Multi-criteria decision-making analysis for hospital selection in the telemedicine environment

In this study, a new module for telemedicine architecture, namely Tier 4, was developedto provide intelligent data and services management in the telemedicine environment. Fora suitable hospital to provide remote healthcare services, a new hospital selectionframework based on multi-criteria decision...

Full description

Saved in:

Bibliographic Details
Main Author:	Albahrey, Osamah Shihab Ahmed
Format:	thesis
Language:	eng
Published:	2019
Subjects:	R Medicine
Online Access:	https://ir.upsi.edu.my/detailsg.php?det=6317
Tags:	Add Tag No Tags, Be the first to tag this record!

id	oai:ir.upsi.edu.my:6317
record_format	uketd_dc
institution	Universiti Pendidikan Sultan Idris
collection	UPSI Digital Repository
language	eng
topic	R Medicine
spellingShingle	R Medicine Albahrey, Osamah Shihab Ahmed Multi-criteria decision-making analysis for hospital selection in the telemedicine environment
description	In this study, a new module for telemedicine architecture, namely Tier 4, was developedto provide intelligent data and services management in the telemedicine environment. Fora suitable hospital to provide remote healthcare services, a new hospital selectionframework based on multi-criteria decision making (MCDM) of Tier 4 was developed forchronic heart disease patients who lived in remote places. An experiment was conductedon the basis of three stages. Firstly, health data, such as electrocardiogram, oxygensaturation sensor, blood pressure monitor, and non-sensory measurement, were collectedfrom 500 patients with different symptoms. The number of healthcare servicesrepresenting the hospital status was collected from 12 hospitals located in Baghdad City.A decision matrix based on the crossover of ?multi-healthcare services and ?hospital listof Tier 4 was also constructed. Secondly, the hospitals were then ranked using MCDMtechniques, namely the integrated Analytic Hierarchy Process (AHP) andVlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Thirdly, means andstandard deviations were computed to ensure hospital ranking could be systematicallyperformed to facilitate objective validation. The results showed that (1) the integration ofAHP and VIKOR would able to effectively solve hospital selection problems. (2) In theobjective validation, significant differences in scores between groups were observed,indicating that the ranking results were identical. (3) In the evaluation, the resultsrevealed that the proposed framework was more effective by 56.25% than the benchmarkframework. In conclusion, hospitals with multiple-healthcare services received thehighest ranks compared to those of the hospitals with fewer healthcare services. Theimplications of this study provide several benefits to medical organizations by balancingthe healthcare services loading among hospitals, assist medical teams by performing atimely and accurate treatment for their patients, and provide healthcare services forpatients living in unserved or underserved areas.
format	thesis
qualification_name
qualification_level	Doctorate
author	Albahrey, Osamah Shihab Ahmed
author_facet	Albahrey, Osamah Shihab Ahmed
author_sort	Albahrey, Osamah Shihab Ahmed
title	Multi-criteria decision-making analysis for hospital selection in the telemedicine environment
title_short	Multi-criteria decision-making analysis for hospital selection in the telemedicine environment
title_full	Multi-criteria decision-making analysis for hospital selection in the telemedicine environment
title_fullStr	Multi-criteria decision-making analysis for hospital selection in the telemedicine environment
title_full_unstemmed	Multi-criteria decision-making analysis for hospital selection in the telemedicine environment
title_sort	multi-criteria decision-making analysis for hospital selection in the telemedicine environment
granting_institution	Universiti Pendidikan Sultan Idris
granting_department	Fakulti Seni, Komputeran dan Industri Kreatif
publishDate	2019
url	https://ir.upsi.edu.my/detailsg.php?det=6317
_version_	1747833256076640256
spelling	oai:ir.upsi.edu.my:63172021-10-18 Multi-criteria decision-making analysis for hospital selection in the telemedicine environment 2019 Albahrey, Osamah Shihab Ahmed R Medicine In this study, a new module for telemedicine architecture, namely Tier 4, was developedto provide intelligent data and services management in the telemedicine environment. Fora suitable hospital to provide remote healthcare services, a new hospital selectionframework based on multi-criteria decision making (MCDM) of Tier 4 was developed forchronic heart disease patients who lived in remote places. An experiment was conductedon the basis of three stages. Firstly, health data, such as electrocardiogram, oxygensaturation sensor, blood pressure monitor, and non-sensory measurement, were collectedfrom 500 patients with different symptoms. The number of healthcare servicesrepresenting the hospital status was collected from 12 hospitals located in Baghdad City.A decision matrix based on the crossover of ?multi-healthcare services and ?hospital listof Tier 4 was also constructed. Secondly, the hospitals were then ranked using MCDMtechniques, namely the integrated Analytic Hierarchy Process (AHP) andVlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Thirdly, means andstandard deviations were computed to ensure hospital ranking could be systematicallyperformed to facilitate objective validation. The results showed that (1) the integration ofAHP and VIKOR would able to effectively solve hospital selection problems. (2) In theobjective validation, significant differences in scores between groups were observed,indicating that the ranking results were identical. (3) In the evaluation, the resultsrevealed that the proposed framework was more effective by 56.25% than the benchmarkframework. In conclusion, hospitals with multiple-healthcare services received thehighest ranks compared to those of the hospitals with fewer healthcare services. Theimplications of this study provide several benefits to medical organizations by balancingthe healthcare services loading among hospitals, assist medical teams by performing atimely and accurate treatment for their patients, and provide healthcare services forpatients living in unserved or underserved areas. 2019 thesis https://ir.upsi.edu.my/detailsg.php?det=6317 https://ir.upsi.edu.my/detailsg.php?det=6317 text eng closedAccess Doctoral Universiti Pendidikan Sultan Idris Fakulti Seni, Komputeran dan Industri Kreatif Abdullah, L. (2013). Fuzzy multi criteria decision making and its applications : A briefreview of category. Procedia - Social and Behavioral Sciences, 97, 131136.https://doi.org/10.1016/j.sbspro.2013.10.213Abdullateef, B. N., Elias, N. F., Mohamed, H., Zaidan, A. A., & Zaidan, B. B. (2016). An evaluationand selection problems of OSS-LMS packages. SpringerPlus, 5(1), 248.https://doi.org/10.1186/s40064-016-1828-yAcampora, G., Cook, D. J., Rashidi, P., & Vasilakos, A. V. (2013). A Survey on Ambient Intelligencein Health Care. Proceedings of the IEEE. Institute of Electrical and Electronics Engineers, 101(12), 24702494.https://doi.org/10.1109/JPROC.2013.2262913Adibi, S. (2015). A mobile health network disaster management system. In 2015 Seventh InternationalConference on Ubiquitous and Future Networks (pp. 424428). IEEE.https://doi.org/10.1109/ICUFN.2015.7182579Adunlin, G., Diaby, V., & Xiao, H. (2015). Application of multicriteria decision analysis in healthcare: a systematic review and bibliometric analysis. Health Expectations, 18(6), 18941905.Ahmadi, H., Nilashi, M., & Ibrahim, O. (2015). Organizational decision to adopt hospitalinformation system: An empirical investigation in the case of Malaysian public hospitals.International Journal of Medical Informatics, 84(3), 166188.Akdag, H., Kalayc?, T., Karagz, S., Zlfikar, H., & Giz, D. (2014). The evaluation of hospitalservice quality by fuzzy MCDM. Applied Soft Computing, 23, 239248.Aktan, H. E., & Samut, P. K. (2013). Agricultural performance evaluation by integrating fuzzy AHP and VIKOR methods. International Journal of Applied Decision Sciences, 6(4), 324.https://doi.org/10.1504/IJADS.2013.056865Albahri, A. S., Zaidan, A. A., Albahri, O. S., Zaidan, B. B., & Alsalem, M. A. (2018,August 23). Real-Time Fault-Tolerant mHealth System: Comprehensive Review of Healthcare Services,Opens Issues, Challenges and Methodological Aspects. Journal of Medical Systems. Springer US.https://doi.org/10.1007/s10916-018-0983-9Aldlaigan, A. H., & Buttle, F. A. (2002). SYSTRA-SQ: a new measure of bank service quality.International Journal of Service Industry Management, 13(4), 362381.Ali, R., Siddiqi, M., Idris, M., Ali, T., Hussain, S., Huh, E.-N., Lee, S. (2015).GUDM: Automatic Generation of Unified Datasets for Learning and Reasoning in Healthcare. Sensors,15(12), 1577215798. https://doi.org/10.3390/s150715772Almadani, B., Saeed, B., & Alroubaiy, A. (2016). Healthcare systems integration using Real TimePublish Subscribe (RTPS) middleware. Computers & Electrical Engineering, 50, 6778.https://doi.org/10.1016/j.compeleceng.2015.12.009Alnanih, R., Ormandjieva, O., & Radhakrishnan, T. (2013). Context-based and Rule- based Adaptation of Mobile User Interfaces in mHealth. Procedia ComputerScience, 21, 390397. https://doi.org/10.1016/j.procs.2013.09.051Alsalem, M. A., Zaidan, A. A., Zaidan, B. B., Hashim, M., Albahri, O. S., Albahri, A. S., Mohammed, K. I. (2018). Systematic Review of an Automated MulticlassDetection and Classification System for Acute Leukaemia in Terms of Evaluationand Benchmarking, Open Challenges, Issues and Methodological Aspects. Journalof Medical Systems, 42(11), 204. https://doi.org/10.1007/s10916-018-1064-9Alsalem, M. A., Zaidan, A. A., Zaidan, B. B., Hashim, M., Madhloom, H. T., Azeez, N.D., & Alsyisuf, S. (2018). A review of the automated detection and classification ofacute leukaemia: Coherent taxonomy, datasets, validation and performancemeasurements, motivation, open challenges and recommendations. ComputerMethods and Programs in Biomedicine, 158, 93112.https://doi.org/10.1016/j.cmpb.2018.02.005Ar, I. M., & Kurtaran, A. (2013). Evaluating the relative efficiency of commercial banksin Turkey: an integrated AHP/DEA approach. International Business Research,6(4), 129.Archenaa, J., & Anita, E. A. M. (2015). A Survey of Big Data Analytics in Healthcareand Government. Procedia Computer Science, 50(4), 408413.https://doi.org/10.1016/j.procs.2015.04.021Aruldoss, M., Lakshmi, T. M., & Venkatesan, V. P. (2013). A survey on multi criteriadecision making methods and its applications. American Journal of InformationSystems, 1(1), 3143.Ashour, O. M., & Okudan, G. E. (2010). Fuzzy AHP and utility theory based patientsorting in emergency departments. International Journal of CollaborativeEnterprise, 1(34), 332358.Azeez, D., Ali, M. A. M., Gan, K. B., & Saiboon, I. (2013). Comparison of adaptiveneuro-fuzzy inference system and artificial neutral networks model to categorizepatients in the emergency department. SpringerPlus, 2(1), 416.Baehr, D., McKinney, S., Quirk, A., & Harfoush, K. (2014). On the practicality of ellipticcurve cryptography for medical sensor networks. In 2014 11th Annual HighCapacity Optical Networks and Emerging/Enabling Technologies (Photonics forEnergy) (pp. 4145). IEEE. https://doi.org/10.1109/HONET.2014.7029358Baig, M. M., & Gholamhosseini, H. (2013). Smart health monitoring systems: anoverview of design and modeling. Journal of Medical Systems, 37(2), 9898.Barrios, M. A. O., De Felice, F., Negrete, K. P., Romero, B. A., Arenas, A. Y., & Petrillo,A. (2016). An AHP-Topsis Integrated Model for Selecting the Most AppropriateTomography Equipment. International Journal of Information Technology &Decision Making, 15(04), 861885.Beck, C., & Georgiou, J. (2016). A wearable, multimodal, vitals acquisition unit forintelligent field triage. In 2016 IEEE International Symposium on Circuits andSystems (ISCAS) (Vol. 2016July, pp. 15301533). IEEE.https://doi.org/10.1109/ISCAS.2016.7538853Bellini, P., di Claudio, M., Nesi, P., & Rauch, N. (2013). Tassonomy and Review of BigData Solutions Navigation. In Big Data Computing (pp. 57101).https://doi.org/10.1201/b16014-4Belton, V., & Stewart, T. J. (2002). Multiple Criteria Decision Analysis. Boston, MA:Springer US. https://doi.org/10.1007/978-1-4615-1495-4Ben Elhadj, H., Elias, J., Chaari, L., & Kamoun, L. (2016). Multi-Attribute DecisionMaking Handover Algorithm for Wireless Body Area Networks. ComputerCommunications, 81, 97108. https://doi.org/10.1016/j.comcom.2016.01.007Ben, H., Elias, J., Chaari, L., Kamoun, L., Ben Elhadj, H., Elias, J., Kamoun, L.(2015). A Priority based Cross Layer Routing Protocol for healthcare applications.Ad Hoc Networks, 42, 118. https://doi.org/10.1016/j.adhoc.2015.10.007Ben Othman, S., Zgaya, H., Hammadi, S., Quilliot, A., Martinot, A., & Renard, J.-M.(2016). Agents endowed with uncertainty management behaviors to solve amultiskill healthcare task scheduling. Journal of Biomedical Informatics, 64, 2543.https://doi.org/10.1016/j.jbi.2016.08.011Benmansour, T., Ahmed, T., & Moussaoui, S. (2016). Performance Evaluation of IEEE802.15.6 MAC in Monitoring of a Cardiac Patient. In 2016 IEEE 41st Conferenceon Local Computer Networks Workshops (LCN Workshops) (pp. 241247). IEEE.https://doi.org/10.1109/LCN.2016.054Benson, M., Koenig, K. L., & Schultz, C. H. (1996). Disaster Triage: START, thenSAVEA New Method of Dynamic Triage for Victims of a CatastrophicEarthquake. Prehospital and Disaster Medicine, 11(02), 117124.https://doi.org/10.1017/S1049023X0004276XBernocchi, P., Scalvini, S., Tridico, C., Borghi, G., Zanaboni, P., Masella, C., Marzegalli, M. (2012). Healthcare continuity from hospital to territory in Lombardy:TELEMACO project. American Journal of Managed Care, 18(3), 101108.Bernstein, S. L., & DOnofrio, G. (2009). Public Health in the Emergency Department:Academic Emergency Medicine Consensus Conference Executive Summary.Academic Emergency Medicine, 16(11), 10371039. https://doi.org/10.1111/j.1553-2712.2009.00548.xBesaleva, L. I., & Weaver, A. C. (2013). Mobile electronic triaging for emergencyresponse improvement through crowdsourced and sensor-detected information. InProceedings of the 2013 IEEE/ACM International Conference on Advances inSocial Networks Analysis and Mining - ASONAM 13 (pp. 10921093). New York,New York, USA: ACM Press. https://doi.org/10.1145/2492517.2500327best doctors. (n.d.). Retrieved November 5, 2017, from https://bestdoctors.com/Beveridge, R., Clarke, B., Janes, L., Savage, N., Thompson, J., Dodd, G., Vadeboncoeur, A. (1998). Implementation Guidelines for The Canadian EmergencyDepartment Triage & Acuity Scale ( CTAS ) - endorsed by the CanadianAssociation of Emergency Physicians, the National Emergency Nurses Affiliation ofCanada, and lassociation des medecins durgence du. Canadian Association ofEmergency Physicians, 132.Bharatula, S., & Meenakshi, M. (2016). Design of Cognitive Radio Network for HospitalManagement System. Wireless Personal Communications, 90(2), 10211038.https://doi.org/10.1007/s11277-016-3280-2Bouakaz, S., Vacher, M., Bobillier Chaumon, M.-E., Aman, F., Bekkadja, S., Portet, F., Chevalier, T. (2014). CIRDO: Smart companion for helping elderly to live athome for longer. IRBM, 35(2), 100108. https://doi.org/10.1016/j.irbm.2014.02.011Boursalie, O., Samavi, R., & Doyle, T. E. (2015). M4CVD: Mobile Machine LearningModel for Monitoring Cardiovascular Disease. Procedia Computer Science,63(Icth), 384391. https://doi.org/10.1016/j.procs.2015.08.357Bradai, N., Chaari Fourati, L., & Kamoun, L. (2015). WBAN data scheduling andaggregation under WBAN/WLAN healthcare network. Ad Hoc Networks, 25(PA),251262. https://doi.org/10.1016/j.adhoc.2014.10.017Bradai, N., Charfi, E., Fourati, L. C., & Kamoun, L. (2016). Priority consideration ininter-WBAN data scheduling and aggregation for monitoring systems. Transactionson Emerging Telecommunications Technologies, 27(4), 589600.https://doi.org/10.1002/ett.2995Bres, A., Martnez-Miranda, J., Fuster-Garca, E., & Garca-Gmez, J. M. (2016). Anovel approach to improve the planning of adaptive and interactive sessions for thetreatment of Major Depression. International Journal of Human-Computer Studies,87, 8091. https://doi.org/10.1016/j.ijhcs.2015.11.003Brunetti, N. D., Dellegrottaglie, G., Di Giuseppe, G., Antonelli, G., & Di Biase, M.(2014). All for one, one for all: Remote telemedicine hub pre-hospital triage forpublic Emergency Medical Service 1-1-8 in a regional network for primary PCI inApulia, Italy. European Research in Telemedicine/La Recherche Europenne EnTlmdecine, 3(1), 915.Brunetti, N. D., Scalvini, S., Acquistapace, F., Parati, G., Volterrani, M., Fedele, F., &Molinari, G. (2015). Telemedicine for cardiovascular disease continuum: a positionpaper from the Italian Society of Cardiology Working Group on Telecardiology andInformatics. International Journal of Cardiology, 184, 452458.Busse, R., Schreygg, J., & Smith, P. C. (2008). Variability in healthcare treatment costsamongst nine EU countriesresults from the HealthBASKET project. HealthEconomics, 17(S1).al??kan, H. (2013). Selection of boron based tribological hard coatings using multicriteriadecision making methods. Materials & Design, 50, 742749.Calyam, P., Mishra, A., Antequera, R. B., Chemodanov, D., Berryman, A., Zhu, K., Skubic, M. (2016). Synchronous Big Data analytics for personalized and remotephysical therapy. Pervasive and Mobile Computing, 28, 320.https://doi.org/10.1016/j.pmcj.2015.09.004Chakraborty, S., Ghosh, S. K., Jamthe, A., & Agrawal, D. P. (2013). Detecting Mobilityfor Monitoring Patients with Parkinsons Disease at Home using RSSI in a WirelessSensor Network. Procedia Computer Science, 19, 956961.https://doi.org/10.1016/j.procs.2013.06.132Chang, M.-Y., Pang, C., Tarn, J. M., Liu, T.-S., & Yen, D. C. (2015). Exploring useracceptance of an e-hospital service: An empirical study in Taiwan. ComputerStandards & Interfaces, 38, 3543.Chang, T. H. (2014). Fuzzy VIKOR method: A case study of the hospital serviceevaluation in Taiwan. Information Sciences, 271, 196212.https://doi.org/10.1016/j.ins.2014.02.118Chiang, H., Lai, C., & Huang, Y. (2014). A green cloud-assisted health monitoringservice on wireless body area networks. Information Sciences, 284, 118129.https://doi.org/10.1016/j.ins.2014.07.013Chowdhury, M., Mciver, W., & Light, J. (2012). Data association in remote healthmonitoring systems. IEEE Communications Magazine, 50(6), 144149.https://doi.org/10.1109/MCOM.2012.6211499Christensen, D., Jensen, N. M., Maale, R., Rudolph, S. S., Belhage, B., & Perrild, H.(2011a). Low compliance with a validated system for emergency department triage.Danish Medical Bulletin, 58(6), A4294. Retrieved fromhttp://www.ncbi.nlm.nih.gov/pubmed/21651880Christensen, D., Jensen, N. M., Maale, R., Rudolph, S. S., Belhage, B., & Perrild, H.(2011b). Nurse-administered early warning score system can be used for emergencydepartment triage. Danish Medical Bulletin, 58(6), A4221.https://doi.org/DMBA4221 [pii]Chung, S., & Shannon, M. (2007). Reuniting children with their families during disasters:a proposed plan for greater success. American Journal of Disaster Medicine, 2(3),113117.Chung, Y., & Liu, C. (2013). Design of a Wireless Sensor Network Platform for Tele-Homecare. Sensors, 13(12), 1715617175. https://doi.org/10.3390/s131217156Cicero, M. X., Walsh, B., Solad, Y., Whitfill, T., Paesano, G., Kim, K., Cone, D. C.(2015). Do You See What i See? Insights from Using Google Glass for DisasterTelemedicine Triage. Prehospital and Disaster Medicine, 30(1), 48.https://doi.org/10.1017/S1049023X1400140XCohn, J. N. (1988). Current therapy of the failing heart. Circulation, 78(5), 10991107.Cross, K. P., & Cicero, M. X. (2013). Head-to-Head Comparison of Disaster TriageMethods in Pediatric, Adult, and Geriatric Patients. Annals of Emergency Medicine,61(6), 668676.e7. https://doi.org/10.1016/j.annemergmed.2012.12.023Culley, J. M., Svendsen, E., Craig, J., & Tavakoli, A. (2014). A Validation Study of 5Triage Systems Using Data From the 2005 Graniteville, South Carolina, ChlorineSpill. Journal of Emergency Nursing, 40(5), 453460.https://doi.org/10.1016/j.jen.2014.04.020D Kelen, G., L McCarthy, M., K Kraus, C., Ding, R., B Hsu, E., Li, G., B Green, G.(2009). Creation of Surge Capacity by Early Discharge of Hospitalized Patients atLow Risk for Untoward Events. Disaster Medicine and Public Health Preparedness,3, S10-6.De Backere, F., Bonte, P., Verstichel, S., Ongenae, F., & De Turck, F. (2017). TheOCarePlatform: A context-aware system to support independent living. ComputerMethods and Programs in Biomedicine, 140, 111120.https://doi.org/10.1016/j.cmpb.2016.11.008de la Piedra, A., Braeken, A., Touhafi, A., & Wouters, K. (2013). Secure event logging insensor networks. Computers & Mathematics with Applications, 65(5), 762773.https://doi.org/10.1016/j.camwa.2012.06.019Demchenko, Y., Grosso, P., de Laat, C., & Membrey, P. (2013). Addressing big dataissues in Scientific Data Infrastructure. In 2013 International Conference onCollaboration Technologies and Systems (CTS) (pp. 4855). IEEE.https://doi.org/10.1109/CTS.2013.6567203Diaby, V., Campbell, K., & Goeree, R. (2013). Multi-criteria decision analysis (MCDA)in health care: a bibliometric analysis. Operations Research for Health Care, 2(1),2024.Dolan, J. G., Boohaker, E., Allison, J., & Imperiale, T. F. (2013). Patients preferencesand priorities regarding colorectal cancer screening. Medical Decision Making,33(1), 5970.Doumbouya, M. B., Kamsu-Foguem, B., Kenfack, H., & Foguem, C. (2014).Telemedicine using mobile telecommunication: Towards syntactic interoperabilityin teleexpertise. Telematics and Informatics, 31(4), 648659.https://doi.org/10.1016/j.tele.2014.01.003Doumbouya, M. B., Kamsu-Foguem, B., Kenfack, H., & Foguem, C. (2015). Aframework for decision making on teleexpertise with traceability of the reasoning.IRBM, 36(1), 4051. https://doi.org/10.1016/j.irbm.2014.09.002Duke, J. M., & Aull-Hyde, R. (2002). Identifying public preferences for land preservationusing the analytic hierarchy process. Ecological Economics, 42(1), 131145.Durisko, C., McCue, M., Doyle, P. J., Dickey, M. W., & Fiez, J. A. (2016). A Flexibleand Integrated System for the Remote Acquisition of Neuropsychological Data inStroke Research. Telemedicine and E-Health, 22(12), 10321040.Faulin, J., Juan, A. A., Grasman, S. E., & Fry, M. J. (2012). Decision Making in ServiceIndustries: A Practical Approach. CRC Press.Fernandes, C. M., Wuerz, R., Clark, S., & Djurdjev, O. (1999). How Reliable IsEmergency Department Triage? Annals of Emergency Medicine, 34(2), 141147.https://doi.org/10.1016/S0196-0644(99)70248-9Fezari, M., Rasras, R., & Emary, I. M. M. El. (2015). Ambulatory Health MonitoringSystem Using Wireless Sensors Node. Procedia Computer Science, 65(Iccmit), 8694. https://doi.org/10.1016/j.procs.2015.09.082Fourati, H., Idoudi, H., Val, T., Van Den Bossche, A., & Saidane, L. A. (2015).Performance evaluation of IEEE 802.15.6 CSMA/CA-based CANet WBAN. In2015 IEEE/ACS 12th International Conference of Computer Systems andApplications (AICCSA) (pp. 17). IEEE.https://doi.org/10.1109/AICCSA.2015.7507181Fratini, A., & Caleffi, M. (2014). Medical emergency alarm dissemination in urbanenvironments. Telematics and Informatics, 31(3), 511517.https://doi.org/10.1016/j.tele.2013.11.007Fu, H.-P., Chu, K.-K., Chao, P., Lee, H.-H., & Liao, Y.-C. (2011). Using fuzzy AHP andVIKOR for benchmarking analysis in the hotel industry. The Service Industries Journal,31(14), 23732389. https://doi.org/10.1080/02642069.2010.503874Gambhir, S., & Kathuria, M. (2016). DWBAN: Dynamic priority based WBANarchitecture for healthcare system. 2016 3rd International Conference on Computing for SustainableGlobal Development (INDIACom).Ganapathy, K., Priya, B., Priya, B., Dhivya, Prashanth, V., & Vaidehi, V. (2013). SOA Frameworkfor Geriatric Remote Health Care Using Wireless Sensor Network. Procedia Computer Science, 19(Fams), 10121019.https://doi.org/10.1016/j.procs.2013.06.141Ganapathy, K., Vaidehi, V., Kannan, B., & Murugan, H. (2014). Hierarchical ParticleSwarm Optimization with Ortho-Cyclic Circles. Expert Systems with Applications, 41(7), 34603476.https://doi.org/10.1016/j.eswa.2013.10.050Ganz, A., Schafer, J. M., Tang, J., Yang, Z., Yi, J., & Ciottone, G. (2015). Urban Search andRescue Situational Awareness using DIORAMA Disaster Management System. Procedia Engineering, 107,349356. https://doi.org/10.1016/j.proeng.2015.06.091Gaynor, M., & Waterman, J. (2016). Design framework for sensors and RFID tags with healthcare applications. Health Policy and Technology, 5(4), 357369.https://doi.org/10.1016/j.hlpt.2016.07.007Ghanavati, S., Abawaji, J., & Izadi, D. (2015). A Congestion Control Scheme Based on Fuzzy Logicin Wireless Body Area Networks. In 2015 IEEE 14th International Symposium on Network Computing and Applications (pp. 235242). IEEE. https://doi.org/10.1109/NCA.2015.38Ghanavati, S., Abawajy, J., & Izadi, D. (2016). ECG rate control scheme in pervasivehealth care monitoring system. In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 22652270). IEEE. https://doi.org/10.1109/FUZZ- IEEE.2016.7737975Gilboy, N., Tanabe, P., Travers, D., & Rosenau, A. M. (2012). Emergency Severity Index (ESI): atriage tool for emergency department care, version 4. Implementation Handbook, 1214.Gilpin, R., & Gilpin, J. M. (2000). The challenge of global capitalism: The worldeconomy in the 21st century (Vol. 5). Princeton University Press Princeton, NJ.Godfrey, B., et al. (2000). Emergency Medical Guidelines. Sunshine Act of Florida, (3), 245.Gmez, J., Oviedo, B., & Zhuma, E. (2016). Patient Monitoring System Based on Internet of Things. Procedia Computer Science, 83(Ant), 9097.https://doi.org/10.1016/j.procs.2016.04.103Gunasekaran, S., & Suresh, M. (2014). A novel control of disaster protection (NCDP) for pilgrims by pan technology. In 2014 IEEE 8th International Conference on Intelligent Systems and Control (ISCO) (pp. 103107). IEEE.https://doi.org/10.1109/ISCO.2014.7103927Gndo?du, K., & alhan, A. (2016). An Implementation of Wireless Body AreaNetworks for Improving Priority Data Transmission Delay. Journal of MedicalSystems, 40(3), 75. https://doi.org/10.1007/s10916-016-0443-3Hamdi, O., Chalouf, M. A., Ouattara, D., & Krief, F. (2014). eHealth: Survey on researchprojects, comparative study of telemonitoring architectures and main issues. Journalof Network and Computer Applications, 46, 100112.https://doi.org/10.1016/j.jnca.2014.07.026Haque, S. A., & Aziz, S. M. (2013). False Alarm Detection in Cyber-physical Systemsfor Healthcare Applications. AASRI Procedia, 5, 5461.https://doi.org/10.1016/j.aasri.2013.10.058He, C., Fan, X., & Li, Y. (2013). Toward Ubiquitous Healthcare Services With a NovelEfficient Cloud Platform. IEEE Transactions on Biomedical Engineering, 60(1),230234. https://doi.org/10.1109/TBME.2012.2222404Hedin, D. S., Kollmann, D. T., Gibson, P. L., Riehle, T. H., & Seifert, G. J. (2014).Distance bounded energy detecting ultra-wideband impulse radio secure protocol. In2014 36th Annual International Conference of the IEEE Engineering in Medicineand Biology Society (Vol. 2014, pp. 66196622). IEEE.https://doi.org/10.1109/EMBC.2014.6945145Herath, G., & Prato, T. (2006). Using multi-criteria decision analysis in natural resourcemanagement. Ashgate Publishing, Ltd.Hermens, H., op den Akker, H., Tabak, M., Wijsman, J., & Vollenbroek, M. (2014).Personalized Coaching Systems to support healthy behavior in people with chronicconditions. Journal of Electromyography and Kinesiology, 24(6), 815826.https://doi.org/10.1016/j.jelekin.2014.10.003Hilgerink, M. P., Hummel, M. J. M., Manohar, S., Vaartjes, S. R., & IJzerman, M. J.(2011). Assessment of the added value of the Twente Photoacoustic Mammoscopein breast cancer diagnosis. Medical Devices (Auckland, NZ), 4, 107.Hindia, M. N., Rahman, T. A., Ojukwu, H., Hanafi, E. B., & Fattouh, A. (2016).Enabling Remote Health-Caring Utilizing IoT Concept over LTE-FemtocellNetworks. PLOS ONE, 11(5), e0155077.https://doi.org/10.1371/journal.pone.0155077Hodgetts, T. J., Hall, J., Maconochie, I., & Smart, C. (1998). Paediatric triage tape. Pre-Hospital Immediate Care, 2, 155159.Hu, L., Zhang, Y., Feng, D., Hassan, M. M., Alelaiwi, A., & Alamri, A. (2015). Designof QoS-Aware Multi-Level MAC-Layer for Wireless Body Area Network. Journalof Medical Systems, 39(12), 192. https://doi.org/10.1007/s10916-015-0336-xHummel, M. J. M., Volz, F., van Manen, J. G., Danner, M., Dintsios, C.-M., IJzerman,M. J., & Gerber, A. (2012). Using the analytic hierarchy process to elicit patientpreferences. The Patient: Patient-Centered Outcomes Research, 5(4), 225237.Hung, C. Y., Chang, P. Y., & Huang, Y. H. (2006). Comparison of fuzzy-based MCDMand non-fuzzy MCDM in setting a new fee schedule for orthopedic procedures inTaiwans national health insurance program. WSEAS Transactions on Mathematics,5(1), 149153.Hussain, A., Wenbi, R., da Silva, A. L., Nadher, M., & Mudhish, M. (2015). Health andemergency-care platform for the elderly and disabled people in the Smart City.Journal of Systems and Software, 110, 253263.https://doi.org/10.1016/j.jss.2015.08.041Hussain, M., Zaidan, A. A., Zidan, B. B., Iqbal, S., Ahmed, M. M., Albahri, O. S., &Albahri, A. S. (2018). Conceptual framework for the security of mobile healthapplications on Android platform. Telematics and Informatics, 35(5), 13351354.https://doi.org/10.1016/j.tele.2018.03.005Hwang, T. H., Kim, D. S., & Kim, J. G. (2013). An on-time power-aware schedulingscheme for medical sensor SoC-based WBAN systems. Sensors (Switzerland),13(1), 375392. https://doi.org/10.3390/s130100375IFRC. (2015). Disaster and crisis management. Retrieved November 2, 2017, fromhttps://www.ifrc.org/en/what-we-do/disaster-management/Iftikhar, M., & Ahmad, I. (2014). A Novel Analytical Model for Provisioning QoS inBody Area Sensor Networks. Procedia Computer Science, 32, 900907.https://doi.org/10.1016/j.procs.2014.05.509Iftikhar, M., Elaiwi, N. Al, & Aksoy, M. S. (2014). Performance Analysis of PriorityQueuing Model for Low Power Wireless Body Area Networks (WBANs). ProcediaComputer Science, 34, 518525. https://doi.org/10.1016/j.procs.2014.07.060Ilangkumaran, M., Sasirekha, V., Anojkumar, L., & Raja, M. B. (2012). Machine toolselection using AHP and VIKOR methodologies under fuzzy environment.International Journal of Modelling in Operations Management, 2(4), 409.https://doi.org/10.1504/IJMOM.2012.049133Innes, K., Plummer, V., & Considine, J. (2011). Nurses perceptions of their preparationfor triage. Australasian Emergency Nursing Journal, 14(2), 8186.https://doi.org/10.1016/j.aenj.2011.03.003Jadhav, A., & Sonar, R. (2009). Analytic Hierarchy Process (AHP), Weighted ScoringMethod (WSM), and Hybrid Knowledge Based System (HKBS) for SoftwareSelection: A Comparative Study. In Emerging Trends in Engineering andTechnology (ICETET), 2009 2nd International Conference on (pp. 991997). IEEE.Jentsch, M., & Ramirez, L. (2013). The reconfiguration of triage by introduction oftechnology. In Proceedings of the 15th international conference on Humancomputerinteraction with mobile devices and services (MobileHCI 13) (pp. 5564).New York, New York, USA: ACM Press. https://doi.org/10.1145/2493190.2493212Jeong, S., Youn, C.-H., Shim, E. B., Kim, M., Cho, Y. M., & Peng, L. (2012). Anintegrated healthcare system for personalized chronic disease care in homehospitalenvironments. IEEE Transactions on Information Technology in Biomedicine, 16(4),572585.Johnson, C. D., & Taylor, I. (2004). Recent Advances in Surgery 27 (Vol. 27). CRCPress.Jumaah, F. M., Zadain, A. A., Zaidan, B. B., Hamzah, A. K., & Bahbibi, R. (2018).Decision-making solution based multi-measurement design parameter foroptimization of GPS receiver tracking channels in static and dynamic real-timepositioning multipath environment. Measurement, 118, 8395.https://doi.org/10.1016/j.measurement.2018.01.011Jumaah, F. M., Zaidan, A. A., Zaidan, B. B., Bahbibi, R., Qahtan, M. Y., & Sali, A.(2017). Technique for order performance by similarity to ideal solution for solvingcomplex situations in multi-criteria optimization of the tracking channels of GPSbaseband telecommunication receivers. Telecommunication Systems, 119.Kaiser Family Foundation. (2009). Trends in Health Care Costs and Spending. HealthCare, (650), 12.Kalid, N., Zaidan, A. A., Zaidan, B. B., Salman, O. H., Hashim, M., Albahri, O. S., &Albahri, A. S. (2018). Based on Real Time Remote Health Monitoring Systems: ANew Approach for Prioritization ?Large Scales Data? Patients with Chronic HeartDiseases Using Body Sensors and Communication Technology. Journal of MedicalSystems, 42(4). https://doi.org/10.1007/s10916-018-0916-7Kalid, N., Zaidan, A. A., Zaidan, B. B., Salman, O. H., Hashim, M., & Muzammil, H.(2018). Based Real Time Remote Health Monitoring Systems: A Review on PatientsPrioritization and Related" Big Data" Using Body Sensors information andCommunication Technology. Journal of Medical Systems, 42(2), 30.Kanter, R. K. (2007). Strategies to improve pediatric disaster surge response: Potentialmortality reduction and tradeoffs. Critical Care Medicine, 35(12), 28372842.https://doi.org/10.1097/01.CCM.0000287579.10746.43Kateretse, C., Lee, G.-W., & Huh, E.-N. (2013). A practical traffic scheduling scheme fordifferentiated services of healthcare systems on wireless sensor networks. WirelessPersonal Communications, 71(2), 909927.Katib, A., Rao, D., Rao, P., Williams, K., & Grant, J. (2015). A prototype of a novel cellphone application for tracking the vaccination coverage of children in ruralcommunities. Computer Methods and Programs in Biomedicine, 122(2), 215228.https://doi.org/10.1016/j.cmpb.2015.08.008Kaur, J., Saini, K. S., & Grewal, R. (2015). Priority based congestion avoidance hybridscheme for Wireless Sensor Network. In 2015 1st International Conference on NextGeneration Computing Technologies (NGCT) (pp. 158165). IEEE.https://doi.org/10.1109/NGCT.2015.7375104Keeney, R. L., & Raiffa, H. (1993). Decisions with multiple objectives: preferences andvalue trade-offs. Cambridge university press.Khan, A. M. R., Prasad, P. N., & Rajamanoharane, S. (2010). A decision-makingframework for service quality measurements in hospitals. International Journal ofEnterprise Network Management, 4(1), 8091.Kiah, M. L. M., Haiqi, A., Zaidan, B. B., & Zaidan, A. A. (2014). Open source EMRsoftware: profiling, insights and hands-on analysis. Computer Methods andPrograms in Biomedicine, 117(2), 360382.Kiah, M. L. M., Zaidan, B. B., Zaidan, A. A., Nabi, M., & Ibraheem, R. (2014).MIRASS: Medical Informatics Research Activity Support System UsingInformation Mashup Network. Journal of Medical Systems, 38(4), 37.https://doi.org/10.1007/s10916-014-0037-xKim, H.-K. (2014). Convergence agent model for developing u-healthcare systems.Future Generation Computer Systems, 35, 3948.https://doi.org/10.1016/j.future.2013.10.025Kim, K., Kyung, T., Kim, W., Shin, C., Song, Y., Lee, M. Y., Cho, Y. (2009).Efficient management design for swimming exercise treatment. The Korean Journalof Physiology & Pharmacology, 13(6), 497502.Kim, W., Han, S. K., Oh, K. J., Kim, T. Y., Ahn, H., & Song, C. (2010). The dualanalytic hierarchy process to prioritize emerging technologies. TechnologicalForecasting and Social Change, 77(4), 566577.Kitamura, Y. (2010). Decision?making process of patients with gynecological cancerregarding their cancer treatment choices using the analytic hierarchy process. JapanJournal of Nursing Science, 7(2), 148157.Klersy, C., De Silvestri, A., Gabutti, G., Regoli, F., & Auricchio, A. (2009). A metaanalysisof remote monitoring of heart failure patients. Journal of the AmericanCollege of Cardiology, 54(18), 16831694.Klimova, B. (2016). Mobile Health Devices for Aging Population Groups: A ReviewStudy. In M. Younas, I. Awan, N. Kryvinska, C. Strauss, & D. van Thanh (Eds.)(Vol. 9847, pp. 295301). Cham: Springer International Publishing.https://doi.org/10.1007/978-3-319-44215-0_24Kormanyos, B., & Pataki, B. (2013). Multilevel simulation of daily activities: Why andhow? In 2013 IEEE International Conference on Computational Intelligence andVirtual Environments for Measurement Systems and Applications (CIVEMSA) (pp.16). IEEE. https://doi.org/10.1109/CIVEMSA.2013.6617386Kovalchuk, S. V., Krotov, E., Smirnov, P. A., Nasonov, D. A., & Yakovlev, A. N.(2018). Distributed data-driven platform for urgent decision making in cardiologicalambulance control. Future Generation Computer Systems, 79, 144154.https://doi.org/2016.09.017Kumar, N., Kaur, K., Jindal, A., & Rodrigues, J. J. P. C. (2015). Providing healthcareservices on-the-fly using multi-player cooperation game theory in Internet ofVehicles (IoV) environment. Digital Communications and Networks, 1(3), 191203.https://doi.org/10.1016/j.dcan.2015.05.001Lahby, M., Cherkaoui, L., & Adib, A. (2013). A Novel Ranking Algorithm BasedNetwork Selection For Heterogeneous Wireless Access. JNW, 8(2), 263272.Lam, K., & Zhao, X. (1998). An application of quality function deployment to improvethe quality of teaching. International Journal of Quality & Reliability Management,15(4), 389413.Lamprinakos, G. C., Asanin, S., Broden, T., Prestileo, A., Fursse, J., Papadopoulos, K.A., Venieris, I. S. (2015). An integrated remote monitoring platform towardsTelehealth and Telecare services interoperability. Information Sciences, 308(March),2337. https://doi.org/10.1016/j.ins.2015.02.032Leister, J., & Stausberg, J. (2007). Why do patients select a hospital? A conjoint analysisin two German hospitals. Journal of Hospital Marketing & Public Relations, 17(2),1331.Lerner, E. B., Cone, D. C., Weinstein, E. S., Schwartz, R. B., Coule, P. L., Cronin, M., Hunt, R. C. (2011). Mass Casualty Triage: An Evaluation of the Science andRefinement of a National Guideline. Disaster Medicine and Public HealthPreparedness, 5(02), 129137. https://doi.org/10.1001/dmp.2011.39Lerner, E. B., Schwartz, R., L. Coule, P., Weinstein, E., C. Cone, D., C. Hunt, R., OConnor, R. (2009). Mass Casualty Triage: Universal Versus Specific: Lerner et alreply. Disaster Medicine and Public Health Preparedness, 3.Li, C., Yuan, X., Yang, L., & Song, Y. (2015). A Hybrid Lifetime Extended DirectionalApproach for WBANs. Sensors, 15(12), 2800528030.https://doi.org/10.3390/s151128005Li, N., Lin, K., Yong, S., Chen, X., Wang, X., & Zhang, X. (2015). Design andimplementation of a MAC protocol for a wearable monitoring system on humanbody. In 2015 IEEE 11th International Conference on ASIC (ASICON) (pp. 14).IEEE. https://doi.org/10.1109/ASICON.2015.7517194Li, S. H., Cheng, K. A., Lu, W. H., & Lin, T. C. (2012). Developing an active emergencymedical service system based on WiMAX technology. Journal of Medical Systems,36(5), 31773193. https://doi.org/10.1007/s10916-011-9809-8Liberatore, M. J., & Nydick, R. L. (2008). The analytic hierarchy process in medical andhealth care decision making: A literature review. European Journal of OperationalResearch, 189(1), 194207.Lin, D., Labeau, F., Yao, Y., Vasilakos, A. V, & Tang, Y. (2016). Admission Controlover Internet of Vehicles Attached with Medical Sensors for Ubiquitous HealthcareApplications. IEEE Journal of Biomedical and Health Informatics, 20(4), 11951204. https://doi.org/10.1109/JBHI.2015.2431744Lingsma, H. F., Steyerberg, E. W., Eijkemans, M. J. C., Dippel, D. W. J., Scholte OpReimer, W. J. M., Van Houwelingen, H. C., & Investigators, N. S. S. (2009).Comparing and ranking hospitals based on outcome: results from The NetherlandsStroke Survey. QJM: An International Journal of Medicine, 103(2), 99108.Liu, C.-T., Long, A.-G., Li, Y.-C., Tsai, K.-C., & Kuo, H.-S. (2001). Sharing patient carerecords over the World Wide Web. International Journal of Medical Informatics,61(2), 189205.Lounis, A., Hadjidj, A., Bouabdallah, A., & Challal, Y. (2016). Healing on the cloud:Secure cloud architecture for medical wireless sensor networks. Future GenerationComputer Systems, 55, 266277. https://doi.org/10.1016/j.future.2015.01.009Lwin, M. O., Vijaykumar, S., Fernando, O. N. N., Cheong, S. A., Rathnayake, V. S.,Lim, G., Foo, S. (2014). A 21st century approach to tackling dengue:Crowdsourced surveillance, predictive mapping and tailored communication. ActaTropica, 130, 100107. https://doi.org/10.1016/j.actatropica.2013.09.021Malczewski, J. (1999). GIS and multicriteria decision analysis. John Wiley & Sons.Mamoon, I. Al, Muzahidul-Islam, A. K. M., Baharun, S., Komaki, S., & Ahmed, A.(2015). Architecture and communication protocols for cognitive radio networkenabled hospital. In 2015 9th International Symposium on Medical Information andCommunication Technology (ISMICT) (Vol. 2015May, pp. 170174). IEEE.https://doi.org/10.1109/ISMICT.2015.7107522Mansooreh, M., & Pet-Edwards, J. (1997). Technical Briefing: Making Multiple-Objective Decisions. The Institute of Electrical ve Electronics Engineers Inc., IEEEComputer Society Press, USA.Mazomenos, E. B., Biswas, D., Acharyya, A., Chen, T., Maharatna, K., Rosengarten, J., Curzen, N. (2013). A Low-Complexity ECG Feature Extraction Algorithm forMobile Healthcare Applications. IEEE Journal of Biomedical and HealthInformatics, 17(2), 459469. https://doi.org/10.1109/TITB.2012.2231312Megahed, F. M., & Jones-Farmer, L. A. (2015). Statistical Perspectives on ?Big Data.? InFrontiers in Statistical Quality Control 11 (Vol. 11th ed, pp. 2947). Cham:Springer International Publishing. https://doi.org/10.1007/978-3-319-12355-4_3Meizoso, J. P., Allen, C. J., Ray, J. J., Van Haren, R. M., Teisch, L. F., Baez, X. R., Proctor, K. G. (2016). Evaluation of Miniature Wireless Vital Signs Monitor in aTrauma Intensive Care Unit. Military Medicine, 181(5S), 199204.https://doi.org/10.7205/MILMED-D-15-00162Mendes, J., Simes, H., Rosa, P., Costa, N., Rabado, C., & Pereira, A. (2014). SecureLow-cost Solution for Elders eCardio Surveillance. Procedia Computer Science,27(Dsai 2013), 4656. https://doi.org/10.1016/j.procs.2014.02.007Merin, O., Miskin, I. N., Lin, G., Wiser, I., & Kreiss, Y. (2011). Triage in mass-casualtyevents: the Haitian experience. Prehospital and Disaster Medicine, 26(5), 386390.Merzougui, R. (2015). Adaptation of an Intelligent Mobile Assistant Medical (IMAM) ofthe Heterogeneous Data for the Telemedicine Services: Design and Implementation.Wireless Personal Communications, 84(4), 30913107.Miah, S. J., Hasan, J., & Gammack, J. G. (2017). On-Cloud Healthcare Clinic: An ehealthconsultancy approach for remote communities in a developing country.Telematics and Informatics, 34(1), 311322.https://doi.org/10.1016/j.tele.2016.05.008Miao, F., Cheng, Y., He, Y., He, Q., & Li, Y. (2015). A Wearable Context-Aware ECGMonitoring System Integrated with Built-in Kinematic Sensors of the Smartphone.Sensors, 15(5), 1146511484. https://doi.org/10.3390/s150511465Minelli, M., Chambers, M., & Dhiraj, A. (2013). Big Data Analytics - Emerging BI andAnalitics trends for todays businesses.Minutolo, A., Esposito, M., & De Pietro, G. (2015). Design and validation of a lightweightreasoning system to support remote health monitoring applications.Engineering Applications of Artificial Intelligence, 41, 232248.https://doi.org/10.1016/j.engappai.2015.01.019Mirkovic, J., Bryhni, H., & Ruland, C. M. (2012). A framework for the development ofubiquitous patient support systems. In Pervasive Computing Technologies forHealthcare (PervasiveHealth), 2012 6th International Conference on (pp. 8188).IEEE.Misra, S., & Chatterjee, S. (2014). Social choice considerations in cloud-assisted WBANarchitecture for post-disaster healthcare: Data aggregation and channelization.Information Sciences, 284, 95117. https://doi.org/10.1016/j.ins.2014.05.010Misra, S., & Sarkar, S. (2015). Priority-Based Time-Slot Allocation in Wireless BodyArea Networks During Medical Emergency Situations: An Evolutionary Game-Theoretic Perspective. IEEE Journal of Biomedical and Health Informatics, 19(2),541548. https://doi.org/10.1109/JBHI.2014.2313374Moghadas, A., Jamshidi, M., & Shaderam, M. (2008). Telemedicine in healthcaresystem. In Automation Congress, 2008. WAC 2008. World (pp. 16). IEEE.Mohaghar, A., Fathi, M. R., Zarchi, M. K., & Omidian, A. (1969). A Combined VIKOR Fuzzy AHP Approach to Marketing Strategy Selection. Business Management andStrategy, 3(1). https://doi.org/10.5296/bms.v3i1.957Moore, P., Thomas, A., Qassem, T., Bessis, N., & Hu, B. (2015). Monitoring Patientswith Mental Disorders. In 2015 9th International Conference on Innovative Mobileand Internet Services in Ubiquitous Computing (pp. 6570). IEEE.https://doi.org/10.1109/IMIS.2015.15Moreno, S., Quintero, A., Ochoa, C., Bonfante, M., Villareal, R., & Pestana, J. (2016).Remote monitoring system of vital signs for triage and detection of anomalouspatient states in the emergency room. In 2016 XXI Symposium on Signal Processing,Images and Artificial Vision (STSIVA) (pp. 15). IEEE.https://doi.org/10.1109/STSIVA.2016.7743353Moretti, S., Cical, S., Mazzotti, M., Tralli, V., & Chiani, M. (2014). Content/Context -aware Multiple Camera Selection and Video Adaptation for the Support of m-HealthServices. Procedia Computer Science, 40, 206213.https://doi.org/10.1016/j.procs.2014.12.028Moutacalli, M. T., Marmen, V., Bouzouane, A., & Bouchard, B. (2013). Activity patternmining using temporal relationships in a smart home. In 2013 IEEE Symposium onComputational Intelligence in Healthcare and e-health (CICARE) (pp. 8387).IEEE. https://doi.org/10.1109/CICARE.2013.6583073Mhlbacher, A. C., & Kaczynski, A. (2016). Making good decisions in healthcare withmulti-criteria decision analysis: the use, current research and future development ofMCDA. Applied Health Economics and Health Policy, 14(1), 2940.Nageba, E., Rubel, P., & Fayn, J. (2013). Towards an intelligent exploitation ofheterogeneous and distributed resources in cooperative environments of eHealth.IRBM, 34(1), 7985. https://doi.org/10.1016/j.irbm.2012.12.002Nager, A. L., & Khanna, K. (2009). Emergency department surge: models and practicalimplications. Journal of Trauma and Acute Care Surgery, 67(2), S96S99.Nguyen, T., Khosravi, A., Creighton, D., & Nahavandi, S. (2015). Classification ofhealthcare data using genetic fuzzy logic system and wavelets. Expert Systems withApplications, 42(4), 21842197.Nilsson, H., Nordstrm, E.-M., & hman, K. (2016). Decision support for participatoryforest planning using AHP and TOPSIS. Forests, 7(5), 100.Niswar, M., Ilham, A. A., Palantei, E., Sadjad, R. S., Ahmad, A., Suyuti, A., Adi.(2013). Performance evaluation of ZigBee-based wireless sensor network formonitoring patients pulse status. In 2013 International Conference on InformationTechnology and Electrical Engineering (ICITEE) (pp. 291294). IEEE.https://doi.org/10.1109/ICITEED.2013.6676255Niswar, M., Wijaya, A. S., Ridwan, M., Adnan, A., Ilham, A. A., Sadjad, R. S., & Vogel,A. (2015). The design of wearable medical device for triaging disaster casualties indeveloping countries. In 2015 5th International Conference on Digital InformationProcessing and Communications, ICDIPC 2015 (pp. 207212). IEEE.https://doi.org/10.1109/ICDIPC.2015.7323030Nodhturft, V., Schneider, J. M., Hebert, P., Bradham, D. D., Russo, K., ARNPC, C., Clark, V. (2000). Chronic disease self-management. Nurs Clin North Am, 35, 507518.Okura, T., Enomoto, D., Miyoshi, K., Nagao, T., Kukida, M., Tanino, A., Uemura, H.(2016). The Importance of Walking for Control of Blood Pressure: Proof Using aTelemedicine System. Telemedicine and E-Health, 22(12), 10191023.Oliveira, M., Fontes, D. B. M. M., & Pereira, T. (2013). Multicriteria decision making: acase study in the automobile industry. In International Symposium on OperationalResearch and Applications (ISORAP2013).Opricovic, S. (1998). Multicriteria optimization of civil engineering systems. Faculty ofCivil Engineering, Belgrade, 2(1), 521.Opricovic, S., & Tzeng, G.-H. (2004). Compromise solution by MCDM methods: Acomparative analysis of VIKOR and TOPSIS. European Journal of OperationalResearch, 156(2), 445455. https://doi.org/10.1016/S0377-2217(03)00020-1Organization, W. H. (2003). Surgical care at the district hospital. World HealthOrganization.Ortz, M. A., Cmbita, J. P., Hoz, . lvaro A. D. la, Felice, F. De, & Petrillo, A. (2016).An integrated approach of AHP-DEMATEL methods applied for the selection ofallied hospitals in outpatient service. International Journal of Medical Engineeringand Informatics, 8(2), 87107.Palozzi, G., Binci, D., & Appolloni, A. (2017). E-Health and Co-production: CriticalDrivers for Chronic Diseases Management Models, Strategies, Tools.Patel, S., Park, H., Bonato, P., Chan, L., & Rodgers, M. (2012). A review of wearablesensors and systems with application in rehabilitation. Journal of NeuroEngineeringand Rehabilitation, 9(1), 21. https://doi.org/10.1186/1743-0003-9-21Paulus, A., Meisen, P., Meisen, T., Jeschke, S., Czaplik, M., & Hirsch, F. (2015).AUDIME: Augmented disaster medicine. In 2015 17th International Conference onE-health Networking, Application & Services (HealthCom) (pp. 342345). IEEE.https://doi.org/10.1109/HealthCom.2015.7454522Peleg, M., Shahar, Y., Quaglini, S., Broens, T., Budasu, R., Fung, N., van Schooten,B. (2017). Assessment of a personalized and distributed patient guidance system.International Journal of Medical Informatics, 101, 108130.https://doi.org/10.1016/j.ijmedinf.2017.02.010Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014). Sensing as aservice model for smart cities supported by Internet of Things. Transactions onEmerging Telecommunications Technologies, 25(1), 8193.https://doi.org/10.1002/ett.2704Petrovic-Lazarevic, S., & Abraham, A. (2004). Hybrid fuzzy-linear programmingapproach for multi criteria decision making problems. ArXiv Preprint Cs/0405019.Puri, T., Challa, R. K., & Sehgal, N. K. (2015). Energy efficient QoS aware MAC layertime slot allocation scheme for WBASN. In 2015 International Conference onAdvances in Computing, Communications and Informatics (ICACCI) (pp. 966972).IEEE. https://doi.org/10.1109/ICACCI.2015.7275736Qader, M. A., Zaidan, B. B., Zaidan, A. A., Ali, S. K., Kamaluddin, M. A., & Radzi, W.B. (2017). A methodology for football players selection problem based on multimeasurementscriteria analysis. Measurement: Journal of the InternationalMeasurement Confederation, 111, 3850.https://doi.org/10.1016/j.measurement.2017.07.024Radhakrishnan, S., Duvvuru, A., & Kamarthi, S. V. (2014). Investigating Discrete EventSimulation Method to Assess the Effectiveness of Wearable Health MonitoringDevices. Procedia Economics and Finance, 11(14), 838856.https://doi.org/10.1016/S2212-5671(14)00248-2Rae Hyun Kim, Pyung Soo Kim, & Jeong Gon Kim. (2015). An effect of delay reducedMAC protocol for WBAN based medical signal monitoring. In 2015 IEEE PacificRim Conference on Communications, Computers and Signal Processing (PACRIM)(Vol. 2015Novem, pp. 434437). IEEE.https://doi.org/10.1109/PACRIM.2015.7334876Rahman, H., Begum, S., & Ahmed, M. U. (2016). Ins and Outs of Big Data : A Review,1819.Rahmani, A. M., Gia, T. N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., &Liljeberg, P. (2017). Exploiting smart e-Health gateways at the edge of healthcareInternet-of-Things: A fog computing approach. Future Generation ComputerSystems, 78, 641658. https://doi.org/10.1016/j.future.2017.02.014Raikhelkar, J., & Raikhelkar, J. K. (2015). The Impact of Telemedicine in CardiacCritical Care. Critical Care Clinics, 31(2), 305317.https://doi.org/10.1016/j.ccc.2014.12.008Rajkumar, R., & Sriman Narayana Iyengar, N. C. (2013). Dynamic Integration of MobileJXTA with Cloud Computing for Emergency Rural Public Health Care. OsongPublic Health and Research Perspectives, 4(5), 255264.https://doi.org/10.1016/j.phrp.2013.09.004Ren, J., Wu, G., Li, X., Pirozmand, P., & Obaidat, M. S. (2015). Probabilistic responsetimeanalysis for real-time systems in body area sensor networks. InternationalJournal of Communication Systems, 28(16), 21452166.https://doi.org/10.1002/dac.2990Renner, A., Williams, R., McCartney, M., Harmon, B., Boswell, L., Ganapathy, S., Weinle, N. (2014). RIPPLE: Scalable medical telemetry system for supportingcombat rescue. In NAECON 2014 - IEEE National Aerospace and ElectronicsConference (Vol. 2015Febru, pp. 228232). IEEE.https://doi.org/10.1109/NAECON.2014.7045807Rezaee, A. A., Yaghmaee, M. H., & Rahmani, A. M. (2014). Optimized CongestionManagement Protocol for Healthcare Wireless Sensor Networks. Wireless PersonalCommunications, 75(1), 1134. https://doi.org/10.1007/s11277-013-1337-zRezaee, A. A., Yaghmaee, M. H., Rahmani, A. M., & Mohajerzadeh, A. H. (2014a).HOCA: Healthcare aware optimized congestion avoidance and control protocol forwireless sensor networks. Journal of Network and Computer Applications, 37(1),216228. https://doi.org/10.1016/j.jnca.2013.02.014Rezaee, A. A., Yaghmaee, M. H., Rahmani, A. M., & Mohajerzadeh, A. H. (2014b).HOCA: Healthcare Aware Optimized Congestion Avoidance and control protocolfor wireless sensor networks. Journal of Network and Computer Applications, 37,216228.Rezvani, S., & Ghorashi, S. A. (2013). Context aware and channel-based resourceallocation for wireless body area networks. IET Wireless Sensor Systems, 3(1), 1625. https://doi.org/10.1049/iet-wss.2012.0100Ritchie, C., & Lai, R. (2005). A systematic review of the scientific evidence for theefficacy of a palliative care approach in dementia A systematic review of thescientific evidence. International Psychogeriatrics, 17(November 2014), 3140.https://doi.org/10.1017/S1041610205001018Rn, A. B., Nurse, C., Rn, D. E. C., & Dean, A. (2013). Reducing uncertainty in triagingmental health presentations : Examining triage decision-making. INTERNATIONALEMERGENCY NURSING, 15. https://doi.org/10.1016/j.ienj.2013.01.005Rocha, A., Martins, A., Freire, J. C., Kamel Boulos, M. N., Vicente, M. E., Feld, R., Rodr??guez-Molinero, A. (2013). Innovations in health care services: TheCAALYX system. International Journal of Medical Informatics, 82(11), 114.https://doi.org/10.1016/j.ijmedinf.2011.03.003Rodrigues, E. M. G., Godina, R., Cabrita, C. M. P., & Catalo, J. P. S. (2017).Biomedical Signal Processing and Control Experimental low cost reflective typeoximeter for wearable health systems. Biomedical Signal Processing and Control,31, 419433. https://doi.org/10.1016/j.bspc.2016.09.013Rodriguez, D., Heuer, S., Guerra, A., Stork, W., Weber, B., & Eichler, M. (2014).Towards automatic sensor-based triage for individual remote monitoring duringmass casualty incidents. In 2014 IEEE International Conference on Bioinformaticsand Biomedicine (BIBM) (pp. 544551). IEEE.https://doi.org/10.1109/BIBM.2014.6999217Rogove, H. J., McArthur, D., Demaerschalk, B. M., & Vespa, P. M. (2012). Barriers totelemedicine: survey of current users in acute care units. Telemedicine and EHealth,18(1), 4853.Ru Kong, Chen, C., Yu, W., Yang, B., & Guan, X. (2013). Data priority based slotallocation for Wireless Body Area Networks. In 2013 International Conference onWireless Communications and Signal Processing (pp. 16). IEEE.https://doi.org/10.1109/WCSP.2013.6677273Rubio, . J., Trigo, J. D., Alesanco, ., Serrano, L., & Garca, J. (2016). Analysis ofISO/IEEE 11073 built-in security and its potential IHE-based extensibility. Journalof Biomedical Informatics, 60, 270285. https://doi.org/10.1016/j.jbi.2016.02.006Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal ofMathematical Psychology, 15(3), 234281.Saaty, T. L. (1980). The Analytic Hierarchy Process, New York: McGrew Hill.International, Translated to Russian, Portuguesses and Chinese, Revised Edition,Paperback (1996, 2000), Pittsburgh: RWS Publications.Saaty, T. L., & Ozdemir, M. S. (2003). Why the magic number seven plus or minus two.Mathematical and Computer Modelling, 38(34), 233244.Sakanushi, K., Hieda, T., Shiraishi, T., Ode, Y., Takeuchi, Y., Imai, M., Tanaka, H.(2013). Electronic triage system for continuously monitoring casualties at disasterscenes. Journal of Ambient Intelligence and Humanized Computing, 4(5), 547558.https://doi.org/10.1007/s12652-012-0130-2Sakr, S., & Elgammal, A. (2016). Towards a Comprehensive Data Analytics Frameworkfor Smart Healthcare Services. Big Data Research, 4(May), 4458.https://doi.org/10.1016/j.bdr.2016.05.002Saksrisathaporn, K., Bouras, A., Reeveerakul, N., & Charles, A. (2016). Application of adecision model by using an integration of AHP and TOPSIS approaches withinhumanitarian operation life cycle. International Journal of Information Technology& Decision Making, 15(04), 887918.Sakuragui, R. R. M., Rebelo, M. S., Gutierrez, M. A., Nslund, M., & Hkansson, P.(2013). Mobile health in emerging countries : A survey of research initiatives inBrazil. International Journal of Medical Informatics, 82(5), 283298.https://doi.org/10.1016/j.ijmedinf.2013.01.003Saleem, K., Derhab, A., Al-Muhtadi, J., & Shahzad, B. (2015). Human-oriented design ofsecure Machine-to-Machine communication system for e-Healthcare society.Computers in Human Behavior, 51, 977985.https://doi.org/10.1016/j.chb.2014.10.010Salman, O. H., Rasid, M. F. A., Saripan, M. I., & Subramaniam, S. K. (2014). Multisourcesdata fusion framework for remote triage prioritization in telehealth. Journalof Medical Systems, 38(9), 103. https://doi.org/10.1007/s10916-014-0103-4Salman, O. H., Rasid, M. F. A., Saripan, M. I., & Subramaniam, S. K. (2014). Multi-Sources Data Fusion Framework for Remote Triage Prioritization in Telehealth.Journal of Medical Systems, 38(9), 103. https://doi.org/10.1007/s10916-014-0103-4Salman, O. H., Zaidan, A. A., Zaidan, B. B., Naserkalid, & Hashim, M. (2017). NovelMethodology for Triage and Prioritizing Using ?Big Data? Patients with ChronicHeart Diseases Through Telemedicine Environmental. International Journal ofInformation Technology & Decision Making, 16(05), 12111245.https://doi.org/10.1142/S0219622017500225Sanders, T. H., Devergnas, A., Wichmann, T., & Clements, M. A. (2013). Remotesmartphone monitoring for management of Parkinsons Disease. In Proceedings ofthe 6th International Conference on PErvasive Technologies Related to AssistiveEnvironments (p. 42). ACM.Santos, J. R. B. Dos, Blard, G., Oliveira, A. S. R., & Carvalho, N. B. De. (2015).Wireless Sensor Tag and Network for Improved Clinical Triage. In 2015 EuromicroConference on Digital System Design (pp. 399406). IEEE.https://doi.org/10.1109/DSD.2015.66Sarkar, P., & Sinha, D. (2014). An approach to continuous pervasive care of remotepatients based on priority based assignment of nurse. In IFIP InternationalConference on Computer Information Systems and Industrial Management (pp.327338). Springer.Sebillo, M., Tortora, G., Tucci, M., Vitiello, G., Ginige, A., & Di Giovanni, P. (2015).Combining personal diaries with territorial intelligence to empower diabeticpatients. Journal of Visual Languages & Computing, 29, 114.https://doi.org/10.1016/j.jvlc.2015.03.002Seising, R., & Tabacchi, M. (2013). Fuzziness and Medicine: Philosophical Reflectionsand Application Systems in Health Care. (R. Seising & M. E. Tabacchi, Eds.) (Vol.302). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-36527-0Sene, A., Kamsu-foguem, B., & Rumeau, P. (2015). Telemedicine framework using casebased.Computer Methods and Programs in Biomedicine, 121(1), 2135.https://doi.org/10.1016/j.cmpb.2015.04.012Services, C. for M. and M. (2015). The Affordable Care Act: helping providers helppatients: a menu of options for improving care.Sevin, A., Bayilmis, C., & Kirbas, I. (2016). Design and implementation of a new qualityof service-aware cross-layer medium access protocol for wireless body areanetworks. Computers & Electrical Engineering, 56, 145156.https://doi.org/10.1016/j.compeleceng.2016.02.003Shah, M. A., Kim, J., Khadra, M. H., & Feng, D. (2014). Home Area Network forOptimizing Telehealth Services- Empirical Simulation Analysis. 36th AnnualInternational Conference of the IEEE Engineering in Medicince and BiologySociety, 13701373. https://doi.org/10.1109/EMBC.2014.6943854Sherekar, V., Tatikonda, M., & Student, M. (2016). Impact of Factor Affecting on LabourProductivity in Construction Projects by AHP Method. International Journal ofEngineering Science and Computing, 6.Singh, S., Dolan, J. G., & Centor, R. M. (2006). Optimal management of adults withpharyngitisa multi-criteria decision analysis. BMC Medical Informatics and Decision Making, 6(1), 14.Smith, J., Cook, A., & Packer, C. (2010). Evaluation criteria to assess the value ofidentification sources for horizon scanning. International Journal of TechnologyAssessment in Health Care, 26(3), 348353.Sneha, S., & Varshney, U. (2013). A framework for enabling patient monitoring viamobile ad hoc network. Decision Support Systems, 55(1), 218234.https://doi.org/10.1016/j.dss.2013.01.024Sockolow, P. S., Bowles, K. H., Adelsberger, M. C., Chittams, J. L., & Liao, C. (2014).Impact of homecare electronic health record on timeliness of clinical documentation,reimbursement, and patient outcomes. Applied Clinical Informatics, 5(2), 445.Sparks, R., Celler, B., Okugami, C., Jayasena, R., & Varnfield, M. (2016). TelehealthMonitoring of Patients in the Community. Journal of Intelligent Systems, 25(1), 3753. https://doi.org/10.1515/jisys-2014-0123Sudha, G. F., Karthik, S., & Kumar, N. S. (2014). Activity aware energy efficient prior itybased multi patient monitoring adaptive system for body sensor networks.Technology and Health Care : Official Journal of the European Society forEngineering and Medicine, 22(2), 16777. https://doi.org/10.3233/THC-140782Sun, J., Guo, Y., Wang, X., & Zeng, Q. (2016). mHealth For Aging China: Opportunitiesand Challenges. Aging and Disease, 7(1), 53.https://doi.org/10.14336/AD.2015.1011Sung, W., & Chang, K. (2014). Health parameter monitoring via a novel wireless system.Applied Soft Computing, 22, 667680. https://doi.org/10.1016/j.asoc.2014.04.036Tamura, T., Maeno, S., Hattori, T., Kimura, Y., Kimura, Y., Yoshida, M., & Minato, K.(2014). Assessment of participant compliance with a Web-based home healthcaresystem for promoting specific health checkups. Biocybernetics and BiomedicalEngineering, 34(1), 6369. https://doi.org/10.1016/j.bbe.2013.12.001Tawfik, H., & Anya, O. (2015). Evaluating practice-centered awareness in crossboundarytelehealth decision support systems. Telematics and Informatics, 32(3),486503. https://doi.org/10.1016/j.tele.2014.11.002Tegegne, T., & (Theo) van der Weide, T. P. (2014). Enriching queries with userpreferences in healthcare. Information Processing & Management, 50(4), 599620.https://doi.org/10.1016/j.ipm.2014.03.004Teijeiro, T., Flix, P., Presedo, J., & Zamarrn, C. (2013). An open platform for theprotocolization of home medical supervision. Expert Systems with Applications,40(7), 26072614. https://doi.org/10.1016/j.eswa.2012.11.001Thokala, P., Devlin, N., Marsh, K., Baltussen, R., Boysen, M., Kalo, Z., Watkins, J.(2016). Multiple criteria decision analysis for health care decision makinganintroduction: report 1 of the ISPOR MCDA Emerging Good Practices Task Force.Value in Health, 19(1), 113.Topol, E. J. (2015). The patient will see you now: the future of medicine is in your hands.Tantor Media. https://doi.org/http://dx.doi.org/10.4258/hir.2015.21.4.321Touati, F., & Tabish, R. (2013). U-healthcare system: State-of-the-art review andchallenges. Journal of Medical Systems, 37(3), 9949.https://doi.org/10.1007/s10916-013-9949-0Triantaphyllou, E. (2000). Multi-criteria Decision Making Methods: A ComparativeStudy. Multi-criteria decision making methods: A comparative study (Vol. 44).Boston, MA: Springer US. https://doi.org/10.1007/978-1-4757-3157-6Triantaphyllou, E., Shu, B., Sanchez, S. N., & Ray, T. (1998). Multi-criteria decisionmaking: an operations research approach. Encyclopedia of Electrical andElectronics Engineering, 15(1998), 175186.Ullah, F., Khelil, A., Sheikh, A. A., Felemban, E., & Bojan, H. M. A. (2013). Towardsautomated self-tagging in emergency health cases. In 2013 IEEE 15th InternationalConference on e-Health Networking, Applications and Services (Healthcom 2013)(pp. 658663). IEEE. https://doi.org/10.1109/HealthCom.2013.6720758Urovi, V., Jimenez-del-Toro, O., Dubosson, F., Ruiz Torres, A., & Schumacher, M. I.(2017). COMPOSE: Using temporal patterns for interpreting wearable sensor datawith computer interpretable guidelines. Computers in Biology and Medicine, 81, 2431. https://doi.org/10.1016/j.compbiomed.2016.11.015Vaidehi, V., Vardhini, M., Yogeshwaran, H., Inbasagar, G., Bhargavi, R., & Hemalatha,C. S. (2013). Agent Based Health Monitoring of Elderly People in IndoorEnvironments Using Wireless Sensor Networks. Procedia Computer Science,19(Ant), 6471. https://doi.org/10.1016/j.procs.2013.06.014van Dyk, L. (2014). A review of telehealth service implementation frameworks.International Journal of Environmental Research and Public Health, 11(2), 12791298. https://doi.org/10.3390/ijerph110201279van Til, J. A., Renzenbrink, G. J., Dolan, J. G., & IJzerman, M. J. (2008). The use of theanalytic hierarchy process to aid decision making in acquired equinovarusdeformity. Archives of Physical Medicine and Rehabilitation, 89(3), 457462.Varshney, U. (2014). A model for improving quality of decisions in mobile health.Decision Support Systems, 62, 6677. https://doi.org/10.1016/j.dss.2014.03.005Villalonga, C., Pomares, H., Rojas, I., & Banos, O. (2017). MIMU-Wear: Ontologybasedsensor selection for real-world wearable activity recognition.Neurocomputing, 250(2017), 76100. https://doi.org/10.1016/j.neucom.2016.09.125Villarreal, V., Fontecha, J., Hervas, R., & Bravo, J. (2014). Mobile and ubiquitousarchitecture for the medical control of chronic diseases through the use of intelligentdevices: Using the architecture for patients with diabetes. Future GenerationComputer Systems, 34, 161175. https://doi.org/10.1016/j.future.2013.12.013Wallis, L. A., & Carley, S. (2006). Comparison of paediatric major incident primarytriage tools. Emergency Medicine Journal, 23(6), 475478.Wang, J., Qiu, M., & Guo, B. (2017). Enabling real-time information service ontelehealth system over cloud-based big data platform. Journal of SystemsArchitecture, 72, 6979. https://doi.org/10.1016/j.sysarc.2016.05.003Wang, L., & Alexander, C. A. (2015). Big Data in Medical Applications and Health Care.American Medical Journal, 6(1), 18. https://doi.org/10.3844/amjsp.2015.1.8Westergren, H., Ferm, M., & Hggstrm, P. (2014). First evaluation of the paediatricversion of the Swedish rapid emergency triage and treatment system shows goodreliability. Acta Paediatrica, 103(3), 305308.Widgren, B. R., & Jourak, M. (2011). Medical Emergency Triage and Treatment System(METTS): A New Protocol in Primary Triage and Secondary Priority Decision inEmergency Medicine. The Journal of Emergency Medicine, 40(6), 623628.https://doi.org/10.1016/j.jemermed.2008.04.003Wind, Y., & Saaty, T. L. (1980). Marketing applications of the analytic hierarchyprocess. Management Science, 26(7), 641658.Winkler, S., Schieber, M., Lcke, S., Heinze, P., Schweizer, T., Wegertseder, D., Braecklein, M. (2011). A new telemonitoring system intended for chronic heartfailure patients using mobile telephone technologyfeasibility study. InternationalJournal of Cardiology, 153(1), 5558.Wiseman, D. B., Ellenbogen, R., & Shaffrey, C. I. (2002). Triage for the neurosurgeon.Neurosurgical Focus, 12(3), E5. https://doi.org/120305 [pii]Wizig, L. H. (2004, May 11). Method and system for providing a user-selected healthcareservices package and healthcare services panel customized based on a usersselections. Google Patents.Wolfe, P. J. (2013). Making sense of big data. Proceedings of the National Academy ofSciences, 110(45), 1803118032. https://doi.org/10.1073/pnas.1317797110Wyte-Lake, T., Claver, M., & Dobalian, A. (2016). Assessing Patients DisasterPreparedness in Home-Based Primary Care. Gerontology, 62(3), 263274.Xiong, W., Bair, A., Sandrock, C., Wang, S., Siddiqui, J., & Hupert, N. (2012).Implementing telemedicine in medical emergency response: concept of operation fora regional telemedicine hub. Journal of Medical Systems, 36(3), 16511660.Yas, Q. M., Zadain, A. A., Zaidan, B. B., Lakulu, M. B., & Rahmatullah, B. (2017).Towards on develop a framework for the evaluation and benchmarking of skindetectors based on artificial intelligent models using multi-criteria decision-makingtechniques. International Journal of Pattern Recognition and Artificial Intelligence,31(03), 1759002.Yas, Q. M., Zaidan, A. A., Zaidan, B. B., Rahmatullah, B., & Abdul Karim, H. (2018).Comprehensive insights into evaluation and benchmarking of real-time skindetectors: Review, open issues & challenges, and recommended solutions.Measurement, 114, 243260. https://doi.org/10.1016/j.measurement.2017.09.027Yeguas, V., & Casado, R. (2014). Big data issues in computational chemistry. InProceedings - 2014 International Conference on Future Internet of Things andCloud, FiCloud 2014 (pp. 389392). https://doi.org/10.1109/FiCloud.2014.69Yi, C., Alfa, A. S., & Cai, J. (2016). An Incentive-Compatible Mechanism forTransmission Scheduling of Delay-Sensitive Medical Packets in E-Health Networks.IEEE Transactions on Mobile Computing, 15(10), 24242436.https://doi.org/10.1109/TMC.2015.2500241Yi, C., Zhao, Z., Cai, J., Lobato de Faria, R., & (Michael) Zhang, G. (2016). Priorityaware pricing-based capacity sharing scheme for beyond-wireless body areanetworks. Computer Networks, 98, 2943.https://doi.org/10.1016/j.comnet.2016.01.010Yoon, K. P., & Hwang, C.-L. (1995). Multiple attribute decision making: an introduction(Vol. 104). Sage publications.Yuan, X., Li, C., Song, Y., Yang, L., & Ullah, S. (2015). On energy-saving in ehealthcare:A directional MAC protocol for WBAN. In 2015 IEEE GlobecomWorkshops, GC Wkshps 2015 - Proceedings.https://doi.org/10.1109/GLOCOMW.2015.7414214Zachariasse, J. M., Seiger, N., Rood, P. P. M., Alves, C. F., Freitas, P., Smit, F. J., Moll, H. A. (2017). Validity of the Manchester triage system in emergency care: Aprospective observational study. PLoS ONE, 12(2), 114.https://doi.org/10.1371/journal.pone.0170811Zaidan, A. A., Zaidan, B. B., Al-Haiqi, A., Kiah, M. L. M., Hussain, M., & Abdulnabi,M. (2015). Evaluation and selection of open-source EMR software packages basedon integrated AHP and TOPSIS. Journal of Biomedical Informatics, 53, 390404.https://doi.org/10.1016/j.jbi.2014.11.012Zaidan, A. A., Zaidan, B. B., Albahri, O. S., Alsalem, M. A., Albahri, A. S., Yas, Q. M.,& Hashim, M. (2018). A review on smartphone skin cancer diagnosis apps inevaluation and benchmarking: coherent taxonomy, open issues and recommendationpathway solution. Health and Technology, 8(4), 223238.https://doi.org/10.1007/s12553-018-0223-9Zaidan, A. A., Zaidan, B. B., Kadhem, Z., Larbani, M., Lakulu, M. B., & Hashim, M.(2015). Challenges, Alternatives, and Paths to Sustainability: Better Public HealthPromotion Using Social Networking Pages as Key Tools. Journal of MedicalSystems, 39(2), 7. https://doi.org/10.1007/s10916-015-0201-yZaidan, A. A., Zaidan, B. B., Qahtan, M. Y., Albahri, O. S., Albahri, A. S., Alaa, M., Lim, C. K. (2018). A survey on communication components for IoT-basedtechnologies in smart homes. Telecommunication Systems, 69(1), 125.https://doi.org/10.1007/s11235-018-0430-8Zaidan, B. B., & Zaidan, A. A. (2017). Software and hardware FPGA-based digitalwatermarking and steganography approaches: Toward new methodology forevaluation and benchmarking using multi-criteria decision-making techniques.Journal of Circuits, Systems and Computers, 26(07), 1750116.Zaidan, B. B., & Zaidan, A. A. (2018). Comparative study on the evaluation andbenchmarking information hiding approaches based multi-measurement analysisusing TOPSIS method with different normalisation, separation and contexttechniques. Measurement, 117, 277294.Zaidan, B. B., Zaidan, A. A., Abdul Karim, H., & Ahmad, N. N. (2017). A new approachbased on multi-dimensional evaluation and benchmarking for data hidingtechniques. International Journal of Information Technology & Decision Making,142.Zanjal, S. V., & Talmale, G. R. (2016). Medicine Reminder and Monitoring System forSecure Health Using IOT. Procedia Computer Science, 78(3), 471476.https://doi.org/10.1016/j.procs.2016.02.090Zarabzadeh, A., ODonoghue, J., OConnor, Y., OKane, T., Woodworth, S., Gallagher,J., & OConnor, S. (2013). Variation in health care providers perceptions: decisionmaking based on patient vital signs. Journal of Decision Systems, 22(3), 168189.https://doi.org/10.1080/12460125.2013.817063Zhang, J., Goode, K. M., Cuddihy, P. E., & Cleland, J. G. F. (2009). Predictinghospitalization due to worsening heart failure using daily weight measurement:analysis of the Trans?European Network?Home?Care Management System (TENHMS)study. European Journal of Heart Failure, 11(4), 420427.Zhang, K., Liang, X., Baura, M., Lu, R., & Shen, X. (Sherman). (2014). PHDA: Apriority based health data aggregation with privacy preservation for cloud assistedWBANs. Information Sciences, 284, 130141.https://doi.org/10.1016/j.ins.2014.06.011Zhang Yi, Wang Zhu-juan, Li Jin, Wang Jun, Xiao Shi, Xia Ge, & Fang Hao. (2015).Emergency treatment in smart terminal-based e-healthcare networks. In 2015 4thInternational Conference on Computer Science and Network Technology (ICCSNT)(pp. 11781181). IEEE. https://doi.org/10.1109/ICCSNT.2015.7490943Zhao, Y., & Kerkhoff, H. G. (2014). Design of an Embedded Health MonitoringInfrastructure for Accessing Multi-processor SoC Degradation. In 2014 17thEuromicro Conference on Digital System Design (pp. 154160). IEEE.https://doi.org/10.1109/DSD.2014.80Zhu, G., Hu, J., Qi, J., Gu, C., & Peng, Y. (2015). An integrated AHP and VIKOR fordesign concept evaluation based on rough number. Advanced EngineeringInformatics, 29(3), 408418. https://doi.org/10.1016/j.aei.2015.01.010Zionts, S. (1979). MCDMIf not a Roman numeral, then what? Interfaces, 9(4), 94101.

Multi-criteria decision-making analysis for hospital selection in the telemedicine environment

Similar Items