Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT01116323 |
| Other study ID # |
AE1.7.005.11.N.00 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
June 2010 |
| Est. completion date |
December 2013 |
Study information
| Verified date |
August 2021 |
| Source |
KU Leuven |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
Since the report "To Err is Human" by the Institute of Medicine (IOM) in 1999, attention was
brought to the general public that adverse events in medicine are common and are one of the
leading causes of morbidity and mortality within the United States. The report estimates that
44,000 - 98,000 patients hospitalized in the United States die each year as a result of
medical errors.
In spite of the growing patient safety movement worldwide, health care has not become
measurably safer. Health care is one of the few risk-prone areas in which public demand
limits the use of common-sense safety-enhancing solutions, such as limiting the flow and
choosing the type of incoming patients. The latter is especially true for emergency
departments (EDs) since they deliver an important public service by providing emergency care
24 hours a day, 365 days per year, without discrimination by social or economic status. One
of the key expectations of EDs is the ability to provide immediate access and stabilization
for those patients who have an emergency medical condition. However, emergency department
(ED) crowding is recognized to be a major, international problem that affects patients and
providers. A recent report from the IOM noted that the increasing strain caused by crowding
is creating a deficit in quality of emergency care. Crowding has been associated with reduced
access to emergency medical services, delays in care for cardiac patients, increased patient
mortality, inadequate pain management, increased costs of patient care, and delays in
administration of antibiotic therapy.
Several issues remain concerning ED crowding and it's relation to adverse events. First, the
existing evidence on adverse event occurrence during ED crowding is largely anecdotal and
inconclusive. Secondly, although a few studies showed a relationship between ED crowding and
mortality, neither of these examined the causes of excess mortality. Finally, although a
significant increase in the average length of hospital stay was shown during ED crowding the
reasons for this are open to speculation.
The purpose of this study therefore is to identify six explicit adverse events and mortality
for patients who were admitted through ED and to compare these results in relation to ED
crowding. This will provide us novel insight into the reasons for the hypothesized increased
mortality during ED crowding.
Description:
Since "ED crowding" is an unplanned condition, a randomized controlled trial is not possible
to assess its impact on adverse patients' outcome. Therefore, a large prospective cohort
study, with careful matching and correcting for risk factors is the second best design.
The ED occupancy rate, defined as the ratio of the total number of ED patients to the number
of licensed treatment bays per hour, will be used as a measure of ED crowding. The numerator
includes all patients in the ED at any point during each study hour, regardless of ED
location (including in the waiting room, boarding, hallway location). The denominator,
constant per study hour, includes the total number of licensed treatment bays as defined
according to the ED's original blueprint but excludes hallway locations. For each hour of the
day, the ED occupancy rate will be derived from the ED information system. 104 weeks are
divided into 13-week seasonal blocks and nursing shifts starting 23:00, 07:00 and 15:00. The
mean ED occupancy rate is calculated for each shift as the sum of the occupancy rates within
that shift divided by 8. The top quartile of all mean ED occupancy rates during the cohort
period is considered as crowded. In order to match both 'crowded 'and 'not crowded' cohorts,
the following data elements are extracted from the hospital information system for each
registered patient: demographic data (age, sex, co-morbidities); referral source, surgical or
medical admission; time of arrival (including season, month of year, day of week, time of
day); triage category; ED and total hospital length of stay; and final admission diagnosis.
Medical records of patients who presented to the ED will be reviewed for the occurrence of
six adverse events and mortality up to ten days of their ED stay. The six adverse events are
searched through explicit clinical criteria. The reviewer first rates on a scale of 1 to 6
the confidence that medical management caused an adverse event. If the rating is 5 or 6,
indicating that the injury is probably or definitely caused by management, the event is
considered an adverse event. The same rating score is used to assess the degree of
preventability. Hospital mortality will be searched for all patients who presented to the ED
at some point in time and died during that hospital stay.
In order to identify an adverse event occurrence hazard ratio of 1.2 with a power of 0.9
during ED crowding, a cohort of 104,000 patients is needed. Therefore, data will be retrieved
during a 2 year period during which the reviewer is blinded to the degree of ED crowding in
relation to the findings on adverse events. The occurrence of adverse events and mortality
will be compared to not crowded shifts, corrected for baseline risk factors. A carefully
standardized admission form for registration of relevant information as well as a
computerized search tool for screening for adverse events will allow finalizing this study
within the foreseen time frame.
