Healthcare is an industry with a very low margin for error, so in order to maximize efficiency, providers should utilize data science, writes Sanjeev Agrawal, the president of healthcare and chief marketing officer at healthcare predictive analytics company LeanTaaS, for the Harvard Business Review.
Here are four ways providers can use data science tools to improve their operational efficiency.
1. Operating room scheduling is notoriously inefficient, and block-scheduling through phone calls, email and fax is inexcusable when there are other advanced technologies available. Providers can use cloud computing and predictive analytics to improve OR scheduling and utilize mobile apps to allow patients to directly schedule appointments and enable surgeons to release their blocks more quickly.
2. Predicting infusion center wait times can be tricky, but applying predictive analytics tools and machine learning to optimize schedule templates can not only improve long-term scheduling but also better accommodate last-minute changes such as no-shows.
3. Streamlining emergency department operations with insights from patient data would cut down on patient wait times. Patients are often prescribed multiple procedures such as X-rays and blood drawings, and though the order of those procedures is usually given little thought, analytics-driven software can help determine the most efficient sequence of operations to minimize patient wait times.
4. Providers can use predictive tools to know when a patient in the ED might need to be transferred to a bed in a different unit. These tools can also analyze previously collected data to understand greater trends in onboarding flow and accelerate discharge processes.