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Home Healthcare Matching Service System Using the Internet of Things

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Abstract

Home healthcare services enable patients to live in an environment and amongst people that they are familiar with while receiving the healthcare that they need. To provide such an arrangement, readings from healthcare devices are collected and analyzed on a regular basis to determine healthcare services needed by patients, and then the services needed are matched with a limited number of healthcare professionals that are capable of providing the services needed. To meet these requirements, this work presents a home healthcare matching service system that enables patients to feel that the system is in charge of their healthcare while licensing requirements, legal requirements, and travel schedule restrictions of the healthcare professionals are met. Rather than just focusing on satisfying needs of healthcare providers or professionals, this system takes a balanced approach by satisfying preferences of the patients. In particular, patients are able to prioritize their specific preferences and the system will try to satisfy them as fully as possible rather than ignoring the patient preferences in its entirety when a feasible schedule for healthcare professionals cannot be scheduled while meeting patient preferences in its entirety.

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References

  1. Gokalp H, Clarke M (2013) Monitoring activities of daily living of the elderly and the potential for its use in telecare and telehealth: a review. Telemed e-Health 19(12):910–923

    Article  Google Scholar 

  2. Darkins A, Ryan P, Kobb R, Foster L, Edmonson E, Wakefield B, Lancaster AE (2008) Care coordination/home telehealth: the systematic implementation of health informatics, home telehealth, and disease management to support the care of veteran patients with chronic conditions. Telemed e-Health 14(10):1118–1126

    Article  Google Scholar 

  3. Du G, Sun C (2015) Location planning problem of service centers for sustainable home healthcare: evidence from the empirical analysis of shanghai. Sustainability 7(12):15812–15832

    Article  Google Scholar 

  4. Bai H, Atiquzzaman M, Lilija D (2005) Wirelss sensor network for aircraft health monitoring. China Commun 2(1):70–77

    Google Scholar 

  5. Lin CC, Deng DJ, Lu LY (2017) Many-objective sensor selection in IoT systems. IEEE Wirel Commun Mag 24(3):40–47

    Article  Google Scholar 

  6. Woznowski P et al (2015) A multi-modal sensor infrastructure for healthcare in a residential environment. In: Proceedings of 2015 IEEE International Conference on Communication Workshop (ICCW), IEEE Press, p 271–277

  7. Lee CO, Lee M, Han D, Jung S, Cho J (2008) A framework for personalized healthcare service recommendation. In: Proceedings of 10th International Conference on e-health Networking, Applications and Services (HealthCom 2008), IEEE Press, p 90–95

  8. Duque PM, Castro M, Sörensen K, Goos P (2015) Home care service planning. The case of Landelijke Thuiszorg. Eur J Oper Res 243(1):292–301

    Article  MATH  Google Scholar 

  9. Mısır M, Smet P, Berghe GV (2015) An analysis of generalised heuristics for vehicle routing and personnel rostering problems. J Oper Res Soc 66(5):858–870

    Article  Google Scholar 

  10. Yuan B, Liu R, Jiang Z (2015) A branch-and-price algorithm for the home health care scheduling and routing problem with stochastic service times and skill requirements. Int J Prod Res 53(24):7450–7464

    Article  Google Scholar 

  11. Hiermann G, Prandtstetter M, Rendl A, Puchinger J, Raidl GR (2015) Metaheuristics for solving a multimodal home-healthcare scheduling problem. CEJOR 23(1):89–113

    Article  MathSciNet  MATH  Google Scholar 

  12. Braekers K, Hartl RF, Parragh SN, Tricoire F (2016) A bi-objective home care scheduling problem: analyzing the trade-off between costs and client inconvenience. Eur J Oper Res 248(2):428–443

    Article  MathSciNet  MATH  Google Scholar 

  13. Cappanera P, Scutellà MG (2014) Joint assignment, scheduling, and routing models to home care optimization: a pattern-based approach. Transp Sci 49(4):830–852

    Article  Google Scholar 

  14. Milburn AB, Spicer J (2013) Multi-objective home health nurse routing with remote monitoring devices. Int J Plan Sched 1(4):242–263

    Article  Google Scholar 

  15. Depari A, Flammini A, Rinaldi S, Vezzoli A (2013) Multi-sensor system with Bluetooth connectivity for non-invasive measurements of human body physical parameters. Sensors Actuators A Phys 202:147–154

    Article  Google Scholar 

  16. Hassanalieragh M, Page A, Soyata T, Sharma G, Aktas M, Mateos G, Andreescu S (2015) Health monitoring and management using Internet-of-Things (IoT) sensing with cloud-based processing: Opportunities and challenges. In: Proceedings of 2015 IEEE International Conference on Services Computing (SCC), IEEE Press, p 285–292

  17. Ricci F, Rokach L, Shapira B (2011) Introduction to recommender systems handbook. In: Rokach L, Shapira B, Kantor P (eds) Recommender Systems Handbook. Springer, Boston, pp 1–35

    Chapter  Google Scholar 

  18. Wirnitzer J, Heckmann I, Meyer A, Nickel S (2016) Patient-based nurse rostering in home care. Oper Res Health Care 8:91–102

    Article  Google Scholar 

  19. Saaty TL (1980) The analytic hierarchy process: Planning, priority setting, resource allocation. McGraw-Hill, NYC, USA

    MATH  Google Scholar 

  20. Liao CN, Kao HP (2010) Supplier selection model using Taguchi loss function, analytical hierarchy process and multi-choice goal programming. Comput Ind Eng 58(4):571–577

    Article  Google Scholar 

  21. Algethami H, Pinheiro RL, Landa-Silva D (2016) A genetic algorithm for a workforce scheduling and routing problem. In: Proceedings of 2016 IEEE Congress on Evolutionary Computation (CEC 2016), IEEE Press

  22. Lin CC, Deng DJ, Wang SB (2016) Extending the lifetime of dynamic underwater acoustic sensor networks using multi-population harmony search algorithm. IEEE Syst J 16(10):4034–4042

    Google Scholar 

  23. Dhahri A, Zidi K, Ghedira K (2015) A variable neighborhood search for the vehicle routing problem with time windows and preventive maintenance activities. Electron Notes Discrete Math 47:229–236

    Article  MathSciNet  MATH  Google Scholar 

  24. Tozlu B, Daldal R, Ünlüyurt T, Çatay B (2015) Crew constrained home care routing problem with time windows. In: Proceedings of 2015 IEEE Symposium Series on Computational Intelligence, IEEE Press, p 1751–1757

  25. Yalçındağ S, Matta A, Şahin E, Shanthikumar JG (2016) The patient assignment problem in home health care: using a data-driven method to estimate the travel times of care givers. Flex Serv Manuf J 28(1–2):304–335

    Google Scholar 

  26. Redjem R, Marcon E (2016) Operations management in the home care services: a heuristic for the caregivers’ routing problem. Flex Serv Manuf J 28(1–2):280–303

    Article  Google Scholar 

  27. Siekkinen M, Hiienkari M, Nurminen J K, Nieminen J (2012) How low energy is bluetooth low energy? Comparative measurements with Zigbee/802.15.4. In: Proceedings of 2012 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), IEEE Press, p 232–237

  28. Wang X, Sheng MJ, Lou YY, Shih YY, Chiang M (2016) Internet of things session management over LTE—balancing signal load, power, and delay. IEEE Internet Things J 3(3):339–353

    Article  Google Scholar 

  29. Lien SY, Hung SC, Deng DJ, Wang YJ (2017) Optimum ultra-reliable and low latency communications in 5G new radio. Mobile Netw Appl. https://doi.org/10.1007/s11036-017-0967-x

  30. Deng DJ, Lien SY, Lin CC, Hung SC, Chen WB (2017) Latency control in software defined cloud/edge vehicular networking. IEEE Commun Mag 55(8):87–93

    Article  Google Scholar 

  31. Lin CC, Chin HH, Deng DJ (2014) Dynamic multiservice load balancing in cloud-based multimedia system. IEEE Syst J 8(1):225–234

    Article  Google Scholar 

  32. Outcome and Assessment Information Set (OASIS) - Centers for Medicare and Medicaid Services. Available at: https://www.cms.gov/oasis

  33. Bard JF, Shao Y, Jarrah AI (2014) A sequential GRASP for the therapist routing and scheduling problem. J Sched 17(2):109–133

    Article  MathSciNet  MATH  Google Scholar 

  34. Lin CC, Hung LP, Liu WY, Tsai MC (2018) Jointly rostering, routing, and rerostering for home health care services: a harmony search approach with genetic, saturation, inheritance, and immigrant schemes. Comput Ind Eng 115:151–166

    Article  Google Scholar 

  35. Deng DJ, Lin YP, Yang X, Zhu J, Li YB, Chen KC (2017) IEEE 802.11ax: highly efficient WLANs for intelligent information infrastructure. IEEE Commun Mag 55(12):52–59

    Article  Google Scholar 

  36. Deng DJ, Chen KC, Cheng RS (2014) IEEE 802.11ax: Next generation wireless local area networks. In: Proceedings of 10th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (Qshine 2015)

  37. Deng DJ, Yen HC (2005) Quality-of-service provision system for multimedia transmission in IEEE 802.11 wireless LANs. IEEE J Sel Area Commun 23(6):1240–1252

    Article  Google Scholar 

  38. Deng DJ, Lien SY, Lee J, Chen KC (2016) On quality-of-service provisioning in IEEE 802.11ax WLANs. IEEE Access 4:6086–6104

    Article  Google Scholar 

  39. Hang Y, Deng DJ, Chen KC (2017) Performance analysis of IEEE 802.11ax UL OFDMA-based random access mechanism. In: Proceedings of IEEE Global Communications Conference (IEEE GLOBECOM 2017)

  40. Deng DJ, Ke CH, Chen HH, Huang YM (2008) Contention window optimization for IEEE 802.11 DCF access control. IEEE Trans Wirel Commun 7(12):5129–5135

    Article  Google Scholar 

  41. Deng DJ, Chang RS (1999) A priority scheme for IEEE 802.11 DCF access method. IEICE Trans Commun E82-B(1):96–102

    Google Scholar 

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Acknowledgements

The authors thank the anonymous referees for comments that improved the content as well as the presentation of this paper. This work has been supported in part by MOST 106-2221-E-009-101-MY3.

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Authors and Affiliations

  1. Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, 300, Taiwan

    Tzong-Shyan Lin, Pei-Yu Liu & Chun-Cheng Lin

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  1. Tzong-Shyan Lin
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  3. Chun-Cheng Lin
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Correspondence to Chun-Cheng Lin.

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Lin, TS., Liu, PY. & Lin, CC. Home Healthcare Matching Service System Using the Internet of Things. Mobile Netw Appl 24, 736–747 (2019). https://doi.org/10.1007/s11036-018-1087-y

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  • DOI: https://doi.org/10.1007/s11036-018-1087-y

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