition of this annual conference is ‘The practice of patient centered care: Empowering and engaging patients in the digital era’. The aim of the conference series is to increase interaction and collaboration between the stakeholder groups from both health and ICT across, but not limited to, Europe by providing a platform for researchers, data scientists, practitioners, decision makers and entrepreneurs to discuss sustainable and inclusive digital health innovations aimed at the engagement and empowerment of patients/consumers.
The book is divided into 3 sections: full papers, short communications, and posters, and covers a wide range of topics from the field of medical informatics. It will be of interest to healthcare planners and providers everywhere.
The EFMI STC 2017 was jointly organised by the European Federation for Medical Informatics (EFMI) and the Israelian Association for Medical Informatics (ILAMI). The aim of EFMI Special Topic Conferences is to provide a forum for discussing achievements and actual experiences on specific topics in medical informatics. STCs are organised in close collaboration with EFMI Working Groups and the national society of the hosting country.
Carrying on the series of EFMI Special Topic Conferences started in 2001 in Bucharest, under the presidency of Assa Reichert and Rolf Engelbrecht, and it is of great appreciation to his lifetime achievements, that we hold EFMI STC 2017 in Israel in memory of Assa Reichert. EFMI STC 2017 is one of the key European events in the common sphere of medicine and informatics in this year. Its major goal is to increase interaction and collaboration between the stakeholder groups from both health and ICT across, but not limited to, Europe. The 2017 event has been actively supported by the EFMI Working Groups “Health Information Management Europe (HIME)”, “Education (EDU)”, and “Portable Personal Devices (PPD)”.
The theme of STC 2017 is “The practice of patient centered care: Empowering and engaging patients in the digital era”. STC 2017 provides a platform for researchers, practitioners, decision makers and entrepreneurs to discuss ways for sustainable and inclusive innovations aimed at patient's/consumer's uptake, engagement and empowerment. Realising the potential of consumers' eHealth products (electronic tools for patients, informal caregivers and healthy consumers) in improving health care delivery and outcomes requires practitioners and designers to take account of existing diversity among users. This diversity contributes to differential access, uptake, and benefits derived from emerging eHealth technologies.
STC 2017 brings experience, innovation, new concepts and actual research and development into a constructive discussion resulting in a partnership for modernisation. Success stories but also failures which provide a basis for further improvement of health information systems' applications will be presented.
This publication reflects the objective of the conference to highlight research and development supporting the use of information and communication technology (eHealth) at national, regional, and also at international level. It results in requirements for national and regional solutions for medical informatics and health information management.
ILAMI was founded in 1983. Israel is a long standing member of the European Federation for Medical Informatics. ILAMI is representing Israel in EFMI and organised MIE1993 in Jerusalem.
Fostering partnerships for modernisation with this important country is another goal of this STC 2017. Efficient and effective delivery of health care requires accurate and relevant methodologies, e.g. patient-centered clinical data, its communication and application in medical decision support. This publication enables some insight in the use of information and communication technology in different countries. It is designed to have a high relevance in practice and further research.
The editors would like to thank all the authors for their excellent work as well as the reviewers for lending their expertise to the conference, thereby contributing to the final achievements. Furthermore, they are indebted for sponsoring the publication of the proceedings. Final thanks are dedicated to Carina Gutharz, who collaboratively organised the review processes.
Rolf Engelbrecht, Ran Balicer, Mira Hercigonja-Szekeres (Editors)
In Sweden, and internationally, there is a movement towards increased transparency in healthcare including giving patients online access to their electronic health records (EHR). The purpose of this paper is to analyze the Swedish patient accessible EHR (PAEHR) service using a socio-technical framework, to increase the understanding of factors that influence the design, implementation, adoption and use of the service. Using the Sitting and Singh socio-technical framework as a basis for analyzing the Swedish PAEHR system and its context indicated that there are many stakeholders engaged in these types of services, with different driving forces and incentives that may influence the adoption and usefulness of PAEHR services. The analysis was useful in highlighting important areas that need to be further explored in evaluations of PAEHR services, and can act as a guide when planning evaluations of any PAEHR service.
Harshana Liyanage, Uy Hoang, Filipa Ferreira, Denise Alexander, Michael Rigby, Mitch Blair, Simon De Lusignan
8 - 12
Computerised medical record (CMR) system data can be used to compare different models of health care for children. We identified sources of data from the Models of Child Health Appraised (MOCHA) project that compares family doctor led with paediatrician led and mixed models of child care using index conditions. Asthma and immunisation coverage are the first of these. We explored the extent to which an established Patient Registries Initiative (PARENT); MOCHA's own survey (MIROI); the European Centre for Disease Control (ECDC) immunisation information system survey and the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP) registry of data sources provided data to make comparisons of child health care. Five countries had data repositories for our index conditions from paediatrician lead services, compared with 14 for mixed, and 11 for family doctor led services. PARENT identified 212 sources, MIROI 148 sources, ECDC 17 sources and ENCePP 42; with immunisation related data sources found in all four but asthma in only three. There are less sources of electronic data available to study paediatrician led systems than other models; this risks unequal sample size bias.
Frederic Ehrler, Johan N. Siebert, Jessica Rochat, Franck Schneider, Annick Galetto, Alain Gervaix, Christian Lovis
13 - 17
Introduction: Patient centred care fosters a holistic approach of care switching the focus from a disease perspective to a patient's experience perspective. Patient centred care is of particular importance in the context of paediatric emergency medicine. Indeed, parents entering a paediatric emergency department (PED) are usually under stress caused by their children's illness, the unfamiliar setting of the PED and delays of care. All these factors can deteriorate their experience as well as the relationships between healthcare providers, the patients and their parents.
Methods: We explore potential areas to improve the patient experience during his journey into PED. The dimensions of the picker's patient centred care are used to guide observations, conduct interviews and focus groups. The areas of improvement are then operationalized through their translation into app functionalities.
Results: Our novel application allows supporting users on 7 of the 8 dimensions of picker's patient centred care model. The app supports parents in their decision-making to consult a PED, it provides relevant medical information to avoid unrealistic expectations and accompany the family after discharge thanks to tailored information sheets about diagnostics.
Conclusion: Our mobile app allows to make a big step toward the improvement of the patient-caregiver relationship. The direct benefits will be shared by patients and caregivers, as well as the institution.
HMOs record medical data and their interactions with patients. Using this data we strive to identify sub-populations of healthcare customers based on their communication patterns and characterize these sub-populations by their socio-demographic, medical, treatment effectiveness, and treatment adherence profiles. This work will be used to develop tools and interventions aimed at improving patient care. The process included: (1) Extracting socio-demographic, clinical, laboratory, and communication data of 309,460 patients with diabetes in 2015, aged 32+ years, having 7+ years of the disease treated by Clalit Healthcare Services; (2) Reducing dimensions of continuous variables; (3) Finding the K communication-patterns clusters; (4) Building a hierarchical clustering and its associated heatmap to summarize the discovered clusters; (5) Analyzing the clusters found; (6) Validating results epidemiologically. Such a process supports understanding different communication-channel usage and the implementation of personalized services focusing on patients' needs and preferences.
Vasiliki Foufi, Christophe Gaudet-Blavignac, Raphaël Chevrier, Christian Lovis
23 - 27
Maintaining data security and privacy in an era of cybersecurity is a challenge. The enormous and rapidly growing amount of health-related data available today raises numerous questions about data collection, storage, analysis, comparability and interoperability but also about data protection. The US Health Portability and Accountability Act (HIPAA) of 1996 provides a legal framework and a guidance for using and disclosing health data. Practically, the approach proposed by HIPAA is the de-identification of medical documents by removing certain Protected Health Information (PHI). In this work, a rule-based method for the de-identification of French free-text medical data using Natural Language Processing (NLP) tools will be presented.
Mihaela Crisan-Vida, Oana Sorina Lupse, Lacramioara Stoicu-Tivadar, Daniela Salvari, Radu Catanet, Elena Bernad
28 - 32
Cervical cancer is one of the most important causes of death in women in fertile age in Romania. In order to discover high-risk situations in the first stages of the disease it is important to enhance prevention actions, and ICT, respectively cloud computing and Big Data currently support such activities. The national screening program uses an information system that based on data from different medical units gives feedback related to the women healthcare status and provides statistics and reports. In order to ensure the continuity of care it is updated with HL7 CDA support and cloud computing. The current paper presents the solution and several results.
Naiara Muro, Nekane Larburu, Jacques Bouaud, Brigitte Seroussi
33 - 37
Technologies such as decision support systems are expected to help clinicians implement clinical practice guidelines (CPGs) with the aim of decreasing practice variations and improving clinical outcomes. However, if CPGs provide recommendations to improve patient care, they may fail to take into account actual clinical outcomes associated to the recommended treatment, such as adverse events or secondary effects. In this paper, we present a novel experience-based decision support approach applied to the management of breast cancer, the most commonly diagnosed cancer among women worldwide. Capitalizing on the clinical know-how of physicians and the modeling of patient's outcomes and toxicities in a computer interpretable way, we are able to discover new knowledge that helps improving patient-centered clinical care. This work is conducted within the EU Horizon 2020 project DESIREE.
Outcomes research and evidence-based medical practice is being positively impacted by proliferation of healthcare databases. Modern epidemiologic studies require complex data comprehension. A new tool, DisEpi, facilitates visual exploration of epidemiological data supporting Public Health Knowledge Discovery. It provides domain-experts a compact visualization of information at the population level. In this study, DisEpi is applied to Attention-Deficit/Hyperactivity Disorder (ADHD) patients within Clalit Health Services, analyzing the socio-demographic and ADHD filled prescription data between 2006 and 2016 of 1,605,800 children aged 6 to 17 years. DisEpi's goals facilitate the identification of (1) Links between attributes and/or events, (2) Changes in these relationships over time, and (3) Clusters of population attributes for similar trends. DisEpi combines hierarchical clustering graphics and a heatmap where color shades reflect disease time-trends. In the ADHD context, DisEpi allowed the domain-expert to visually analyze a snapshot summary of data mining results. Accordingly, the domain-expert was able to efficiently identify that: (1) Relatively younger children and particularly youngest children in class are treated more often, (2) Medication incidence increased between 2006 and 2011 but then stabilized, and (3) Progression rates of medication incidence is different for each of the 3 main discovered clusters (aka: profiles) of treated children. DisEpi delivered results similar to those previously published which used classical statistical approaches. DisEpi requires minimal preparation and fewer iterations, generating results in a user-friendly format for the domain-expert. DisEpi will be wrapped as a package containing the end-to-end discovery process. Optionally, it may provide automated annotation using calendar events (such as policy changes or media interests), which can improve discovery efficiency, interpretation, and policy implementation.
Traditionally, patient empowerment has been used as a strategy for health promotion. The rise of online communities of patients represents a good example of how patient empowerment occurs, independently of the intervention of existing healthcare providers and insurers, allowing thus a more accurate definition of meaning of this concept. We describe two situations related with the development of health-related social networks: (1) The emergence of a new biomedical research model in which patients lead research, shifting the equilibrium of power from the professionals to research subjects themselves, and (2) The emergence of Lay Crowd-Sourced Expertise in these communities, arising from the daily exchange among patients affected by chronic conditions and their relatives, giving place to a new era of bottom-up data generation, previously unknown in biomedical sciences. We enrich these descriptions by analyzing interviews to key actors of these “on line” communities": Michael Chekroun, founder of “Carenity, France”, and Paul Wicks Vice President at “PatientsLikeMe, USA”.
Sharing personal health data for direct care, health improvement, planning and research is recognised as important to improving the quality and safety of care. However, the complexities of sharing data, including technology, information governance and consent issues, means that many projects have difficulty communicating with the public about why they wish to share data, or what the benefits might be. Great Manchester Academic Health Science Network has established a Public Experience Group to help co-design the requirements for a health information exchange, called DataWell, across over 30 health and care organisations in Greater Manchester. This group has allowed the programme to uniquely respond to questions of how consent and data sharing should work with DataWell for direct care, as well as exploring other uses of the data, including planning and research.
The amount of stored data in health information systems can reach tera- and petabytes and application of specific algorithms in the field of data mining makes finding useful information suitable for making quality business decisions. A frequently used method for determining the rules of the relationship between attributes is the Association rule by applying Apriori algorithm. Lack of basic Apriori algorithm is derived from the slow work due to multiple scanned data sets. By examining the speed of generating the basic rules in relation to the improved Apriori algorithm by using software RapidMiner confirmed that the time required to generate rules for Improved algorithm is shorter, the rules are quickly generated particularly for large data sets, which is an advantage for making decisions.
Health care services face the challenge of providing individualised treatment to a growing ageing population prone to chronic conditions and multi-morbidities. The research project Patients and Professionals in Productive Teams aims to study health care services that are run with a patient-centred teamwork approach. In this context, a case study was made of a hospital-driven telemedicine service for chronic obstructive pulmonary disease patients after hospital discharge, with a focus on information flow and technology use. The methods used were observation and interviews with key informants. The results showed that the technology was perceived as well-functioning for telemedicine support, but the technology used was a standalone system and not integrated with the electronic health record of the hospital. In addition, there was lack of support to provide the patients at home with written instructions on advices of medical treatment and care. The electronic information used for this telemedicine services, allowed shared access of information for teamwork between professional only within the hospital.
The work described in this paper summarizes the development process and presents the results of a human genetics training application, studying the 20 amino acids formed by the combination of the 3 nucleotides of DNA targeting mainly medical and bioinformatics students. Currently, the domain applications using recognized human gestures of the Leap Motion sensor are used in molecules controlling and learning from Mendeleev table or in visualizing the animated reactions of specific molecules with water. The novelty in the current application consists in using the Leap Motion sensor creating new gestures for the application control and creating a tag based algorithm corresponding to each amino acid, depending on the position in the 3D virtual space of the 4 nucleotides of DNA and their type. The team proposes a 3D application based on Unity editor and on Leap Motion sensor where the user has the liberty of forming different combinations of the 20 amino acids. The results confirm that this new type of study of medicine/biochemistry using the Leap Motion sensor for handling amino acids is suitable for students. The application is original and interactive and the users can create their own amino acid structures in a 3D-like environment which they could not do otherwise using traditional pen-and-paper.
The new board EFMIs Working Group have has planned the future strategy for involving nurses in informatics. The strategy is to bring nursing informatics into the future. It is important to ensure that the next generation of nurses is involved in the work with Nursing Informatics and share knowledge. It must be done with a targeted effort including of social media and a more offensive effort at the annual MIE meetings.
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