Ciudad Real Hospital

A Spanish hospital is using predictive analytics to make significant improvements in the treatment of severe eating disorders

Published on 29-Jun-2011

Validated on 16 Dec 2013

"In our opinion we were provided with enough support and it met our needs to incorporate this solution into the work we were beginning." - Dr. Luis Beato Fernández, Ciudad Real Hospital

Customer:
Ciudad Real Hospital

Industry:
Healthcare

Deployment country:
Spain

Solution:
BA - Business Analytics, BA - Business Intelligence, Smarter Planet

Smarter Planet:
Smarter Healthcare

Overview

Hospital General Universitario de Ciudad Real (Ciudad Real Hospital) is a teaching hospital approximately 125 miles south of Madrid that operates in close conjunction with the neighboring University of Castilla-LaMancha. While the original Ciudad Real Hospital dates to 1796, the latest iteration of this institution opened its doors in 2006 in the form of an expansive hospital complex that has established itself as one of the top hospitals in Spain.

Business need:
The hospital wanted to identify positive and negative prognosis factors in long-term monitoring of patients being treated for serious eating disorders, such as anorexia and bulimia. Because such disorders affect almost 3 percent of Spain’s population, the goal was an urgent one. But due to the high number of variables that potentially factor into prognosis, the hospital had been unable to execute the complex statistical analysis required to identify those that were most important. A more powerful solution was needed.

Solution:
The ability to effectively handle and analyze data is essential to diagnosing illnesses earlier and speeding patients to recovery. The hospital implemented a powerful predictive analytics solution that enabled its practitioners to establish reliable forecasting, control and early diagnosis variables for patients with severe eating disorders. The solution provides more accurate initial patient evaluations, helping to identify specific subgroups for which initial interventions should lead to more successful treatment outcomes. The solution is also pointing the way toward new lines of research.

Benefits:
- Enabled 100 percent improvement in data handling for more accurate initial patient evaluations, helping to develop more successful treatment outcomes - Uncovered specific links between patients’ expectations and treatment results - Helped identify new lines of research to be explored

Case Study

Hospital General Universitario de Ciudad Real (Ciudad Real Hospital) is a teaching hospital approximately 125 miles south of Madrid that operates in close conjunction with the neighboring University of Castilla-LaMancha. While the original Ciudad Real Hospital dates to 1796, the latest iteration of this institution opened its doors in 2006 in the form of an expansive hospital complex that has established itself as one of the top hospitals in Spain.

The Opportunity
The hospital wanted to identify positive and negative prognosis factors in long-term monitoring of patients being treated for serious eating disorders, such as anorexia and bulimia. Because such disorders affect almost 3 percent of Spain’s population, the goal was an urgent one. But due to the high number of variables that potentially factor into prognosis, the hospital had been unable to execute the complex statistical analysis required to identify those that were most important. A more powerful solution was needed.

What Makes it Smarter
The ability to effectively handle and analyze data is essential to diagnosing illnesses earlier and speeding patients to recovery. The hospital implemented a powerful predictive analytics solution that enabled its practitioners to establish reliable forecasting, control and early diagnosis variables for patients with severe eating disorders. The solution provides more accurate initial patient evaluations, helping to identify specific subgroups for which initial interventions should lead to more successful treatment outcomes. The solution is also pointing the way toward new lines of research.

What if you could know in advance which patients would benefit most from initial interventions?

Real Business Results
- Enabled 100 percent improvement in data handling for more accurate initial patient evaluations, helping to develop more successful treatment outcomes
- Uncovered specific links between patients’ expectations and treatment results
- Helped identify new lines of research to be explored

Products and services used

IBM products and services that were used in this case study.

Software:
SPSS Modeler, SPSS Statistics Base

Legal Information

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