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Incidence and types of non-ideal care events in an emergency department
  1. Kendall K Hall1,
  2. Stephen M Schenkel2,3,
  3. Jon Mark Hirshon4,5,
  4. Yan Xiao6,
  5. Gary A Noskin7,8,9
  1. 1Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services, Rockville, Maryland, USA
  2. 2Department of Emergency Medicine, University of Maryland School of Medicine and Mercy Medical Center, Baltimore, Maryland, USA Jon Mark Hirshon - University of Maryland School of Medicine, Baltimore, Maryland, USA
  3. 3Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
  4. 4Department of Emergency Medicine, National Study Center for Trauma and EMS, University of Maryland School of Medicine, Maryland, USA
  5. 5Department of Epidemiology and Preventive Medicine, National Study Center for Trauma and EMS, University of Maryland School of Medicine, Maryland, USA
  6. 6Patient Safety Research, Baylor Health Care System, Dallas, Texas, USA
  7. 7Feinberg School of Medicine Northwestern University, and Northwestern Memorial Hospital, Chicago, Illinois, USA
  8. 8Healthcare Epidemiology and Quality, Northwestern Memorial Hospital, Chicago, Illinois, USA
  9. 9Northwestern Center for Patient Safety, Northwestern Memorial Hospital, Chicago, Illinois, USA
  1. Correspondence to Dr Kendall K Hall, Center for Quality Improvement and Patient Safety, Agency for Healthcare Research and Quality, 540 Gaither Road, Rockville, MD 20850, USA; kendall.hall{at}


Aim To identify and characterise hazardous conditions in an Emergency Department (ED) using active surveillance.

Methods This study was conducted in an urban, academic, tertiary care medical centre ED with over 45 000 annual adult visits. Trained research assistants interviewed care givers at the discharge of a systematically sampled group of patient visits across all shifts and days of the week. Care givers were asked to describe any part of the patient's care that they considered to be ‘not ideal.’ Reports were categorised by the segment of emergency care in which the event occurred and by a broad event category and specific event type. The occurrence of harm was also determined.

Results Surveillance was conducted for 656 h with 487 visits sampled, representing 15% of total visits. A total of 1180 care giver interviews were completed (29 declines), generating 210 non-duplicative event reports for 153 visits. Thirty-two per cent of the visits had at least one non-ideal care event. Segments of care with the highest percentage of events were: Diagnostic Testing (29%), Disposition (21%), Evaluation (18%) and Treatment (14%). Process-related delays were the most frequently reported events within the categories of medication delivery (53%), laboratory testing (88%) and radiology testing (79%). Fourteen (7%) of the reported events were associated with patient harm.

Conclusions A significant number of non-ideal care events occurred during ED visits and involved failures in medication delivery, radiology testing and laboratory testing processes, and resulted in delays and patient harm.

  • Emergency medicine
  • patient safety
  • errors
  • adverse event
  • error detection
  • emergency department
  • incident reporting
  • medical error

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Of all types of healthcare settings, the emergency department (ED) is likely to be the most unsafe for patients.1 By nature, ED care is transitional and more likely than other locations to be influenced by multiple factors such as variable patient acuity, handoffs, distractions and a lack of information.2–4 Emergency care is complex as a result of the many people, decision points, uncertainties and overlapping processes of care that must be integrated both within and outside the ED. The care activities are also tightly coupled, with many time-dependent, critical processes requiring sequential performance to achieve a safe, successful outcome.5 An error that occurs in the ED can compound and propagate to subsequent care in both the hospital and ambulatory settings. The combination of complexity and tight coupling makes the ED a unique system highly prone to adverse events.6

In the US, the ED represents the first line of care for over 119 million patients annually.7 This is due in part to the US governmental mandate that anyone presenting to an ED requires an appropriate medical screening exam regardless of ability to pay (Emergency Medical Treatment and Labour Act).8 Surprisingly, current knowledge about the frequency and types of errors and adverse events occurring within the ED is limited. The majority of previous studies conducted in the ED have focused on missed diagnoses of high-stakes conditions,9–11 with only a small number of studies evaluating the epidemiology of errors and adverse events.12 13 For hospitals, the method most often used to collect information about hazards within the ED is the staff-initiated ‘incident report.’ Many hospitals implement incident reporting systems with a classification scheme for types and causes; some have broadened this approach to develop an all-purpose safety reporting mechanism. These systems can provide valuable information for process improvement and identification of hazards, but the quality of these incident reports is highly variable.14 The types of reports generated are likely to be non-systematic sampling of risks and hazards. Furthermore, incident reports provide the so-called numerator representing the number of reported incidents that have occurred but lack the denominator which allows for the determination of the prevalence.15 The reports are prone to bias as the decision to classify an event as an incident is made by the reporter, and does not necessarily reflect important contributing factors that are precursors to harm. This type of information is critical to improving the safety of emergency care.16–18

In this study, we sought to determine the incidence and types of non-ideal care events in an urban, academic medical centre through the use of active surveillance on a systematically sampled group of patient visits.



The study was conducted in the ED of a large urban, academic medical centre located in the Mid-Atlantic region of the US, with approximately 45 000 adult visits annually. Paediatric patients, defined as those 18 years of age or younger, are treated by paediatric specialists in a separate area of the ED.

This study was evaluated by the University of Maryland Institutional Review Board and determined to be exempt.

Selection of visits

Patient visits to the ED were systematically sampled based on sequentially generated financial numbers. Patient visits were eligible for inclusion if they met the following criteria: (1) the sequentially generated financial number for the visit ended in a 0 or 5; (2) the visit occurred in the adult ED (patient over the age of 18 years); and (3) the visit ended (patient discharged home, transferred, or admitted and moved to an inpatient unit) during the data-collection periods. This final criteria ensured that all patient safety data obtained referred to the entire ED evaluation, from arrival to discharge.


The objective of this project was to identify and quantify non-ideal care events that occur for patients being treated in the ED through active surveillance. Based on the model used in infection control, active surveillance is the continuous and systematic collection, analysis and interpretation of information.19 In contrast to passive surveillance, which relies on the initiative of the staff to report events, active surveillance involves direct solicitation of event reports. Active surveillance is likely to be the most accurate and precise method of measuring events within the ED because it minimises various limitations found in other methodologies, such as selection bias.20 21

A non-ideal care event was described as any event in the patient's care that the care giver judged to be less than ideal. The term ‘non-ideal care event,’ rather than ‘error,’ was developed in order to reduce reporting bias by the care givers. This terminology was determined, through pilot testing of the surveillance process, to be less fraught with negative connotations and less blame-oriented than the term ‘error.’ Harm was defined as ‘any physical or psychological injury or damage to the health of a person, including both temporary and permanent injury.’22

Two types of event schemes were developed to facilitate identification and categorisation of events. These were designed for both face validity—important for communication and buy-in—and the potential link to targeted improvement projects. First, the research team outlined the basic steps in the process of delivering emergency care. These segments of care are as follows: triage, registration, evaluation, diagnostic testing, treatment and disposition. An additional category, transitions, was added to account for periods where an event occurred during the transfer of care from one clinician to another. Other safety researchers have successfully used similar systems for categorising errors into the care delivery segment during which they occurred.23 The second categorisation scheme was developed to describe the broad event category (eg, medication delivery; laboratory testing) and specific event type (eg, administration—wrong drug; results—delay or failure to report results). This taxonomy was derived from the hospital's online event reporting system and iteratively refined as the study progressed and reports became available.

Care giver and research assistant education

Staff members were educated to the goals of the study and the definition of non-ideal care events through regular staff meetings, memoranda and emails. Residents, through their regular weekly conference, were educated as part of a quality and patient safety lecture series. Emphasis was placed on the non-punitive nature of the study and the appreciation of systems factors, rather than individual blame, as related to events in the ED. Care givers were instructed to report any events through the standard hospital event-reporting system, as they would through their normal course of work. Cards were given to all staff with information on how to access the online reporting system.

Four research assistants (RAs), from a cohort of trained RAs at the medical centre, participated in the study. For this project, each RA had at least a Bachelor of Science in nursing or Master's level degree in a healthcare related field (eg, Master's in Public Health) and experience collecting data within the ED environment. RAs were trained in patient safety principles and practised querying care givers prior to the initiation of data collection.

Data collection

RAs contacted all available care givers for sampled patient visits within 1 h of the patient's discharge. Care givers contacted for interviews were those who were responsible for the patient at the time of discharge. For patients whose visits spanned more than one shift, only the care givers who were present at the time of discharge were interviewed. In this academic hospital with an Emergency Medicine (EM) residency, there were typically three care givers identified for each patient: an attending physician, a resident physician and a nurse.

For the interviewed care givers, RAs asked the following questions:

  • What was your role in the patient's care (eg, nurse)?

  • Was this patient's care handed-off to you by another staff member?

  • Was there any part of this patient's care that was not ideal?

  • If yes, please describe how it was not ideal, and why do you think it might have happened?

In addition to the interviews, the RAs collected basic demographic data and visit characteristics (listed in table 1) for the sampled patients. No information was collected that could identify an individual patient or care giver. Care givers were informed that they could withdraw from participation at any time during the interview.

Table 1

Patient demographics and visit characteristics

Data analysis

All reports were entered into a database and were independently reviewed by two of the investigators (KKH, SMS). The review involved categorising the events into the Segment of Care during which the event occurred, and the Event Category and Specific Event Type. Discrepancies between the two reviewers were resolved through discussion. Throughout the review, continuous reference was made to previously evaluated events in order to ensure consistency. The categorisation of any event could be questioned at any point in the analysis. The conflict would then be resolved through further discussion.

The same investigators (KKH, SMS) reviewed all reports and, when there was sufficient information, determined whether or not any events had associated harm. Both reviewers had to agree on the occurrence of harm, discussing each event to resolve any conflict.


A total of 656 h of RA surveillance was conducted with 487 visits sampled for inclusion, representing approximately 15% of the total visits during the study period. The surveillance represented 82 shifts (26 day, 28 evening and 28 night shifts) over a 15-week period. Of the 487 visits, there were five visits for which it was not possible to obtain care-giver interviews. The basic patient demographics and visit characteristics for the 482 visits with associated interviews are described in table 1.

There were 1180 interviews conducted, with a median of three interviews conducted for each of the 482 sampled visits. Interviews were conducted with nurses (39% of interviews), resident physicians (32%), attending physicians (28%) and technicians (1%). There were 27 attempted interviews for which the care giver declined to participate (2%). Since no individual identifying information was collected for the care givers, it is not known how many unique individuals these 27 interview attempts represent.

Through the 1180 interviews, 263 reports of non-ideal care events were generated (53% by nurses, 28% by resident physicians, 19% by attending physicians, 0% by technicians). The 263 reports represented 210 non-duplicative events occurring in 153 of the 482 (32%) visits. Approximately one-third of visits had at least one associated non-ideal care event reported with 13% of the visits having more than one event.

Of the 482 visits with interviews, 187 (39%) had at least one interview of a care giver who received the patient through a handoff. For the 153 visits with reported events, 90 (59%) had at least one interview with a care giver who received the patient through a handoff.

The non-ideal care events were categorised by the segment of care in which they occurred (figure 1). These events occurred most commonly during the diagnostic phase (29%), which included laboratory and radiology testing. Events during the disposition phase (eg, no inpatient bed availability) accounted for 21% of the discrete events.

Figure 1

Non-ideal care events by segment of emergency care.

The results as categorised by event category and specific event type are listed in table 2. A significant portion of events reported were related to delays or failures, particularly for laboratory and radiology study and result acquisition. Some examples of reports are listed in table 3.

Table 2

Events by category and type (N=210)

Table 3

Examples of non-ideal care event reports

Thirteen visits had a total of 14 events that were judged to be associated with harm. The majority of these harms were related to repeated attempts at obtaining intravenous access. Other events that led to recognised harm included a case of an incomplete triage evaluation that resulted in a significant delay in definitive care for a patient with an acute coronary syndrome; an incomplete initial ED evaluation that led to a missed diagnosis that was discovered by the subsequent shift; an allergic reaction to a medication; and a case where definitive treatment was delayed because of a reported lack of resident supervision.


The method of proactively querying care givers regarding non-ideal care events used in this project is a feasible method for identifying safety issues within the emergency department. The method was deployed successfully to systematically sample patient visits, with success rates of more than 97% in interview attempts. Of the 482 visits for which clinician interviews were conducted, 32% had at least one non-ideal care event, with 13% having more than one reported event. Three per cent of the visits had an event which caused known harm. The segments of care incurring the greatest risks to patient safety were the diagnostic testing phase, followed by the disposition phase. The specific event type, delay or failure of bed availability for admitted patients, had the greatest number of reports.

The method most often used to collect information about hazards within the ED is the staff-initiated voluntary reporting system. These systems, whether paper-based or electronic, are widely accessible in many US hospitals and provide a standard classification scheme for events across the individual institution. A significant limitation of these systems is the lack of consistency in reporting: what one individual considers a reportable event may not match the impression of another. Implementation of incident reporting systems is variable, leading to inconsistent data potentially with significant biases. These systems cannot provide reliable information regarding the incidence or prevalence of errors and adverse events,21 making assessments of the success or failure of patient safety interventions unreliable. In addition, these types of reporting systems tend to focus primarily on adverse events causing harm and may miss important factors that are precursors to errors.

Studies evaluating ED events often ask clinicians to provide information about ‘errors’ and ‘adverse events.’ However reported, whether through in-person interviews or through standardised reporting mechanisms, the clinician must make a judgement as to what constitutes an error or adverse event. This is particularly difficult in an environment where reporting is associated with negative consequences for the individuals involved. Missing lab results, delayed consultation or even a lack of inpatient beds necessitating holding patients in the ED (‘boarding’) may not be reported, yet each of these events has the ability to harm the patient.24–27

As demonstrated in this study, ED staff clearly have their own sense of what is a non-ideal event. As might be expected in a highly time-dependent location, such as the ED, many of the reported events had to do with delays in care, specifically delays to diagnostic tests or delays in provision of a bed for an admitted patient. These are far more subtle findings than the typically reported medical errors, and more common than even medication errors. In pointing out these non-ideal events, ED staff are suggesting the degree to which interventions to improve daily ED care also represent interventions that would bolster patient safety. The reported events demonstrate to what degree activities of daily care and patient safety are closely intertwined: when processes are broken, the quality of care has the potential to suffer.

Event categorisation and taxonomy of reporting remain a substantial challenge for any reporting system. Through iterative evaluation of events, we developed a system of categorisation that worked for this series of events and that maintains face validity within the work stream of the ED. One of the reasons for the development of our system of categorisation was that our institutional event reporting system provided no clear strategy for categorising a number of the reported events. The ED provides a unique environment, as, we suspect, do many other areas of the healthcare system. A significant challenge is presented in balancing the need for an institution-wide reporting system with a system that meets the needs, both in mechanism and in content, of a local environment. Categorisation affects how we think about and respond to events. The choice between local categorisation with face value and broad categories that may not fit local circumstances may influence the ability to develop and track interventions in a meaningful and effective way.

In a majority of cases, there was no clear report of harm associated with events. This appears to be partly a result of the encouragement to report on any non-ideal event. It also indicates another challenge in the collection of patient safety data in a location where there is a relatively transient interaction with the patient along the entire continuum of care. ED care typically represents early care in what may be a prolonged episode of care or hospitalisation—follow-up on this more extended care was not available to the study investigators and is not typically available to ED staff. For patients who are discharged and return home, clinical follow-up is also rarely available to ED staff. The study was based on concurrent evaluation of non-ideal events, and so reflects staff perception of the state of patient safety while the patient was still in the ED. Therefore, it is perhaps not surprising that when attempting to identify harm, the vast majority of events fell into an ‘uncertain’ category—care givers had no way of knowing whether harm might be in the process of developing. Simply stated, from active surveillance in the ED, it is very difficult to tell whether a non-ideal event leads to any definitive harm. This raises a challenge for any reporting system in an ED environment. Active reporting through surveillance, as practised in this study, is likely to provide the fullest stories and therefore the most actionable results, but it appears to bias the results towards a collection of events that led to less harm, not because harm did not occur, but because the staff simply do not know at the time the question is asked. This may also be a reason that incident-reporting systems are used so infrequently in transient settings such as the ED—if the threshold for reporting is harm, then that threshold will only rarely be definitively met.


Despite the large number of reports, as with any reporting system relying on the care giver to determine if an event has occurred, this method is likely to underestimate the true number of events. In addition, since the care givers were queried at the end of the patient visit, it could be that the patient had been in the ED across multiple shifts with multiple care givers who were more aware of events occurring earlier in the course of care. A goal of this study was to establish the prevalence of events by knowing the number of patients for whom events were reported (the numerator) and the number of patients for whom the clinicians were interviewed (the denominator). A large number of events were identified, but the limitations noted here suggest that this could still be an underestimate. To increase reporting would require tackling the challenge from both sides by developing more continuous methods that would query providers throughout the patients' course while also tracking the patient in follow-up to see whether non-ideal ED events became known later in the patients' course of illness.

The agreement between professions (eg, nurse perception vs physician perception) as to what constitutes non-ideal care was not addressed in this study. Only 37 of the 153 visits with events had duplicate reports of the same event. This phenomenon may be a result of the individual's role in the care of the patient: a physician who is waiting for a radiology study to diagnose a patient is likely to be more sensitive to issues with process delays or failures originating in the Radiology Department. Similarly, a nurse who is responsible for transferring a patient to the inpatient unit is likely to be more sensitive to delays related to a lack of inpatient beds.

Reporting will naturally be biased by the nature of the questions asked and the environment in which it is asked. ED staff constantly work under the pressure of time. The pressure is both real, as that faced when there are sick patients and a full waiting room, and artificial, as found in standard ED management variables such as length of stay and time to evaluation. To the degree that staff are always thinking about time, delays in care are more likely to be reported as non-ideal events. The mechanism used here to ask about events—specifically avoiding any mention of error or harm—may have biased responses towards a larger number of less potentially dangerous reports. Respondents may have assumed that ‘big’ events—that is, events causing harm—should be reported by the more traditional incident reporting system or not at all.

The simplification of adverse events into categories results in a trade-off between a loss of detail that categorisation invokes and the broader understanding that such categorisation allows. We used iterative analysis to develop categories for events while consistently reviewing all of the event details. The two mechanisms developed here, with categorisation based on the stage of ED care and by nature of the event, made sense within the context of the events reported and the clinical experience of the investigators. While these mechanisms allowed for the production of appropriate categories that reflected this data set, there is hesitance to recommend them as a rigid taxonomy.28 Ultimately, any system of categorisation must survive first based on its face validity and subsequently, and most importantly, on its usefulness in directing interventions.


One in three patients experienced a non-ideal care event during their course of ED care. The majority of these events had to do with delays and failures in the process of care, from delays and failures in the reporting of laboratory results to delays in obtaining inpatient beds for admitted patients. Despite the large number of reported events, relatively few were identified as causing patient harm, though the assessment of harm appears to be severely limited in the ED. This limitation sets emergency care apart from other more discrete episodes of hospital care such as surgical procedures. Much of emergency care occurs in a grey zone where the outcomes are reserved for another time and place. While likely an underestimate, these results provide an estimate for the total number of non-ideal events that occur in the course of ED care.


The authors would like to thank B Browne (University of Maryland) and JG Adams (Northwestern University), for their support and guidance with the project, and K Henriksen and JB Battles, for their review of the manuscript.



  • Funding This project was supported by grant no P20HS017111 from the Agency for Healthcare Research and Quality.

  • Competing interests None.

  • Ethics approval Ethics approval was provided by the University of Maryland IRB.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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