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Keynote Speakers

Conference information

  • Conference date
    March 19th 2018
    9.30 am - 5.30 pm

  • Seminar date
    March 20th 2018
    9 am - 12 pm  

  • Venue
    Aarhus Universitet, Fredrik Nielsensvej 7, 8000 Aarhus C, Denmark.
    Building: 1333. Room: Auditorium A1
     
  • Deadline registration
    March 10th 2018

  • Price
    150 Dkkr

Data-driven policies? Contemporary Danish policy visions of health data use

Klaus Hoeyer, Department of Healthcare Research, University of Copenhagen, Denmark

Abstract:

Denmark has long been regarded as being at the forefront of not only systematic compilation of health data but also digitalization and data reuse. National policies envision a ‘data-driven’ health-care sector, but the vision itself is not necessarily based on data, and the policies in which it is articulated are highly selective in terms of the types of knowledge that are recognized. Taking an anthropological approach to data intensification as a cultural construct, I present an introduction to the on-going Danish restructuring of the health data infrastructure arguing that ‘data’ have come to serve as much as promises for the future as conveyors of lessons from the past. They are mythical forms of orientation as much as rational forms of evidence. In many cases, policies of digitalized data collection serve to postpone ‘data-driven healthcare’ to a yet-to-come future and make collection per se a responsible response to contemporary problems.

Bio:

Klaus Hoeyer is Professor of medical STS at the University of Copenhagen, Centre for medical STS. His background is in social anthropology and he currently leads an European Research Council-funded project on intensified data sourcing in healthcare. His research is concerned with the social, political and economic conditions and consequences related to biobank research and with the anthropology of potentiality. Klaus Hoeyer has authored the book: Exchanging human bodily material (Springer 2013).

The future of health is cognitive

Jens Edlef Møller, Executive Architect, IBM Nordic

Abstract:

Using large sets of unstructured and structured data it is possible to gain insight which can be used for a better treatment of patients. Precision medicine requires much more than data captured in EMR systems in hospitals and clinics. Other data sources such as weather data and data generated by the patient is needed to construct the best possible decision support algorithms. This presentation will describe a platform for collecting and analyzing large sets of data which are leveraged for building clinical decision support tools for clinical staff and patients.

Bio:

Jens Edlef Møller, M.Sc. Computer Science. Healthcare Technical Leader, IBM Nordic.  Jens E. Møller has worked with healthcare information systems in IBM across the globe since 1998 and has been lead architect of some of the largest healthcare IT systems in Denmark.  Current focus of work is health data platforms and diagnostic advisor applications based on cognitive technology. 

Constructing and Governing ‘Quality’ Healthcare

Katie Pine, Arizona State University, USA

Abstract:

The erosion of public trust in healthcare professionals and organizations has forced hospitals to establish new practices of accountability and visibly embrace new forms of performance measurement. In service of measuring, verifying, narrating, and “performing” performance, the healthcare industry in the United States has developed a massive enterprise premised on the capacities of information technologies. Automated performance measurement algorithms and expanded capabilities for data storage, retrieval, and analytics have become critical tools in demonstrating attention to cost, performance, and effectiveness—indeed, hospitals are now assigned publicly accessible letter grades (A-F) for safety. However, these techniques of future making are radically configuring practices of accountability on the ground —for example professionals have become accountable for adhering to minute work processes rather than to producing acceptable outcomes and organizations are actively redesigning themselves in service of quantified outcomes. Drawing on critical accounting literature that examines the reformulation of examinations in other domains (e.g. education), we analyze emerging forms of accountability of healthcare organizations as key shifts in practice that have both direct impacts for professionals and organizational performance and are also introducing fundamental shifts in how healthcare organizations ‘learn to learn.’ Changes in accountability practice are restructuring the way that healthcare organizations and individuals reflect and learn about performance, and fundamentally reshaping the patterns that relations between power and knowledge about healthcare performance can and do take.  To do so we draw on multi-sited ethnographic research on performance measurement of healthcare quality focused around maternal/child healthcare to describe how the reconfiguration of accountability plays out through situated practices of performance measurement. 

Bio:  

Kathleen H. Pine is assistant professor in the School for the Science of Health Care Delivery at Arizona State University. Her research lies at the intersection of human-centered computing (CSCW/HCI/health informatics), organization studies, and science and technology studies. The research and teaching  focuses on socio-technical systems and their potential to both cause and address complex social and organizational problems, particularly in the domains of healthcare organizations, health promotion, and environmental health.

Adoption of Electronic Health Records (EHR) in the U.S. and Quality of EHR Data

Kai Zheng, University of California – Irvine, USA

Abstract: 

Stimulated by policy changes and monetary incentives, the majority of U.S.-based hospitals and clinics have by now implemented electronic health records (EHR) systems. While use of EHR leads to better capturing of structured and computable patient care data, it is also shown to create new issues such as redundancy, inconsistency of data recorded in different sources, and new types of errors introduced by software or poorly designed software-user interfaces. In this talk, I will first present a brief introduction to the status of EHR adoption in the U.S., followed by a discussion of numerous issues reported in the literature that may jeopardize the value of EHR-recorded data for patient care and for secondary use purposes such as quality improvement and research. I conclude that while progresses are being made, significant future work is needed to improve the accuracy and completeness of data recorded in EHR systems in order to unleash their true power for improving patient care processes and ultimately patient health outcomes.

Bio:

Kai Zheng is associate professor at Department of Informatics, and associate adjunct professor, Department of emergency medicine, UC-Irvine. Prior to joining UCI, he was Associate Professor of Health Management and Policy in the School of Public Health and Associate Professor of Information in the School of Information at the University of Michigan. He was Director of University of Michigan's Health Informatics Program preparing students for careers that will harness the power of information to enhance health and transform individual health and healthcare.

How Can Big Data be utiliized and made useful for health care professionals?

Kaj Grønbæk, Department of Computer Science, Aarhus University

Abstract:

Large amounts of data are generated everywhere in the health sector and there are untapped potentials to improve quality both in relation to logistics and treatment.

The presentation gives examples of experiences using Big Data analytics tools and methods on different types of health data spanning from sensor data collected via wearables to hospital logistics data based on indoor positioning and activity recognition. Methods based on machine learning and visual analytics of event sequence data will be explained.

Bio:

Kaj Grønbæk is professor at the Department of Computer Science, University of Aarhus, Denmark. He is manager of the Center for Interactive, and presently WP leader in the Big Data Analytics project, DABAI, supported by the Innovation Foundation Denmark. In addition to research into visual analytics for Big Data, he conducts research into Ubiquitous and Pervasive Computing, Augmented Reality, Visual Analytics, Interaction Design, Interactive Spaces, and Computer Supported Cooperative Work.

Living in a world of numbers: the myth of quantified-self and the downside of self-tracking in healthcare

Yunan Chen, University of California – Irvine, USA

Abstract: 

Recent proliferation of mobile and sensor based health applications has created a culture of quantified health and the deep pursuit of numbers in individual health management. From daily steps, food intake, to specific health indicators such as body temperature, blood pressure, mood, the ability to collect personal health data has led to increasing concerns and engagements with the tracked data. Drawing on several projects examining the practices of self-tracking in healthcare, this talk I will outline several negative impacts of quantified health on individual health consumers. In particular, our studies show that people chose to live in a world of numbers where their everyday lives have been influenced and guided by the data they collected and by the data they anticipate having. The passion towards data has led to serious unintended physical and emotional consequences that are opposite to the promises held by the qualified-self initiative. I will discuss factors that help individuals to move away from living in numbers, and discuss ways to mitigate the unintended consequences of datafication on health consumers.

Bio:

Yunan Chen is associate professor of Informatics at the Donald Bren School of Information and Computer Sciences at the University of California, Irvine. Her research focuses on designing and evaluating interactive systems for clinical documentation, patient-provider interaction and personal information management during chronic care, and lies in the intersection of Human-Computer Interaction (HCI), Computer Supported Cooperative Work (CSCW) and Health Informatics.

Collection of health data for primary and secondary use and all that in between

Karen Marie Lyng, Head of Department, Dept. of Data quality and content, Danish Health Data Authority

Abstract:

Data are collected in the health care sector for a wide variety of aims. Primary collection and use of data are usually related to the clinical setting and treatment of the individual patient. Secondary use of data have traditionally been when the data are  reported to central registries and applied for monitoring of the health sector activities, the quality of care, the use of resources etc.  However, currently a number of new data sources are being deployed, it has become possible to efficiently and securely exchange large data sets and further the use of new data processing tools have become possible; this all together provide new possibilities in the borderline territory between primary and secondary use of health data. With the high quality, Danish health care registries covering most of the Danish healthcare sector and all Danish citizens, we can expect in the near future to see a wide range of decision support and predictive tools based on established data collections. 

Exemplified by the National Patient Registry (Landspatientregistret – LPR3) and the national focus area in Patient Reported Outcome/Information – PRO, I will present some of the upcoming possibilities of the datafication in the healthcare sector. 

Bio:

Karen Marie Lyng started her career as a trained surgeon. Since 1998 she has been an administrator, mostly working within the field of data driven quality improvement. Her PhD from 2010 is on the topic of how to integrate clinical practice guidelines in electronic patient records. She is currently responsible for several major projects in the health data area among them is new a National Patient Register and establishment of infrastructure and content for reporting of Patient Reported Information (PRO).