How predicting patient length of stay enables hospitals to save millions

Extended lengths of stay are a drain on hospital resources, personnel and the bottom line, costing hospitals millions of dollars a year. But by using more unconventional data sources and predictive analytics, hospital administrators are equipped to more accurately predict discharge dates and plan care accordingly.

Recent legislative changes for hospital Medicare reimbursement, specifically the inpatient prospective payment system, incentivize hospitals to promote shorter stays by standardizing payments for procedures performed, regardless of the number of days the patient actually spends in the hospital. This standardization of Medicare reimbursement is forcing hospitals to use resources — such as hospital beds — more efficiently. To achieve this, the hospital must be able to accurately predict a patient's discharge.

Forecasting LOS enables hospitals to identify patients who might be at risk for an extended stay, and subsequently alter a patient's treatment plan from the point of admission to reduce the hospital stay. Predicting LOS also empowers hospitals to improve patient satisfaction by meeting expectations regarding the hospital stay that are set during admission. Finally, it improves hospital resource management by efficiently allocating resources and accommodating more patients with the same volume of resources.

Predictive analytics with Cloudera distribution of Hadoop — an open-source software framework for storing data and running applications — provides hospitals with the means to accurately predict patient LOS.

Cloudera is revolutionizing enterprise data management by offering the first unified platform for big data, an enterprise data hub built on Apache Hadoop. The Cloudera enterprise offers one place to store, access, process, secure and analyze all data that could be used to inform LOS predictions.

Together, partners Intel and Cloudera take the guesswork out of Hadoop. Using a unique collaborative approach, the two deliver excellent performance, security and quality distribution, built on open standards.

Read more on Intel and Cloudera's solution for predicting LOS, including a case study involving a large hospital group, by downloading the whitepaper "Intel and Cloudera Help a Large Hospital Group Allocate Resources by Predicting Patient Length-of-Stay."