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Factors Influencing Adoption of Medical IoT in U.S. Nursing Homes.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Factors Influencing Adoption of Medical IoT in U.S. Nursing Homes./
作者:	Manners, Erin.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	157 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-02, Section: B.
Contained By:	Dissertations Abstracts International82-02B.
標題:	Information technology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28023166
ISBN:	9798662494213

Factors Influencing Adoption of Medical IoT in U.S. Nursing Homes.
Manners, Erin.

Factors Influencing Adoption of Medical IoT in U.S. Nursing Homes. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 157 p.

Source: Dissertations Abstracts International, Volume: 82-02, Section: B.

Thesis (D.I.T.)--Capella University, 2020.

This item must not be sold to any third party vendors.

The rise of the Internet of Things (IoT) gives people the ability to check the status of their home securities, start their cars, and remotely open and close their garage doors from anywhere in the world via smartphones and other applications. Industries, such as the health care sector, are also set to benefit from the unlimited potential of IoT-based technologies in the form of improved efficiency, safety, monitoring, reduction of errors, and compliance, which could ultimately provide new profit streams. Despite the opportunities that the internet of medical things (M-IoT) presents for health care organizations, such as skilled nursing homes, in many cases, the technology has not been adopted to the extent that was previously expected. This research is a quantitative investigation of the socio-organizational and individualistic factors of effort expectancy, performance, social influence, perceived risk, and how these factors may influence adoption and use of M-IoT within US-based small and medium-sized skilled nursing homes. The study used the Unified Theory of Acceptance and Use of Technology (UTAUT) combined with Perceived Risk (PR) as a means to evaluate the social factors influencing user adoption intention and behavior, with the goal to assess if these variables can be used as a predictor for M-IoT system adoption. Based on the findings, the variables in question predict over 69% of M-IoT system acceptance and use within small and medium-sized (SME) U.S. skilled nursing organizations. In general, the findings are in alignment with past studies that employed the UTAUT model. However, the study identified a significant result, which was that PR is not a significant predictor for M-IoT adoption in this population. Future adoption and implementation strategies of M-IoT could leverage this information with the goal of widespread use to increase efficiency, productivity, safety, and compliance for SME U.S. skilled nursing organizations.

ISBN: 9798662494213Subjects--Topical Terms:

532993
Information technology.
Subjects--Index Terms:

Health information technology

Factors Influencing Adoption of Medical IoT in U.S. Nursing Homes.
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