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From the August 2006 Issue
Building a Safety Net The Cure for the Fatally Flawed EMR Software Model
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Building a Safety Net By leveraging huge amounts of data and applying it to a wide array of projects and purposes, hospitals stay focused on patient safety and make headway. By Richard R. Rogoski, Contributing Editor
Whether it’s reducing medication errors or monitoring the onset of
symptoms to facilitate treatment protocols, clinicians are tapping into
huge databases for their answers. But, to achieve the desired results,
hospitals need to invest in newer clinical systems that feature
medication reference databases or find new uses for existing databases,
like those that are integral parts of electronic medical records. For Opelousas General Health System (OGHS) in Opelousas, La., the
solution came from Mountain View, Calif-based Omnicell Inc. “We were
looking for a product to improve patient safety and reduce medication
errors in our facility,” says Jared Lormand, OGHS’s chief information
officer. “We needed a product that would simplify the process and
automate our medication administration by using bar codes.” Interestingly, poor communication problems between nurses and the
pharmacy were one of the issues contributing to the organization’s
medication error rates, Lormand says, and, the situation wasn’t helped
by evenings and night shifts, when typically no on-site pharmacist is
available. But Donna Copper, R.N., OGHS’s chief nursing officer, says
even when a pharmacist was available, there were “multiple phone calls
and multiple questions.” In many cases, the questions pertained to the
appropriateness of specific drugs or a request to clarify an individual
order. And on occasion, there was also finger pointing, according to
Lormand. By installing a system that uses an automated MAR (Medication
Administration Record) and provides nurses with alerts as to possible
drug/drug, drug/food or drug/allergy interactions, the human factor and,
therefore, the possibility of human error, was taken out of the
equation, Copper says. OGHS began rolling out the bulk of Omnicell’s MedGuard system between
2003 and 2005, according to Lormand. The hospital first invested in the
vendor’s medication dispensing cabinets, then purchased SafetyMed RN, a
nursing workflow automation solution for the bedside that uses bar
coding, and then SafetyPak, a barcode medication packaging system. In
addition, OGHS installed OmniLinkRx, which currently allows physician
orders to be electronically faxed into the pharmacy’s system. “We’re
considering buying a CPOE (computerized physician order entry) system,
but for our size organization, price is a consideration. At 193 beds, we
can’t afford to buy the latest and greatest software each year. We have
to alternate our capital purchases with building buildings and
installing the latest diagnostic equipment.” Plus, he notes, “With the
best-of-breed technology we have here, finding a CPOE that plays well
with other systems is hard to do.” Process Improvements Not only does the system eliminate those parts of the process where
human error can cause problems, but it greatly simplifies the entire
process. Prior to rolling out this automated system, physicians would
write their orders and nurses would fax the orders to the pharmacist,
who would then enter each order into the McKesson pharmacy information
system, and then file away the paper fax, Lormand says. After medication
labels were printed and the medication cart filled, the nurses would use
a paper MAR to verify which drugs were to be given to which patient. Now, after the physician signs an order, it’s electronically faxed
directly into the pharmacy’s dual monitor workstation, Lormand explains.
Then, while viewing the electronic physician order on one monitor, the
pharmacist enters the order into the pharmacy system on the other. A
message is automatically sent to the SafetyPak system, which prints out
and affixes bar-code labels onto each patient’s individually wrapped
medication. When it’s time to dispense these medications, the nurse logs into the
system and scans her badge, which brings up her list of patients. Then,
she scans the bar code on the patient’s wrist band, which brings up a
list of all meds to be administered to that patient. Once the nurse
scans the bar code on the medication package, the system automatically
checks the “five rights” (right patient, right medication, right dose,
right time and right route). “If there’s an error or an alert, she calls
the pharmacy immediately,” Lormand says. Overcoming Hesitancy
Taking extra time at the bedside and automating the entire
medication-use process by using an end-to-end system with built-in
alerts has definitely paid off for OGHS. Because most common errors
involved drugs that look alike or sound alike, Lormand says, “We have
seen a 66 percent reduction in medication errors housewide.” In
addition, the Omnicell solution has reduced by one-half the amount of
time required for a pharmacist to fill orders, which now allows the
pharmacist to spend more time on the floor as an integral part of the
healthcare delivery team. Analyzing Data Relying on an early X-Windows (UNIX) based EMR from San Diego, Calif-based CliniComp
International, Kapiolani Medical Center, which delivers about 5,000
babies per year, initiated a program called the Center for Health
Outcomes, designed to promote and support physician-directed quality
improvement. “It’s to answer questions about the care being provided,”
says Ashton, “and it’s the physicians who are asking the questions.”
Between 30 and 40 physicians have been involved in this project since it
was launched in early 2004. By combining CliniComp’s clinical documentation and EMR solutions with
ICD-9 codes, financials, and infection control data, the hospital has
been able to track key disease factors in order to deliver better
long-term outcomes. Ashton says the program consists of four major
projects. Data as a Foundation for Improvement Hawaii has three times the national rate of jaundice in newborns, Ashton
notes. But as a result of this screening program, the highest levels of
jaundice were eliminated. There are no babies with a bilirubin count
over 24, which characterizes severe jaundice, and fewer babies with a
bilirubin count over 20 compared to babies who were not part of the
screening program. The results of the study even had an effect on Ashton
herself. “I used to be less concerned about jaundice,” she says. “But
now, I find myself paying closer attention to those babies at higher
risk.” The Newborn Special Care Nutrition Management Program was designed to
reduce the risk of complications in babies fed intravenously for more
than 14 days; the goal was to accelerate the conversion to oral feeding.
Evaluation of three years worth of data pertaining to the care of
premature babies began in 2001, but the project was actually launched in
2004. Several definite patterns emerged from this study, leading to the
creation of standards for the way babies are fed in the newborn special
care unit (NSCU). As a result, IV feedings were reduced from 20 days to
11 days, and the infection rate dropped dramatically. Ashton says that
the CliniComp system allowed for “the standardization of the approach,
and also allowed us to look at the results of these standards.” A project to reduce nosocomial infections in the NSCU was actually part
of the hospital’s contribution to the Institute for Healthcare
Improvement’s “100,000 Lives Campaign,” this project was begun in the
fall of 2005. The EMR can be mined for data to indicate when
improvements in care have been successful. Better central line
management and an emphasis on hand washing resulted in a significant
reduction in hospital-acquired infections, Ashton notes. Finally, a project to reduce infection rates in laboring patients began
in early 2004 and continues today. This program’s goal is to reduce
infection rates among women in labor. “We tried to understand the
factors involved in women developing fevers during labor,” Ashton
explains. “Fever likely represents an infection that needs to be
treated.” Infection rates during labor are about 6 percent nationwide
and are usually caused by bacteria, she says. But while the mother may
have the infection, her child also is at greater risk for the same
infection. As a result of this study thus far, Kapiolani Medical Center has
improved the way it induces labor and the way it administers epidurals,
Ashton says. Tracking both mothers and babies required tapping into huge
amounts of data, but as Ashton notes, “We used the CliniComp system to
gather the data and mine the data. We wanted to make sure we were not
missing any infected babies.” The emphasis of each of the projects was to improve patient safety, so collectively, the four projects showed physicians where improvements were needed. There was little resistance on the parts of these physicians to make the necessary changes to improve healthcare outcomes. “Once they understand the data, they can change their practices,” says Ashton. “Having data on our own patients changes their minds.”
For more information on Medi-Span from Wolters Kluwer Health,
For more information about Essentris and other patient safety
solutions from CliniComp, For more information about MedGuard, SafetyMed RN and other
patient safety solutions from Omnicell,
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