How Analytics Can Help You Improve Quality and Reduce Costs

I found a terrific example of the use of "Big Data" in Fast Company magazine this month.   The article by Farhad Manjoo describes a situation at Washington Hospital Center.   ER doctors became concerned that many patients returned to the hospital just a short time after being discharged.  A computer scientist at Microsoft Research began to investigate.  He wanted to identify some triggers that would predict whether a patient would be readmitted.  Specifically, he was looking to help doctors identify some predictors that might not otherwise receive much attention by ER physicians and nurses.  He analyzed more than 300,000 ER visits.    Among other things, he discovered that the length of a patient's stay in ER tended to be a good predictor of readmission.  If a patient stayed in the ER for more than 14 hours, they were likely to return to the hospital within a few weeks.  Similarly, if the patient's chart mentioned the word "fluid" at some point, that seemed to predict readmission quite well too.  

This story illustrates how companies can use analytics to help them understand how to improve the quality of customer service, as well as to reduce costs.  Take an automobile dealer.   They conduct repair and maintenance on thousands of cars per year.  A fair number of those cars return shortly after a repair or maintenance appointment, because something is not working correctly or hasn't been done to the customer's satisfaction.   An automobile dealer could analyze the data from thousands of those cases, and it could try to identify the predictors of return visits.  If they could identify a few solid predictors, then they could try to intervene to reduce those return visits.  Those interventions could improve quality and customer satisfaction, while reduce costs (since every return visit is costly).   Many service businesses could apply a similar logic and use analytics to achieve positive results.   Can your company benefit from such an approach?