From identifying ailments, interpreting medical records to foreseeing the respective consequences on the patient, Machine Learning and Artificial Intelligence is gaining significant momentum in the Healthcare sector in modern time. The level of accuracy of these technologies surpasses human doctors in tasks like autism diagnosis in newborns and performing surgical sutures. Here the quality is measured based on the Readmission and length of stay (LOS) details of the patients. However, Length of Stay (LOS is one of the most monitored criterion in in-patient department of all Hospitals and a major focal point for Insurance industry too
Recently Microsoft has come up with a solution for Hospital Length of Stay with SQL Server 2016 and R services. Length of stay is the number of days from the date a patient gets admitted initially till he/she gets discharged from any Medical facility. Leveraging this solution, the Hospitals and Healthcare providers will now be able to predict the patient’s stay of Hospital using machine learning.
Microsoft has issued this solution in the Cortana Intelligence Solutions Gallery. The overview states, “This solution enables a predictive model for Length of Stay for in-hospital admissions. Length of Stay (LOS) is defined in number of days from the initial admit date to the date that the patient is discharged from any given hospital facility. There can be significant variation of LOS across various facilities and across disease conditions and specialties even within the same healthcare system. Advanced LOS prediction at the time of admission can greatly enhance the quality of care as well as operational workload efficiency and help with accurate planning for discharges resulting in lowering of various other quality measures such as readmission.”
The solution offers an explicit experience by installing it into Azure subscription. The installation could be done in few clicks and the solution will run on Microsoft Data Science VM (DSVM) that consists of all tools that a data scientist would require. The code is issued in GitHub, therefore if one requires to run on his or her own machine they could simply follow the online instructions available in the website.
Why predicting Length of stay is useful?
- The Hospital Length of stay solution provides ability for a Chief Medical Information Officer (CMIO) to accurately predict which facilities are overflowing and which have space. Based on this, patients with critical needs could be allotted medical needs without any delay
- To the Care Line Manager, who is directly involved with the care of patients, they are required to monitor individual patients by wards while ensuring that the right staff is available to meet specific care for their patients. They are required to accurately predict the staff resources needed to handle the discharge of the patients and thus having a highly trusted system will save the hospital and the patients time and money.
Apart from above there are numerous use cases which are boon to the Healthcare sector. This solution was developed in collaboration with KenSci, a Risk Prediction Platform for Healthcare, built by doctors and data scientists, by leveraging Machine Learning on SQL, Cortana, Azure and Power BI.