53 © 2017 IMIA and Schattauer GmbH The Role of Free/Libre and Open Source Software in Learning Health Systems C. Paton1, T. Karopka2 1 Group Head for Global Health Informatics, Centre for Tropical Medicine and Global Health, University of Oxford, UK 2 Chair of IMIA OS WG, Chair of EFMI LIFOSS WG, Project Manager, BioCon Valley GmbH, Greifswald, Germany LHSs, examining the academic literature, Summary Introduction the MedFLOSS database that catalogues Objective: To give an overview of the role of Free/Libre and As more patient data are collected electron- FLOSS in use in healthcare [6], and the Open Source Software (FLOSS) in the context of secondary use of ically through Electronic Health Records grey literature from websites, reports, and patient data to enable Learning Health Systems (LHSs). (EHRs) and other information systems used personal communications with experts in Methods: We conducted an environmental scan of the academic in healthcare organisations, the opportunity the area of FLOSS adoption in healthcare. and grey literature utilising the MedFLOSS database of open to reuse the data these systems collect for Although some EHRs and research source systems in healthcare to inform a discussion of the role research and quality improvement becomes systems are fully open source, such as the of open source in developing LHSs that reuse patient data for more apparent. There is now a wide range of Veterans Information Systems and Technology research and quality improvement. large-scale research projects [1, 2] that are Architecture (VistA) [7], modern healthcare Results: A wide range of FLOSS is identified that contributes to reusing routinely collected data for analysis infrastructure is often a combination of the information technology (IT) infrastructure of LHSs including and the concept of a Learning Health Sys- open source and proprietary systems. In our operating systems, databases, frameworks, interoperability tem (LHS) has been coined to summarise analysis, we will therefore examine how the software, and mobile and web apps. The recent literature around this cycle of data collection, analysis, and open source (OS) ‘stack’ from infrastructure the development and use of key clinical data management tools health service improvement [3–5]. to user interfaces is used in healthcare appli- is also reviewed. There is a plethora of different information cations. We will then examine the range of Conclusions: FLOSS already plays a critical role in modern systems in use across healthcare systems OS data analysis tools and look at how new health IT infrastructure for the collection, storage, and analysis around the world. Although many user-facing modular EHR “apps” that utilise open source of patient data. The nature of FLOSS systems to be collaborative, systems are proprietary in nature, meaning software and open standards can close the modular, and modifiable may make open source approaches that source code for the software is protected loop to create a LHS that reuses patient data appropriate for building the digital infrastructure for a LHS. and cannot be modified, many systems use in- to enable better clinical decision making. frastructure components that are open source Keywords (meaning that the source code is licenced in a FLOSS; Open Source; Learning Health Systems; Secondary Use way that allows for modification and reuse). This paper aims to discuss the role of Free/ Yearb Med Inform 2017:53-8 Libre and Open Source Software (FLOSS) in Results http://dx.doi.org/10.15265/IY-2017-006 modern healthcare information technology Our environmental scan has resulted in the Published online May 8, 2017 (IT) infrastructure and will highlight some identification of a wide range of FLOSS that of the major open source projects that are contribute to health IT projects critical for contributing to the development of LHSs LHSs. We have therefore divided our find- that reuse patient data for research and health ings into general purpose FLOSS building service improvement. blocks such as operating systems, frame- works, and databases (Core Infrastructure FLOSS); FLOSS projects used to analyse patient data but not specifically designed for clinical purposes such as general purpose Methodology statistical software; FLOSS projects that We have undertaken a broad environmental are used in healthcare but may or may not scan utilising a snowballing approach to contribute to LHS development depending the discovery of FLOSS that contributes to on how they are implemented, such as open IMIA Yearbook of Medical Informatics 2017 54 Paton et al. source EHR systems (Clinical FLOSS); and Table 1 General categories of FLOSS Clinical Data Management FLOSS that, when combined with EHR systems and core Categories Examples technologies, can form the digital infrastruc- Core Infrastructure FLOSS Operating Systems, Frameworks, Databases, Core Applications ture for LHSs. Table 1 displays the set of the (See Table 2) general categories identified along with a list Data Analysis FLOSS Statistical Software, Big Data Software, AI/Machine Learning of examples in each category. (Table 4) Clinical FLOSS EHRs, HIS, LIMS, PACS, Interoperability Engines (See Table 3) Clinical Data Management FLOSS OpenClinica, TranSMART, i2b2, CohortExplorer, SEMCARE, OMOP Core Infrastructure FLOSS Open source operating systems are now used Table 2 Example of FLOSS used in Core Infrastructure in a wide variety of clinical environments. Servers running Linux often power in-house Operating Systems Frameworks Databases Applications data-centres and cloud-based EHR systems. Databases such as MySQL, PostgresQL and Linux AngularJS MySQL Apache newer NoSQL languages are now storing Android Bootstrap PostgresQL Chromium clinical data for a wide range of EHR sys- Apache Spark Riak Firefox tems including the NHS ‘spine’ that uses Java Spring Eclipse the OS Riak NoSQL system at its core [8]. Django Most modern EHR systems allow clinicians to input and retrieve data through mobile devices or web interfaces (or web interfaces Table 3 Examples of FLOSS used in Data Analysis to run complex analyses over large datasets on mobile devices). The two major mobile by breaking the dataset down into chunks operating systems are based on OS projects: Statistical Software Big Data/AI which are analysed in parallel using open Android is a fully open source system and source systems such as Apache Hadoop. R HDFS iOS is based on the BSD version of Unix. Table 3 details some of the core FLOSS DataMelt MapReduce Clinical apps use a variety of OS frameworks projects designed for data analysis that are including AngularJS, the Spring framework, GNU Octave Weka used as building blocks for LHSs. and Django to deliver the user interface. Table Mondrian Torch 2 shows a few examples of core infrastructure OpenNN FLOSS (although the number of projects in use in various healthcare systems around the Clinical FLOSS world is too numerous to list in full here). As or levels of adherence to clinical guidelines. There are now a number of large scale an example, the development of a nursing in- A simple analysis can often be performed FLOSS projects that enable the collection telligence system in a large university hospital by exporting information from an EHR of patient data in clinical settings. Most of [9] illustrates how these building blocks can database into a CSV file for analysis in a these are not specifically designed for data be put together to build a LHS. The authors spread sheet. As more data are collected and reuse as part of a LHS but, as with the core use different open source tools for data ware- analyses become more automated as part of infrastructure tools and statistical software housing and business intelligence. They used a formal LHS, this approach becomes more described above, can form part of a LHS the Talend Open Studio for data integration difficult and organisations and researchers when combined with other software. Some (www.talend.com), a PostgreSQL (www.post- use more sophisticated systems for manag- high-profile examples from the MedFLOSS gresql.org) database for data management, ing and analysing the clinical data. The R database are detailed in Table 4. and for data analysis, business intelligence, open source statistical analysis package is and result presentation, they used the BIRT often used as part of the infrastructure of a (Business Intelligence and Reporting Toolkit, LHS as there is now a large library of open www.eclipse.org/birt) toolkit. source tools that allow data to be import- Clinical Data Management FLOSS ed, analysed, and exported to dashboards At the heart of a LHS is the ability to trans- or other visualisation systems often in an form clinical data into new knowledge. This automated or semi-automated fashion. As knowledge may be generalizable and may Data Analysis FLOSS datasets grow larger and analyses become contribute to new scientific understanding or In order to reuse data from clinical sys- more complex, the limits of statistical tools it may be specific to a particular healthcare tems, they must first be analysed to create such as R mean that new “Big Data” tools organisation and contribute to local quality actionable insights such as mortality rates are required. These tools enable researchers improvement. Over recent years, a number IMIA Yearbook of Medical Informatics 2017 55 The Role of Free/Libre and Open Source Software in Learning Health Systems Table 4 Examples of Clinical FLOSS TranSMART: TranSMART is another open source clinical and basic science re- Application Types Examples search platform, originally developed by Johnson and Johnson and then established Electronic Health Record (EHR) WorldVistA, OpenMRS, GNU Health, OpenMAXIMS, LibreHealth EHR, as an open source platform supported by the tranSMART Foundation from 2013 [22]. Picture Archive and Communication System (PACS) MRIdb, Orthanc, DICoogle, Xebra, OSPACS, Both the tranSMART and OpenClinica OpenSourcePACS, ClearCanvas, Conquest DICOM software, CDMEDIC PACS WEB, DCMTK - DICOM Toolkit, dcm4che platforms have been extended, connected, and enhanced by the international open Health Information System (HIS) DHIS2 source community.