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6
Contributors to Error in the
Training Environment
Residents can make errors, but the proportion of errors they make relative
to those of other healthcare workers is unknown. Inexperience, fatigue,
inadequate supervision, workload intensity, and other work system fac-
tors (poor handover practices, inadequate medication labeling) contribute
to errors by residents as they may for all health care workers. Data are
insufficient to determine the relative contribution of each of these factors.
Because residents are in supervised training programs and work within
teams, many mistakes can be intercepted before they can harm patients.
Uncertainty surrounds the impact of the 00 reduction of resident duty
hours on patient safety (adverse patient outcomes) and whether further
adjustments to duty hours might diminish unsafe conditions (e.g., sleep
deprivation) and reduce errors. The few national studies that have at-
tempted to capture the impact of duty hour reform show no evidence of
harm as measured by mortality rates. A well-designed randomized trial
in two intensive care units of a single institution found a reduction in
rates of serious medical error committed by first-year residents when their
extended duty periods (up to 0 hours) were reduced to hours, total
weekly work hours were also reduced, and they obtained more sleep. The
study found no statistically significant difference in unit-wide preventable
adverse events or patient mortality between the reduced duty hour and
standard hours. Nor was it able to isolate the effect of the shorter shift
from reduced total workweek hours, increased sleep, having an additional
intern, or increased handovers. A larger-scale, multicenter trial with suf-
ficient statistical power would be necessary to confirm the positive findings
in other settings and for residents in other training years.
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0 RESIDENT DUTY HOURS
This chapter examines what is known about the relationship between
resident duty hours and patient safety. By definition the performance of
trainees is imperfect as they learn, and they, just as other healthcare profes-
sionals, will make errors. The response of the system to those errors and
its actions to prevent future errors determine the safety of patients. First,
this chapter discusses what is known about the overall frequency of medi-
cal errors in hospitals by all staff and the resulting patient harm. Then it
examines what evidence is available on the relative contribution of residents
to the overall patient safety burden in teaching hospitals, and examines
whether the degree to which resident fatigue contributes to the occurrence
of error can be ascertained. The chapter continues with a discussion of the
results of two natural experiments (the 1989 New York State and the 2003
Accreditation Council for Graduate Medical Education [ACGME] national
duty hour reforms). Then a detailed review follows of the effects of an
interventional study in which both total duty hours and the 30-hour duty
period were further constrained from the limits allowable under the 2003
ACGME duty hour rules. Finally, literature on how other factors contribute
to hospital errors, including the influence of poorly designed work systems
on individual performance is considered.
The discussion that follows presents research that helps answer five
broad questions:
1. Do residents make errors that contribute to patient harm?
2. Is resident fatigue from long duty hours among the most significant
risks to patient safety?
3. Did the 2003 reduction in resident duty hours affect patient
safety?
4. Would further reductions in resident duty hours improve patient
safety?
5. What factors in the resident work and learning environment con-
tribute to error?
The committee’s answers to these questions will be drawn together in
this chapter in a final section of conclusions. The next chapter (Chapter 7)
looks to the human performance and sleep literature on how adults perform
under scheduling practices that contribute to sleep deprivation, and con-
tains the committee’s recommendations on adjustments to duty hours.
MEASURING HOSPITAL-BASED ERROR RATES
AND RESIDENT INVOLVEMENT
This Institute of Medicine (IOM) study grew out of questions about
how significant a part residents play within the universe of hospital errors
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CONTRIBUTORS TO ERROR
that affect inpatients and to what degree the long duty hours and associated
fatigue contribute to making errors (Dingell et al., 2007). The purpose here
is to determine what is known scientifically about resident-associated errors
and the degree to which fatigue and sleep deprivation of residents affect
patient safety. Lessons learned from resident errors may reveal approaches
for improving overall patient safety. Evidence on the subject is limited to
a few studies.
Measuring Patient Safety
Before beginning, it is important to understand basic terms and ap-
proaches used in discussing and measuring patient safety.
Defining Medical Errors
A spectrum of medical errors may occur during the treatment and
care of hospital patients. If it is a very serious error, death, injury, or other
preventable harm (e.g., delays in treatment, extended days in hospital,
complications) could result if an error is not intercepted and corrected.
Other errors may have no or very little impact on a patient’s condition or
may be intercepted before they reach the patient and cause harm. The 2000
IOM report To Err Is Human: Building a Safer Health System presents an
extensive analysis of safety and errors, based in large part on the research of
James Reason and Charles Perrow. The framework, terms, and definitions
used here are from that report (see Box 6-1).
Measuring Medical Errors
The measurement of patient safety is neither easy nor cost-free, and the
ideal method for system-level surveillance has not been established. There
are several types of measures commonly found in the literature that are
used to assess patient safety (freedom from accidental injury). These include
measuring the following:
• The occurrence of errors,
• The occurrence of adverse events (AEs) and preventable adverse
events (PAEs), and
• Patient outcomes such as injury or death or length of stay in the
hospital.
Errors with the potential to harm patients tend to be classified in stud-
ies according to their seriousness and category (e.g., medication, diagnostic,
procedural, or other errors). Different approaches to collecting data both
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RESIDENT DUTY HOURS
BOX 6-1
Taxonomy of Errors
Error: “. . . failure of a planned action to be completed as intended (i.e., error of
execution) or the use of a wrong plan to achieve an aim (i.e., error of planning)”
(p. 28). An error of execution could be an error of omission of an essential step, a
critical piece of data, etc.; could be caused by a poorly designed system requiring
staff to “work around” the design fault or miscommunications; an error of planning
could result from a misdiagnosis or lack of knowledge about the patient’s medical
problem. Some errors are caught and corrected before they harm the patient.
Harm or adverse event: An unintended physical injury resulting from or contrib-
uted to by medical care rather than the underlying condition of the patient, that
requires additional monitoring, treatment, or hospitalization or results in death. Not
all adverse events are caused by errors.
Preventable adverse event (PAE): “An adverse event attributable to error . . .”
(p. 28).
Sentinel event: An unexpected occurrence (which may or may not result from
an error) in a hospital patient’s case, including actual or risk of death or serious
physical or psychological injury (Joint Commission, 2007).
Negligent adverse event: A subset of preventable adverse events that satisfy
a legal standard of negligence (i.e., the care provided did not meet the standard
of care reasonably expected of an average physician qualified to care for the
patient) (p. 28).
Safety: “. . . freedom from accidental injury” (p. 58).
SOURCE: IOM, 2000.
for internal hospital quality improvement efforts and for research purposes
capture different pieces of data but not a whole picture of patient safety
or the universe of error. Data sources include (1) voluntary reporting by
patients and families; (2) mandatory or voluntary but facilitated reporting
systems for healthcare workers; (3) direct, prospective observation of work
being done in the hospital; (4) retrospective review of medical records us-
ing formal criteria or a “trigger tool” approach (i.e., clues in data that help
predict adverse events) (Classen et al., 2008; Griffin and Classen, 2008);
(5) use of administrative data on average length of stay, complication rates,
readmission rates, and mortality; and (6) hybrid approaches that combine
two or more of these methods.
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CONTRIBUTORS TO ERROR
No one method of data collection is ideal. The method used to identify
medical errors and assess the preventability of a patient’s death in the stud-
ies that produced the early IOM estimates used trained physicians conduct-
ing a structured implicit review of medical records. This method has been
shown to have a low interrater reliability and other limitations (Hayward
and Hofer, 2001), although other studies have found similar rates of pre-
ventable deaths. In recognition of this fact, institutions and researchers are
increasingly employing a combination of different methods for collecting
data on errors and analyzing them (Bates et al., 1995; Rothschild et al.,
2005). In fact, one study that observed staff in a medical care unit and a
coronary intensive care unit (ICU) reported that 62 percent of identified
incidents were found through direct observation, 49 percent through chart
review, 15 percent through solicited staff reporting, 7 percent through
pharmacy reports including adverse drug event monitoring, and 4 percent
through formal incident reporting (Rothschild et al., 2005). Only 23 per-
cent of these events were identified by more than one approach.
The common feature of these methods is the reliance on frontline pro-
vider knowledge and description of the patient’s treatment and condition
to inform voluntary or mandatory reporting systems, or to record direct or
indirect observations of care (e.g., medical records, non-participant observ-
ers). The reproducibility and precision of measurements of AEs and PAEs
are limited (Classen et al., 2008; Hayward and Hofer, 2001). In particular,
the determination of preventability is subjective and can change based on
the state of medical knowledge available at the time of assessment.
Error-Reporting Systems
While national data on errors and PAEs are nearly nonexistent, more
information exists at the hospital level since most now have voluntary
error-reporting systems. The Joint Commission requires hospitals seek-
ing accreditation to implement a voluntary reporting system for sentinel
events, to conduct a root-cause analysis of reported events, and to prepare
a corrective action plan to avoid similar incidents in the future (Joint Com-
mission, 2007). These error-reporting systems can provide useful data, but
they do not define the universe of errors, only those events recognized as
problematic and reported by an observer or participant. Underreporting
appears to be a common problem; such systems may detect fewer than 10
percent of adverse events (Classen et al., 2008; Rothschild et al., 2005),
but the data provided nonetheless can have important uses to the reporting
facility when they are embedded in a vigorous error elimination program.
Such voluntary systems focus on the circumstances surrounding the adverse
event and the systems involved, rather than identifying the individuals in-
volved. Hence, even well-supported reporting systems do not typically note
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4 RESIDENT DUTY HOURS
whether a resident was involved with the patient’s care. Also, because of
the complexity associated with some adverse events, it may be difficult to
attribute the event to a specific individual or even to know exactly when it
was committed.
Compliance with voluntary reporting systems by physicians and other
clinicians depends in part on the importance given to safety issues by
the organization’s leadership, whether such data (when gathered) are
actually used in respected improvement efforts, and importantly whether
workers feel safe to discuss errors without fear of punishment, retribu-
tion, or other negative consequences (Garbutt et al., 2008; Kaldjian et
al., 2008). These issues are discussed in Chapter 8. Although voluntary
reporting systems cannot be used to define the frequency of harmful and
other medical errors, they can be an important source of information to
hospital leaders for identifying vulnerabilities in their systems that should
be considered for corrective action. Along with risk management reports,
patient complaints, error reports, quality assurance audits, and quality
improvement reports, such systems can indicate areas for more detailed
retrospective review, which can identify many more adverse events (Griffin
and Classen, 2008). Error-reporting systems can provide data to assist in
priority setting for quality improvement projects. The committee believes
strongly that they can also be of educational value to doctors in training
and should become an integral part of residency programs, as discussed
in Chapter 8.
Determining the Universe of Errors and PAEs with Limited Data
As background for the committee’s study of the impact of residents’
duty hours on patient safety, it would be useful to follow a chain of
inquiry and quantify, in order, the universe of medical errors, medical
errors made in hospitals, medical errors made by residents, and medi-
cal errors made by residents in which fatigue is a contributing factor.
The universe of medical errors affecting patient safety would encompass
PAEs as defined earlier, including both fatal preventable errors and the
larger number of nonfatal preventable errors. The data to determine the
universe of errors and the subelements in the above-mentioned hierarchy
are not available to present a full picture. This lack inhibits the ability of
the medical community to track and guide progress on patient safety. It
has constrained the ability of the committee to answer fully some of the
important questions put forth by the sponsors of this inquiry. Nonetheless,
this section of the chapter gathers available data to paint a partial picture
of the relationship between residents, errors in hospitals, and patient
safety.
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Estimates of PAEs
U.S. short stay, non-federal hospitals treated and discharged 35 million
inpatients in 2006 (DeFrances et al., 2008) and can produce miraculous
cures, but an estimated 44,000-98,000 patients die from preventable errors
(IOM, 2000). The broad range of that estimate reflects, in part, the meth-
odological challenges mentioned above. The estimate of deaths was based
on studies in which researchers examined hospital medical records from
large samples of admissions in New York, Colorado, and Utah to determine
whether the patients had experienced AEs as a consequence of medical er-
rors (Brennan et al., 1991; Leape et al., 1991). A later study determined
that 2.9 percent of admissions in Utah and Colorado and 3.7 percent of
admissions in New York State experienced an AE; that 53 percent of Utah
and Colorado events and 58 percent of the events in New York were at-
tributable to errors and therefore were PAEs (Thomas et al., 1999). Another
study by Thomas and colleagues determined that the AE rates in Utah and
Colorado varied by teaching status: 4.0 percent in major teaching hospitals,
3.9 percent in minor teaching hospitals, and 2.5 percent in non-teaching
and private hospitals. The study did not focus on case mix differences
among individual hospitals or categories of hospitals. The researchers did
not present sufficient data to explain the variation based on their available
data (Thomas et al., 2000a). The estimated number of deaths resulting from
PAEs was extrapolated from 1992 data by applying the death rates due to
errors in the three states noted to the total of national hospital admissions
in 1997. The committee uses the Thomas study (1999) as the basis for cost
estimates of PAEs discussed in Chapter 9.
Experts believe that the rate of preventable deaths has not improved
substantially since the report To Err Is Human brought these issues to the
public’s attention in 2000 (Leape and Berwick, 2005). A significant and
unsatisfactory level of errors is also indicated by several smaller studies
of medical errors in a single hospital or hospital service since that time
(AHRQ, 2002; Forster et al., 2003; Hayward and Hofer, 2001; IOM, 2006;
Leape and Berwick, 2005; Rothschild et al., 2005). No recent estimate of
the universe of errors nationwide exists, and because studies use different
definitions of errors and PAEs and a variety of inconsistent methodologies
for identifying PAEs and calculating error rates, their results cannot be
aggregated.
Assessing Patient Safety and Quality
In the absence of a national error-reporting system, several commercial
organizations as well as the Centers for Medicare and Medicaid Services
(CMS), the Agency for Healthcare Research and Quality (AHRQ), and the
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RESIDENT DUTY HOURS
Commonwealth Fund have developed alternative methods for assessing
quality and safety using existing data sources. CMS posts provider-level
quality measures, including indicators for hospitals, nursing homes, home
health providers, and dialysis facilities to help consumers make more in-
formed choices (HHS, 2008). AHRQ created national estimates of hospital
quality from existing data sources for its annual National Healthcare Qual-
ity Report, which includes some indicators of safety, but not errors. For
example, a composite indicator of selected generally avoidable postopera-
tive complications shows that such adverse events occurred in 6.55 percent
of cases in 2005, and that nearly one-quarter of surgical patients did not
receive appropriately timed antibiotics (AHRQ, 2007). The improvements
in quality according to a variety of ambulatory and hospital indicators used
in AHRQ’s National Healthcare Quality Reports amounted to only 1.5
percent per year between 2000 and 2005 (Brady et al., 2008). The Com-
monwealth Fund uses a safety indicator for U.S. hospitals—a construction
of unexpected mortality, calculated by Jarman—that it tracks over time
(Commonwealth Fund, 2008). The U.S. rate shows an improvement of 19
percent in the 2004-2006 period compared to 2000-2002. Nonetheless,
both of these quality reports indicate the persistence of significant hospital
mortality and injury related to conditions that generally should be avoid-
able or should be caught and treated before the patient dies, indicating the
continuing need for improvement in patient care.
Errors and PAEs Involving Residents
The above “classic” studies involving statewide hospital AEs do not re-
port errors or PAEs that were related specifically to residents’ care although
there would appear to be higher AE rates in teaching hospitals based on
these data alone (Brennan et al., 1991; Leape et al., 1991; Thomas et al.,
1999, 2000b). A more recent set of papers by Rothschild, Landrigan, Lock-
ley, and colleagues examined resident error through a randomized trial in
two critical care units at a single institution (Landrigan et al., 2004; Lockley
et al., 2004; Rothschild et al., 2005). This section discusses the studies with
a focus on the baseline incidence of errors while a later section of this chap-
ter examines the effect of a scheduling intervention on error and PAE rates.
Malpractice negligence claims provide another source of data (Gandhi et
al., 2006; Regenbogen et al., 2007; Singh et al., 2007).
Incidence of Error and PAEs in ICUs
Rothschild (2005) and colleagues conducted a prospective observa-
tional study of two critical care units at a major urban teaching hospital.
This study focused on errors made by all caregivers when first-year residents
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CONTRIBUTORS TO ERROR
were following a traditional duty hour schedule. The authors found that
20.2 percent of patients suffered at least one AE and 45 percent of those
AEs were found to be preventable (Rothschild et al., 2005). The authors
note that their definition of an AE is more inclusive than the earlier study
by Brennan et al. (1991) cited above and that the ICU setting of their trial
would be expected to have higher medical error rates than other areas
(Beckmann et al., 2003). The unit-wide error rates per 1,000 patient-days
were 80.5 for all AEs, 36.2 for PAEs, and 149.7 for serious errors. Serious
errors did not always result in harm to patients “either because the patient
had sufficient reserve to buffer an error (nonintercepted serious error) or
because the error was caught before reaching the patient or before harm
developed” (Rothschild et al., 2005, p. 1697). The Rothschild data along
with the national reports from AHRQ, CMS, and the Commonwealth
Fund support the committee’s conclusion that 8 years after publication of
the IOM report To Err Is Human (2000), patient safety remains a serious
issue in the United States (AHRQ, 2007; Commonwealth Fund, 2008;
HHS, 2008).
The complementary article by Landrigan et al. (2004) reporting on
data collected in the same setting but for a slightly shorter period describes
differences in error rates unit-wide and for first-year residents. It found
the rates per 1,000 patient-days involving all staff unit-wide were 38.6 for
PAEs and 193.2 for serious errors. Incidents involving first-year residents
working a schedule with overnight call every third night appear to make
up a substantial portion of the reported errors, including 20.9 per 1,000
patient-days for PAEs and 136.0 per 1,000 patient-days for serious errors
(Landrigan et al., 2004). Rothschild notes that compared to the unit-wide
data, the “data on interns were somewhat more comprehensive because of
the presence of the observers” who kept the interns under direct continuous
observation, but that the unit-wide results were within the range identified
by other studies (Rothschild et al., 2005, p. 1695). Thus, the error rates
for other workers may have been underestimated relative to the error rates
of first-year residents.
Errors and PAEs in Malpractice Claims
Another study that identified errors associated specifically with doctors
in training (both residents and fellows) is based on 1,452 closed malpractice
claims from five liability insurers in different parts of the country (Singh
et al., 2007). Malpractice claims represent only a small proportion of er-
rors and AEs—the more serious AEs for which negligence is assessed. It is
unclear in what other ways these data might differ from the universe of
PAEs. Singh identified 889 cases that reviewers determined to have included
both an error and an adverse outcome; 240 (27 percent) involved trainees.
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RESIDENT DUTY HOURS
Residents were involved with 87 percent of the 240 cases involving trainees,
and fellows were involved with 13 percent of those cases. Multiple train-
ees could have been involved in a single case, with interns involved in 13
percent of the 240 cases. The study’s physician reviewers considered these
doctors in training to have had at least a moderately important contributory
role in those cases with a PAE.
A study of 307 diagnosis-related ambulatory care malpractice claims
closed between 1984 and 2004 found that 181 such claims involved diag-
nostic errors that led to adverse outcomes (Gandhi et al., 2006). Of the
181 cases, trainees (intern, resident, or fellow) were identified as involved
in 20 percent of them by trained reviewers. The study also identified several
causes of breakdowns in the diagnostic process and concluded that multiple
factors were involved. Researchers in a different study examined surgi-
cal malpractice claims, selecting a random sample of 444 cases for closer
study. Among the 52 percent (n = 133) that included technical errors, the
researchers determined that 9 percent involved poorly supervised residents
(Regenbogen et al., 2007).
Conclusion About Whether Residents Make Errors
These studies provide enough evidence to answer the question: Do
residents make errors that contribute to patient harm? Common sense
and these studies lead to the conclusion that the answer is, Yes, they do.
Additional information from resident surveys confirms this as well (Jagsi
et al., 2005, 2008; Wu et al., 2003). Without more quantitative data, it is
impossible to determine what proportion of all errors or what proportion
of PAEs involve residents. Consequently, the magnitude of the impact of
residents on patient safety is unknown.
FATIGUE AS A CONTRIBUTOR TO ERROR
A principal aim of this study is to determine the degree to which resi-
dent fatigue from long duty hours poses a significant risk to patient safety
and whether there are interventions that might reduce that risk. As Howard
and colleagues have observed, “continuous operational demands [of pro-
viding access to health care in hospitals 24 hours a day] present unique
physiologic challenges to the humans who are called on to provide safe
operations within these systems” (Howard et al., 2002b, p. 1281). While
long work hours and fatigue appear to play a role, other systemic factors
also contribute. Resident reports give some insight into how great a factor
they believe fatigue to be. In a survey of two large teaching institutions just
before the required 2003 ACGME duty hour limits were in force, medi-
cal and surgical specialty and subspecialty residents were asked what the
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CONTRIBUTORS TO ERROR
contributing factors were for mistakes related to AEs. They reported that
long work hours were a contributing factor in 19 percent of the mistakes
observed, but they also noted that lack of supervision (20 percent), faulty
handovers (15 percent), large patient caseloads (12 percent), and cross-
covering too many patients (5 percent) were important factors (Jagsi et
al., 2005). Working more than 80 hours in the past week was a significant
predictor of caring for a patient with an AE in the last week (odds ratio 1.8)
(Jagsi et al., 2005). Chapter 7 details the evidence base that establishes the
link between fatiguing aspects of resident work-rest schedules and what is
known about how fatigue affects human performance and the propensity
for error.
Assessing Incidence of AEs Involving Fatigue
This section examines data from the U.S. Department of Veterans
Affairs (VA) and from malpractice claims to evaluate the contribution of
fatigue as a factor. The VA offers residency training through approximately
8,800 residency positions in its facilities (9 percent of U.S. total), and be-
cause residents from other facilities rotate through the VA, this training
reaches about one-third of residents in training in any single year (Chang,
2007). The VA has a heavy emphasis on patient safety and has trained its
staff in the value of reporting both AEs and close calls. The system has ac-
cumulated more than 10,000 root-cause analyses (RCAs) of individual seri-
ous incidents or groups of events since its inception in 1999. The analyses
tend to look beyond the individuals involved with an AE to the underly-
ing systemic causes. The database is not designed to identify the specific
involvement of residents. It does, however, include fatigue as a “cause”
choice on its structured data collection tool. Fewer than 4.5 percent of the
VA RCA reports included fatigue as an associated factor and 0.7 percent
included a more extensive discussion of fatigue-related causation. A review
of a random sample of 4,742 reports drawn from approximately 180,000
reports from the same time period concerning less serious safety incidents
showed that 1.0 to 3.3 percent included fatigue-associated causes.1,2 It
is unknown what percent of those cases associated with fatigue included
fatigued residents because the VA does not routinely track residency status
of the involved parties.
Fatigue related to medical errors is recorded in some cases in the Singh
study of malpractice claims discussed above: 5 percent (n = 12) of the trainee
1 Personal communication, J. P. Bagian, Director, VA National Center for Patient Safety,
Department of Veterans Affairs, February 11, 2008.
2 Personal communication, J. P. Bagian, Director, VA National Center for Patient Safety,
Department of Veterans Affairs, February 14, 2008.
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0 RESIDENT DUTY HOURS
al., 2006). On the positive side, well-rested residents find their clinical deci-
sion making is improved especially on post-call days, working conditions
are better, and they have a generally improved sense of personal well-being.
They report downsides including that hour limits are inflexible, patient care
can be rushed under the compressed duty hours, treatment decisions are
sometimes delayed, and information can be lost in handoffs, thus creating
fragmented and less patient-centered care. From the resident’s perspective,
duty hours alone are not the only issue when it comes to making errors
(Jagsi et al., 2005, 2008; Lin et al., 2006).
A systems view of AEs in hospitals and other nonmedical environments
recognizes the organizational contribution to a chain of events that can
lead to error rather than blaming the individual (Barach and Small, 2000;
Leape, 1994; Shojania et al., 2002; Volpp and Grande, 2003). Residents
often blame their inexperience and faulty judgment for making errors
(e.g., did not ask for advice, missed patient warning signs, had never seen
a patient with an atypical presentation of a certain condition, hesitated
to act for too long) (Wu et al., 2003). Yet just as frequently they note job
overload—too much work to do within the time allotted (Jagsi et al., 2008;
Wu et al., 2003). Adverse events are “more likely when suboptimal working
conditions occur” (Tibby et al., 2004, p. 1160). Vidyarthi and colleagues
(2007), in their analysis of a cross-sectional survey of internal medicine
residents (n = 125), found that a multifactorial work stress factor (fatigue,
excessive workload, inadequate time, distractions, and stress) (mean = 2.92,
SD = 0.67 on a 5-point Likert scale) contributes more often than an in-
tellectual stress factor (inadequate knowledge, inadequate supervision)
(mean = 2.39, SD = 0.54, p < .0001) to errors. Resident use of suboptimal
care practices (e.g., working while fatigued, forgetting to transmit informa-
tion during sign-out) was the only significant feature predictive of error
(p < .0001). These internal medicine residents also report that they make
cognitive errors more often than administrative errors or procedural ones.
Other specialties make procedural errors more often (Jagsi et al., 2005).
Jagsi and colleagues (2008) later surveyed residents in 76 different
residency programs at two major teaching hospitals before and after imple-
mentation (n = 684/801 residents) of the 2003 duty hour limits to look for
contributors to error. In the post-duty hour reform period, similar propor-
tions of residents respond as to what the contributing factors for errors are
whether they are in programs that reduced their total weekly work hours
(e.g., reduced by 5 or more hours) or made no change in work hours. The
values, respectively, for the reduced hours group and the other programs
follow: poor handoffs (63.5-61.6 percent), working too many hours (44.0-
45.4 percent), carrying or admitting too many patients (47-51.8 percent),
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CONTRIBUTORS TO ERROR
cross-covering too many patients (46.9-45.9 percent), or inadequate super-
vision (24.7-34.1 percent).
Studies of resident errors should identify how the work system itself
contributes to resident errors. Rothschild et al. (2005) point out that most
of the errors in which residents were involved occurred during treatments
involving medications and in procedures (78 percent of incidents) and
communication (13.7 percent), and these can be system-level problems not
just individual performance issues. It is unreasonable to expect residents
not to make mistakes in unreliable work settings. For example, medication
vials that look almost identical increase the risk of a mistake. Improving
systems (e.g., changing paging practices to decrease interruptions, improved
handover procedures, computerized orders to avoid illegible handwriting,
better supervision) can improve the performance of residents and improve
patient safety (Volpp and Grande, 2003).
Wu says that residents need help: “although patients are the first and
obvious victims of medical mistakes, doctors are wounded by the same er-
rors; they are the second victims” (Wu, 2000, p. 358). West and colleagues
confirm this observation, finding that errors appear to beget increased
burnout and depression and that these, in turn, may set up a continuing
cycle as burnt-out residents make errors more frequently (West et al., 2006).
Fahrenkopf and colleagues also report that depressed pediatric residents
make 6.2 times more medication errors than those who are not depressed
(Fahrenkopf et al., 2008). Burnout in residents is discussed more fully in
Chapter 5.
Learning from Errors
Wu and colleagues (2003, republished from 1991, p. 221) argue that
mistakes can be “powerful formative experiences” and ideally should be
used as teaching tools. They queried internal medicine residents (n = 114) at
three large tertiary care facilities about the most significant medical mistake
they ever made and how they responded to it. Mistakes were defined as
“an act or omission for which the resident felt responsible that had serious
or potentially serious consequences for the patient and would have been
judged wrong by knowledgeable peers at the time it occurred.” The most
significant mistakes reported by residents fell into several categories (33
percent diagnosis, 29 percent prescribing, 21 percent evaluation, 11 percent
procedural, 5 percent communication) and the majority occurred in the
first year of residency. Residents perceived that 90 percent of the patients
involved had adverse outcomes as a result of their mistake (e.g., physical
discomfort, additional procedure, prolonged hospital stay, death).
In June 2003, Jagsi and colleagues surveyed medical and surgical resi-
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0 RESIDENT DUTY HOURS
dents doing clinical training in 15 specialties at two major teaching hospi-
tals about their exposure to errors made during the delivery of patient care
by themselves or others (Jagsi et al., 2005). More than half of the surveyed
medical and surgical residents (55 percent) reported that they had cared for
a patient who had experienced an AE sometime during their training, with
the residents’ most recent AE “exposure” (median time since last event =
21 days) being related to procedures (31 percent), adverse drug events (21
percent), and infections (11 percent). The categories of error are consis-
tent with medical records review studies (Gawande et al., 1999; Leape et
al., 1991; Neale et al., 2001; Thomas and Brennan, 2000; Thomas et al.,
2000a). Eighteen percent of these residents reported exposure to an AE in
the past week in a patient that they cared for,5 and about one-third of these
residents felt that they had, at least in part, been responsible (Jagsi et al.,
2005). The percentage of those who report AEs caused by mistakes that
they felt at least partially responsible for varied by specialty (surgical 10.9
percent, medical 4.7 percent, hospital based such as radiology or anesthe-
siology 3.4 percent), procedural specialty (yes 8.0 percent, no 3.7 percent),
and year of training (PGY-1 8.2 percent, PGY-2 or more 5.4 percent).
This high level of self-reported exposure in this study illustrates the key
role residents could play in the reduction of errors if error reporting and
system quality improvement were integrated into residency programs. In
Chapter 8, the committee recommends changes in error-reporting systems
to enhance the opportunity for teaching and learning when errors occur.
Conclusion About Other Factors
The committee concludes that a number of factors can contribute to
resident errors (whether errors of commission or omission) and that it is
not just a matter of hours worked or length of shift. Because first-year
residents tend to work longer hours than residents in other years, more
frequently violate duty hours, and appear to be more vulnerable to making
mistakes—and yet can be reluctant to reach out for help—the committee
has recommended in Chapter 4 the particular need to increase supervision
for these trainees. Additionally, the committee has concluded in Chapters 3
and 4 that excessive workload creates pressure to violate work hours and
can limit learning.
The resident self-report studies discussed in this section examine the
experiences of residents at a small number of major teaching institutions. As
noted earlier in this chapter, clearly, residents make mistakes during patient
5 Note that these are not considered rates of “resident-committed errors” because the study
questioned exposure to events and thus could be double counting errors due to cross-coverage
of patients by different residents.
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CONTRIBUTORS TO ERROR
care and these can result in harm to patients, but research studies to date
do not allow us to determine with precision the frequency and the severity
of those mistakes across all specialties or how often they lead to adverse
patient effects that would be preventable. However, first-year residents
appear particularly vulnerable to these mistakes or near misses although
they occur with residents of all training years, and the types of mistakes
(diagnosis, delays in treatment, and performing procedures) are ones that
better supervision would help address (Jagsi et al., 2005; Wu et al., 2003).
Many of the perceived causes of the mistakes that residents make appear
avoidable not only by better supervision but also by workload reduction,
more rest, better handovers, and other changes in the work environment.
SUMMARY
This chapter has examined five questions that are central to the debate
on the scope of resident errors while in training, the extent to which duty
hour reforms have already made a difference, and the potential contribution
of further duty hour reductions.
1. Do residents make errors that contribute to patient harm? Resi-
dents do make errors that contribute to patient harm (Jagsi et al.,
2005, 2008; Landrigan et al., 2004; Rothschild et al., 2005; Wu et
al., 2003). However, data are too limited to determine what por-
tion of errors in training facilities are due to residents and what
portion of errors result in preventable adverse events that contrib-
ute to patient harm.
2. Is resident fatigue from long duty hours among the most significant
risks to patient safety? There is evidence that residents can expe-
rience fatigue under the current ACGME duty hours (2003) and
that fatigue may derive from a number of factors, one of which
is lengthy duty hours. There is also evidence that schedules that
induce fatigue can result in increased medical errors by residents,
which are a potential risk to patients’ safety. The one randomized
controlled trial of duty hour reduction reported to date found that
serious medical errors (including medication and diagnostic errors)
and non-intercepted serious errors were significantly higher with
longer duty hours and less sleep (Landrigan et al., 2004). However,
they did not find a statistically significant difference in patient
safety as directly measured by PAEs (Landrigan et al., 2004). Con-
sequently, while resident fatigue might pose a risk to patient safety,
it is not possible to determine the extent of this risk.
3. Did the 00 reduction in resident duty hours affect patient safety?
The national studies of mortality, at the very least, show that
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0 RESIDENT DUTY HOURS
there is no evidence of widespread harm occurring after imple-
mentation of the limits (i.e., 2003 duty hour restrictions did not
lead to an increase in mortality rates for the common conditions
studied) and there may be modest improvements for medical if
not surgical patients (Landrigan et al., 2004; Prasad, 2008; Shetty
and Bhattacharya, 2007; Volpp et al., 2007a,b). The results from
national studies as well as smaller institution-specific studies indi-
cate how difficult it is to scientifically substantiate the conventional
wisdom that reduced hours would clearly result in improved pa-
tient care. Based on the available data, the committee concludes
that movement toward the 80-hour week has not had an adverse
effect on patient outcomes. It also recognizes that all training pro-
grams in the country have not actually achieved compliance with
the 80-hour week consistently.
4. Would further reductions in resident duty hours improve patient
safety? At this point, no study indicates that 80 hours or some
other lower duty hour total is optimal for patient safety. A num-
ber of studies of individual programs have found that they have
been able to accommodate to the 80-hour week, even in surgical
programs, without sacrificing educational or patient outcomes or
increasing error (e.g., de Virgilio et al., 2006; Vaughn et al., 2008).
The study by Landrigan and colleagues tested in an ICU setting an
intervention with a shorter workweek, shorter shift lengths, and
more sleep for interns. This study suggests that further reductions
in resident work hours could potentially improve conditions for
patient safety by reducing errors although the reduction in PAEs
was not statistically significant. As noted by Landrigan et al. (2004,
p. 1844), “Therefore, it remains to be determined whether the de-
crease in the rate of serious medical errors by interns will translate
into a reduction in the rate of adverse events.” Although Landrigan
and colleagues conducted a well-designed study, there are a number
of questions about its generalizability to other settings, specialties,
and years of training. Chapter 7 examines evidence from the hu-
man performance literature on the contribution of shift length,
night work, and amount of sleep in order to help identify the
factors that contribute to diminished performance and to identify
opportunities for preventing and mitigating fatigue.
5. What factors in the resident work and learning environment con-
tribute to error? Numerous factors can contribute to resident er-
rors. The causes of resident errors as well as those of other clinical
staff are not one-dimensional but include multiple factors in ad-
dition to fatigue: a work and learning environment with insuffi-
cient staffing and heavy workload, inadequate supervision, mental
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CONTRIBUTORS TO ERROR
health (e.g., burnout, depression), level of skills and knowledge,
complexity of patient’s clinical condition, communication problems
between team members, language barriers with patients, and inher-
ent system failures (Carayon and Gurses, 2008; Dean et al., 2002;
Fahrenkopf et al., 2008; West et al., 2006; Wu et al., 2003).
The committee encourages additional research on the questions in this
chapter. Identifying ways to prevent resident fatigue and the risks it poses
to patient safety requires a more systematic understanding of the extent to
which fatigued residents are causing patient harm and, if so, under what
conditions. For example, the following information would help identify
how to best protect patients from errors by residents: When during shifts
are errors made? Are many errors made by a few residents or are all
residents equally likely to commit errors? What types of errors are made,
and how serious and preventable are they? To what extent are errors cor-
rected by other clinicians and systems, and to what extent could more be
prevented by the committee’s recommendations for changes in supervision,
handovers, and protected sleep? Larger samples of residents from a greater
variety of programs and institutions would provide a better population es-
timate for identifying best practices to prevent risks to patient and resident
safety. Notwithstanding some of the excellent research that has been done
in recent years, multi-institutional studies would also have the power to
detect changes in preventable adverse errors and mortality as a function of
changes in duty hours and any resultant increases in handovers, and would
provide data on what kinds of situations need to be targeted to reduce risks
to patients and residents.
While the research studies discussed in this chapter concerning resi-
dents, duty hours, and patient safety generally have limitations and are less
conclusive about the effects of duty hours on patient safety, the research
discussed in Chapter 7 presents strong evidence that sleep deprivation,
which can result from some aspects of current duty hours, can cause
fatigue, which contributes to reduced well-being, increased errors, and
accidents. The evidence presented in the next chapter provides the basis
for the committee’s recommendations concerning changes in duty hours to
prevent fatigue.
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