Knowledge and perception of healthcare workers towards the adoption of artificial intelligence in healthcare service delivery in Nigeria

Michael Promise Ogolodom; Anna Daniel Ochong; Egop Egop Brownson; Catherine Ugwem Jeremiah; Anelechi Kenneth Madume; Clement U. Nyenke; Musa Y. Dambele; Dlama Zira Joseph; Abdul Fatai K Bakre; Elizabeth O Balogun; Nengi Alazigha; Mark C. Okeji; Kenneth S. Ordu; Hyacienth Uche Chiegwu Hyacienth Uche Chiegwu; Joy Johnson; Awajimijan Nathaniel Mbaba; Victor Kelechi Nwodo

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Knowledge and perception of healthcare workers towards the adoption of artificial intelligence in healthcare service delivery in Nigeria

Ogolodom , Michael Promise ^[4] ; Daniel Ochong , Anna ^[5] ; Brownson Egop, Egop ^[6] ; Ugwem Jeremiah , Catherine ^[7] ; Kenneth Madume, Anelechi ^[8] ; Nyenke , Clement U. ^[9] ; Dambele, Musa Y. ^[1] ; Joseph, Dlama Zira ^[2] ; Bakre, Abdul Fatai K. ^[3] ; Balogun, Elizabeth O. ^[10] ; Alazigha, Nengi ^[11] ; Okeji, Mark C. ^[12] ; Ordu, Kenneth S. ^[13] ; Hyacienth Uche Chiegwu, Hyacienth Uche Chiegwu ^[14] ; Johnson , Joy ^[9] ; Mbaba, Awajimijan Nathaniel Mbaba ^[11] ; Kelechi Nwodo , Victor ^[14]
1. [1] Bayero University Kano
  
  Bayero University Kano
  
  Shahuchi, Nigeria
2. [2] Federal University Lafia
  
  Federal University Lafia
  
  Nigeria
3. [3] Osun State University
  
  Osun State University
  
  Nigeria
4. [4] Department of Radiography, Faculty of Basic Medical Sciences, College of Medical Sciences, Rivers State University, Port Harcourt, Nigeria
5. [5] Department of Radiology, Asi Ukpo Hospital, Calabar, Cross River State, Nigeria
6. [6] Department of Radiology, Rivers State Government House Clinic, Port Harcourt, Nigeria
7. [7] Department of Nurse Sciences, Rivers State School of Nursing Sciences, Port Harcourt, Nigeria
8. [8] Department of Physiotherapy, , Faculty of Basic Medical Sciences, College of Medical Sciences, Rivers State University, Port Harcourt, Nigeria
9. [9] Department of Medical Laboratory Sciences, PAMO University of Medical Sciences, Rivers State, Port Harcourt, Nigeria
10. [10] Department of Radiography and Radiation Sciences, Faculty of Basic Medical Sciences, Ajayi Crowther University, Oyo, Oyo State, Ibadan, Nigeria
11. [11] Department of Radiology, Rivers State University Teaching Hospital, Port Harcourt, Nigeria
12. [12] Department of Medical Radiography, University of Nigeria, Nsukka, Nigeria
13. [13] Department of Anatomy, Faculty of Basic Medical Sciences, College of Medical Sciences, Rivers State University, Port Harcourt, Nigeria
14. [14] Department of Radiography and Radiological Sciences, Faculty of Health Sciences and Technology, Nnamdi Azikwe University, Nnewi Campus, Anambra State, Nigeria
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Localización: AG Salud, ISSN-e 3006-6859, Vol. 1, Nº. 0, 2023 (Ejemplar dedicado a: AG Salud)
Idioma: inglés
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Resumen
- Background: Artificial Intelligence (AI) is seen as the machine that replaces human labour to work for men with a more effective and speedier result. There is a paucity of data on the knowledge and perception of healthcare workers regarding AI technology. This study aims to assess the knowledge and perception of healthcare workers towards the application of AI in healthcare services in Nigeria. Materials and methods: Cross-sectional questionnaire-based survey designed was used to achieve the aim of this study. Both electronic (Google form) and hardcopy version of the questionnaire were distributed to healthcare workers in Nigeria and their responses were retrieved and statistically analyzed. Results: Out of 263 respondents, most 51.3% (n=135) were females. Greater percentage 25.5% (n=67) of the respondents were radiographers, followed by medical consultants 14.8% (n=39) and the least 1.5 %(n=4) were pharmacists. Greater proportion 61 %(n=160) of the respondents has the opinion that AI can be incorporated into all medical specialties. Out of 263 respondents, 51.7% (n=136) had good knowledge of AI and the least 6.4% (n=16) had very poor knowledge of AI. Greater proportion 78.7% (n=207) of the respondents, agreed that AI can help to reduce the number of medical errors. Majority 29.3% (n=77) of the respondents agreed that human specialists will be replaced by AI in the near future. A large proportion 40.3% (n=106) of the respondents agreed that some employers may prefer AI to human specialists because AI has no emotional exhaustion or physical limitation. Conclusion: The respondents in this study showed good knowledge of both the medical areas of applications of AI as well as the benefits of AI application in healthcare services. However, most of the respondents were afraid that their jobs would be taken over by AI in the near future