You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Detecting adverse events for patient safety research: a review of current methodologies 
Chapter Title:  Observers 
1. Abstract of Cited Paper (BIB001):  Objectives The purpose of this study was to investigate the nature and causes of human errors in the intensive care unit (ICU), adopting approaches proposed by human factors engineering. The basic assumption was that errors occur and follow a pattern that can be uncovered.Design Concurrent incident 
2. Abstract of Cited Paper (BIB002):  BACKGROUND ::: Data about the frequency of adverse events related to inappropriate care in hospitals come from studies of medical records as if they represented a true record of adverse events. In a prospective, observational design we analysed discussion of adverse events during the care of all patients admitted to three units of a large, urban teaching hospital affiliated to a university medical school. Discussion took place during routine clinical meetings. We undertook the study to enhance understanding of the incidence and scope of adverse events as a basis for preventing them. ::: ::: ::: METHODS ::: Ethnographers trained in qualitative observational research attended day-shift, weekday, regularly scheduled attending rounds, residents' work rounds, nursing shift changes, case conferences, and other scheduled meetings in three study units as well as various departmental and section meetings. They recorded all adverse events during patient care discussed at these meetings and developed a classification scheme to code the data. Data were collected about health-care providers' own assessments about the appropriateness of the care that patients received to assess the nature and impact of adverse events and how health-care providers and patients responded to the adverse events. ::: ::: ::: FINDINGS ::: Of the 1047 patients in the study, 185 (17.7%) were said to have had at least one serious adverse event; having an initial event was linked to the seriousness of the patient's underlying illness. Patients with long stays in hospital had more adverse events than those with short stays. The likelihood of experiencing an adverse event increased about 6% for each day of hospital stay, 37.8% of adverse events were caused by an individual, 15.6% had interactive causes, and 9.8% were due to administrative decisions. Although 17.7% of patients experienced serious events that led to longer hospital stays and increased costs to the patients, only 1.2% (13) of the 1047 patients made claims for compensation. ::: ::: ::: INTERPRETATION ::: This study shows that there is a wide range of potential causes of adverse events that should be considered, and that careful attention must be paid to errors with interactive or administrative causes. Healthcare providers' own discussions of adverse events can be a good source of data for proactive error prevention. 
3. Abstract of Cited Paper (BIB003):  PURPOSE ::: Adverse drug events (ADEs), or injuries due to drugs, are common and often preventable. However, identifying ADEs, potential ADEs, and medication errors can be a major challenge. In this review, we describe methodologies that have been used to identify these events and give strategies for identification in non-study settings. ::: ::: ::: RESULTS ::: Methods such as voluntary reporting, chart review, and computerized monitoring for events have been most commonly used in studies of ADEs in inpatients. However, voluntary reporting, the method most hospitals currently use, has a very low yield of events. Chart review is much more sensitive but the costs are prohibitive. Computerized monitoring for ADEs (using rules or triggers) is a high yield and relatively inexpensive strategy that should be adopted by organizations. A limitation of this strategy, however, is that it identifies few medication errors and potential ADEs, which are also important. These can be captured through pharmacy logs, chart review, and direct observation. Once events have been identified, they can be classified by type of event, severity, and preventability. In non-study settings, the most practical method for identifying ADEs is computerized monitoring, and for identifying prescribing errors it is pharmacy logs of interventions. Once problems are found, a structure (either individual or committee) must be in place to classify them, identify opportunities for improvement, and carry out the necessary changes. ::: ::: ::: CONCLUSIONS ::: Health care organizations have the technology to significantly improve their detection of ADEs, medication errors, and potential ADEs. Identification and subsequent classification of events is crucial for quality efforts to improve patient safety. 
4. Abstract of Cited Paper (BIB004):  The validity and cost-effectiveness of three methods for detecting medication errors were examined. A stratified random sample of 36 hospitals and skilled-nursing facilities in Colorado and Georgia was selected. Medication administration errors were detected by registered nurses (R.N.s), licensed practical nurses (L.P.N.s), and pharmacy technicians from these facilities using three methods: incident report review, chart review, and direct observation. Each dose evaluated was compared with the prescriber's order. Deviations were considered errors. Efficiency was measured by the time spent evaluating each dose. A pharmacist performed an independent determination of errors to assess the accuracy of each data collector. Clinical significance was judged by a panel of physicians. Observers detected 300 of 457 pharmacist-confirmed errors made on 2556 doses (11.7% error rate) compared with 17 errors detected by chart reviewers (0.7% error rate), and 1 error detected by incident report review (0.04% error rate). All errors detected involved the same 2556 doses. All chart reviewers and 7 of 10 observers achieved at least good comparability with the pharmacist's results. The mean cost of error detection per dose was $4.82 for direct observation and $0.63 for chart review. The technician was the least expensive observer at $2.87 per dose evaluated. R.N.s were the least expensive chart reviewers at $0.50 per dose. Of 457 errors, 35 (8%) were deemed potentially clinically significant; 71% of these were detected by direct observation. Direct observation was more efficient and accurate than reviewing charts and incident reports in detecting medication errors. Pharmacy technicians were more efficient and accurate than R.N.s and L.P.N.s in collecting data about medication errors. 
5. Abstract of Cited Paper (BIB005):  OBJECTIVE: To evaluate the frequency of medication errors using a multidisciplinary approach, to classify these errors by type, and to determine how often medication errors are associated with adverse drug events (ADEs) and potential ADEs.

Literature Review:
Another method used to detect adverse events has been the use of trained observers. This approach has advantages over chart review in that is can be performed prospectively. Observers have been used to detect adverse events in the intensive care unit BIB002 and surgical care floors BIB003 . In one study, observers were trained in how to recognize adverse events and recorded physicianÕs comments made during patient care activities BIB003 . These observers were able to detect serious adverse events in 17.7% of all patients studied. Medication errors, defined as any error occurring during the ordering, transcribing, dispensing, administering, and monitoring of medications, are common occurrences that sometimes result in patient injury BIB006 . In a study that compared direct observation, chart review, and incident reports to determine the most effective means for detecting medication errors, direct observation detected 300 errors made on 2556 doses compared with only 17 errors detected on the same doses detected by chart review BIB005 . Several investigators have described direct observation as the most sensitive detection method for identifying medication errors BIB001 . A limitation of direct observation is that it can be an expensive method for error detection with a mean cost of $4.82 per error detected versus $0.63 per error detected by chart review BIB005 . Furthermore, even though more errors are detected, the errors tend to be less likely to result in an injury than errors detected through other methodologies BIB004 .