We found that ADEs were frequent and that a computerized detection approach could identify these events with moderate sensitivity in a primary care setting that uses an electronic record. In addition to the symptoms involved, these ADEs resulted in many additional ambulatory visits and hospitalization in an important proportion of cases. Many of the ADEs were judged to be preventable. Currently, hospitals do not routinely detect these events.
Most previous studies of ADEs in outpatients used chart review and self-report in cohorts of patients and extrapolated their findings on the basis of total annual visits, to arrive at an estimated occurrence rate.21–33
Our approach uses the information contained in the electronic record to identify incidents that may be associated with ADEs. Compared with manual chart review, this approach to estimating an occurrence rate is faster and much less expensive. The ADE rate we identified undoubtedly represents a lower bound, since our assessment suggests that we missed 42 percent of the ADEs recorded in the medical record; in addition, other work suggests that many ADEs in the ambulatory setting are not even recorded in the medical record.40
Studies of ADEs in ambulatory settings using patient surveys report higher rates of ADEs (30–50 percent).28,29,31,33,40–42
Studies based on chart reviews in small clinic populations in which ADEs are defined as events requiring consultation or therapy generally report a lower incidence (1–3 percent).26,27,30
Kellaway and McCrae31
surveyed patients who were prescribed new medications and had recently been discharged from the hospital, and 41 percent said they “certainly or probably” had a reaction to a drug. Most of these patients, however, also had a significant medical or surgical problem, which initiated the hospitalization, thus making it difficult to definitively assess the relationship between the symptoms and the drugs. Similar problems of causality were encountered in Martys' study of a general practice in England,33
in which 41 percent of patients described adverse events secondary to newly prescribed drugs. Klein et al.29
and Darnell et al.28
used telephone surveys to detect ADEs among patients in a medical clinic and a high-rise building of elderly persons (study populations, 200 to 250) and reported that 30 percent had ADEs. These rates are much higher than our findings, but these samples included high-risk populations. Campbell et al.27
used ICD claims of a 5 percent sampling of a Kaiser population in Oregon and reported an incidence of 3.1 percent for ADEs. Our findings of 2 percent ADEs using ICD-9 claims are similar. In addition, he reported that 30 percent of patients with ADEs required more than two additional clinic visits, a rate twice what we found, but only 0.23 percent of those with ADEs in that study required hospitalization, compared with 9.1 percent in this population.
Several studies identify cardiovascular drugs (including ACE inhibitors), CNS (central nervous system) agents, antibiotics, and diuretics, as the leading causes of ADEs in the outpatient setting.24,26,27
More data (including the associated medications) are available regarding the epidemiology of ADEs in inpatients than in outpatients. ADEs occur in 4 to 7 percent of hospitalized patients.5,7,8,14,18
The proportions of events that are life threatening was reported as being higher (1 to 2 percent) than in this outpatient population, but the incidence of serious and significant events was similar. Nevertheless, even a significant event in an outpatient can result in multiple visits to a clinic or emergency department. For hospitalized patients, ADEs resulted in prolonged length of stay and higher health care costs.7,8
Although we did not do a cost analysis, it is likely that repeated visits to providers will result in higher health care costs as well.
Persons with ADEs in this study were different from those without ADEs. Although they were similar with respect to age, gender, and race, the patients with ADEs had many more visits to their providers, were receiving more drugs, and had more new drugs prescribed. The profiles of those patients with ADEs were also different from the profile reported in studies of inpatients, in the symptoms they manifested and the drugs that caused the ADE.11,13,14,16
This outpatient population had fewer CNS agents producing ADEs, and more ADEs were associated with antihypertensive and antidepressant medications. Drugs used for long-term therapies seemed to have more ADEs associated with their use, perhaps in part reflecting lack of documentation of ADEs associated with short-term therapies. In addition, the frequency of skin manifestations tended to be higher in outpatients whereas the frequencies of CNS and gastrointestinal complaints were similar.
Our finding that 38 percent of outpatient ADEs were preventable was generally similar to the reported proportion in inpatients, which has ranged from 28 to 50 percent.14
Such preventable ADEs represent important opportunities for improvement in quality of care. Most of the ADEs determined to be preventable were found by the allergy rule. Allergy prevention is an area that can readily be addressed by alerts delivered using computerized prescribing. However, even with this system in the inpatient setting, drugs to which patients were allergic were still not only ordered but administered.42
This occurred because providers frequently failed to add new allergy information into the medical record. Other types of decision support that may be useful are alerts about drug–drug interactions, interpretation of critical laboratory results, and laboratory results in relation to drugs prescribed, dose limits, and guided dosing algorithms.43
In addition to computer decision support, pharmacists represent an important safety net, especially in the outpatient setting, in which education is pivotal.
The tool we used could be improved further; several aspects of the search process deserve mention. ICD-9 terms identifying ADEs—such as E codes (mechanism of illness or injury), which are specific to drug events—were not routinely used by the physicians at the study institution. The list of ICD-9 codes included some for nonspecific allergic reactions, such as allergic rhinitis and conjunctivitis and adverse reactions to food substances [693.1–693.9] rather than being specific for drug events. In addition, physicians often used these codes inappropriately. If coding were more accurate and if the list of ICD-9 codes were narrowed to be more drug oriented, the sensitivity of this search method would be higher.
Not surprisingly, recording a new allergy to a medication or prescribing a medication to which the patient was allergic can be a very sensitive marker for adverse events. However, in this electronic medical record, true allergies were not separated from sensitivities such as nausea due to codeine or erythromycin. Although not true allergies, drug sensitivities are often listed by the provider and entered into the electronic medical record as allergies, reducing the specificity of this method.
We modified the computer rules for inpatient ADE detection described by Jha et al.,16
in order to use them in an outpatient practice. After being piloted, some of the rules required modification, while others were eliminated because of different practice patterns or less frequent use of some laboratory tests. Many of these rules would require additional modification to be more sensitive in ambulatory settings.
Textual searching of the electronic medical record is potentially important because it requires only that dictated text be available electronically. This detection method required major modifications, since the first searches yielded a database with too many “hits.” Some of these adjustments included eliminating sentences with negative terms (e.g., “no,” “not”) or ambiguous terms (e.g., “rule out”), limiting the terms used for adverse events (“e.g., ovarian disease,” “cancer”) and adjusting for terms that are used for adverse events and primary conditions (e.g., “swelling,” “rash,” “irritation”). The PPV remained low even after these modifications.
Since ADEs are both costly and frequent43–46
and represent an important aspect of quality of care,15
many attempts at providing better monitoring of these events at a lower cost have been attempted. Our program for ADE detection expanded on some of those developed earlier by Classen et al.18
and Bates et al.43
by including a greater breadth of detection approaches.
This study has a number of limitations. It was performed at only one institution, so the results may not be generalizable to other outpatient settings. However, previous studies provide evidence that these events are common. In addition, this institution had an advanced electronic medical record, which provided access to multiple patient events. Collating and reformatting electronic information may not be possible in all institutions, since most such records are currently not coded; however, most electronic information can be reformatted to be searched by this approach.
The searches undoubtedly missed many events that were documented; thus, the sensitivity could be improved. Furthermore, many other events were probably not noted in the record40
—in particular, telephone contacts, which are variably documented. In addition, only utilization that occurred within this network could be identified.
Another limitation is that only those medications prescribed at these outpatient settings were analyzed. Over-the-counter medications, which may have also caused adverse events, were not investigated. The lexicon used for text searching was in the early stages of development. By including only the most common important adverse effects, the sensitivity would have been improved. Also, the point estimates for sensitivity and specificity, especially for sensitivity, are uncertain. Finally, the PPV of the rules was only 7 percent, which is good enough for signal detection but not sufficient for use as a quality monitor. If this proportion could be improved to 80 percent , for example, it might be possible to use this as an independent quality tool.