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The impact of wearable devices and performance payments on health outcomes

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  • Tarakci, Hakan
  • Kulkarni, Shailesh
  • Ozdemir, Zafer D.

Abstract

In this paper, we study a healthcare system consisting of a healthcare provider and a patient. We first look at a patient with a chronic condition, such as asthma or diabetes, where the patient needs to go through a restorative treatment when she falls sick and through an occasional full treatment. We assume that the health condition of the patient deteriorates faster over time; hence, the need for the full treatment. Borrowing from maintenance/reliability techniques to describe a system prone to failure, we model the health condition of the patient as a reliability problem and find the optimal frequency of full treatment visits to the hospital. We then assume that the patient can use a wearable device that can reduce the health deterioration rate due to more accurate and real-time information; it can also be used to partially administer restorative treatments. The healthcare provider chooses the optimal technology level of the wearable devices, and depending on the cost, we find that they might not always go for the most advanced technology available. We also show that the use of wearable devices increases the overall health condition of the patient. We then apply the same procedure to a patient with a critical condition where each bout of sickness needs to be treated fully instead of a corrective/restorative treatment of the chronic patient. We then quantify the benefits of wearables (especially in terms of patient wellness) in a numerical study.

Suggested Citation

  • Tarakci, Hakan & Kulkarni, Shailesh & Ozdemir, Zafer D., 2018. "The impact of wearable devices and performance payments on health outcomes," International Journal of Production Economics, Elsevier, vol. 200(C), pages 291-301.
    • Handle: RePEc:eee:proeco:v:200:y:2018:i:c:p:291-301
    DOI: 10.1016/j.ijpe.2018.04.003
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    References listed on IDEAS

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    1. Hakan Tarakci & Kwei Tang & Sunantha Teyarachakul, 2013. "Learning and forgetting effects on maintenance outsourcing," IISE Transactions, Taylor & Francis Journals, vol. 45(4), pages 449-463.
    2. Meller, Russell D. & Kim, David S., 1996. "The impact of preventive maintenance on system cost and buffer size," European Journal of Operational Research, Elsevier, vol. 95(3), pages 577-591, December.
    3. Hakan Tarakci, 2016. "Two types of learning effects on maintenance activities," International Journal of Production Research, Taylor & Francis Journals, vol. 54(6), pages 1721-1734, March.
    4. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    5. R. Pascual & D. Godoy & H. Figueroa, 2013. "Optimizing maintenance service contracts under imperfect maintenance and a finite time horizon," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 29(5), pages 564-577, September.
    6. Zafer Ozdemir & Jack Barron & Subhajyoti Bandyopadhyay, 2011. "An Analysis of the Adoption of Digital Health Records Under Switching Costs," Information Systems Research, INFORMS, vol. 22(3), pages 491-503, September.
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    Cited by:

    1. Zhao, Heng & Liu, Zixian & Li, Mei & Liang, Lijun, 2022. "Optimal monitoring policies for chronic diseases under healthcare warranty," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

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