A recent study found that 22 adverse drug events—half of which were preventable—occurred for every 100 nursing home residents within a one-year period. The Fleetwood Model is designed to aid consultant pharmacists working in long-term care facilities. The model relies on prospective review of patients deemed to be at risk for medication problems, and Web-based software to enhance communication between dispensing pharmacists and those working at nursing homes.
Organizations: Brown Medical School and American Society of Consultant Pharmacists, Research and Education Foundation
Date of Implementation: January 2004
Intended for: Clinical Pharmacists
Target Population: Nursing Home Residents
The issue: Medication errors that cause injury, permanent impairment, or even death are prevalent in the elderly population due to their high use of prescribed drugs and the physiological changes associated with aging. Adverse drug events, which can result from inappropriate medication, over-medication, or under-medication, are common in nursing homes, where the average resident takes six different medications and 20 percent take at least 10. A recent study found that 22 adverse drug events—half of which were preventable—occurred for every 100 nursing home residents within a one-year period. Beyond their health implications, these prescription errors have associated treatment costs, estimated at $2 for every $1 spent on medications. Even though the Centers for Medicare and Medicaid Services (CMS) requires consultant pharmacists to perform monthly drug regimen reviews for each nursing home resident, problems remain. The reviews typically occur retrospectively, leaving nursing home residents at risk for an adverse drug event during their first month of residence. In addition, consultant pharmacists have large caseloads, up to 1,000 residents, and often do not have time to do a comprehensive review.
The intervention: This is where a prospective drug management program developed by the American Society of Consultant Pharmacists comes in. Currently in its third phase, the Fleetwood Project has created a new model of practice for consultant pharmacists working in long-term care facilities. It is based on a prospective review of patients who are at high risk for medication-related problems.
The first phase of the project evaluated the cost of medication errors and the benefits of consultant pharmacist review of nursing home residents' drug regimens. It found that consultant pharmacists increased the number of patients experiencing an optimal outcome by 43 percent and reduced medication-related costs by $3.6 billion annually. The second phase demonstrated the feasibility of implementing the Fleetwood Model in long-term care pharmacy practice. In January 2004, the third phase was implemented at 26 North Carolina nursing homes.
Kate Lapane, Ph.D., an assistant professor of medical science at Brown University and director of this phase of the project, worked with a software vendor to develop a real-time algorithm that identifies residents at high-risk for medication-related problems. The various risk factors for each resident are calculated based on their prescription and over-the-counter medications, and residents with a total greater than or equal to four are labeled as "high risk." A resident, for example, who receives an opioid, antidepressant, muscle relaxant, and five other medications would be labeled high risk. A preliminary screening of residents at 30 nursing homes found that from 15 to 48 percent would be considered high risk, for a median of 33 percent. It also found that the medication class most likely to trigger a chart review was the use of seven or more medications, with one medication being an antidepressant. A baseline assessment of potentially inappropriate medication use ranged from zero to 13.2 percent.
Prior to implementing the intervention, Lapane developed evidence-based treatment algorithms that pharmacists can use to make clinical recommendations in response to problems identified by the automated review process. Ticlopidine, for example, is not appropriate for use in the elderly. If a patient has been prescribed this medication for stroke prevention, the algorithm suggests that the pharmacist recommend aspirin/dipyridamole, aspirin, or clopidogrel as possible alternatives. In addition, Web-based software was created to enhance communication between dispensing pharmacists and those working at nursing homes. Using the software, dispensing pharmacists can enter current medication data, such as their recommendations for treatment, into a patient's file and this data will be available to the consultant pharmacist the next day.
The project also aims to encourage consultant pharmacists to spend more time evaluating patients and communicating directly with prescribing physicians. While this model of care demands greater pharmacist involvement in planning and delivering care, there are no incentives under the current payment structure for them to do so. It is envisioned that the dispensing pharmacist, based on the automated algorithms, will take responsibility for alerting prescribing physicians of medication problems and free up the consultant pharmacists for in-person consults with patients and physicians. Staff shortages, particularly of dispensing pharmacists, might work against this ideal. However, because the model utilizes more of dispensing pharmacists' skills, project leaders are optimistic that their participation in this process could enhance job satisfaction. The third phase of this project will evaluate the extent to which the model can be practical and effective.