6 Data Science Use Cases in Healthcare
Since there are multiple sources to collect healthcare information, data science can be utilized efficiently to yield better advancements in the healthcare industry, through appropriate decision making. Data gathered from patient behaviour, proven care methods, response and other information can provide insights to improve operations in this patient-oriented industry.
Let’s discuss a few major use cases in healthcare, where data science can be utilized to enhance patient experience.
1. Patient engagement and satisfaction:
The patient-centric industry can implement data science to keep patients engaged in multiple aspects of healthcare. Access to relevant and reliable data is significant to design an efficient patient engagement practices. Data science can be applied over multiple healthcare data sources to fetch information. In the present scenario of patients increasing day by day, managing the data associated with them is a challenge. Data science helps to deal and utilize such enormous data. Clinics/hospitals can use this information to improve patient engagement and satisfaction.
2. Discovery of drugs and therapies:
Data science techniques can be used to design clinical trials, predict outcomes and understand the effectiveness, dosage and safety. During drug creation, data science implementation to the available relevant data can quicken up the process so that the drug is available in the market sooner.
Likewise, mapping patient’s response to genetic information helps in discovering new therapies that are effective based on patient’s acceptance and cohorts. This results in highest likelihood of success.
3. Patient data security:
Healthcare organization tends to have potential cyber threats. Analytics tools can be put to use in this use case. Monitoring patterns in data in terms of access, shareability and usability can help in preventing cyberattacks and ensures patient data security.
4. Supply chain management:
Healthcare industry can utilize data science to gain more actionable insights and to improve efficiency. The patterns in the supply chain can make manufactures proactive, reduce counterfeits. Observation of available data can make organizations act data drivingly and manage supply chain effectively based of availability, necessity and reachability.
5. Diagnostic accuracy and effectiveness:
There is always a chance of misdiagnosis in conventional methods. But, using data science along with Ai, and machine learning can significantly reduce such cases. By scrutinizing patient’s historical data and applying certain algorithms, results of diagnosis are much accurate and allow scope for better treatment.
6. Prevent patient health downturn:
Wearables and implanted devices are in usage to monitor bodily functions. The data collected from them can be used to create medication and diet plans or suggestions to improve lifestyle to maintain health. The insights derived from the collected data helps in prevention of chronic illnesses and also in better decision making on ongoing treatments.
Patients who are already at hospital are also prone to sudden attacks. Data science can be used on the vital information, historic data, symptoms and diagnosis can quicken up the treatment. This can also help in staff being attentive for the emergencies to respond on time.
Let’s wrap it up……
Data science provides any business with the right insights and information to advance. It’s the same with healthcare, it can improve efficiency, reduce costs and advance operations and facilities. Athena helps you to get ready for an enriched digital experience in healthcare industry. To contact us Click here