IMPROVING OPERATIONAL EFFICIENCY THROUGH THE INTEGRATION OF AI IN OPERATIONS MANAGEMENT IN HEALTH CARE (WITH FOCUS ON REPRODUCTIVE MEDICINE)
| dc.contributor.author | Mazepa, Ostap | |
| dc.date.accessioned | 2025-04-16T12:33:24Z | |
| dc.date.available | 2025-04-16T12:33:24Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | This research aims to explore the possibility of artificial intelligence in implementing operations management in reproductive health and increasing patient efficacy. To achieve this, the following objectives are proposed: determine how AI technologies can help clinics manage patient traffic and workload, as well as document and analyze treatment outcomes of reproductive medicine clinics. Employing synthetic data from twenty different clinics located in Europe, the United States, Ukraine, and Australia containing more than 534,379 documents and questionnaires filled in by one thousand employees, the study obtained both a detailed account of the current practices and an evaluation of the effects of applied AI- interventions. The object of this research is the management practices and operational frameworks within reproductive health clinics, with a particular focus on the integration of artificial intelligence (AI) into operations management. Quantitative and qualitative data were analyzed using descriptive statistics, comparative, qualitative content, and cost-benefit analyses. The quantitative and qualitative data were reasonably analyzed using Microsoft Azure Machine Learning, Google AI Platform, and IBM Watson NLP TOOLS. The outcome shows that it offers considerable time and cost reduction, increased patient satisfaction for all clinics, and other operational advantages. For instance, overarching task optimizations using AI technology decreased documentation time by 20%, patient wait time by 19.67%, and enhanced treatment effectiveness by 10%. These outcomes lead to annual cost savings of over $360,000 per clinic, patient retention, and increased clinic capacity. The insights thus highlight the prospects of AI in reproductive medicine and specific ideas on deploying technology in healthcare companies. The proposed AI capabilities will enable the clinics to demonstrate sustainable development of clinics, which will lead to an increase in the quality of services offered to the patient and an improvement in clinics’ competitive advantage in the healthcare market. Future work should extend the potential of these proposed strategies to other medical specialties to validate the effectiveness of AI implementation. | |
| dc.identifier.citation | Mazepa, O. (2025). IMPROVING OPERATIONAL EFFICIENCY THROUGH THE INTEGRATION OF AI IN OPERATIONS MANAGEMENT IN HEALTH CARE (WITH FOCUS ON REPRODUCTIVE MEDICINE). Kyiv: American University Kyiv. 50 p. | |
| dc.identifier.uri | https://er.auk.edu.ua/handle/234907866/138 | |
| dc.language.iso | en_US | |
| dc.publisher | Manuscript | |
| dc.subject | operations management | |
| dc.subject | organizational competency | |
| dc.subject | health care organizations | |
| dc.subject | fertility treatment | |
| dc.subject | patient-oriented care | |
| dc.subject | clinical activities | |
| dc.title | IMPROVING OPERATIONAL EFFICIENCY THROUGH THE INTEGRATION OF AI IN OPERATIONS MANAGEMENT IN HEALTH CARE (WITH FOCUS ON REPRODUCTIVE MEDICINE) | |
| dc.title.alternative | ПІДВИЩЕННЯ ОПЕРАЦІЙНОЇ ЕФЕКТИВНОСТІ ЗА РАХУНОК ІНТЕГРАЦІЇ ШІ В СИСТЕМУ ОПЕРАЦІЙНОГО МЕНЕДЖМЕНТУ В ГАЛУЗІ ОХОРОНИ ЗДОРОВ'Я (З ФОКУСОМ НА РЕПРОДУКТИВНУ МЕДИЦИНУ) | |
| dc.type | Thesis |