Get staff in step with data collection dance
Get staff in step with data collection dance
Follow new moves to gather infection data
It’s a glaring truth: Infection control monitoring can result in messy data collection if agencies aren’t vigilant.
Some nurses might see a patient twice a week and collect data each time; others might see a patient only once a week. Are these two sets of data comparable?
Also, an experienced nurse might recognize that a patient has an infection based on an unusual symptom, such as irritability; a new nurse might believe the patient is fine because there are no signs of fever or tenderness.
So it’s a mind-boggling task for quality managers to figure out how to make data collection as consistent as possible. Then when you add in a long-term goal of benchmarking the data with other agencies, it turns into a Rubik’s cube.
There is hope on the horizon, however. A group of home care agencies in Missouri have spent the past few years working on an infection surveillance project. So far they have had no statewide results, but the agencies involved now have clean infection control data, which they can use to improve internal processes, quality managers say.
One agency, for instance, discovered a problem with perineal care and was able to correct it after the agency began to monitor indwelling bladder catheter infections.
The group did this with guidance from the Missouri Alliance for Home Care (MAHC) in Jefferson City. It’s a nonprofit organization representing home care agencies.
The group launched its Infection Surveillance Project in 1993 with a goal of benchmarking infection control in home care agencies statewide.
"We decided to start a committee of home care nurses to begin exploring this issue," says Mary Schantz, executive director of Missouri Alliance for Home Care. About a year ago the committee decided to choose one set of criteria and definitions that each agency would use for at least one year while collecting data.
While they’re a long way from reaching their ultimate goal of benchmarking, they have created a tool for measuring data consistently. (See infection surveillance project tools on bladder catheter infection and central venous catheter infection, inserted in this issue.)
Homecare Quality Management asked the Missouri group to share some of its trials and tribulations, and to offer quality managers guidance in creating a protocol for consistent data collection and keeping data collection as clean as possible. (See story on keeping data collection clean, p. 153.)
Here are their suggestions for consistent data collection:
1. Establish goals.
The Missouri Alliance for Home Care Infection Surveillance Project started with the goal of establishing a system for data collection and dissemination of infection surveillance results in comparable home care populations, Schantz says. (See the alliance’s goals and objectives, inserted in this issue.)
"We wanted to improve patient outcomes in the home care setting, and that goal remains the same," Schantz adds.
The committee formally delineated the project’s goals. These are:
• Establish a uniform method of infection surveillance.
• Analyze data.
• Disseminate data and information.
• Apply processes in order to benchmark other home care outcomes data.
Then the committee detailed processes for each objective. For example, under the "Disseminate data and information" objective, the committee wrote that the processes were the following:
• Establish format for results and information presentation.
• Disseminate information through the MAHC office according to the policy of the Infection Surveillance Project.
2. Bring in an expert.
The group sought the advice of Eddie Hedrick, BS, MT(ASCP), CIS, manager of infection control and staff health services at the University of Missouri’s University Hospitals and Clinics in Columbia.
"He’s been involved with infection control, particularly in hospitals, for years and years, and he’s given us ideas and guidance," says Pat Huttegger, RNC, BSN, quality improvement director of the Visiting Nurse Association of Southeast Missouri in Kennett. The agency covers a rural and small-town area and averages more than 70,000 visits a year.
"The sophistication of gathering data and understanding what it means is in its infancy," Hedrick says. "Other groups across the country are doing similar things, and I’ve been trying to hook them all up."
3. Focus; narrow the scope of collection.
More is definitely not better when it comes to data collection.
"You need to try to figure out what are the most likely problems you’re going to have in the environment you’re working in," Hedrick notes. "We send people home with catheters, and these are a common cause of infection."
Hedrick says quality managers should ask themselves what they’re most concerned about in their patient population.
The committee chose two of the more common sources of infection to monitor: central venous catheter infections and bladder catheter infections.
4. Create a definition for each infection measured.
"You need a similar definition of a central line infection," Hedrick says.
The Missouri committee defined the infection occurrence as when the patient has a central venous catheter and two or more of the following six signs and symptoms are present:
• Do you get a positive blood culture?
• Is there a fever of 100.5 or greater?
• Is there purulent drainage from the exit site?
• Is there pain associated with the central line?
• Is there erythema associated with the central line?
• Is there an elevated serum WBC?
The committee’s definition for an acute bladder catheter infection says the patient has an indwelling urethral or suprapubic catheter and a change in the character of the urine, such as hematuria, increasing levels of sediment, and foul odor. There also must be two or more of the following signs and symptoms:
• fever of 100.5 or greater;
• new flank pain or suprapubic pain;
• elevated serum WBC;
• worsening or change in mental status;
• a pathogen or pathogens cultured from the urine.
5. Select measurement standards.
The committee soon ran into trouble with how it was measuring the infection rate. "We started out using 100 days of having a central line to figure the attack rate for infection," Huttegger says. "Now we’ve switched over and are using 1,000 days, so you get whole numbers instead of tenths of whole numbers."
Hedrick recommended the change because the larger measurement standard is what’s being used by hospitals and other organizations that measure infection rates, and therefore would yield comparable numbers.
This clearly defines the measurement tool. And Hedrick says it is far superior to the haphazard way some agencies might collect data, which is to say they had three infections in 10 discharges, resulting in a 30% infection rate.
"The problem is that all the people in the denominator may not have shared in the risk," he explains. "If you’re monitoring central lines and not every patient had a central line, then that dilutes the number."
Hence, the best measuring tool is to use the infection rate per central line days.
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