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Journal of Intelligent & Robotic Systems

, Volume 88, Issue 1, pp 163–180 | Cite as

Drone-Aided Healthcare Services for Patients with Chronic Diseases in Rural Areas

  • Seon Jin Kim
  • Gino J. LimEmail author
  • Jaeyoung Cho
  • Murray J. Côté
Article

Abstract

This paper addresses the drone-aided delivery and pickup planning of medication and test kits for patients with chronic diseases who are required to visit clinics for routine health examinations and/or refill medicine in rural areas. For routine healthcare services, the work proposes two models: the first model is to find the optimal number of drone center locations using the set covering approach, and the second model is the multi-depot vehicle routing problem with pickup and delivery requests minimizing the operating cost of drones in which drones deliver medicine to patients and pick up exam kits on the way back such as blood and urine samples. In order to improve computational performance of the proposed models, a preprocessing algorithm, a Partition method, and a Lagrangian Relaxation (LR) method are developed as solution approaches. A cost-benefit analysis method is developed as a tool to analyze the benefits of drone-aided healthcare service. The work is tested on a numerical example to show its applicability.

Keywords

Drone Healthcare Delivery Chronic disease Rural health 

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References

  1. 1.
    Epping-Jordan, J., Pruitt, S., Bengoa, R., Wagner, E.: Improving the quality of health care for chronic conditions. Qual. Saf. Health Care 13(4), 299–305 (2004)CrossRefGoogle Scholar
  2. 2.
    Ward, B.W.: Multiple chronic conditions among us adults: A 2012 update (2014)Google Scholar
  3. 3.
    Gerteis, J., Izrael, D., Deitz, D., LeRoy, L., Ricciardi, R., Miller, T., Basu, J.: Multiple chronic conditions chartbook (2014)Google Scholar
  4. 4.
    Association, N.R.H., et al.: What’s different about rural health care, http://www.ruralhealthweb.org (2015)
  5. 5.
    Lee, W., Jiang, L., Phillips, C.D., Ohsfeldt, R.L.: Rural-urban differences in health care expenditures: Empirical data from us households. Adv. Public Health 2014, 1–8 (2014)CrossRefGoogle Scholar
  6. 6.
    Hartley, D.: Rural health disparities, population health, and rural culture. Amer. J. Public Health 94(10), 1675–1678 (2004)CrossRefGoogle Scholar
  7. 7.
    O’Shea, J., Berger, R., Samra, C., Van Durme, D., et al.: Telemedicine in education: Bridging the gap. Educ. Health 28(1), 64–67 (2015)CrossRefGoogle Scholar
  8. 8.
    Brown, M.T., Bussell, J.K.: Medication adherence: Who cares? Mayo Clinic Proceedings, vol. 86, pp. 304–314. Elsevier (2011)Google Scholar
  9. 9.
    Weaver, K.E., Geiger, A.M., Lu, L., Case, L.D.: Rural-urban disparities in health status among us cancer survivors. Cancer 119(5), 1050–1057 (2013)CrossRefGoogle Scholar
  10. 10.
    Kubat, B.: Home, where the future is. Caring Ages 15(5), 14 (2014)CrossRefGoogle Scholar
  11. 11.
    Omachonu, V.K., Einspruch, N.G.: Innovation in healthcare delivery systems: A conceptual framework. Innov. J.: Public Sect. Innov. J. 15(1), 1–20 (2010)Google Scholar
  12. 12.
    Perednia, D.A., Allen, A.: Telemedicine technology and clinical applications. Jama 273(6), 483–488 (1995)CrossRefGoogle Scholar
  13. 13.
    Blank, J.J., Clark, L., Longman, A.J., Atwood, J.R.: Perceived home care needs of cancer patients and their caregivers. Cancer Nurs. 12(2), 78–84 (1989)CrossRefGoogle Scholar
  14. 14.
    Capua, C.D., Meduri, A., Morello, R.: A remote doctor for homecare and medical diagnoses on cardiac patients by an adaptive ecg analysis 2009. MeMeA 2009. IEEE International Workshop on Medical Measurements and Applications, pp. 31–36. IEEE (2009)Google Scholar
  15. 15.
    Hein, A., Nee, O., Willemsen, D., Scheffold, T., Dogac, A., Laleci, G., et al.: Saphire-intelligent healthcare monitoring based on semantic interoperability platform-the homecare scenario. ECEH, pp. 191–202 (2006)Google Scholar
  16. 16.
    Bredström, D., Rönnqvist, M.: Combined vehicle routing and scheduling with temporal precedence and synchronization constraints. Eur. J. Oper. Res. 191(1), 19–31 (2008)CrossRefzbMATHGoogle Scholar
  17. 17.
    Cappanera, P., Scutellà, M.G.: Joint assignment, scheduling, and routing models to home care optimization: A pattern-based approach. Transp. Sci. 49(4), 830–852 (2014)CrossRefGoogle Scholar
  18. 18.
    Liu, R., Xie, X., Garaix, T.: Hybridization of tabu search with feasible and infeasible local searches for periodic home health care logistics. Omega 47, 17–32 (2014)CrossRefGoogle Scholar
  19. 19.
    Rasmussen, M.S., Justesen, T., Dohn, A., Larsen, J.: The home care crew scheduling problem: Preference-based visit clustering and temporal dependencies. Eur. J. Oper. Res. 219(3), 598–610 (2012)CrossRefzbMATHGoogle Scholar
  20. 20.
    Arcury, T.A., Preisser, J.S., Gesler, W.M., Powers, J.M.: Access to transportation and health care utilization in a rural region. J. Rural Health 21(1), 31–38 (2005)CrossRefGoogle Scholar
  21. 21.
    Goins, R.T., Williams, K.A., Carter, M.W., Spencer, S.M., Solovieva, T.: Perceived barriers to health care access among rural older adults: a qualitative study. J. Rural Health 21(3), 206–213 (2005)CrossRefGoogle Scholar
  22. 22.
    Molfenter, T., Boyle, M., Holloway, D., Zwick, J.: Trends in telemedicine use in addiction treatment. Addict. Sci. Clin. Pract. 10(1), 14 (2015)CrossRefGoogle Scholar
  23. 23.
    Sia, C., Tonniges, T.F., Osterhus, E., Taba, S.: History of the medical home concept. Pediatrics 113(Supplement 4), 1473–1478 (2004)Google Scholar
  24. 24.
    Reid, R.J., Coleman, K., Johnson, E.A., Fishman, P.A., Hsu, C., Soman, M.P., Trescott, C.E., Erikson, M., Larson, E.B.: The group health medical home at year two: cost savings, higher patient satisfaction, and less burnout for providers. Health Aff. 29(5), 835–843 (2010)CrossRefGoogle Scholar
  25. 25.
    Trondsen, M.V., Bolle, S.R., Stensland, G.Ø., Tjora, A.: Videocare: Decentralised psychiatric emergency care through videoconferencing. BMC Health Serv. Res. 12(1), 470 (2012)CrossRefGoogle Scholar
  26. 26.
    Todd, C., Watfa, M., El Mouden, Y., Sahir, S., Ali, A., Niavarani, A., Lutfi, A., Copiaco, A., Agarwal, V., Afsari, K., et al.: A proposed uav for indoor patient care. Technology and Health Care (Preprint), pp. 1–8 (2015)Google Scholar
  27. 27.
    Lennartsson, J.: Strategic placement of ambulance drones for delivering defibrillators to out of hospital cardiac arrest victims (2015)Google Scholar
  28. 28.
    Scott, J., Scott, C.: Drone delivery models for healthcare. In: Proceedings of the 50th Hawaii International Conference on System Sciences (2017)Google Scholar
  29. 29.
    Hallewas, C., Momont, A.: TU Delft’s ambulance drone drastically increases chances of survival of cardiac arrest patients, http://www.tudelft.nl/en/ (2017)
  30. 30.
    Li, X., Zhao, Z., Zhu, X., Wyatt, T.: Covering models and optimization techniques for emergency response facility location and planning: a review. Math. Methods Oper. Res. 74(3), 281–310 (2011)MathSciNetCrossRefzbMATHGoogle Scholar
  31. 31.
    Bernardini, S., Fox, M., Long, D.: Planning the behaviour of low-cost quadcopters for surveillance missions. In: Proceeding of International Conference on Automated Planning and Scheduling (2014)Google Scholar
  32. 32.
    Reed, T., Geis, J., Dietrich, S.: Skynet: A 3g-enabled mobile attack drone and stealth botmaster. In: WOOT, pp. 28–36 (2011)Google Scholar
  33. 33.
    Miller, C.E., Tucker, A.W., Zemlin, R.A.: Integer programming formulation of traveling salesman problems. J. ACM (JACM) 7(4), 326–329 (1960)MathSciNetCrossRefzbMATHGoogle Scholar
  34. 34.
    Wheeler, W.C.: The triangle inequality and character analysis. Mol. Biol. Evol. 10, 707–707 (1993)Google Scholar
  35. 35.
    Lenstra, J.K., Kan, A.: Complexity of vehicle routing and scheduling problems. Networks 11(2), 221–227 (1981)CrossRefGoogle Scholar
  36. 36.
    Wolsey, L.A.: Integer programming, vol. 42. Wiley, New York (1998)Google Scholar
  37. 37.
    Kallehauge, B., Larsen, J., Madsen, O.B., Solomon, M.M.: Vehicle routing problem with time windows. Springer (2005)Google Scholar
  38. 38.
    Fisher, M.L.: The Lagrangian relaxation method for solving integer programming problems. Manag. Sci. 27(1), 1–18 (1981)MathSciNetCrossRefzbMATHGoogle Scholar
  39. 39.
    Phillips, C., Thompson, G.: What is cost-effectiveness?, Hayward Medical Communications (1997)Google Scholar
  40. 40.
    Phillips, C., Thompson, G.: What is a QALY?, vol. 1, Hayward Medical Communications (1998)Google Scholar
  41. 41.
    Newnan, D.G., Eschenbach, T., Lavelle, J.P.: Engineering economic analysis, Vol. 2, Oxford University Press (2004)Google Scholar
  42. 42.
    GAMS Development, C.: General Algebraic Modeling System (GAMS) Release 24.5.6, DC, USA, http://www.gams.com/
  43. 43.
    Stepp, E.: Owning and operating your vehicle just got a little cheaper according to AAA’s 2014 ’your driving costs’ study, http://newsroom.aaa.com/2014/ (2015)

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  1. 1.Department of Industrial EngineeringUniversity of HoustonHoustonUSA
  2. 2.Department of Industrial EngineeringLamar UniversityBeaumontUSA
  3. 3.School of Public HealthTexas A&M UniversityCollege StationUSA

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