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“A prescription is a treatment plan. And that treatment plan is, in its most general sense, an algorithm,” says Ian Brooks, who leads a health science research group at the National Center for Supercomputing Applications at the University of Illinois. “So you can apply the same processes to a prescription as you can to a computer science program.”

ILLINOIS (US)—Software design principles and debugging methods are helping researchers identify a way to reduce the number of injuries and deaths related to errors in how drugs are administered to hospital patients.

At a pilot hospital, researchers report the approach reduced the number of severe incidents related to pain management to zero.

“A prescription is a treatment plan. And that treatment plan is, in its most general sense, an algorithm,” says Ian Brooks, who leads a health science research group at the National Center for Supercomputing Applications at the University of Illinois.

“So you can apply the same processes to a prescription as you can to a computer science program.”

Over a five year period, the research team looked at prescriptions as a “medical algorithm,” a precise set of rules for solving a problem, and then created and debugged a pain management protocol for adult patients at OSF Saint Francis Medical Center.

Once anesthesia and initial surgical pain medicines were out of the patient’s system, non-opioid analgesics (such as acetaminophen, ibuprofen, or ketorolac) were administered on a fixed round-the-clock schedule, cutting the patients’ opioid requirements in half.

The potent opioid fentanyl was then given through a subcutaneous catheter—avoiding the interruptions that can occur with intravenous administration of drugs. The fentanyl was provided via a patient–controlled pump, allowing the patient to have more control over pain relief.

Patients’ pain severity was assessed on a fixed schedule with a “pain scale”—a device that looks like an old-fashioned slide rule.

Patients slid the marker to indicate their pain level, from no pain at the left to intolerable pain at the far right. The nurse would record the corresponding number on a prescription form and follow the specified protocol for that pain level. The amount of oxygen in each patient’s blood also was monitored, to catch early signs of a bad opioid reaction.

The pain “algorithm” also included orders to handle common post-surgical complaints, such as nausea and constipation, and detailed instructions for recognizing and responding to severe opioid–associated adverse drug events.

The researchers called the results astounding. While there were seven severe or fatal adverse drug events (ADEs) in one month during the study’s first year, as the protocols were introduced and consistently followed, the number steadily declined, reaching zero for the study’s final six months.

These results were published in Clinical Pharmacology and Therapeutics. After the initial study concluded in December 2002, the protocols were implemented hospital-wide. In the more than six years since, the hospital still has not experienced a single adverse drug event relating to opioid prescriptions.

Brooks says the protocol worked in part because it empowered nurses to rapidly respond, easily converting pain measurements into direct action.

“The ward nurses loved it,” he says.

The protocol also introduced around-the-clock use of common non-prescription painkillers that have a lower incidence of adverse effects. Maintaining a steady dose of those analgesics aided patients in managing their pain, often reducing a patient’s need for stronger painkillers.

With the increasing use of computers in hospital wards and the push for the expansion of electronic medical records, Brooks believes the time is right to implement digital prescription protocols.

Researchers from the University of Illinois College of Medicine in Peoria, OSF Saint Francis Medical Center, and Jesse Brown Veterans Affairs Medical Center in Chicago contributed to the study.

University of Illinois news: www.ncsa.illinois.edu/News/