relating to medications, laboratory results, and signs and symptoms. Using this tool, it takes a reviewer about 20 minutes to review an average inpatient chart. This low-tech tool has produced consistent, reliable, and relevant data, although the cost of its use is not low (Rozich et al., 2003); indeed, relative to computer screening, the cost per event is very high.
An epidemiological study at Brigham and Women’s Hospital using primary care data collected in 1995–1996 exemplifies some of the different approaches to automated surveillance. This study demonstrated the feasibility of identifying ADEs using automated surveillance of outpatient electronic medical records (Honigman et al., 2001). The study used four different approaches for identifying ADEs:
International Classification of Diseases (ICD)-9 codes—Each patient record is scanned for ICD-9 codes that are often associated with the presence of possible ADEs.
New allergies—An ADE may be present when a patient has a known allergy or a medication is listed as a new allergy. This approach requires knowing the patient’s medications, including dose, interval, and quantity.
Computer detection rules—These are Boolean combinations of medical events, for example, new medication orders or laboratory results outside certain limits that suggest an ADE might be present. One such rule is “If patient is receiving phytonadione (vitamin K) AND on Coumadin, then an ADE may be present.” A list of such rules is given in Box 6-2.
Data mining—Free-text searching of the electronic medical record is used to identify for each medication taken an indication of its known adverse reactions. For the drug type “diuretic,” fatigue is a potential adverse reaction and “drowsiness,” “drowsy,” and “lassitude” are some of the synonyms used instead of the word “fatigue.” Box 6-3 lists some potential adverse reactions (plus synonyms) for the diuretic drug group.
The progress of patients can be monitored as they pass through the care process both to anticipate and protect against circumstances that could lead to adverse events and to implement corrective actions based on analysis of patient injuries discovered in the past. Monitoring systems are particularly important when addressing potential injuries of omission. One example of