@article {1210, title = {Open Source Infrastructure for Health Care Data Integration and Machine Learning Analyses.}, journal = {JCO Clin Cancer Inform}, volume = {3}, year = {2019}, month = {2019 Aug}, pages = {1-16}, abstract = {

PURPOSE: We have created a cloud-based machine learning system (CLOBNET) that is an open-source, lean infrastructure for electronic health record (EHR) data integration and is capable of extract, transform, and load (ETL) processing. CLOBNET enables comprehensive analysis and visualization of structured EHR data. We demonstrate the utility of CLOBNET by predicting primary therapy outcomes of patients with high-grade serous ovarian cancer (HGSOC) on the basis of EHR data.

MATERIALS AND METHODS: CLOBNET is built using open-source software to make data preprocessing, analysis, and model training user friendly. The source code of CLOBNET is available in GitHub. The HGSOC data set was based on a prospective cohort of 208 patients with HGSOC who were treated at Turku University Hospital, Finland, from 2009 to 2019 for whom comprehensive clinical and EHR data were available.

RESULTS: We trained machine learning (ML) models using clinical data, including a herein developed dissemination score that quantifies the disease burden at the time of diagnosis, to identify patients with progressive disease (PD) or a complete response (CR) on the basis of RECIST (version 1.1). The best performance was achieved with a logistic regression model, which resulted in an area under receiver operating characteristic curve (AUROC) of 0.86, with a specificity of 73\% and a sensitivity of 89\%, when it classified between patients who experienced PD and CR.

CONCLUSION: We have developed an open-source computational infrastructure, CLOBNET, that enables effective and rapid analysis of EHR and other clinical data. Our results demonstrate that CLOBNET allows predictions to be made on the basis of EHR data to address clinically relevant questions.

}, issn = {2473-4276}, doi = {10.1200/CCI.18.00132}, author = {Isoviita, Veli-Matti and Salminen, Liina and Azar, Jimmy and Lehtonen, Rainer and Roering, Pia and Carp{\'e}n, Olli and Hietanen, Sakari and Gr{\'e}nman, Seija and Hynninen, Johanna and F{\"a}rkkil{\"a}, Anniina and Hautaniemi, Sampsa} } @article {1228, title = {PatientExploreR: an extensible application for dynamic visualization of patient clinical history from Electronic Health Records in the OMOP Common Data Model Title.}, journal = {Bioinformatics}, year = {2019}, month = {2019 Jun 19}, abstract = {

MOTIVATION: Electronic Health Records (EHR) are quickly becoming omnipresent in healthcare, but interoperability issues and technical demands limit their use for biomedical and clinical research. Interactive and flexible software that interfaces directly with EHR data structured around a common data model could accelerate more EHR-based research by making the data more accessible to researchers who lack computational expertise and/or domain knowledge.

RESULTS: We present PatientExploreR, an extensible application built on the R/Shiny framework that interfaces with a relational database of EHR data in the Observational Medical Outcomes Partnership Common Data Model (CDM) format. PatientExploreR produces patient-level interactive and dynamic reports and facilitates visualization of clinical data without any programming required. It allows researchers to easily construct and export patient cohorts from the EHR for analysis with other software. This application could enable easier exploration of patient-level data for physicians and researchers. PatientExploreR can incorporate EHR data from any institution that employs the CDM for users with approved access. The software code is free and open-source under the MIT license, enabling institutions to install and users to expand and modify the application for their own purposes.

AVAILABILITY: PatientExploreR can be freely obtained from GitHub: https://github.com/BenGlicksberg/PatientExploreR. We provide instructions for how researchers with approved access to their institutional EHR can use this package. We also release an open sandbox server of synthesized patient data for users without EHR access to explore: http://patientexplorer.ucsf.edu.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btz409}, author = {Glicksberg, Benjamin S and Oskotsky, Boris and Thangaraj, Phyllis M and Giangreco, Nicholas and Badgeley, Marcus A and Johnson, Kipp W and Datta, Debajyoti and Rudrapatna, Vivek and Rappoport, Nadav and Shervey, Mark M and Miotto, Riccardo and Goldstein, Theodore C and Rutenberg, Eugenia and Frazier, Remi and Lee, Nelson and Israni, Sharat and Larsen, Rick and Percha, Bethany and Li, Li and Dudley, Joel T and Tatonetti, Nicholas P and Butte, Atul J} } @article {1235, title = {A Platform for Innovation and Standards Evaluation: a Case Study from the OpenMRS Open-Source Radiology Information System.}, journal = {J Digit Imaging}, volume = {31}, year = {2018}, month = {2018 06}, pages = {361-370}, abstract = {

Open-source development can provide a platform for innovation by seeking feedback from community members as well as providing tools and infrastructure to test new standards. Vendors of proprietary systems may delay adoption of new standards until there are sufficient incentives such as legal mandates or financial incentives to encourage/mandate adoption. Moreover, open-source systems in healthcare have been widely adopted in low- and middle-income countries and can be used to bridge gaps that exist in global health radiology. Since 2011, the authors, along with a community of open-source contributors, have worked on developing an open-source radiology information system (RIS) across two communities-OpenMRS and LibreHealth. The main purpose of the RIS is to implement core radiology workflows, on which others can build and test new radiology standards. This work has resulted in three major releases of the system, with current architectural changes driven by changing technology, development of new standards in health and imaging informatics, and changing user needs. At their core, both these communities are focused on building general-purpose EHR systems, but based on user contributions from the fringes, we have been able to create an innovative system that has been used by hospitals and clinics in four different countries. We provide an overview of the history of the LibreHealth RIS, the architecture of the system, overview of standards integration, describe challenges of developing an open-source product, and future directions. Our goal is to attract more participation and involvement to further develop the LibreHealth RIS into an Enterprise Imaging System that can be used in other clinical imaging including pathology and dermatology.

}, keywords = {Diagnostic Imaging, Humans, Radiology Information Systems, Software, Systems Integration, Workflow}, issn = {1618-727X}, doi = {10.1007/s10278-018-0088-5}, author = {Gichoya, Judy W and Kohli, Marc and Ivange, Larry and Schmidt, Teri S and Purkayastha, Saptarshi} } @article {1206, title = {Health care consumer{\textquoteright}s perception of the {Electronic} {Medical} {Record} ({EMR}) system within a referral hospital in {Kigali}, {Rwanda}}, journal = {Rwanda Journal}, volume = {4}, year = {2017}, pages = {48{\textendash}53{\textendash}53}, abstract = {Background: Worldwide Electronic Medical Records (EMR) when compared to a paper-based system has been proven to improve service delivering numerous health care facilities. However, no research has been described in the literature regarding the user{\textquoteright}s perception of the clinical electronic medical record (EMR) system in Rwanda. The objective of this study is to evaluate the health care consumer{\textquoteright}s perception of the Electronic Medical Record (EMR) OpenClinic regarding improving the quality of health care delivery within the hospital setting. How does the OpenClinic system affect the patients{\textquoteright} waiting time? How complete is the information obtained from OpenClinic as compared to paper medical records, and the level of satisfaction of the users of OpenClinic.Method: A structured questionnaire was developed, validated and utilized in this quantitative research project. Quantitative data were collected from 170 participants while an interview guide was used to collect qualitative data from 6 key informants at a referral hospital in Kigali. The SPSS version 20.0 was used to analyze the quantitative data. The interviews transcribed verbatim; the data were thematically analyzed and categorized by pre-determined themes. Permission to conduct the study was approved from the ethics committee of the University of Rwanda, College of Health Sciences and the hospital.Results: The majority of the participants were satisfied with OpenClinic, (90\%), while only a few (10\%) did not perceive any advantage of a computer-based EMR and preferred paper based records.Conclusion: Openclinc EMR was seen to be an improvement in the data collection involving health care delivery in Kigali, Rwanda.Keywords: Electronic Medical Records, OpenClinic and Perceptions}, keywords = {Electronic medical records, OpenClinic and Perceptions}, issn = {2305-2678}, doi = {10.4314/rj.v4i1.7F}, url = {https://www.ajol.info/index.php/rj/article/view/156412}, author = {Uwambaye, Peace and Njunwa, Kato and Nuhu, Assouman and Kumurenzi, Anne and Isyagi, Moses and Murererehe, Julienne and Ngarambe, Donart} } @inbook {1119, title = {BiobankCloud: A Platform for the Secure Storage, Sharing, and Processing of Large Biomedical Data Sets}, booktitle = {Biomedical Data Management and Graph Online Querying: VLDB 2015 Workshops, Big-O(Q) and DMAH, Waikoloa, HI, USA, August 31 {\textendash} September 4, 2015, Revised Selected Papers}, year = {2016}, pages = {89{\textendash}105}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {Biobanks store and catalog human biological material that is increasingly being digitized using next-generation sequencing (NGS). There is, however, a computational bottleneck, as existing software systems are not scalable and secure enough to store and process the incoming wave of genomic data from NGS machines. In the BiobankCloud project, we are building a Hadoop-based platform for the secure storage, sharing, and parallel processing of genomic data. We extended Hadoop to include support for multi-tenant studies, reduced storage requirements with erasure coding, and added support for extensible and consistent metadata. On top of Hadoop, we built a scalable scientific workflow engine featuring a proper workflow definition language focusing on simple integration and chaining of existing tools, adaptive scheduling on Apache Yarn, and support for iterative dataflows. Our platform also supports the secure sharing of data across different, distributed Hadoop clusters. The software is easily installed and comes with a user-friendly web interface for running, managing, and accessing data sets behind a secure 2-factor authentication. Initial tests have shown that the engine scales well to dozens of nodes. The entire system is open-source and includes pre-defined workflows for popular tasks in biomedical data analysis, such as variant identification, differential transcriptome analysis using RNA-Seq, and analysis of miRNA-Seq and ChIP-Seq data.}, isbn = {978-3-319-41576-5}, doi = {10.1007/978-3-319-41576-5_7}, url = {http://dx.doi.org/10.1007/978-3-319-41576-5_7}, author = {Bessani, Alysson and Brandt, J{\"o}rgen and Bux, Marc and Cogo, Vinicius and Dimitrova, Lora and Dowling, Jim and Gholami, Ali and Hakimzadeh, Kamal and Hummel, Micheal and Ismail, Mahmoud and Laure, Erwin and Leser, Ulf and Litton, Jan-Eric and Martinez, Roxanna and Niazi, Salman and Reichel, Jane and Zimmermann, Karin}, editor = {Wang, Fusheng and Luo, Gang and Weng, Chunhua and Khan, Arijit and Mitra, Prasenjit and Yu, Cong} } @article {1135, title = {Improving documentation of clinical care within a clinical information network: an essential initial step in efforts to understand and improve care in Kenyan hospitals.}, journal = {BMJ Glob Health}, volume = {1}, year = {2016}, month = {2016 May 24}, pages = {e000028}, abstract = {

In many low income countries health information systems are poorly equipped to provide detailed information on hospital care and outcomes. Information is thus rarely used to support practice improvement. We describe efforts to tackle this challenge and to foster learning concerning collection and use of information. This could improve hospital services in Kenya. We are developing a Clinical Information Network, a collaboration spanning 14 hospitals, policy makers and researchers with the goal of improving information available on the quality of inpatient paediatric care across common childhood illnesses in Kenya. Standardised data from hospitals{\textquoteright} paediatric wards are collected using non-commercial and open source tools. We have implemented procedures for promoting data quality which are performed prior to a process of semi-automated analysis and routine report generation for hospitals in the network. In the first phase of the Clinical Information Network, we collected data on over 65 000 admission episodes. Despite clinicians{\textquoteright} initial unfamiliarity with routine performance reporting, we found that, as an initial focus, both engaging with each hospital and providing them information helped improve the quality of data and therefore reports. The process has involved mutual learning and building of trust in the data and should provide the basis for collaborative efforts to improve care, to understand patient outcome, and to evaluate interventions through shared learning. We have found that hospitals are willing to support the development of a clinically focused but geographically dispersed Clinical Information Network in a low-income setting. Such networks show considerable promise as platforms for collaborative efforts to improve care, to provide better information for decision making, and to enable locally relevant research.

}, issn = {2059-7908}, doi = {10.1136/bmjgh-2016-000028}, author = {Tuti, Timothy and Bitok, Michael and Malla, Lucas and Paton, Chris and Muinga, Naomi and Gathara, David and Gachau, Susan and Mbevi, George and Nyachiro, Wycliffe and Ogero, Morris and Julius, Thomas and Irimu, Grace and English, Mike} } @article {1131, title = {Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience.}, journal = {Med Image Anal}, year = {2016}, month = {2016 Jul 7}, abstract = {

The National Alliance for Medical Image Computing (NA-MIC) was launched in 2004 with the goal of investigating and developing an open source software infrastructure for the extraction of information and knowledge from medical images using computational methods. Several leading research and engineering groups participated in this effort that was funded by the US National Institutes of Health through a variety of infrastructure grants. This effort transformed 3D Slicer from an internal, Boston-based, academic research software application into a professionally maintained, robust, open source platform with an international leadership and developer and user communities. Critical improvements to the widely used underlying open source libraries and tools-VTK, ITK, CMake, CDash, DCMTK-were an additional consequence of this effort. This project has contributed to close to a thousand peer-reviewed publications and a growing portfolio of US and international funded efforts expanding the use of these tools in new medical computing applications every year. In this editorial, we discuss what we believe are gaps in the way medical image computing is pursued today; how a well-executed research platform can enable discovery, innovation and reproducible science ("Open Science"); and how our quest to build such a software platform has evolved into a productive and rewarding social engineering exercise in building an open-access community with a shared vision.

}, issn = {1361-8423}, doi = {10.1016/j.media.2016.06.035}, author = {Kapur, Tina and Pieper, Steve and Fedorov, Andriy and Fillion-Robin, J-C and Halle, Michael and O{\textquoteright}Donnell, Lauren and Lasso, Andras and Ungi, Tamas and Pinter, Csaba and Finet, Julien and Pujol, Sonia and Jagadeesan, Jayender and Tokuda, Junichi and Norton, Isaiah and Estepar, Raul San Jose and Gering, David and Aerts, Hugo J W L and Jakab, Marianna and Hata, Nobuhiko and Ibanez, Luiz and Blezek, Daniel and Miller, Jim and Aylward, Stephen and Grimson, W Eric L and Fichtinger, Gabor and Wells, William M and Lorensen, William E and Schroeder, Will and Kikinis, Ron} } @article {1121, title = {Open Source Drug Discovery with the Malaria Box Compound Collection for Neglected Diseases and Beyond.}, journal = {PLoS Pathog}, volume = {12}, year = {2016}, month = {2016 Jul}, pages = {e1005763}, abstract = {

A major cause of the paucity of new starting points for drug discovery is the lack of interaction between academia and industry. Much of the global resource in biology is present in universities, whereas the focus of medicinal chemistry is still largely within industry. Open source drug discovery, with sharing of information, is clearly a first step towards overcoming this gap. But the interface could especially be bridged through a scale-up of open sharing of physical compounds, which would accelerate the finding of new starting points for drug discovery. The Medicines for Malaria Venture Malaria Box is a collection of over 400 compounds representing families of structures identified in phenotypic screens of pharmaceutical and academic libraries against the Plasmodium falciparum malaria parasite. The set has now been distributed to almost 200 research groups globally in the last two years, with the only stipulation that information from the screens is deposited in the public domain. This paper reports for the first time on 236 screens that have been carried out against the Malaria Box and compares these results with 55 assays that were previously published, in a format that allows a meta-analysis of the combined dataset. The combined biochemical and cellular assays presented here suggest mechanisms of action for 135 (34\%) of the compounds active in killing multiple life-cycle stages of the malaria parasite, including asexual blood, liver, gametocyte, gametes and insect ookinete stages. In addition, many compounds demonstrated activity against other pathogens, showing hits in assays with 16 protozoa, 7 helminths, 9 bacterial and mycobacterial species, the dengue fever mosquito vector, and the NCI60 human cancer cell line panel of 60 human tumor cell lines. Toxicological, pharmacokinetic and metabolic properties were collected on all the compounds, assisting in the selection of the most promising candidates for murine proof-of-concept experiments and medicinal chemistry programs. The data for all of these assays are presented and analyzed to show how outstanding leads for many indications can be selected. These results reveal the immense potential for translating the dispersed expertise in biological assays involving human pathogens into drug discovery starting points, by providing open access to new families of molecules, and emphasize how a small additional investment made to help acquire and distribute compounds, and sharing the data, can catalyze drug discovery for dozens of different indications. Another lesson is that when multiple screens from different groups are run on the same library, results can be integrated quickly to select the most valuable starting points for subsequent medicinal chemistry efforts.

}, issn = {1553-7374}, doi = {10.1371/journal.ppat.1005763}, author = {Van Voorhis, Wesley C and Adams, John H and Adelfio, Roberto and Ahyong, Vida and Akabas, Myles H and Alano, Pietro and Alday, Aintzane and Alem{\'a}n Resto, Yesmalie and Alsibaee, Aishah and Alzualde, Ainhoa and Andrews, Katherine T and Avery, Simon V and Avery, Vicky M and Ayong, Lawrence and Baker, Mark and Baker, Stephen and Ben Mamoun, Choukri and Bhatia, Sangeeta and Bickle, Quentin and Bounaadja, Lotfi and Bowling, Tana and Bosch, J{\"u}rgen and Boucher, Lauren E and Boyom, Fabrice F and Brea, Jose and Brennan, Marian and Burton, Audrey and Caffrey, Conor R and Camarda, Grazia and Carrasquilla, Manuela and Carter, Dee and Belen Cassera, Maria and Chih-Chien Cheng, Ken and Chindaudomsate, Worathad and Chubb, Anthony and Colon, Beatrice L and Col{\'o}n-L{\'o}pez, Daisy D and Corbett, Yolanda and Crowther, Gregory J and Cowan, Noemi and D{\textquoteright}Alessandro, Sarah and Le Dang, Na and Delves, Michael and DeRisi, Joseph L and Du, Alan Y and Duffy, Sandra and Abd El-Salam El-Sayed, Shimaa and Ferdig, Michael T and Fern{\'a}ndez Robledo, Jos{\'e} A and Fidock, David A and Florent, Isabelle and Fokou, Patrick V T and Galstian, Ani and Gamo, Francisco Javier and Gokool, Suzanne and Gold, Ben and Golub, Todd and Goldgof, Gregory M and Guha, Rajarshi and Guiguemde, W Armand and Gural, Nil and Guy, R Kiplin and Hansen, Michael A E and Hanson, Kirsten K and Hemphill, Andrew and Hooft van Huijsduijnen, Rob and Horii, Takaaki and Horrocks, Paul and Hughes, Tyler B and Huston, Christopher and Igarashi, Ikuo and Ingram-Sieber, Katrin and Itoe, Maurice A and Jadhav, Ajit and Naranuntarat Jensen, Amornrat and Jensen, Laran T and Jiang, Rays H Y and Kaiser, Annette and Keiser, Jennifer and Ketas, Thomas and Kicka, Sebastien and Kim, Sunyoung and Kirk, Kiaran and Kumar, Vidya P and Kyle, Dennis E and Lafuente, Maria Jose and Landfear, Scott and Lee, Nathan and Lee, Sukjun and Lehane, Adele M and Li, Fengwu and Little, David and Liu, Liqiong and Llin{\'a}s, Manuel and Loza, Maria I and Lubar, Aristea and Lucantoni, Leonardo and Lucet, Isabelle and Maes, Louis and Mancama, Dalu and Mansour, Nuha R and March, Sandra and McGowan, Sheena and Medina Vera, Iset and Meister, Stephan and Mercer, Luke and Mestres, Jordi and Mfopa, Alvine N and Misra, Raj N and Moon, Seunghyun and Moore, John P and Morais Rodrigues da Costa, Francielly and M{\"u}ller, Joachim and Muriana, Arantza and Nakazawa Hewitt, Stephen and Nare, Bakela and Nathan, Carl and Narraidoo, Nathalie and Nawaratna, Sujeevi and Ojo, Kayode K and Ortiz, Diana and Panic, Gordana and Papadatos, George and Parapini, Silvia and Patra, Kailash and Pham, Ngoc and Prats, Sarah and Plouffe, David M and Poulsen, Sally-Ann and Pradhan, Anupam and Quevedo, Celia and Quinn, Ronald J and Rice, Christopher A and Abdo Rizk, Mohamed and Ruecker, Andrea and St Onge, Robert and Salgado Ferreira, Rafaela and Samra, Jasmeet and Robinett, Natalie G and Schlecht, Ulrich and Schmitt, Marjorie and Silva Villela, Filipe and Silvestrini, Francesco and Sinden, Robert and Smith, Dennis A and Soldati, Thierry and Spitzm{\"u}ller, Andreas and Stamm, Serge Maximilian and Sullivan, David J and Sullivan, William and Suresh, Sundari and Suzuki, Brian M and Suzuki, Yo and Swamidass, S Joshua and Taramelli, Donatella and Tchokouaha, Lauve R Y and Theron, Anjo and Thomas, David and Tonissen, Kathryn F and Townson, Simon and Tripathi, Abhai K and Trofimov, Valentin and Udenze, Kenneth O and Ullah, Imran and Vallieres, Cindy and Vigil, Edgar and Vinetz, Joseph M and Voong Vinh, Phat and Vu, Hoan and Watanabe, Nao-Aki and Weatherby, Kate and White, Pamela M and Wilks, Andrew F and Winzeler, Elizabeth A and Wojcik, Edward and Wree, Melanie and Wu, Wesley and Yokoyama, Naoaki and Zollo, Paul H A and Abla, Nada and Blasco, Benjamin and Burrows, Jeremy and Laleu, Beno{\^\i}t and Leroy, Didier and Spangenberg, Thomas and Wells, Timothy and Willis, Paul A} } @article {1163, title = {{RABIX}: {AN} {OPEN}-{SOURCE} {WORKFLOW} {EXECUTOR} {SUPPORTING} {RECOMPUTABILITY} {AND} {INTEROPERABILITY} {OF} {WORKFLOW} {DESCRIPTIONS}}, journal = {Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing}, volume = {22}, year = {2016}, pages = {154{\textendash}165}, abstract = {As biomedical data has become increasingly easy to generate in large quantities, the methods used to analyze it have proliferated rapidly. Reproducible and reusable methods are required to learn from large volumes of data reliably. To address this issue, numerous groups have developed workflow specifications or execution engines, which provide a framework with which to perform a sequence of analyses. One such specification is the Common Workflow Language, an emerging standard which provides a robust and flexible framework for describing data analysis tools and workflows. In addition, reproducibility can be furthered by executors or workflow engines which interpret the specification and enable additional features, such as error logging, file organization, optim1izations to computation and job scheduling, and allow for easy computing on large volumes of data. To this end, we have developed the Rabix Executor, an open-source workflow engine for the purposes of improving reproducibility through reusability and interoperability of workflow descriptions.}, issn = {2335-6936}, author = {Kaushik, Gaurav and Ivkovic, Sinisa and Simonovic, Janko and Tijanic, Nebojsa and Davis-Dusenbery, Brandi and Kural, Deniz} } @article {999, title = {Role of OpenEHR as an open source solution for the regional modelling of patient data in obstetrics.}, journal = {J Biomed Inform}, volume = {55}, year = {2015}, month = {2015 Jun}, pages = {174-87}, abstract = {

This work investigates, whether openEHR with its reference model, archetypes and templates is suitable for the digital representation of demographic as well as clinical data. Moreover, it elaborates openEHR as a tool for modelling Hospital Information Systems on a regional level based on a national logical infrastructure. OpenEHR is a dual model approach developed for the modelling of Hospital Information Systems enabling semantic interoperability. A holistic solution to this represents the use of dual model based Electronic Healthcare Record systems. Modelling data in the field of obstetrics is a challenge, since different regions demand locally specific information for the process of treatment. Smaller health units in developing countries like Brazil or Malaysia, which until recently handled automatable processes like the storage of sensitive patient data in paper form, start organizational reconstruction processes. This archetype proof-of-concept investigation has tried out some elements of the openEHR methodology in cooperation with a health unit in Colombo, Brazil. Two legal forms provided by the Brazilian Ministry of Health have been analyzed and classified into demographic and clinical data. LinkEHR-Ed editor was used to read, edit and create archetypes. Results show that 33 clinical and demographic concepts, which are necessary to cover data demanded by the Unified National Health System, were identified. Out of the concepts 61\% were reused and 39\% modified to cover domain requirements. The detailed process of reuse, modification and creation of archetypes is shown. We conclude that, although a major part of demographic and clinical patient data were already represented by existing archetypes, a significant part required major modifications. In this study openEHR proved to be a highly suitable tool in the modelling of complex health data. In combination with LinkEHR-Ed software it offers user-friendly and highly applicable tools, although the complexity built by the vast specifications requires expert networks to define generally excepted clinical models. Finally, this project has pointed out main benefits enclosing high coverage of obstetrics data on the Clinical Knowledge Manager, simple modelling, and wide network and support using openEHR. Moreover, barriers described are enclosing the allocation of clinical content to respective archetypes, as well as stagnant adaption of changes on the Clinical Knowledge Manager leading to redundant efforts in data contribution that need to be addressed in future works.

}, issn = {1532-0480}, doi = {10.1016/j.jbi.2015.04.004}, author = {Pahl, Christina and Zare, Mojtaba and Nilashi, Mehrbakhsh and de Faria Borges, Marco Aur{\'e}lio and Weingaertner, Daniel and Detschew, Vesselin and Supriyanto, Eko and Ibrahim, Othman} } @article {1009, title = {AccessMRS: integrating OpenMRS with smart forms on Android.}, journal = {Stud Health Technol Inform}, volume = {192}, year = {2013}, month = {2013}, pages = {866-70}, abstract = {

We present a new open-source Android application, AccessMRS, for interfacing with an electronic medical record system (OpenMRS) and loading {\textquoteright}Smart Forms{\textquoteright} on a mobile device. AccessMRS functions as a patient-centered interface for viewing OpenMRS data; managing patient information in reminders, task lists, and previous encounters; and launching patient-specific {\textquoteright}Smart Forms{\textquoteright} for electronic data collection and dissemination of health information. We present AccessMRS in the context of related software applications we developed to serve Community Health Workers, including AccessInfo, AccessAdmin, AccessMaps, and AccessForms. The specific features and design of AccessMRS are detailed in relationship to the requirements that drove development: the workflows of the Kenyan Ministry of Health Community Health Volunteers (CHVs) supported by the AMPATH Primary Health Care Program. Specifically, AccessMRS was designed to improve the quality of community-based Maternal and Child Health services delivered by CHVs in Kosirai Division. AccessMRS is currently in use by more than 80 CHVs in Kenya and undergoing formal assessment of acceptability, effectiveness, and cost.

}, keywords = {electronic health records, Forms and Records Control, Information Storage and Retrieval, Medical Record Linkage, Mobile Applications, Programming Languages, Software Design, Systems Integration, User-Computer Interface}, issn = {0926-9630}, author = {Fazen, Louis E and Chemwolo, Benjamin T and Songok, Julia J and Ruhl, Laura J and Kipkoech, Carolyne and Green, James M and Ikemeri, Justus E and Christoffersen-Deb, Astrid} } @article {840, title = {The Evolving Role of Open Source Software in Medicine and Health Services}, journal = {Technology Innovation Management Review}, year = {2013}, month = {01/2013}, pages = {32-39}, abstract = {The past five decades have witnessed immense coevolution of methods and tools of information technology, and their practical and experimental application within the medical and healthcare domain. Healthcare itself continues to evolve in response to change in healthcare needs, progress in the scientific foundations of treatments, and in professional and managerial organization of affordable and effective services, in which patients and their families and carers increasingly participate. Taken together, these trends impose highly complex underlying challenges for the design, development, and sustainability of the quality of supporting information services and software infrastructure that are needed. The challenges are multidisciplinary and multiprofessional in scope, and they require deeper study and learning to inform policy and promote public awareness of the problems health services have faced in this area for many years. The repeating pattern of failure to live up to expectations of policy-driven national health IT initiatives has proved very costly and remains frustrating and unproductive for all involved. In this article, we highlight the barriers to progress and discuss the dangers of pursuing a standardization framework devoid of empirical testing and iterative development. We give the example of the openEHR Foundation, which was established at University College London (UCL) in London, England, with members in 80 countries. The Foundation is a not-for-profit company providing open specifications and working for generic standards for electronic records, informed directly by a wide range of implementation experience. We also introduce the Opereffa open source framework, which was developed at UCL based on these specifications and which has been downloaded in some 70 countries. We argue that such an approach is now essential to support good discipline, innovation, and governance at the heart of medicine and health services, in line with the new mandate for health commissioning in the United Kingdom{\textquoteright}s National Health Service (NHS), which emphasizes patient participation, innovation, transparency, and accountability.}, keywords = {electronic health care record, information retrieval, open source framework, openEHR Foundation, persistence, standards based}, issn = {1927-0321}, author = {David Ingram and Sevket Seref Arikan} } @article {1055, title = {The NIH National Center for Integrative Biomedical Informatics (NCIBI).}, journal = {J Am Med Inform Assoc}, volume = {19}, year = {2012}, month = {2012 Mar-Apr}, pages = {166-70}, abstract = {

The National Center for Integrative and Biomedical Informatics (NCIBI) is one of the eight NCBCs. NCIBI supports information access and data analysis for biomedical researchers, enabling them to build computational and knowledge models of biological systems to address the Driving Biological Problems (DBPs). The NCIBI DBPs have included prostate cancer progression, organ-specific complications of type 1 and 2 diabetes, bipolar disorder, and metabolic analysis of obesity syndrome. Collaborating with these and other partners, NCIBI has developed a series of software tools for exploratory analysis, concept visualization, and literature searches, as well as core database and web services resources. Many of our training and outreach initiatives have been in collaboration with the Research Centers at Minority Institutions (RCMI), integrating NCIBI and RCMI faculty and students, culminating each year in an annual workshop. Our future directions include focusing on the TranSMART data sharing and analysis initiative.

}, keywords = {Biomedical Research, Databases as Topic, Forecasting, Goals, Information Dissemination, Integrative Medicine, Medical Informatics, National Institutes of Health (U.S.), United States}, issn = {1527-974X}, doi = {10.1136/amiajnl-2011-000552}, author = {Athey, Brian D and Cavalcoli, James D and Jagadish, H V and Omenn, Gilbert S and Mirel, Barbara and Kretzler, Matthias and Burant, Charles and Isokpehi, Raphael D and DeLisi, Charles} } @article {1038, title = {An online method for diagnosis of difficult TB cases for developing countries.}, journal = {Stud Health Technol Inform}, volume = {164}, year = {2011}, month = {2011}, pages = {168-73}, abstract = {

Optimal use of limited human, technical and financial resources is a major concern for tuberculosis (TB) control in developing nations. Further impediments include a lack of trained physicians, and logistical difficulties in arranging face-to-face (f-2-f) TB Diagnostic Committee (TBDC) consultations. Use of e-Health for virtual TBDCs (Internet and "iPath"), to address such issues is being studied in the Philippines and Pakistan. In Pakistan, radiological diagnosis of 88 sputum smear negative but suspected TB patients has been compared with the {\textquoteright}gold standards{\textquoteright} (TB culture, and 2-month clinical follow up). Of 88 diagnostic decisions made by primary physicians at the spoke site and electronic TBDC (e-TBDC) at hub site, there was agreement in 71 cases and disagreement on 17 cases. The turn-around time (TAT; patient registration at spoke site for f-2-f diagnosis to receiving the electronic diagnosis), averaged 34.6 hours; ranging 9 minutes to 289.2 hours. Average TAT at the rural site (59.15 hours) was more than the urban site (15.9 hours). Comparison of e-TBDC and f-2-f diagnosis with the gold standards showed only slight differences. Using culture as the gold standard, e-TBDC decisions showed greater accuracy (sensitivity - 32.4\%) as compared to f-2-f (27.6\%); using 2-month clinical follow-up as the gold standard, f-2-f diagnosis showed slightly better improvement in patient symptoms and weight as compared to e-TBDC. In Philippines "iPath" was trialed and demonstrated that e-TBDCs have potential. Such groups could review cases, diagnose, and write comments remotely, reducing the diagnosis and treatment delay compared to usual care.

}, keywords = {Adult, Developing Countries, Diagnostic Techniques and Procedures, Female, Humans, Internet, Male, Middle Aged, Mycobacterium Infections, Nontuberculous, Pakistan, Philippines, Telemedicine, Tuberculosis, Pulmonary}, issn = {0926-9630}, author = {Marcelo, Alvin and Fatmi, Zafar and Firaza, Paul Nimrod and Shaikh, Shiraz and Dandan, Alvin Joseph and Irfan, Muhammad and Bari, Vaqar and Scott, Richard E} } @article {599, title = {Wikipedia: a key tool for global public health promotion.}, journal = {Journal of medical Internet research}, volume = {13}, year = {2011}, month = {2011}, pages = {e14}, abstract = {The Internet has become an important health information resource for patients and the general public. Wikipedia, a collaboratively written Web-based encyclopedia, has become the dominant online reference work. It is usually among the top results of search engine queries, including when medical information is sought. Since April 2004, editors have formed a group called WikiProject Medicine to coordinate and discuss the English-language Wikipedia{\textquoteright}s medical content. This paper, written by members of the WikiProject Medicine, discusses the intricacies, strengths, and weaknesses of Wikipedia as a source of health information and compares it with other medical wikis. Medical professionals, their societies, patient groups, and institutions can help improve Wikipedia{\textquoteright}s health-related entries. Several examples of partnerships already show that there is enthusiasm to strengthen Wikipedia{\textquoteright}s biomedical content. Given its unique global reach, we believe its possibilities for use as a tool for worldwide health promotion are underestimated. We invite the medical community to join in editing Wikipedia, with the goal of providing people with free access to reliable, understandable, and up-to-date health information.}, keywords = {Consumer Health Information, Encyclopedias as Topic, Health Promotion, Humans, Information Dissemination, Information Services, Internet, Patient Education as Topic, Public Health, World Health}, issn = {1438-8871}, author = {Heilman, James M and Kemmann, Eckhard and Bonert, Michael and Chatterjee, Anwesh and Ragar, Brent and Beards, Graham M and Iberri, David J and Harvey, Matthew and Thomas, Brendan and Stomp, Wouter and Martone, Michael F and Lodge, Daniel J and Vondracek, Andrea and de Wolff, Jacob F and Liber, Casimir and Grover, Samir C and Vickers, Tim J and Mesk{\'o}, Bertalan and Laurent, Micha{\"e}l R} } @article {20663194, title = {ImmunoRatio: a publicly available web application for quantitative image analysis of estrogen receptor (ER), progesterone receptor (PR), and Ki-67.}, journal = {Breast cancer research : BCR}, volume = {12}, year = {2010}, month = {2010 Jul 27}, pages = {R56}, abstract = {ABSTRACT: INTRODUCTION: Accurate assessment of estrogen receptor (ER), progesterone receptor (PR), and Ki-67 is essential in the histopathologic diagnostics of breast cancer. Commercially available image analysis systems are usually bundled with dedicated analysis hardware and, to our knowledge, no easily installable, free software for immunostained slide scoring has been described. In this study, we describe a free, Internet-based web application for quantitative image analysis of ER, PR, and Ki-67 immunohistochemistry in breast cancer tissue sections. METHODS: The application, named ImmunoRatio, calculates the percentage of positively stained nuclear area (labeling index) by using a color deconvolution algorithm for separating the staining components (diaminobenzidine and hematoxylin) and adaptive thresholding for nuclear area segmentation. ImmunoRatio was calibrated using cell counts defined visually as the gold standard (training set, n=50). Validation was done using a separate set of 50 ER, PR, and Ki-67 stained slides (test set, n=50). In addition, Ki-67 labeling indexes determined by ImmunoRatio were studied for their prognostic value in a retrospective cohort of 123 breast cancer patients. RESULTS: The labeling indexes by calibrated ImmunoRatio analyses correlated well with those defined visually in the test set (correlation coefficient r=0.98). Using the median Ki-67 labeling index (20\%) as a cutoff, a hazard ratio of 2.2 was obtained in the survival analysis (n=123, P=0.01). ImmunoRatio was shown to adapt to various staining protocols, microscope setups, digital camera models, and image acquisition settings. The application can be used directly with web browsers running on modern operating systems (e.g., Microsoft Windows, Linux distributions, and Mac OS). No software downloads or installations are required. ImmunoRatio is open source software, and the web application is publicly accessible on our website. CONCLUSIONS: We anticipate that free web applications, such as ImmunoRatio, will make the quantitative image analysis of ER, PR, and Ki-67 easy and straightforward in the diagnostic assessment of breast cancer specimens.}, author = {Tuominen, Vilppu J and Ruotoistenmaki, Sanna and Viitanen, Arttu and Jumppanen, Mervi and Isola, Jorma} } @article {487, title = {An open source software project for obstetrical procedure scheduling and occupancy analysis.}, journal = {Health care management science}, year = {2010}, month = {2010 Oct 27}, abstract = {Increases in the rate of births via cesarean section and induced labor have led to challenging scheduling and capacity planning problems for hospital inpatient obstetrical units. We present occupancy and patient scheduling models to help address these challenges. These patient flow models can be used to explore the relationship between procedure scheduling practices and the resulting occupancy on inpatient obstetrical units such as labor and delivery and postpartum. The models capture numerous important characteristics of inpatient obstetrical patient flow such as time of day and day of week dependent arrivals and length of stay, multiple patient types and clinical interventions, and multiple patient care units with inter-unit patient transfers. We have used these models in several projects at different hospitals involving design of procedure scheduling templates and analysis of inpatient obstetrical capacity. In the development of these models, we made heavy use of open source software tools and have released the entire project as a free and open source model and software toolkit.}, issn = {1386-9620}, author = {Isken, Mark W and Ward, Timothy J and Littig, Steven J} } @booklet {UCAM-CL-TR-768, title = {Report on existing open-source electronic medical records}, number = {UCAM-CL-TR-768}, year = {2010}, publisher = {University of Cambridge, Computer Laboratory}, abstract = {In this report we provide an overview of existing open-source electronic medical records and assess them against the criteria established by the EViDence group.}, issn = {1476-2986}, url = {http://www.cl.cam.ac.uk/techreports/UCAM-CL-TR-768.pdf}, author = {Morrison, Cecily and Iosif, Adona and Danka, Miklos} } @article {19056288, title = {Dimensional error of selective laser sintering, three-dimensional printing and PolyJet models in the reproduction of mandibular anatomy.}, journal = {Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery}, volume = {37}, year = {2009}, month = {2009 Apr}, pages = {167-73}, abstract = {BACKGROUND: Selective laser sintering (SLS), three-dimensional printing (3DP) and PolyJet are rapid prototyping (RP) techniques to fabricate prototypes from virtual biomedical images. To be used in maxillofacial surgery, these models must accurately reproduce the craniofacial skeleton. PURPOSE: To analyze the capacity of SLS, 3DP and PolyJet models to reproduce mandibular anatomy and their dimensional error. MATERIAL: Dry mandible, helical CT images, SLS, 3DP and PolyJet prototypes, and digital electronic caliper. METHODS: Helical CT images were acquired from a dry mandible (criterion standard) and manipulated with the InVesalius software. Prototypes were produced using SLS, 3DP and PolyJet techniques. Thirteen linear measurements of each prototype were made and compared with the dry mandible measurements. RESULTS: The results showed a dimensional error of 1.79\%, 3.14\% and 2.14\% for SLS, 3DP and PolyJet models, respectively. The models satisfactorily reproduced anatomic details and the SLS and PolyJet prototypes showed greater dimensional precision and reproduced mandibular anatomy more accurately than the 3DP model. CONCLUSIONS: The SLS prototype had a greater dimensional accuracy than the PolyJet and 3DP models. The PolyJet technique reproduced anatomic details of the mandible more accurately.}, author = {Ibrahim, Danilo and Broilo, Tiago Leonardo and Heitz, Claiton and Gerhardt de Oliveira, Mar{\'\i}lia and de Oliveira, Helena Willhelm and Nobre, Stella Maris Wanderlei and Dos Santos Filho, Jos{\'e} Henrique Gomes and Silva, Daniela Nascimento} } @article {17356215, title = {Comparison of four freely available frameworks for image processing and visualization that use ITK.}, journal = {IEEE transactions on visualization and computer graphics}, volume = {13}, year = {2007}, month = {2007 May-Jun}, pages = {483-93}, abstract = {Most image processing and visualization applications allow users to configure computation parameters and manipulate the resulting visualizations. SCIRun, VolView, MeVisLab, and the Medical Interaction Toolkit (MITK) are four image processing and visualization frameworks that were built for these purposes. All frameworks are freely available and all allow the use of the ITK C++ library. In this paper, the benefits and limitations of each visualization framework are presented to aid both application developers and users in the decision of which framework may be best to use for their application. The analysis is based on more than 50 evaluation criteria, functionalities, and example applications. We report implementation times for various steps in the creation of a reference application in each of the compared frameworks. The data-flow programming frameworks, SCIRun and MeVisLab, were determined to be best for developing application prototypes, while VolView was advantageous for nonautomatic end-user applications based on existing ITK functionalities, and MITK was preferable for automated end-user applications that might include new ITK classes specifically designed for the application.}, author = {Bitter, Ingmar and Van Uitert, Robert and Wolf, Ivo and Ib{\'a}{\~n}ez, Luis and Kuhnigk, Jan-Martin} } @article {802, title = {The image-guided surgery toolkit IGSTK: an open source C++ software toolkit.}, journal = {J Digit Imaging}, volume = {20 Suppl 1}, year = {2007}, month = {2007 Nov}, pages = {21-33}, abstract = {This paper presents an overview of the image-guided surgery toolkit (IGSTK). IGSTK is an open source C++ software library that provides the basic components needed to develop image-guided surgery applications. It is intended for fast prototyping and development of image-guided surgery applications. The toolkit was developed through a collaboration between academic and industry partners. Because IGSTK was designed for safety-critical applications, the development team has adopted lightweight software processes that emphasizes safety and robustness while, at the same time, supporting geographically separated developers. A software process that is philosophically similar to agile software methods was adopted emphasizing iterative, incremental, and test-driven development principles. The guiding principle in the architecture design of IGSTK is patient safety. The IGSTK team implemented a component-based architecture and used state machine software design methodologies to improve the reliability and safety of the components. Every IGSTK component has a well-defined set of features that are governed by state machines. The state machine ensures that the component is always in a valid state and that all state transitions are valid and meaningful. Realizing that the continued success and viability of an open source toolkit depends on a strong user community, the IGSTK team is following several key strategies to build an active user community. These include maintaining a users and developers{\textquoteright} mailing list, providing documentation (application programming interface reference document and book), presenting demonstration applications, and delivering tutorial sessions at relevant scientific conferences.}, keywords = {Computer Systems, Data Display, Database Management Systems, Humans, Information Dissemination, Information Storage and Retrieval, Safety, Software, Software Design, Software Validation, Surgery, Computer-Assisted, Systems Integration, User-Computer Interface}, issn = {0897-1889}, doi = {10.1007/s10278-007-9054-3}, author = {Enquobahrie, Andinet and Cheng, Patrick and Gary, Kevin and Ibanez, Luis and Gobbi, David and Lindseth, Frank and Yaniv, Ziv and Aylward, Stephen and Jomier, Julien and Cleary, Kevin} } @inbook {springerlink:10.1007/978-3-540-73044-6_189, title = {O3-RWS: a Java-based, IHE-compliant open-source radiology workstation}, booktitle = {11th Mediterranean Conference on Medical and Biomedical Engineering and Computing 2007}, series = {IFMBE Proceedings}, volume = {16}, year = {2007}, note = {10.1007/978-3-540-73044-6_189}, pages = {727-731}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, abstract = {Within the Open Three Consortium (O3) an open source radiological reporting workstation, called O3- RWS, has been studied, developed and experimented in the routine of European and US hospitals. The O3 Consortium is an international open-source project constituted in 2005 by Higher Education in Clinical Engineering (HECE) of the University of Trieste; it deals with the multi-centric integration of hospitals, RHIOs and citizen (care at home and on the move, and ambient assisted living). O3-RWS has been studied and developed with the goal to give a solution for the needs of the physician, who wants to have an easy-to-use, light and complete solution for the radiology reporting and report creation. O3-RWS, a very versatile platform-independent radiology workstation, providing user authentication and being easy to use also for private users, is able to retrieve, visualize and manage medical images; in an universal version, it is going to be able to deal with vital signs like ECG, hemodynamical and pneumological data.}, isbn = {978-3-540-73044-6}, url = {http://dx.doi.org/10.1007/978-3-540-73044-6_189}, author = {Faustini, Giorgio and Inchingolo, P.}, editor = {Magjarevic, Ratko and Jarm, Tomaz and Kramar, Peter and Zupanic, Anze} } @article {566, title = {O3-DPACS Open-Source Image-Data Manager/Archiver and HDW2 Image-Data Display: an IHE-compliant project pushing the e-health integration in the world.}, journal = {Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society}, volume = {30}, year = {2006}, month = {2006 Sep-Oct}, pages = {391-406}, abstract = {After many years of study, development and experimentation of open PACS and Image workstation solutions including management of medical data and signals (DPACS project), the research and development at the University of Trieste have recently been directed towards Java-based, IHE compliant and multi-purpose servers and clients. In this paper an original Image-Data Manager/Archiver (O3-DPACS) and a universal Image-Data Display (HDW2) are described. O3-DPACS is also part of a new project called Open Three (O3) Consortium, promoting Open Source adoption in e-health at European and world-wide levels. This project aims to give a contribution to the development of e-health through the study of Healthcare Information Systems and the contemporary proposal of new concepts, designs and solutions for the management of health data in an integrated environment: hospitals, Regional Health Information Organizations and citizens (home-care, mobile-care and ambient assisted living).}, keywords = {Data Display, Database Management Systems, Diagnostic Imaging, Equipment Design, Equipment Failure Analysis, Guidelines as Topic, Information Storage and Retrieval, Internationality, Medical Records Systems, Computerized, Programming Languages, Radiology Information Systems, Systems Integration, User-Computer Interface}, issn = {0895-6111}, author = {Inchingolo, Paolo and Beltrame, Marco and Bosazzi, Pierpaolo and Cicuta, Davide and Faustini, Giorgio and Mininel, Stefano and Poli, Andrea and Vatta, Federica} }