Please activate JavaScript!
Please install Adobe Flash Player, click here for download

EH 4_2015

www.mediaform.de Secure identification No medical treatment errors Personalised medication labels Bedside scanning SCAN2PRINT: MORE PATIENT SAFETY www.healthcare-in-europe.com 7IT & TELEMED Beating the clock in disease surveillance Big Data may stream­ line epidemic control Report: Sascha Keutel It’s a race against the clock; every hour counts in efforts to halt the spread of a disease, but identifying anyone with whom the infected patient has had contact is time-consuming, with Contact Officers generally collecting data on paper. Now, however, scientists from the Nigerian Field Epidemiology Laboratory & Training Programme, the Helmholtz Centre for Infection Research, the Hasso Plattner Institute (HPI), Robert Koch Institute and Bernhard Nocht Institute for Tropical Medicine are developing a system to support reporting, communica- tion and management of infectious diseases outbreaks including Ebola, Measles, Avian Flu and Cholera with the help of a mobile app and Big Data technology. The prototype from the Surveillance and Outbreak Response Management System (SORMAS) is currently being tested in Nigeria. The system was designed to offer real-time and interactive capabilities to manage outbreak management procedures, analyse data and gener- ate reports. ‘SORMAS covers surveil- lance as well as containment func- tionalities,’ explains Professor Gérard Krause, head of the Epidemiology Department at Helmholtz Centre for Infection Research and the project coordinator. Mobile technology The system supports the different parties involved in epidemic surveil- lance, e.g. Contact Officers (Cos) who visit those who may have had contact with infected persons. Whilst the COs previously collected data on a hard copy questionnaire, with SORMAS they enter detailed case data directly on to the mobile device and transfer these in real-time to the relevant authorities. The data are stored in a cloud to be accessed by all other authorized participants in the process. ‘Involvement’ is a key issue for the epidemiologists: ‘From the outset, we designed SORMAS to integrate fully into existing national and international information pro- cesses and to comply with statutory requirements. We did not want to develop an additional and separate system but provide a tool to make the existing systems more efficient.’ SORMAS is based on in-memory database technology developed at HPI. It combines Big Data tech- nologies with smart applications. Commercially available smartphones and tablet PCs, which can be used even in remote rural areas, are equipped with specialised apps for mobile data collection in the field. In the background, complex processes run on cloud technology working with SAP‘s HANA database structure, which can handle information pro- cesses on Big Data level. Pilot phase ends After returning from a site visit dur- ing the field pilot in Nigeria, Krause reports, ‘fortunately there are no Ebola cases in Nigeria currently. So we had to design a complex virtual environment in which we simulated an Ebola outbreak, but we carried out the simulation under field condi- tions in the close to 100 localities and staff that would normally have to cope with the outbreak.’ The current funding of this research project from the German Ministry for Research and Education is scheduled for completion soon. In late August the data will be evaluated. Based on the results, the project partners will decide whether this approach will be persued for further development and expansion. Summarising his initial impressions, Krause said: ‘SORMAS definitely has an enormeous poten- tial. People in the field want such a system and, as far as the technology is concerned, it’s feasible. The con- cept offers several advantages com- pared to other current approaches using mobile devicest.’ A medical graduate from the University of Mainz, with a research doctorate in tropical hygiene from the University of Heidelberg, Gérard Krause worked as a physician and research associate in tropical hygiene, internal medicine and hospital hygiene in different hospitals and universities. He was epidemic intelligence service officer at the Centres for Disease Control and Prevention in Atlanta, USA, before moving to the Robert Koch Institute (RKI), in 2000, and there became director of the infectious dis- ease epidemiology department (2005-13). In 2011 Dr Krause became chair for infe- cious disease epidemiology at the Hannover Medical School and head of the epidemiol- ogy department at the Helmholtz Centre for Infection Research, Braunschweig. Rudi Balling studied nutrition at the University of Bonn and Washington State University (USA) and gained a PhD in Human Nutrition from the University of Bonn in 1984. After several research posts, in 1993 he was appointed Director of the Institute of Mammalian Genetics at the GSF National Research Centre for Environment and Health in Munich. Then, in 2001, he joined the Helmholtz Centre for Infection Research in Braunschweig as its Scientific Director. Eight years later, Prof. Balling became the founding direc- tor of the Luxembourg Centre for Systems Biomedicine (LCSB). Professor Heyo Kroemer studied phar- macy at Braunschweig Technical University and, in 1992, received his postdoctoral lec- ture qualification (habilitation) in pharmacy and toxicology at Eberhard Karls University Tubingen. He was professor of pharmacol- ogy and toxicology at Ernst Moritz Arndt University Greifswald (1998-2012), Dean of the Medical School at University Hospital Greifswald (2000-2012) and is currently Dean, Chairman for Research and Teaching and Chairman of the Managing Board at the University Medical Centre Göttingen. Dr Kroemer is also President of the German Medical Faculty Association. Epidemiologists and a Surveillance Officer testing SORMAS in Nigeria An ebola exercise with SORMAS seases How do you explain ‘Big Data’? ‘Big Data refers to data sets that are either too large or too complex to be analysed by conventional means. Note that complexity here is even more of an issue than size. I per- sonally would classify Big Data in healthcare in three categories: 1. Conventional Big Data, meaning information from genome or tran- scription analyses 2. Unused Big Data, meaning infor- mation that is being stored for regular healthcare purpose 3. Private Big Data, meaning data, such as those generated by smart- phones, which potentially could be used for health monitoring purposes. In my opinion Big Data in health- care is a potential research, and therefore knowledge, resource that is currently not being used and which we urgently have to tap.’ Is there European cooperation for this? ‘Many ideas are being discussed worldwide with regard to stand- ardisation. The USA’s government has created massive incentives and invested significantly in electronic patient records and is now in the process of ensuring interoperability. While there is a lively international debate on standards, in Germany, unfortunately, we are lagging miles behind. In healthcare IT, be it with regard to research or provision of care, there are only very few coop- eration projects. We hope there will be an increasing awareness of this issue, since I am utterly convinced that without these technologies we will not be able to master the demo- graphic change in the healthcare system.’ ‘We must change our idea of information technology. IT is a basic resource, just like water or energy. Thus it should not be an item we have to apply for in our individual project applications. IT should be available anywhere and there has to be the will to use or to be allowed to use untapped resources.’ Do patient rights come into play in this context? ‘That’s a crucial issue. As men- tioned before, in modern healthcare there are a number of problems that concern healthcare but cannot be solved by healthcare alone, for example legal, ethical and participa- tion issues. We absolutely must deal with these questions. For example: when I, as a patient, transfer my data via a smartphone to a certain system, such as an EPR in a hospital, it has to be clear beforehand who the owner of these data is.’ Are you afraid we will become ‘transparent patients’? ‘I recommend we don’t approach the issue driven by fear, but that we do a sensible and factual risk assessment: we recognise the posi- tive potential, the risks and the potential for abuse, and we look at them carefully. At the end of the day it is a cost- benefit analysis. I think the benefits of using Big Data far outweigh potential drawbacks.’ tection. In the era of social media, is the data protection law not actually well beyond what is required? As a society, we don’t yet know how to deal with this, but we’ll have to find a way. ‘The discussion around data pro- tection is anyway a lot more inten- sive in Germany than in other coun- tries. Unfortunately, this data protec- tion law is a hindrance in certain ways, not only for research but for patients as well. ‘The discussion around utilisation of the Cloud should also be carried out in a different way. In the future we will have few alternatives to the use of the Cloud, because we won’t be able to efficiently store and transport data in another way. ‘Institutes can no longer cover the storage costs of our own data on internal servers. It might work up to the terabyte and petabyte level, but from the exabyte-level onwards it will no longer be possible. ‘The real question should there- fore be: Do we stop research or will we get secure Clouds? ‘This development will have a dra- matic impact on the next generation because biomedicine cannot work without mathematics – it will there- fore have to work safely with IT and large data volumes.’

Pages Overview