Introduction:
Businesses today are turning to data analytics and business intelligence (BI) to gain insights and make better-informed decisions. In the healthcare industry, one organization that has successfully leveraged BI and analytics is the NewYork-Presbyterian Hospital (NYP).
In this article, we will delve into 5 ways NYP has utilized business intelligence and analytics to improve its bottom line and provide insights on how other healthcare organizations can follow in its footsteps.
1. Improved operational efficiency:
NYP utilized BI and analytics to monitor and analyze its operations, this is how they were able to identify bottlenecks, inefficiencies, and waste in its system. With this, they could then optimize their operations by making data-driven decisions based on the findings. For instance, the hospital identified that it took an average of 25 minutes for patients to get their medications. With analytics, NYP was able to reduce this time to 10 minutes, which saved the hospital time and resources.
2. Better revenue management:
Another way in which NYP used BI and analytics was to better manage its revenue. The hospital used revenue cycle analytics to identify patterns in the reimbursement process, including delayed payments and inaccurately billed amounts. By rectifying these issues, NYP was able to streamline revenue management and increase collections.
3. Enhanced patient safety:
NYP also leveraged business intelligence and analytics to improve patient safety, which is very important in the healthcare industry. By analyzing patient data, the hospital could identify potential safety risks and put in place corrective measures. For example, NYP identified that there was a high rate of hospital-acquired infections, which could lead to severe patient outcomes. With this information, the hospital was able to put measures in place to reduce the risk of these infections.
4. Better resource allocation:
NYP also used BI and analytics to identify where resources were allocated within the organization. By analyzing the data, the hospital could see where there were gaps in resource allocation and make appropriate changes. This helped to reduce waste and optimize resource usage.
5. Improved patient satisfaction:
Last but not least, NYP utilized BI and analytics to improve patient satisfaction. The hospital collected and analyzed data to determine key drivers of patient satisfaction and then implemented changes accordingly. For example, NYP identified that wait times were a factor in patient dissatisfaction. By reducing wait times, the hospital was able to see an increase in patient satisfaction scores.
Conclusion:
In conclusion, NYP is an excellent example of how healthcare organizations can leverage BI and analytics to improve their bottom line. The hospital utilized data analytics to monitor and optimize its operations, better manage its revenue, enhance patient safety, optimize resource usage, and improve patient satisfaction. Other healthcare organizations can implement the same strategies by investing in BI and analytics to make data-driven decisions and better position themselves for success.
