Machine learning – a strategic information system opportunity to strengthen healthcare
- Gayathri Kawshali Mayadunne,
- University of Bedfordshire,
- ,
Abstract
Hemas Holdings PLC is one of Sri Lanka’s top diversified firms, focusing on consumer, healthcare and transportation sectors (Hemas Holdings PLC, 2022). Of their many subsidiaries, Hemas Healthcare has been one of their significant ventures in the Sri Lankan business arena. Hemas Healthcare is Sri Lanka’s most significant privately owned healthcare provider, with a substantial reach across the whole Sri Lankan healthcare value chain, and is well known for its ‘The Australian Council Health Standard International’ (ACHSI) approved hospitals in Wattala and Thalawathugoda, Sri Lanka (Hemas, 2023). Furthermore, Hemas Healthcare introduced Sri Lanka’s first digital healthcare platform under the patronage of the International Finance Corporation (IFC) to provide expert healthcare about medical treatment, health education and information services via telehealth (IFC, 2020). With the introduction of the Digital Health application, Hemas Healthcare has now encountered a strategic information system (SIS) opportunity to further develop and enhance its information technology (IT) resources to strengthen its business endeavours and to gain a competitive advantage in the Sri Lankan Healthcare industry. The Digital Health application has the potential to be further developed into an IT platform where Artificial Intelligence (AI) can be integrated to provided a streamlined healthcare service. Strategies. This paper will discuss how Machine learning ( ML) can strategically strengthen digital healthcare.
Publication Information
Output type
Original language
EnglishPages from-to (Number of pages)
Pages 388-394 (7 pages)Publication milestones
- Published - 25/02/2024
Publication status
Publisher
Springer, Japan, India, Australia, Germany, United States, United Arab Emirates, Austria, Switzerland, Italy, China, United Kingdom, Netherlands, Brazil, France, SingaporePublication series
- Publication series name: Lecture Notes in Electrical Engineering
ISSN (Print): 1876-1100
ISSN (Electronic): 1876-1119
Volume: 1154 LNEE
ISBN (Print)
9789819706648External Publication IDs
- Scopus: 85187777133
Host publication title
Advanced Manufacturing and Automation XIIIHost publication editors
- Yi Wang
- Tao Yu
- Kesheng Wang
