Advancement in the Internet of Things (IoT) for medical services and artificial intelligence (AI) technologies are no longer just a glimpse of the future. Medical devices have been developed and introduced, with the aim to change the way patient data is aggregated, stored and utilized. Moreover, AI establishes itself as the key to hospital workflow optimization, cost control, and disease prevention.
Therefore, there’s no better time to start a career in data science, as the healthcare industry’s demand for data scientists is rapidly increasing. Here are 4 areas which data science that have revolutionised the healthcare industry.
1. Precise Medical Treatment
Data science has the potential to completely transform the way diseases are diagnosed and treated through continued collection and analysis of patient data. This includes genetic data, as well as information about contracted diseases, healing treatments, and outcomes. Not only will this decrease the chances of harming the patients, it can also warn medical professional when using inadequate treatments. Moreover, patient data regarding their lifestyle and environmental exposure can further identify what triggers certain diseases and conditions.
2. Workflow and Clinic Performance Optimization (Hospital Operations)
Hospitals are cost-sensitive and face highly complex operational problems. It includes how many staff to assign at certain hours to maximize efficiency, the amount of available hospital beds to meet patient demand, and how to enhance the utilization of the operating room. Predictive analytics can optimize scheduling and even go so far as to tell hospital staff which beds should be cleaned first and which patients may face challenges during the discharge process.
3. Disease Prevention and Control
The best way to transform healthcare is to quickly identify risks and recommend prevention plans before health risks become a major issue. Through wearables and other tracking devices that take into account historical patterns and genetic information, data science helps to make it possible to recognize a problem before it gets out of hand.
4. Remote Post-Care Monitoring
After any type of surgery or treatment, there is the risk of complications and recurring pain, which can be difficult to manage once the patient leaves the hospital. However, thanks to data science, soon you won’t have to wait in front of the doctor’s office for a routine check-up. Wearable sensors and patient tablets can now track your recovery progress and connect you to your care team if you need help, freeing up limited and costly hospital resources. Such artificial intelligence innovations are increasingly used for monitoring heart conditions and diabetes, as they can alert both patients and healthcare professionals if there are indications for potentially dangerous conditions.
Data science, data analytics and artificial intelligence are already making significant improvements in the quality of healthcare services around the world. However, technology itself is just part of the answer. Despite the superiority of technology, healthcare is all about assisting professionals and empowering people to manage their well-being. Therefore, to achieve meaningful innovations, there need to be a continual effort to develop and fine-tune artificial intelligence with a deep understanding of the personal and clinical context.