THE ROLE OF AI-DRIVEN INVENTORY MANAGEMENT SYSTEMS IN THE PERFORMANCE OF HOSPITALS IN KENYA

This study investigated the role of AI in hospital performance in Kenya. With a cross-sectional comparison, it compared Siaya County Referral Hospital and Ruai Family Hospital in terms of ownership, facility level and resources. Based on Diffusion of Innovations Theory and the Technology-Organization-Environment (TOE) framework, it examined how hospitals acquire, integrate and use AI to improve performance. The study examined the impact of AI-based diagnostic, patient management, inventory and administrative systems on hospital performance and ICT infrastructure's moderating effect. The target population was 175 employees who were using AI-enabled systems. 100 respondents (75 from Siaya and 25 from Ruai) were selected using Yamane's formula and random sampling. The primary data were collected in the form of structured questionnaires and hospital records. Instrument reliability was checked using Cronbach's Alpha (all constructs > 0.70). All data were calculated with SPSS Version 30 using descriptive statistics, Pearson correlation, multiple regression and independent samples t-tests. We found that all four AI-driven systems significantly and positively affected hospital performance accounting for 73.0% variance (R² = 0.730, F = 64.294, p < .001). Inventory management systems had the strongest impact (β = 0.341, p < .001). There were no differences between the two hospitals in any system or performance and thus AI's contribution was the same, regardless of ownership, facility level or resources. The moderating effect of ICT infrastructure could not be tested due to a composite variable computation problem, a methodological issue. The study suggests the investment in all four AI systems should be increased and that future research on ICT infrastructure should be implemented properly to assess how this moderating effect is achieved.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-16
DOI
https://doi.org/10.5281/zenodo.22787077
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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article

THE ROLE OF AI-DRIVEN INVENTORY MANAGEMENT SYSTEMS IN THE PERFORMANCE OF HOSPITALS IN KENYA

1Odhiambo Oduor David, 2Dr. Rahab Lanoi,, 3Dr. Susan Wasike
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

THE ROLE OF AI-DRIVEN INVENTORY MANAGEMENT SYSTEMS IN THE PERFORMANCE OF HOSPITALS IN KENYA

1Odhiambo Oduor David, 2Dr. Rahab Lanoi,, 3Dr. Susan Wasike
article en

Abstract

This study investigated the role of AI in hospital performance in Kenya. With a cross-sectional comparison, it compared Siaya County Referral Hospital and Ruai Family Hospital in terms of ownership, facility level and resources. Based on Diffusion of Innovations Theory and the Technology-Organization-Environment (TOE) framework, it examined how hospitals acquire, integrate and use AI to improve performance. The study examined the impact of AI-based diagnostic, patient management, inventory and administrative systems on hospital performance and ICT infrastructure's moderating effect. The target population was 175 employees who were using AI-enabled systems. 100 respondents (75 from Siaya and 25 from Ruai) were selected using Yamane's formula and random sampling. The primary data were collected in the form of structured questionnaires and hospital records. Instrument reliability was checked using Cronbach's Alpha (all constructs > 0.70). All data were calculated with SPSS Version 30 using descriptive statistics, Pearson correlation, multiple regression and independent samples t-tests. We found that all four AI-driven systems significantly and positively affected hospital performance accounting for 73.0% variance (R² = 0.730, F = 64.294, p < .001). Inventory management systems had the strongest impact (β = 0.341, p < .001). There were no differences between the two hospitals in any system or performance and thus AI's contribution was the same, regardless of ownership, facility level or resources. The moderating effect of ICT infrastructure could not be tested due to a composite variable computation problem, a methodological issue. The study suggests the investment in all four AI systems should be increased and that future research on ICT infrastructure should be implemented properly to assess how this moderating effect is achieved.

Zenodo (CERN European Organization for Nuclear Research)
Catholic University of Eastern Africa (KE)
Industry, innovation and infrastructure
Openalex Percentile: Top 14%
Artificial Intelligence in Healthcare and Education
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