{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T10:04:04Z","timestamp":1775469844401,"version":"3.50.1"},"reference-count":58,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,2,6]],"date-time":"2021-02-06T00:00:00Z","timestamp":1612569600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>Software developers and data scientists use and deal with big data to easily discover useful knowledge and find better solutions to improve healthcare services and patient safety. Big data analytics (BDA) is getting attention due to its role in decision-making across the healthcare field. Therefore, this article examines the adoption mechanism of big data analytics and management in healthcare organizations in Jordan. Additionally, it discusses health big data\u2019s characteristics and the challenges, and limitations for health big data analytics and management in Jordan. This article proposes a conceptual framework that allows utilizing health big data. The proposed conceptual framework suggests a way to merge the existing health information system with the National Health Information Exchange (HIE), which might play a role in extracting insights from our massive datasets, increases the data availability and reduces waste in resources. When applying the framework, the collected data are processed to develop knowledge and support decision-making, which helps improve the health care quality for both the community and individuals by improving diagnosis, treatment, and other services.<\/jats:p>","DOI":"10.3390\/data6020016","type":"journal-article","created":{"date-parts":[[2021,2,8]],"date-time":"2021-02-08T20:51:51Z","timestamp":1612817511000},"page":"16","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Investigating the Adoption of Big Data Management in Healthcare in Jordan"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2962-9449","authenticated-orcid":false,"given":"Hani","family":"Bani-Salameh","sequence":"first","affiliation":[{"name":"Department of Software Engineering, The Hashemite University, Zarqa 13133, Jordan"}]},{"given":"Mona","family":"Al-Qawaqneh","sequence":"additional","affiliation":[{"name":"Department of Software Engineering, The Hashemite University, Zarqa 13133, Jordan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2414-0193","authenticated-orcid":false,"given":"Salah","family":"Taamneh","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Applications, The Hashemite University, Zarqa 13133, Jordan"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ricciardi, C., Amboni, M., De Santis, C., Improta, G., Volpe, G., Iuppariello, L., Ricciardelli, G., D\u2019Addio, G., Vitale, C., and Barone, P. (2019). Using gait analysis\u2019 parameters to classify Parkinsonism: A data mining approach. Comput. Methods Programs Biomed., 180.","DOI":"10.1016\/j.cmpb.2019.105033"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Henriques, J., Neves, N., and de Carvalho, P. (2019, January 26\u201328). Is It Possible to Predict Cardiac Death?. Proceedings of the XV Mediterranean Conference on Medical and Biological Engineering and Computing\u2014MEDICON 2019, MEDICON 2019, IFMBE Proceedings, Coimbra, Portugal.","DOI":"10.1007\/978-3-030-31635-8"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"961","DOI":"10.1007\/s12553-020-00449-y","article-title":"Machine learning models for the prediction of acuity and variability of eye-positioning using features extracted from oculography","volume":"10","author":"Improta","year":"2020","journal-title":"Health Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"189","DOI":"10.25046\/aj020425","article-title":"Deepak and Udaya Kumar Ramanadham. Big Data Analytics for Healthcare Organization, BDA Process, Benefits and Challenges of BDA: A Review","volume":"2","author":"Reddy","year":"2017","journal-title":"Adv. Sci. Technol. Eng. Syst. J."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1145\/2094114.2094129","article-title":"The meaningful use of big data: Four perspectives\u2013four challenges","volume":"40","author":"Bizer","year":"2012","journal-title":"ACM Sigmod Rec."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1080\/07421222.2015.1138364","article-title":"How the use of big data analytics affects value creation in supply chain management","volume":"32","author":"Chen","year":"2015","journal-title":"J. Manag. Inf. Syst."},{"key":"ref_7","unstructured":"Bollier, D., and Firestone, C.M. (2010). The Promise Additionally, Peril of Big Data, Aspen Institute, Communications and Society Program."},{"key":"ref_8","unstructured":"Feldman, B., Martin, E.M., and Skotnes, T. (2012). Big Data in Healthcare Hype and Hope. Dr. Bonnie, 360, Available online: https:\/\/www.ghdonline.org\/uploads\/big-data-in-healthcare_B_Kaplan_2012.pdf."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"917","DOI":"10.1016\/j.ijinfomgt.2016.05.013","article-title":"Big data reduction framework for value creation in sustainable enterprises","volume":"36","author":"Chang","year":"2016","journal-title":"Int. J. Inf. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"95","DOI":"10.18865\/ed.27.2.95","article-title":"Big data science: Opportunities and challenges to address minority health and health disparities in the 21st Century","volume":"27","author":"Zhang","year":"2017","journal-title":"Ethn. Dis."},{"key":"ref_11","unstructured":"Hermon, R., and Williams, P.A. (2014, January 1\u20133). Big data in healthcare: What is it used for?. Proceedings of the 3rd Australian eHealth Informatics and Security Conference, Edith Cowan University, Joondalup Campus, Perth, WA, Australia."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1145\/2500873","article-title":"Big-data applications in the government sector","volume":"57","author":"Kim","year":"2014","journal-title":"Commun. ACM"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"BII-S31559","DOI":"10.4137\/BII.S31559","article-title":"Big data application in biomedical research and health care: A literature review","volume":"8","author":"Luo","year":"2016","journal-title":"Biomed. Inform. Insights"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Wong, H.T., Chiang, V.C.L., Choi, K.S., and Loke, A.Y. (2016). The need for a definition of Big Data for nursing science: A case study of disaster preparedness. Int. J. Environ. Res. Public Health, 13.","DOI":"10.3390\/ijerph13101015"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1089\/big.2014.0053","article-title":"Utilization and monetization of healthcare data in developing countries","volume":"3","author":"Bram","year":"2015","journal-title":"Big Data"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3","DOI":"10.23876\/j.krcp.2017.36.1.3","article-title":"Medical big data: Promise and challenges","volume":"36","author":"Lee","year":"2017","journal-title":"Kidney Res. Clin. Pract."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1130","DOI":"10.1513\/AnnalsATS.201405-185AS","article-title":"What\u2019s so different about big data? A primer for clinicians trained to think epidemiologically","volume":"11","author":"Iwashyna","year":"2014","journal-title":"Ann. Am. Thorac. Soc."},{"key":"ref_18","first-page":"15","article-title":"Healthcare data analysis using dynamic slot allocation in Hadoop","volume":"3","author":"Bansal","year":"2014","journal-title":"Int. J. Recent Technol. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Duggal, R., Khatri, S.K., and Shukla, B. (2015, January 2\u20134). Improving patient matching: Single patient view for Clinical Decision Support using Big Data analytics. Proceedings of the 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions), Noida, India.","DOI":"10.1109\/ICRITO.2015.7359269"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Shahbaz, M., Gao, C., Zhai, L., Shahzad, F., and Hu, Y. (2019). Investigating the adoption of big data analytics in healthcare: The moderating role of resistance to change. J. Big Data, 6.","DOI":"10.1186\/s40537-019-0170-y"},{"key":"ref_21","first-page":"362","article-title":"Leveraging Big Data Analytics to Improve Quality of Care in Healthcare Organizations: A Configurational Perspective","volume":"30","author":"Wang","year":"2018","journal-title":"Spec. Issue Big Data Firm Perform."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Kumar, Y., Sood, K., Kaul, S., and Vasuja, R. (2020). Big Data Analytics and Its Benefits in Healthcare. Big Data Analytics in Healthcare, Springer.","DOI":"10.1007\/978-3-030-31672-3_1"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1007\/s11606-013-2455-8","article-title":"Bringing big data to personalized healthcare: A patient-centered framework","volume":"28","author":"Chawla","year":"2013","journal-title":"J. Gen. Intern. Med."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1186\/s13073-016-0323-y","article-title":"Making sense of big data in health research: Towards an EU action plan","volume":"8","author":"Auffray","year":"2016","journal-title":"Genome Med."},{"key":"ref_25","unstructured":"Groves, P., Kayyali, B., Knott, D., and Van Kuiken, S. (2021, February 05). The \u2018Big Data\u2019 Revolution in Healthcare: Accelerating Value and Innovation. McKinsey & Company, Available online: https:\/\/www.ghdonline.org\/uploads\/Big_Data_Revolution_in_health_care_2013_McKinsey_Report.pdf."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"79","DOI":"10.4258\/hir.2013.19.2.79","article-title":"Potentiality of big data in the medical sector: Focus on how to reshape the healthcare system","volume":"19","author":"Jee","year":"2013","journal-title":"Healthc. Inform. Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"894","DOI":"10.1109\/JBHI.2013.2257818","article-title":"A cloud-based approach for interoperable electronic health records (EHRs)","volume":"17","author":"Bahga","year":"2013","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Demchenko, Y., Ngo, C., and Membrey, P. (2013). Architecture framework and components for the big data ecosystem. J. Syst. Netw. Eng., 1\u201331. Available online: https:\/\/docplayer.net\/1631822-Architecture-framework-and-components-for-the-big-data-ecosystem.html.","DOI":"10.1109\/CTS.2014.6867550"},{"key":"ref_29","first-page":"93","article-title":"Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms","volume":"55","author":"Crawford","year":"2014","journal-title":"BCL Rev."},{"key":"ref_30","first-page":"1492","article-title":"De-Identified Personal health care system using Hadoop","volume":"5","author":"Madhavi","year":"2015","journal-title":"Int. J. Electr. Comput. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Sheriff, C.I., Naqishbandi, T., and Geetha, A. (2015, January 8\u201310). Healthcare informatics and analytics framework. Proceedings of the Computer Communication and Informatics (ICCCI), 2015 International Conference on IEEE, Coimbatore, India.","DOI":"10.1109\/ICCCI.2015.7218108"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3","DOI":"10.4258\/hir.2015.21.1.3","article-title":"Big data analysis framework for healthcare and social sectors in Korea","volume":"21","author":"Song","year":"2015","journal-title":"Healthc. Inform. Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1016\/j.procs.2015.08.536","article-title":"Health twitter big bata management with hadoop framework","volume":"64","author":"Cunha","year":"2015","journal-title":"Procedia Comput. Sci."},{"key":"ref_34","first-page":"264","article-title":"Health Care Analytics with Hadoop Big Data Processing","volume":"2","author":"Kavitha","year":"2016","journal-title":"Int. J. Adv. Res. Biol. Eng. Sci. Technol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1080\/09537287.2017.1336792","article-title":"Big data and the transformation of operations models: A framework and a new research agenda","volume":"28","author":"Roden","year":"2017","journal-title":"Prod. Plan. Control"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/j.jbusres.2016.08.002","article-title":"Exploring the path to big data analytics success in healthcare","volume":"70","author":"Wang","year":"2017","journal-title":"J. Bus. Res."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.im.2017.04.001","article-title":"An integrated big data analytics-enabled transformation model: Application to health care","volume":"55","author":"Wang","year":"2018","journal-title":"Inf. Manag."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1186\/s40537-019-0217-0","article-title":"Big data in healthcare: Management, analysis and future prospects","volume":"6","author":"Dash","year":"2019","journal-title":"J. Big Data"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Bora, D.J. (2019). Chapter 3\u2014Big Data Analytics in Healthcare: A Critical Analysis, In Advances in Ubiquitous Sensing Applications for Healthcare, Big Data Analytics for Intelligent Healthcare Management, Academic Press.","DOI":"10.1016\/B978-0-12-818146-1.00003-9"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"012010","DOI":"10.1088\/1742-6596\/933\/1\/012010","article-title":"AI based HealthCare Platform for Real Time, Predictive and Prescriptive Analytics using Reactive Programming","volume":"933","author":"Kaur","year":"2018","journal-title":"J. Physics Conf. Ser."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"878","DOI":"10.1080\/17517575.2020.1812005","article-title":"Big data analytics in healthcare: A systematic literature review","volume":"14","author":"Khanra","year":"2020","journal-title":"Enterp. Inf. Syst."},{"key":"ref_42","first-page":"8","article-title":"Big data and biomedical informatics: A challenging opportunity","volume":"9","author":"Bellazzi","year":"2014","journal-title":"Yearb. Med. Inform."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.ins.2014.01.015","article-title":"Data-intensive applications, challenges, techniques and technologies: A survey on Big Data","volume":"275","author":"Chen","year":"2014","journal-title":"Inf. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Kaisler, S., Armour, F., Espinosa, J.A., and Money, W. (2013, January 7\u201310). Big data: Issues and challenges moving forward. Proceedings of the System Sciences (HICSS), 2013 46th Hawaii International Conference on IEEE, Wailea, HI, USA.","DOI":"10.1109\/HICSS.2013.645"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1145\/2611567","article-title":"Big data and its technical challenges","volume":"57","author":"Jagadish","year":"2014","journal-title":"Commun. ACM"},{"key":"ref_46","first-page":"114","article-title":"Health big data analytics: Current perspectives, challenges and potential solutions","volume":"1","author":"Kuo","year":"2014","journal-title":"Int. J. Big Data Intell."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1186\/s40537-015-0031-2","article-title":"Visualizing Big Data with augmented and virtual reality: Challenges and research agenda","volume":"2","author":"Olshannikova","year":"2015","journal-title":"J. Big Data"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Kang, K.C., Cohen, S.G., Hess, J.A., Novak, W.E., and Peterson, A.S. (1990). Feature-Oriented Domain Analysis (Foda) Feasibility Study, Software Engineering Institute, Carnegie Mellon University. Tech. Rep. CMU\/SEI-90-TR-21.","DOI":"10.21236\/ADA235785"},{"key":"ref_49","first-page":"142","article-title":"Collaborative features in content sharing Web 2.0 social networks: A domain engineering based on the 3C collaboration model","volume":"Volume 6969","author":"Oliveira","year":"2011","journal-title":"Proceedings of the Collaboration Researchers\u2019 International Workshop on Groupware (CRIWG\u201911)"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1504\/IJNVO.2013.059685","article-title":"Developers\u2019 social networks-tools analysis based on the 3Cs model","volume":"13","author":"Jeffery","year":"2013","journal-title":"Int. J. Netw. Virtual Organ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.bdr.2016.05.002","article-title":"Towards a comprehensive data analytics framework for smart healthcare services","volume":"4","author":"Sakr","year":"2016","journal-title":"Big Data Res."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"36","DOI":"10.15265\/IY-2014-0012","article-title":"Challenges and potential solutions for big data implementations in developing countries","volume":"23","author":"Luna","year":"2014","journal-title":"Yearb. Med. Inform."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.techfore.2015.12.019","article-title":"Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations","volume":"126","author":"Wang","year":"2018","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_54","first-page":"33","article-title":"Big data and visualization: Methods, challenges and technology progress","volume":"1","author":"Wang","year":"2015","journal-title":"Digit. Technol."},{"key":"ref_55","unstructured":"(2021, February 05). VistA. Available online: https:\/\/worldvista.org\/AboutVistA."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1136\/jamia.1997.0040199","article-title":"Understanding and using DICOM, the data interchange standard for biomedical imaging","volume":"4","author":"Bidgood","year":"1997","journal-title":"J. Am. Med. Inform. Assoc. JAMIA"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1136\/adc.83.1.82","article-title":"PACS (picture archiving and communication systems): Filmless radiology","volume":"83","author":"Strickl","year":"2000","journal-title":"Arch. Dis. Child."},{"key":"ref_58","unstructured":"(2021, February 05). YottaDB: What Was Old Is New Again. Available online: https:\/\/docs.yottadb.com\/Presentations\/WhatWasOldIsNewAgain.pdf."}],"container-title":["Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5729\/6\/2\/16\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:20:32Z","timestamp":1760160032000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5729\/6\/2\/16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,6]]},"references-count":58,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2021,2]]}},"alternative-id":["data6020016"],"URL":"https:\/\/doi.org\/10.3390\/data6020016","relation":{},"ISSN":["2306-5729"],"issn-type":[{"value":"2306-5729","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,2,6]]}}}