Medical devices; general hospital and personal use devices; classification of remote medication management system. Final rule.

The Food and Drug Administration (FDA) is classifying the remote medication management systems into class II (special controls). Elsewhere in this issue of the Federal Register, FDA is announcing the availability of a guidance document entitled, "Guidance for Industry and Food and Drug Administration Staff; Class II Special Controls Guidance Document: Remote Medication Management System," which will serve as the special control for this device type. The agency is classifying this device type into class II (special controls) in order to provide a reasonable assurance of safety and effectiveness of these devices.

Findings from the ISMP Medication Safety Self-Assessment for hospitals.

BACKGROUND: Hospital medication practices should be assessed, awareness of the characteristics of a safe medication system heightened, and baseline data to identify national priorities established. DESIGN: A cross-sectional survey of U.S. hospitals (N = 6,180) was conducted in May 2000. The survey instrument contained 194 self-assessment items organized into 20 core characteristics and 10 larger domains. Hospitals were asked to voluntarily submit their confidential assessment data to the Institute for Safe Medication Practices (ISMP) for aggregate analysis. METHOD: A weighting structure was applied to the individual items and used to calculate core characteristic scores, domain scores, and overall self-assessment scores. These scores were then compared to identify areas most in need of improvement. RESULTS: The 1,435 participating hospitals scored highest in domains related to drug storage and distribution; environmental factors; infusion pumps; and medication labeling, packaging, and nomenclature issues. These hospitals scored lowest in domains related to accessible patient information, communication of medication orders, patient education, and quality processes such as double-check systems and organizational culture. CONCLUSIONS: Enormous opportunities exist to improve medication safety, especially in domains related to culture, information management, and communication.

Prioritizing strategies for preventing medication errors and adverse drug events in pediatric inpatients.

OBJECTIVES: Medication errors in pediatric inpatients occur at similar rates as in adults but have 3 times the potential to cause harm. Error prevention strategies in this setting remain largely untested. The objective of this study was to classify the major types of medication errors in pediatric inpatients and to determine which strategies might most effectively prevent them. METHODS: A prospective cohort study was conducted of 1020 patients who were admitted to 2 academic medical centers during a 6-week period in April and May 1999. Medication errors were characterized by subtype. Physician raters evaluated error prevention strategies and identified those that might be most effective in preventing errors. RESULTS: Of 10 778 medication orders reviewed, 616 contained errors. Of these, 120 (19.5%) were classified as potentially harmful, including 115 potential adverse drug events (18.7%) and 5 preventable adverse drug events (0.8%). Most errors occurred at the ordering stage (74%) and involved errors in dosing (28%), route (18%), or frequency (9%). Three interventions might have prevented most potentially harmful errors: 1) computerized physician order entry with clinical decision support systems (76%); 2) ward-based clinical pharmacists (81%); and 3) improved communication among physicians, nurses, and pharmacists (86%). Interrater reliability of error prevention strategy assignment was good (agreement: 0.92; kappa: 0.82). CONCLUSIONS: Of the assessed interventions, computerized physician order entry with clinical decision support systems; ward-based clinical pharmacists; and improved communication among physicians, nurses, and pharmacists had the greatest potential to reduce medication errors in pediatric inpatients. Development, implementation, and assessment of such interventions in the pediatric inpatient setting are needed.

Development of a chronic disease indicator score using a Veterans Affairs Medical Center medication database. IMPROVE Investigators.

OBJECTIVE: Develop a chronic disease index that approximates the number of chronic diseases a patient has using a medication database. METHODS: An expert panel determined whether specific medication classes could be indicative of a chronic disease. Those classes identified were incorporated into a computer program and then used to screen the medication records of 246 randomly selected patients to estimate the number of chronic diseases present in each patient. This number was designated as the chronic disease index (CDI). The CDI was then validated against chart review. The CDI and a measure of disease severity, the chronic disease score (CDS) also were compared. The sensitivity and specificity of the computer program was analyzed for seven common chronic diseases. RESULTS: The expert panel designated 54 drug classes containing medications used to treat chronic diseases. The CDI correlated moderately with the number of chronic diseases found via chart review (r = 0.65; P = 0.001) and highly with the CDS (r = 0.81; P = 0.001). The index predicted the presence of three common diseases with a sensitivity of > or = 75%, and of six common diseases with a specificity of > or = 75%. CONCLUSIONS: The CDI correlates moderately well with the actual number of chronic disease states present. This tool may be useful for researchers when trying to identify patients with specific diseases and also for risk adjustment.