Multi-criteria analysis for OS-EMR software selection problem: A comparative study

Various software packages offer a large number of customizable features to meet the specific needs of organizations. Improper selection of a software package may result in incorrect strategic decisions and subsequent economic loss of organizations. This paper presents a comparative study that aims to evaluate and select open-source electronic medical record (OS-EMR) software based on multiple-criteria decision-making (MCDM) techniques. A hands-on study is performed, and a set of OS-EMR software are implemented locally in separate virtual machines to closely examine the systems. Several measures as evaluation bases are specified, and systems are selected based on a set of metric outcomes by using AHP integrated with different MCDM techniques, namely, WPM, WSM, SAW, HAW, and TOPSIS. Paired sample t-test is then utilized to measure the correlations among different techniques on ranking scores and orders. Findings are as follows. (1) Significant differences exist among MCDM techniques on the basis of different integrations on ranking scores, whereas no significant differences exist among them when representing the ranking scores to the ranking orders in place of the technique scale. (2) The software GNUmed, OpenEMR, OpenMRS, and ZEPRS do not differ in ranking scores/orders of experiments for all MCDM techniques presented. On the contrary, discrepancies among the ranking scores/orders are more noticeable in other software. (3) GNUmed, OpenEMR, and OpenMRS software are the most promising candidates for providing a good basis on ranking scores/orders, whereas ZEPRS is not recommended because it records the worst ranking score/order in comparison with other OS-EMR software. Display Omitted Significant differences exist among MCDM techniques based on different integration's on ranking scores.There is no significant differences among MCDM techniques when the ranking scores are represented to the ranking orders. The software GNUmed, OpenEMR, OpenMRS, and ZEPRS do not differ in ranking scores/orders for all MCDM techniques presentedGNUmed, OpenEMR, and OpenMRS software are the most promising candidates for providing a good basis ranking scores/orders. ZEPRS is not recommended because it records the worst ranking score/order in comparison with other OS-EMR software.

[1]  Ching-Lai Hwang,et al.  Multiple attribute decision making : an introduction , 1995 .

[2]  Shinji Kobayashi,et al.  Open Source Software Development on Medical Domain , 2012 .

[3]  J. Webster,et al.  Electronic medical record systems for developing countries: Review , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[4]  Ilias Maglogiannis,et al.  Towards the Adoption of Open Source and Open Access Electronic Health Record Systems , 2012 .

[5]  Michael J Doyle.  Open source will help drive EHR costs down. The use of open source in healthcare will break down many barriers, from high cost and lack of interoperability, to inaccessibility and complexity. , 2009, Health management technology.

[6]  Neil A. Ernst,et al.  Open Source, Open Standards, and Health Care Information Systems , 2011, Journal of medical Internet research.

[7]  Rajendra M. Sonar,et al.  Evaluating and selecting software packages: A review , 2009, Inf. Softw. Technol..

[8]  B. B. Zaidan,et al.  Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS , 2015, J. Biomed. Informatics.

[9]  Larry L. Constantine,et al.  Software for Use - A Practical Guide to the Models and Methods of Usage-Centered Design , 1999 .

[10]  Paul G. Biondich,et al.  The OpenMRS Implementers Network , 2009, Int. J. Medical Informatics.

[11]  Norliza Katuk,et al.  A Multiple Attribute Decision Making for Improving Information Security Control Assessment , 2014 .

[12]  Sebastian Spaeth,et al.  The open source software phenomenon: Characteristics that promote research , 2007, J. Strateg. Inf. Syst..

[13]  Jian-Qiang Wang,et al.  A Method to Dynamic Stochastic Multicriteria Decision Making with Log-Normally Distributed Random Variables , 2013, TheScientificWorldJournal.

[14]  T. Miranda Lakshmi,et al.  A Survey on Multi Criteria Decision Making Methods and Its Applications , 2013 .

[15]  Wei Gao,et al.  The State and Profile of Open Source Software Projects in health and medical informatics , 2009, Int. J. Medical Informatics.

[16]  Jacques Verville,et al.  An investigation of the decision process for selecting an ERP software: the case of ESC , 2002 .

[17]  Paul Biondich,et al.  OpenMRS, a global medical records system collaborative: factors influencing successful implementation. , 2011, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[18]  Brian Shackel,et al.  Usability - Context, framework, definition, design and evaluation , 1991, Interact. Comput..

[19]  Elaine Toms,et al.  User strategies for handling information tasks in webcasts , 2005, CHI EA '05.

[20]  Dirk Riehle,et al.  The comment density of open source software code , 2009, 2009 31st International Conference on Software Engineering - Companion Volume.

[21]  B. B. Zaidan,et al.  Secure Topology for Electronic Medical Record Transmissions , 2010 .

[22]  Jakob Nielsen,et al.  Usability engineering , 1997, The Computer Science and Engineering Handbook.

[23]  Eric Helms,et al.  Evaluating access control of open source electronic health record systems , 2011, SEHC '11.

[24]  Evangelos Triantaphyllou,et al.  Multi-criteria Decision Making Methods: A Comparative Study , 2000 .

[25]  Evangelos Triantaphyllou,et al.  Multi-Criteria Decision Making: An Operations Research Approach , 1998 .

[26]  B. B. Zaidan,et al.  An Enhanced Security Solution for Electronic Medical Records Based on AES Hybrid Technique with SOAP/XML and SHA-1 , 2013, Journal of Medical Systems.

[27]  Willy Susilo,et al.  Functionalities of free and open electronic health record systems. , 2010, International journal of technology assessment in health care.

[28]  B. B. Zaidan,et al.  Open source EMR software: Profiling, insights and hands-on analysis , 2014, Comput. Methods Programs Biomed..

[29]  Rajendra M. Sonar,et al.  Analytic Hierarchy Process (AHP), Weighted Scoring Method (WSM), and Hybrid Knowledge Based System (HKBS) for Software Selection: A Comparative Study , 2009, 2009 Second International Conference on Emerging Trends in Engineering & Technology.

[30]  Mansooreh Mollaghasemi,et al.  Technical Briefing: Making Multiple-Objective Decisions , 1996 .

[31]  Xavier Franch,et al.  Using Quality Models in Software Package Selection , 2003, IEEE Softw..

[32]  B. B. Zaidan,et al.  Meeting the Security Requirements of Electronic Medical Records in the ERA of High-Speed Computing , 2014, Journal of Medical Systems.

[33]  Thomas L. Saaty,et al.  DECISION MAKING WITH THE ANALYTIC HIERARCHY PROCESS , 2008 .

[34]  Miss Laiha Mat Kiah,et al.  Suitability of using SOAP protocol to secure electronic medical record databases transmission , 2010 .

[35]  Gareth S. Kantor,et al.  Letter to the Editor: Open-source Software and the Primary Care EMR , 2003, J. Am. Medical Informatics Assoc..

[36]  T. Saaty,et al.  Why the magic number seven plus or minus two , 2003 .

[37]  Rex B. Kline,et al.  Usability measurement and metrics: A consolidated model , 2006, Software Quality Journal.

[38]  Cornelius Ncube,et al.  The Limitations of Current Decision-Making Techniques in the Procurement of COTS Software Components , 2002, ICCBSS.

[39]  Rajendra M. Sonar,et al.  Framework for evaluation and selection of the software packages: A hybrid knowledge based system approach , 2011, J. Syst. Softw..

[40]  Matthias Ehrgott,et al.  Multiple criteria decision analysis: state of the art surveys , 2005 .

[41]  Julia Adler-Milstein,et al.  A survey analysis suggests that electronic health records will yield revenue gains for some practices and losses for many. , 2013, Health affairs.

[42]  P. Webster,et al.  The rise of open-source electronic health records , 2011, The Lancet.