By Jill Freeman-Stack

East Alabama Medical Center (EAMC), a 352-bed regional hospital in Opelika, Ala, serves a five-county area. EAMCs infection control professionals work hard to identify and prevent hospital-acquired infections (HAIs).

EAMCs infection identification and prevention efforts centered for many years on traditional methods: manual targeted surveillance of infection data. This work required the time-consuming manual review of patient charts and lab reports in order to find the source of each infection.

According to Benja Morgan, RN, BA, MPA, infection control and employee health manager at EAMC, the paper chase was a daily challenge. You got lost in a paper shuffle, Morgan says. I would go to the lab and pick up the reports and then visit the floors to find the patient. Were the patients still in the hospital? Had they gone home? Had they been moved five times? I had to wear a detective hat, and the work consumed a large amount of time. The delays just compounded the problems.

In January 2004, the hospital adopted the Data Mining Surveillance® service (DMSS) from MedMined of Birmingham, Ala. The DMSS uses a combination of database technology, machine learning, statistical analysis, and modeling techniques to find patterns and subtle relationships in data. The service features the Nosocomial Infection Marker (NIM), an objective, electronic surrogate marker for HAIs. Data mining identifies patterns within hospital data without predefined search criteria that indicate specific opportunities to improve patient care processes.

Morgan says that her introduction to the service and its potential to reduce infection rates, save staff time, and reduce costs was impressive. The service electronically provides infection-related data to the hospitals clinical staff so that the daily work of monitoring for HAIs and antibiotic resistance, performing public health reporting, generating reports for medical and administrative staff, and other activities can be performed electronically and efficiently. It can track significant organisms, sites of infections, facility locations, physicians, and antimicrobial resistance in any combination.

With the support of the director of quality management services and other key executives at EAMC, Morgan planned to adopt the technology as part of the hospitals capital acquisition strategy. However, the service came to EAMC sooner than expected. The hospital was asked to partner with Blue Cross and Blue Shield of Alabama, other Alabama hospitals, and MedMined in the Alabama Hospital Quality Initiative (AHQI) to reduce the incidence of HAIs and improve patient safety.

Installation and training were straightforward, and information on HAIs was almost immediately available. As part of the hospitals commitment to the monitoring technology, Nancy Patterson, RN, BSN, outcomes coordinator for quality management, joined Morgan shortly after the service went online to handle the data monitoring and reports, freeing Morgan to handle the range of infection control and prevention tasks, clinical questions, and emergencies that surface daily.

We started seeing the issues identified by DMSS patterns and taking the information to the units shortly after the service went online, Patterson says. The service provides almost instantaneous availability of information. Every day, we pull up a hospital-wide culture report so that we can survey what is going on throughout the facility. I can go through a list of current patients, see what cultures are out there, their status, and where the cultures came from. The system has helped us reduce the time spent reviewing data tenfold.

The availability of real-time, house-wide information has been a tremendous aid in the hospitals battle against HAIs. According to Morgan, the service allows the presentation of timely feedback to staff members. We can get the information out to the floor and take care of the patient as soon as possible, she says. It is not as if they had a patient on the floor last week with an HAI and we are just finding out about it. It is a current patient. If there is an issue to address, we can do it quickly instead of retroactively.

After using the system for approximately 13 months, the hospital analyzed financial data and was able to demonstrate a significant reduction in infection rates and the high costs associated with treating them. For example, during a nine-month baseline period from March 2004 through November 2004, there were 54 urinary tract infections (UTIs) in one skilled nursing unit. Based on 667 unique admissions to the unit, the hospital-acquired UTI rate was 8.1 percent. In contrast, during a three-month active surveillance period between December 2004 and February 2005, there were only six hospital-acquired UTIs. Based upon 280 unique admissions to the unit, the hospital-acquired UTI rate was 2.14 percent a 73.3 percent reduction rate.

In addition to its positive effect on the quality of care, the technology has impacted the financial bottom line at EAMC, evident through the cost-savings that resulted from its use of the automated surveillance service. In the year since Data Mining Surveillance began, infection rates across the hospital have fallen 12.33 percent. EAMCs cost accounting system data were used to compare patients with an HAI with those without an HAI in the same diagnosis-related group (DRG). Patients with an HAI had relatively higher variable costs and lengths of stay. With little offsetting reimbursement of the extra costs, those patients were incrementally more unprofitable than patients without HAIs in the same DRG. The drop in both the rate of infection and average impact per infection resulted in 427 fewer patient days, a $303,350 reduction in variable costs, and a $226,789 improvement in net operating profits.

Morgan says that being able to quantify the costs associated with HAIs and the savings that result from the hospitals use of the infectiontracking technology have helped the executive staff better understand the scope and impact of HAIs. Patterson adds, For the first time, we have been able to demonstrate in real numbers comparative statistics showing the financial impact of HAIs and quality improvement measures. We can tie dollars to infections and show how infection control will impact the financial bottom line.

Jill Freeman-Stack is a senior program director at Sullivan & Associates, a strategic healthcare communications organization located in Huntington Beach, Calif.

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