Hospital de Santa Bárbara

To read a Spanish version of this case study, please click here.

The client: Santa Bárbara Hospital’s Research Unit

Santa Bárbara Hospital was built in 1973 and has been refurbished and extended in recent years. It currently has 180 beds and close to 500 employees to care for more than 90,000 people in its catchment area, Puertollano.

The challenge: effective data handling

Santa Bárbara Hospital’s Research Unit required a statistical system that could be used to handle all of the information produced by its research and studies, in doctoral theses and consultations, and in its management projects.

The solution: IBM SPSS predictive analytics software

The key to achieving the effective processing of statistical data is having a predictive analytics solution, especially one that can take into account the large volume of data in scientific research. IBM SPSS Statistics was the best option available on the market. Dr. Villar, who works in the hospital’s Research Unit, believes that the final decision to acquire and introduce IBM® SPSS® Statistics software came as a result of taking part in a Clinical Research Methodology Diploma Course in the UAM’s Public Health University Center in Madrid in 1998. He says that: “during the course we were instructed in the use of certain advanced statistical tests including multivariate analysis techniques. From that time onwards I realized that, from my point of view, IBM SPSS Statistics is the most useful statistics program for Health Sciences.”

Thanks to IBM SPSS Statistics’ predictive applications, a large number of conclusions have been reached that have served to confirm theories and open new lines of research in such vital fields as the cardiovascular system (research on deep vein thrombosis), oncology (focused on colon cancer) and respiratory disease (looking at Chronic Obstructive Pulmonary Disease).

The Research Unit’s expectations of the software have been more than satisfied. In fact, Dr. Villar stated that “IBM SPSS Statistics is a fundamental tool for the analysis and presentation of research results.” Equally, IBM SPSS’ customer service has been exceptional. “All of the doubts I have encountered with the software were solved and I have been kept informed and invited, from time to time, to courses, presentations of new versions and other useful activities.”

Advantages: benefits for future patients and ease of installation

Dr. Villar stresses that: “Clinical research is aimed at the prevention, dynamics, frequency, distribution, determinants and characteristics of illnesses. It also focuses on the means to appropriately prevent, diagnose, predict and treat the people affected, and discovering the adverse effects on patients of any treatments.” For those reasons, effective data handling with predictive analysis has been very beneficial. In our research projects, IBM SPSS Statistics software has been used for the following studies:

DVT (deep vein thrombosis) is a rather common condition that can have fatal consequences. DVT is the formation of blood clots in a deep vein, which, if not detected in time, can travel through the veins to the lungs and cause an embolism. Using IBM SPSS Statistics software to analyze data about DVT allowed researchers to establish a new, reliable diagnostic model for the illness.

In colon cancer, researchers confirmed that it affects more patients between 75-79 years of age, being most prevalent in nearly 44 percent of cases. Analysis of the data has shown that no clear link could be drawn for this illness between the risk factors of smoking, dyslipidemia (elevated blood levels of cholesterol and triglyceride) and obesity.

Finally, IBM SPSS Statistics was used to conduct research predicting mortality rates in patients with Chronic Obstructive Pulmonary Disease. The conclusion was that patients with a BODE index (a measure derived from body-mass index, the degree of airflow obstruction, dyspnea – shortness of breath – and exercise capacity) at or above seven have an estimated mortality rate of 80 percent at 48 months, showing the negative influence on this illness of being overweight.

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