東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Scaling Innovations in Healthcare: A...

Govindasamy, Saravana P.

Linked to FindBook

Google Book

Amazon

博客來

Scaling Innovations in Healthcare: A Multi-Method Analysis of Facilitators and Barriers of Innovation Adoption in Hospitals.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Scaling Innovations in Healthcare: A Multi-Method Analysis of Facilitators and Barriers of Innovation Adoption in Hospitals./
Author:	Govindasamy, Saravana P.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	88 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-12, Section: B.
Contained By:	Dissertations Abstracts International80-12B.
Subject:	Information Technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13862408
ISBN:	9781392186213

Scaling Innovations in Healthcare: A Multi-Method Analysis of Facilitators and Barriers of Innovation Adoption in Hospitals.
Govindasamy, Saravana P.

Scaling Innovations in Healthcare: A Multi-Method Analysis of Facilitators and Barriers of Innovation Adoption in Hospitals. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 88 p.

Source: Dissertations Abstracts International, Volume: 80-12, Section: B.

Thesis (D.B.A.)--Temple University, 2019.

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

This research paper examines the innovation adoption of technology, specifically Artificial Intelligence (AI) implementations in hospitals by exploring the capabilities that enables AI innovations using the dynamic capabilities (sensing, seizing and reconfiguring) framework and clinicians' intentions to use AI innovations for patient care by applying the technology adoption/acceptance framework Unified Theory of Acceptance and Use of Technology (UTAUT) utilizing qualitative case study analysis and quantitative survey methodology respectively. This multi-disciplinary research has considerable relevance to both healthcare business leaders and clinical practitioners by identifying the key factors that drives the decisions to adopt innovations to improve healthcare organizations' competitiveness to enhance patient care as well as to reduce overall healthcare costs. The main findings are: (1) On an organizational level, healthcare organizations with strong and versatile dynamic capabilities, who build on their existing knowledge and capabilities are better able to integrate the innovations into their internal operations and existing services. The identified barriers provide a clear sense of organizational barriers and resistance points for innovation adoption. (2) On an individual level, the impact of quality of care and organization leadership support are the key factors that facilitates the adoption of innovation among the clinicians. (3) Current trends and key impact areas of AI technology in the healthcare industry are identified.

ISBN: 9781392186213Subjects--Topical Terms:

1030799
Information Technology.

Scaling Innovations in Healthcare: A Multi-Method Analysis of Facilitators and Barriers of Innovation Adoption in Hospitals.
LDR:02665nmm a2200325 4500 001 2208874
005 20191025102433.5
008 201008s2019 ||||||||||||||||| ||eng d
020 $a 9781392186213
035 $a (MiAaPQ)AAI13862408
035 $a (MiAaPQ)temple:13696
035 $a AAI13862408
040 $a MiAaPQ $c MiAaPQ
100 1 $a Govindasamy, Saravana P. $3 3435937
245 1 0 $a Scaling Innovations in Healthcare: A Multi-Method Analysis of Facilitators and Barriers of Innovation Adoption in Hospitals.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 88 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-12, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Wattal, Sunil.
502 $a Thesis (D.B.A.)--Temple University, 2019.
506 $a This item must not be sold to any third party vendors.
520 $a This research paper examines the innovation adoption of technology, specifically Artificial Intelligence (AI) implementations in hospitals by exploring the capabilities that enables AI innovations using the dynamic capabilities (sensing, seizing and reconfiguring) framework and clinicians' intentions to use AI innovations for patient care by applying the technology adoption/acceptance framework Unified Theory of Acceptance and Use of Technology (UTAUT) utilizing qualitative case study analysis and quantitative survey methodology respectively. This multi-disciplinary research has considerable relevance to both healthcare business leaders and clinical practitioners by identifying the key factors that drives the decisions to adopt innovations to improve healthcare organizations' competitiveness to enhance patient care as well as to reduce overall healthcare costs. The main findings are: (1) On an organizational level, healthcare organizations with strong and versatile dynamic capabilities, who build on their existing knowledge and capabilities are better able to integrate the innovations into their internal operations and existing services. The identified barriers provide a clear sense of organizational barriers and resistance points for innovation adoption. (2) On an individual level, the impact of quality of care and organization leadership support are the key factors that facilitates the adoption of innovation among the clinicians. (3) Current trends and key impact areas of AI technology in the healthcare industry are identified.
590 $a School code: 0225.
650 4 $a Information Technology. $3 1030799
650 4 $a Health care management. $3 2122906
690 $a 0489
690 $a 0769
710 2 $a Temple University. $b Business Administration/Management Information Systems. $3 2099959
773 0 $t Dissertations Abstracts International $g 80-12B.
790 $a 0225
791 $a D.B.A.
792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13862408