According to Paul Cornell, director of the Center for Healthcare and Technology at the University of Memphis, data farming should not be confused with the sometimes controversial data mining, which uses existing de-identified patient data to study marketing patterns. Rather, data farming "grows" data by running thousands of simulations on imaginary patients and imaginary scenarios to find out previously unknown options for providing care.

The Center is also using data farming to look at ways to improve the physical environment to aid nurses, Cornell said. This could include grouping patients together so nurses have less walking around to do, and observing how much will this impact quality of care.

According to Cornell, preliminary results of data farming models have shown it may be possible to make changes that can result in shorter hospital stays, resulting in a positive impact on the bottom line. In addition, if changes can be made to improve a nurse's capacity, the hospital may be able to improve retention of nursing staff and could possibly reduce nurse-to-patient ratios.

"People can make intuitive arguments that if we give them more tools they will do better, but those cost money," Cornell said. Data-farming allows hospital executives an additional bit of information for making decisions about purchasing healthcare IT and making physical changes to the hospital.

Ketcherside said the hospital and the University of Memphis Center for Healthcare Technology will publish a report on what they discover through data farming and it will hold workshops for interested parties on how to do data farming at their facility.