Breaking Barriers: Unveiling Factors Influencing the Adoption of Artificial Intelligence by Healthcare Providers
Artificial intelligence (AI) is an emerging technological system that provides a platform to manage and analyze data by emulating human cognitive functions with greater accuracy, revolutionizing patient care and introducing a paradigm shift to the healthcare industry. The purpose of this study is to...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Big Data and Cognitive Computing |
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| Online Access: | https://www.mdpi.com/2504-2289/7/2/105 |
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| author | BM Zeeshan Hameed Nithesh Naik Sufyan Ibrahim Nisha S. Tatkar Milap J. Shah Dharini Prasad Prithvi Hegde Piotr Chlosta Bhavan Prasad Rai Bhaskar K Somani |
| author_facet | BM Zeeshan Hameed Nithesh Naik Sufyan Ibrahim Nisha S. Tatkar Milap J. Shah Dharini Prasad Prithvi Hegde Piotr Chlosta Bhavan Prasad Rai Bhaskar K Somani |
| author_sort | BM Zeeshan Hameed |
| collection | DOAJ |
| description | Artificial intelligence (AI) is an emerging technological system that provides a platform to manage and analyze data by emulating human cognitive functions with greater accuracy, revolutionizing patient care and introducing a paradigm shift to the healthcare industry. The purpose of this study is to identify the underlying factors that affect the adoption of artificial intelligence in healthcare (AIH) by healthcare providers and to understand “What are the factors that influence healthcare providers’ behavioral intentions to adopt AIH in their routine practice?” An integrated survey was conducted among healthcare providers, including consultants, residents/students, and nurses. The survey included items related to performance expectancy, effort expectancy, initial trust, personal innovativeness, task complexity, and technology characteristics. The collected data were analyzed using structural equation modeling. A total of 392 healthcare professionals participated in the survey, with 72.4% being male and 50.7% being 30 years old or younger. The results showed that performance expectancy, effort expectancy, and initial trust have a positive influence on the behavioral intentions of healthcare providers to use AIH. Personal innovativeness was found to have a positive influence on effort expectancy, while task complexity and technology characteristics have a positive influence on effort expectancy for AIH. The study’s empirically validated model sheds light on healthcare providers’ intention to adopt AIH, while the study’s findings can be used to develop strategies to encourage this adoption. However, further investigation is necessary to understand the individual factors affecting the adoption of AIH by healthcare providers. |
| first_indexed | 2024-03-11T02:45:27Z |
| format | Article |
| id | doaj.art-1de956689165435b8c089241d345d863 |
| institution | Directory Open Access Journal |
| issn | 2504-2289 |
| language | English |
| last_indexed | 2024-03-11T02:45:27Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj.art-1de956689165435b8c089241d345d8632023-11-18T09:18:49ZengMDPI AGBig Data and Cognitive Computing2504-22892023-05-017210510.3390/bdcc7020105Breaking Barriers: Unveiling Factors Influencing the Adoption of Artificial Intelligence by Healthcare ProvidersBM Zeeshan Hameed0Nithesh Naik1Sufyan Ibrahim2Nisha S. Tatkar3Milap J. Shah4Dharini Prasad5Prithvi Hegde6Piotr Chlosta7Bhavan Prasad Rai8Bhaskar K Somani9Department of Urology, Father Muller Medical College, Mangalore 575002, Karnataka, IndiaiTRUE (International Training and Research in Uro-Oncology and Endourology) Group, Manipal 576104, Karnataka, IndiaiTRUE (International Training and Research in Uro-Oncology and Endourology) Group, Manipal 576104, Karnataka, IndiaDepartment of Postgraduate Diploma in Management, Institute of PGDM, Mumbai Education Trust, Mumbai 400050, Maharashtra, IndiaiTRUE (International Training and Research in Uro-Oncology and Endourology) Group, Manipal 576104, Karnataka, IndiaKasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal 576104, Karnataka, IndiaJagdish Sheth School of Management, Electronic City, Bengaluru 560100, Karnataka, IndiaDepartment of Urology, Jagiellonian University in Krakow, Gołębia 24, 31-007 Kraków, PolandDepartment of Urology, Freeman Hospital, Newcastle upon Tyne NE7 7DN, UKDepartment of Urology, University Hospital Southampton NHS Trust, Southampton SO16 6YD, UKArtificial intelligence (AI) is an emerging technological system that provides a platform to manage and analyze data by emulating human cognitive functions with greater accuracy, revolutionizing patient care and introducing a paradigm shift to the healthcare industry. The purpose of this study is to identify the underlying factors that affect the adoption of artificial intelligence in healthcare (AIH) by healthcare providers and to understand “What are the factors that influence healthcare providers’ behavioral intentions to adopt AIH in their routine practice?” An integrated survey was conducted among healthcare providers, including consultants, residents/students, and nurses. The survey included items related to performance expectancy, effort expectancy, initial trust, personal innovativeness, task complexity, and technology characteristics. The collected data were analyzed using structural equation modeling. A total of 392 healthcare professionals participated in the survey, with 72.4% being male and 50.7% being 30 years old or younger. The results showed that performance expectancy, effort expectancy, and initial trust have a positive influence on the behavioral intentions of healthcare providers to use AIH. Personal innovativeness was found to have a positive influence on effort expectancy, while task complexity and technology characteristics have a positive influence on effort expectancy for AIH. The study’s empirically validated model sheds light on healthcare providers’ intention to adopt AIH, while the study’s findings can be used to develop strategies to encourage this adoption. However, further investigation is necessary to understand the individual factors affecting the adoption of AIH by healthcare providers.https://www.mdpi.com/2504-2289/7/2/105artificial intelligencehealthcare systemsperceptionhealth professionalsintention |
| spellingShingle | BM Zeeshan Hameed Nithesh Naik Sufyan Ibrahim Nisha S. Tatkar Milap J. Shah Dharini Prasad Prithvi Hegde Piotr Chlosta Bhavan Prasad Rai Bhaskar K Somani Breaking Barriers: Unveiling Factors Influencing the Adoption of Artificial Intelligence by Healthcare Providers Big Data and Cognitive Computing artificial intelligence healthcare systems perception health professionals intention |
| title | Breaking Barriers: Unveiling Factors Influencing the Adoption of Artificial Intelligence by Healthcare Providers |
| title_full | Breaking Barriers: Unveiling Factors Influencing the Adoption of Artificial Intelligence by Healthcare Providers |
| title_fullStr | Breaking Barriers: Unveiling Factors Influencing the Adoption of Artificial Intelligence by Healthcare Providers |
| title_full_unstemmed | Breaking Barriers: Unveiling Factors Influencing the Adoption of Artificial Intelligence by Healthcare Providers |
| title_short | Breaking Barriers: Unveiling Factors Influencing the Adoption of Artificial Intelligence by Healthcare Providers |
| title_sort | breaking barriers unveiling factors influencing the adoption of artificial intelligence by healthcare providers |
| topic | artificial intelligence healthcare systems perception health professionals intention |
| url | https://www.mdpi.com/2504-2289/7/2/105 |
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