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of the OU are given in Table 9.2. There are five to
six basic or minimal overall variables needed to
build a dataset for the OU, which include the
number of patients placed in observation, their
LOS, disp osition: admit or discharge, and final
diagnosis: noncardiac chest pain, unstable angina,
myocardial infarction (MI), nonspecific abdominal pain, appendicitis, cholecystitis, etc. The chief
complaint is also a useful data element.
Additional clinical information such as laboratory tests (e.g. cardiac enzymes), diagnostic studies
(e.g. stress tests, CT scans, ultrasounds, MRI), procedures (esophagogastroduodenoscopy [EGD],
colonoscopy, etc.), and consults may be valuable
input for a clinical database. Provider information
regarding the physicians and the advanced practice
clinicians may be a useful factor to add to the OU
database.
Whether or not there is an electronic medical
record or a written log should not be an obstacle
to a database for the OU. Even a handwritten
registry for the OU can be utilized as a basis for
data analysis. (See Appendix 9.1: Clinical Decision
Unit or CDU log.)
Specialized or customized databases can be
designed to the require ments of the particular
OU or institution. If the institution is part of a
chest pain registry, for example, then additional
variables can be added to encompass the registry,
such as type of stress test, results of stress test,
number of patients who rule in for MI or those
with an positive enzymes or a NSTEMI (non ST
elevation MI). Trend analysis of the OU data set
may be valuable for operations regarding resource
utilization, staffing, use of ancillary tests, and
other support services.
Documentation for the
Observation Unit
Essential documentation for the OU begins with
an appropriate history and physical examination
of the patient and the reason(s) for placing the
patient in observation status, whether this is done
by the physician or the advanced level practitioner. Along with the justification for the observation care, there should be a plan outlining the
diagnostic studies to be performed and/or treatment to be given, and a strategy for discharge,
which enumerates the conditions for discharge
and the conditions for admission. Progress notes
are also an important part of the documentation.
Nursing assessments are a critical part of the
OU record and generally include an admission
nursing assessment and a notation in the records
of the patient’s discharge (or admission) including the time when discharged or admitted. Key
elements of the nursing OU documentation
include vital signs, and if appropriate, pain assessments, neurologic checks, and/or vascular checks.
Any patient and/or family education/teaching by
OU nursing staff or other personnel such as
respiratory therapists, nurse educators, or nurse
clinical specialists should be noted.
Any and all procedures and treatments should
be documented. These include any respiratory
treatments, intravenous fluids, medications
administered, diagnostic studies or procedures
or therapeutic interventions. Diagnostic interventions may range from an arterial blood gas to a
lumbar puncture, a stress test or an EGD. Treatment commo nly includes intravenous fluids and
parenteral medications, especially pain medications, antiemetics and antibiotics, but can also
include procedures such as an incision and drainage or wound care.
Table 9.2 Data Elements for Observation Unit Database*
Number of patients placed in observation
OU diagnoses
OU length of stay
Disposition from OU
– Inpatient admissions:
• Inpatient service: cardiology, general
surgery (for example)
• Inpatient floor: intensive care unit (ICU):
medical ICU, surgical ICU, cardiology
ICU, respiratory ICU, step-down, ward
– Discharge: home, nursing home,
rehabilitation
– Transfer
– Expired
– Other: LAMA (left against medical advice)
Chief complaint
Final diagnoses
Demographics: age, gender, ethnicity
Health care coverage/insurance**
* This is not an all-inclusive list, but one suggested data set
that can be tailored to the needs of your individual unit.
** May be in a different data set.
Metrics and Performance Improvement
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Again, if such therapeutic or diagnostic procedures are done, and the patient is away from the
OU, perhaps, in the endoscopy suite or in interventional radiology, the total time away from the
OU should be noted and then subtracted from the
total time in the OU as required for reimbursement depending on the payer. Some payers may
allow for an average time for a procedure such as
a stress test or endoscopy to be used instead of the
exact time for an individual patient.
Metrics for the Observation Unit
Length of Stay Metrics
Long Length of Stay (Greater than 24 Hours)
Many key OU metrics center on LOS. (Table 9.3)
Most OUs have as their policy disposition of the
patient in a specific time frame, usually 24 hours.
Therefore, the number of patients in the OU with
an extremely long stay in the OU, for example,
greater than 24 hours, is an outlier. These cases
are generally reviewed to determine the reason for
the inappropriate ly long OU stay and potential
solutions.
For example, when our OU started, we noted
that patients with a LOS > 24 hours tended to be
waiting for a stress test or a gastroenterology test
(such as an EGD or colonoscopy), which often did
not occur until late in the day or was even cancelled. We invited the administrators/physicians
in charge of stress testing and endoscopy suite,
respectively, to our monthly CDU meetings; the
collaborative result was leaving a set number of
early morning openings slotted for CDU patients,
which if unfilled then went to outside referrals or
inpatients.
Short Length of Stay (Less than 8 Hours)
A very short LOS, usually a LOS < 6–8 hours is
another metric. Patients in the OU for < a given
number of hours suggests that they were inappropriately admitted to the OU. If they were placed in
the OU and then admitted quickly as inpatients,
Table 9.3 Metrics for the Observation Unit (OU)
Length of Stay (LOS) Metrics
– LOS > 24 hours
– LOS < 6–8 hours
Observation Unit Metrics Similar to Emergency
Department Metrics
– Volume: number of patients placed in
observation unit
– Disposition
• Admissions to inpatient services
• Discharges from observation unit
• Other: left before treatment completed
(LBTC) and left against medical
advice (LAMA)
– Transfers
– Returns to ED/OU/Hospital within 72 hours
– Complaints
– Incident/SERS (Safety Event Reporting
System) reports (such as falls)
Acuity Metrics
– Admit to Intensive Care Unit: cardiac,
respiratory, medical, surgical, pediatric
– To operating room
– To cardiac catheterization lab
Process Indicators
– Process (steps) involved in obtaining
results for cardiac enzymes
Outcome Indicators
– Morbidity
– Mortality
Rate-Based Indicators
– Admission rate to inpatient unit > 20%
– Myocardial infarction rule in > 10%
Sentinel Event Indicators
– Deaths
– Codes
– Resuscitations
– Airway interventions: intubations,
unplanned use of mechanical ventilation
(Bipap, CPAP)
– Cardiac: use of thrombolytics, emergent
cardioversion, shock, life-threatening
dysrhythmias and/or use of ACLS drugs/
protocols
– Occurrence of rapid response team (RRT)
or medical emergency team (MET) calls
(for an in-house OU)
Benchmarks
– Overall LOS < 24 hours, average LOS <
15–16 hours (national)
– Complaints < 2%
Sharon E. Mace and Elaine Thallner
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this suggests they should have been directly
admitted from the ED and were too ill for the
OU. Conversely, if they were placed in the OU
and were discharged very quickly, this indicates
that they could have been discharged from the ED
and did not need an OU stay. Such extremely
short OU stays have a cost: an inordinate amount
of valuable nursing time and resources. OU stays,
no matter how long the patient’s LOS is, require a
nursing OU admission assessment that costs a
significant amount of nursing time. Moreover,
there is an inconvenience, and perhaps, even
some discomfort, to the patient and family, if
the patient is transferred from one unit to
another. Another reason for looking at LOS <
8 hours is reimbursement, with some payers not
reimbursing for stays less than 8 hours.
It is important to have an active CQI program
with metrics for reviewing data since not all outliers are inappropriate. As an example, a patient
seen in the ED with chest pain with negative
enzymes and a normal ECG is placed in observation status. At 4 hours, a second set of enzymes is
positive, the ECG is unchanged and he is admitted
to the hospital with a diagnosis of a NSTEMI.
This patient would be an outlier because he ruled
in for MI and had a short LOS of < 8 hours, but
on review, it may have been appropriate care
assuming the patient did not have unstable angina
and was not on an IV drip (e.g., nitroglycerin).
Conversely, OU CQI would note the metric
regarding the number of prolonged OU stays >
24 hours, compare this metric with previous
months, noting whether there is an unexpected
increase (or decrease). Cases > 24 hours are then
flagged for review. If the increased LOS was due
to inability to obtain a specific test, such as a stress
test, then this should be reviewed and actions
taken to make sure the required resources are
available.
At the time the patient is placed in observation
status, the patient and family should be informed
about observation being a short stay (e.g., < 24
hour) and that discharge is anticipated within
1 day or < 24 hours.
Metrics Similar to Emergency
Department Metrics
Several metrics for the OU are patterned after
metrics for the ED. Volume data, for example, is
analogous to that for the ED. The number of
patients placed in OU status (OU volume) is analogous to the number of ED visits or ED volume.
Disposition statistics are comparable to that for the
ED: number of patients admitted, discharged or
transferred from the OU, number of patients in the
OU that left against medical advice (LAMA) or left
before treatment completed (LBTC).
Complaints, LBTC including LAMA, and
transfers are standard categories that are reviewed
for the ED and for the OU. Incident or Safety
Event Reporting System (SERS) reports, such as
falls, should be evaluated, whether it occurred in
the ED or the OU.
Complaints
It should be noted that the number of complaints
for the OU are believed to be less than for the ED
and for other nursing units in the hospital. The
fast turnaround of patients with rapid access to
diagnostic testing and therapy tends to result in
fewer complaints. To our knowledge, there is only
one report that dealt specifically with the type of
complaints encountered in the OU. This study
found that the majority of complaints (43%)
involved staffing issues (interpersonal relations,
behavior or attitude) with a 10:1 ratio for nursing
to physician complaints, perhaps, at least partly
related to the fact that patient time spent with
nursing far outweighs that with the time spent
with physicians. However, the next categories of
complaints were similar to those recorded for
other areas of the hospital as opposed to those
received in EDs: discharge processes 25%, environmental concerns (unclean or uncomfortable
rooms) 17.9%, difficulties with diagnostic investigations 10.7%, and miscellaneous issues 3.6%.
14
Acuity Metrics
By definition, the patients placed in observation
are low-risk, low-acuity patients who do not need
intensive nursing or physician care (see CDU
administrative policy) and are expected to have a
high likelihood of being discharged home in less
than 24 hours. Patients who are admitted to an
intensive care unit (ICU), go to the operating
room or to the cardiac catheterization laboratory
are higher-acuity patients, which makes these
groups an important metric to track as part of
OU case review.
Metrics and Performance Improvement
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Types of Indicators for the
Observation Unit
Indicators are a tool used to identify critical components of patient care, and can be employed
for CQI activities that evaluate the quality of patient
care and support activities. Types of indicators
include structure, process, outcome, and sentinel.
16
Structural Indicators
Structure or structural indicators are utilized to
assess items such as equipment, supplies, physical
design, staffing levels, and even organizational
culture; process indicators focus on procedural
issues. Structure indicators would help identify
whether specific equipment has a high failure rate
or supplies have an unusually short life span or
significantly high rate of breakage.
Process Indicators
Process indicators center on procedures or processes, asking such questions as “ Did all chest pain
patients get aspirin?”,or“Were the appropriate
stress tests ordered?”,or“What is the incidence of
‘blood redraws’ because of lost or mislabeled etc.
specimens?” Then analyzing “What are the interrelated actions that must occur for obtaining a set
of cardiac enzym es starting from the time the
order was written, the blood drawn and labeled,
to the result reported and the physician notified?”
and ascertaining what happened when the specimen was lost or mislabeled and taking steps to
prevent this from occurring in the future. “Was
the clinical pathway or process followed?” If not,
what was the rationale? “Was the procedure done
correctly and in a timely fashion?”
Outcome Indicators
Outcome indicators measure patients’ responses
to treatment; these indicators include mortality
and measures of morbidity such as incidence of
MI, dysrhythmias, and shock.
Rate-Based Indicators
Rate-based indicators use a specified threshold or
given level. For example, if the usual admission
rate to the inpatient service from the OU is 20%
(and conversely, the discharge rate is 80%), whenever the inpatient admission rate goes above
say 20% or the discharge rate falls below 80%,
then a review of admissions from the OU to the
inpatient floors is warranted. In the multicenter
chest pain study, the rule in MI rate for OUs was
6.9%.
17
If your OU statistics reveal a high rule in
MI rate of say > 10%, then all the OU cases that
ruled in for an MI for the given time period (e.g.,
month, quarter, or year) should be reviewed to
determine if there are any CQI issues or trends.
Sentinel-Event Indicators
Sentinel-event indicators are used to screen for
serious patient care events and mandate review
whenever they occur. Customary CQI sentinel
events for the ED and hospital should also be
evaluated when they occur in the OU. Such sentinel events include deaths, codes or resuscitations,
airway interventions that indicate respiratory failure as signified by intubation or the unplanned use
of mechanical ventilation (e.g., Bipap or CPAP),
the use of thrombolytics, and the occurrence of
life-threatening dysrhythmias requiring the use of
ACLS drugs/protocols or emergent cardioversion.
Benchmarks
Benchmarking is the process of measuring patient
outcomes and/or patient care delivery or services
Table 9.4 Clinical Decision Unit Meeting (CDU) Agenda
1. Approval of monthly minutes
2. Monthly/Quarterly/Yearly Statistics
3. Metrics
4. Policies:
– Revision/update of old policies
– Adoption of new policies
Procedures:
– Revision/update of old procedures
– Adoption of new procedures
5. Order Sets
– Revision/update of previous order sets
– Adoption of new order sets
6. Triggers for Review (LOS > 24 hours, < 6–8
hours, ICU admissions, others)
7. Chart reviews
8. Complaints
9. Discussion with invited departments/individuals
10. Old business
11. New business
12. Other
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against a set standard or goal, which may be an
internal or institutional standard, or external
based on comparison with other health care
organizations or even a nation al or international
standard. The goal of 10 minutes from the door of
the ED to the ECG is an example of an external
national benchmark.
Protocols, Clinical Pathways, and
Standardized Order Sets
Protocols, pathways, order sets have been shown to
reduce costs, standardize care, cut LOS, lessen
morbidity and mortality, and most importantly,
improve patient outcomes; they are an important
part of any CQI program. (See Chapters 82–96)
Observation Unit or Clinical Decision
Unit Meetings
The CDU monthly meetings serve as a forum to
review data regarding the OU, revise old policies/
procedures/order sets, approve drafts of any new
policies/procedures/order sets, analyze any metrics
or statistics, review charts identified through the
CQI process, set new goals or benchmarks, and
invite representatives of other departments to discuss any issues of concern or areas for improvement. A CDU meeting agenda is outlined in
Table 9.4.
Summary
There must be a well-organized framework and
administrative support for the OU to be successful. An active, robust OU PI/CQI program is
critical to a well-functioning OU and ongoing
learning and improvements.
Appendix 9.1:
Observation Unit
Patient Log
CDU PATIENT LOG
Patient
Name
Medical
Record
#
Diagnosis Age Gender Date/
Time of
CDU
Arrival
Date/Time
of CDU
Discharge
LOS Discharge or
Admit (Floor,
ICU, OR or Cath
Lab)
ICU = Intensive Care Unit
OR = Operating Room
Cath Lab = Catheterization Lab
LOS = Length of Stay
Metrics and Performance Improvement
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References
1. Batalden PB, Nelson EC,
Gardent PB, et al. Leading
macrosystems and
mesosystems for microsystem
peak performance. In: Nelson
EC, Batalden PB, Godfrey MM
(eds). Quality by Design. San
Francisco, CA, Josey-Bass,
2007; ch. 4, pp. 69–105.
2. Francis RCE, Spies CD, Kerner
T. Quality management and
benchmarking in emergency
medicine. Curr Opin
Anesthesiol, 2008; 21:
233–239.
3. Specific Aims. In: Nelson EC,
Batalden PB, Godfrey MM
(eds). Quality by Design. San
Francisco, CA, Josey-Bass,
2007; ch. 18, pp. 308–312.
4. Blumenthal D. Performance
improvement in health care –
seizing the moment. N Engl
J Med, 2012; 366(21):
1953–1955.
5. Mace SE. Patient quality
(continuous quality
improvement), safety and
experience for the observation
unit. In: Observation Medicine.
American College of
Emergency Physicians,
www.acep (Accessed March
20162012).
6. Glickman SW, Schulman KA,
Peterson ED, et al. Evidencebased perspectives on pay for
performance and quality of
patient care and outcomes in
emergency medicine. Ann
Emerg Med, 2008; 51:
622–631.
7. Baker WE. Evaluation of
clinical performance in
emergency medicine. Emerg
Med Clin N Am, 2009; 27:
615–626.
8. Langberg ML, Black JT. Dead
souls comparing Dartmouth
atlas benchmarks with CMS
outcomes. N Engl J Med, 2009;
361(122):e109.
9. Wachter RM. The nature and
frequency of medical errors
and adverse events. In:
Wachter RM. Understanding
Patient Safety. New York:
McGraw Hill, 2008; ch. 1,
pp. 3–16.
10. Hudson S. Patient experience:
How to get the journey
right from start to finish.
Health Service Journal,
March 29, 2012; 122 (6300):
28–29.
11. Glasgow JM, Scott-Caziewell J,
Jill R, et al. Guiding inpatient
quality improvement: a
systematic review of lean and
six sigma. Jt. Comm J Qual
Patient Safety, Dec 2010;
36(12): 531–532.
12. Graff L. Observation units for
elimination of missed
myocardial infarction errors.
Maryland Medicine, 2001;
suppl; 40–42.
13. Mace SE. Continuous quality
improvement for the clinical
decision unit. Healthcare
Quality, 2004; 26(1): 29–36.
14. Mace SE. An analysis of patient
complaints in an observation
unit. J Qual Clin Practice, 1998;
18(2): 151–158.
15. Mace SE. Resuscitations in an
observation unit. J Qual Clin
Practice, 1999; 19: 155–164.
16. Donabedian A. The quality of
care: How can it be measured.
JAMA, 1988; 121(11): 1145–
1150.
17. Graff LG, Dallara J, Ross MA,
et al. Impact on the care of the
emergency department chest
pain patient evaluation registry
(CHEPER) study. Amer J Card
1997; 80(5): 563–568.
Sharon E. Mace and Elaine Thallner
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Part
II
Observation Medicine: Clinical
Setting and Education
12:20:06
Part II
Chapter
10
Observation Medicine: Clinical Setting And Education
The Community Hospital Perspective
in a Suburban/Rural Setting
Ryan Prudoff, DO, MS, FACEP
Stephen Sayles, MD, FACEP
Observation medicine or Clinical Decision Units
(CDUs) can be a valuable asset in the small-tomedium rural community setting. It is important
to have a good working relationship with your
hospital administration to allow for a mutually
beneficial arrangement. There are a myriad of
factors that contribute to a highly functioning
CDU, which can improve the overall flow of the
Emergency Department (ED). The CDU, however,
should be regarded as a separate “service line” and
should be viewed as such with careful consideration given to:
1. How the service will improve patient care and
decrease physician liability
2. How ED through-put will be affected
3. Ancillary service involvement
4. Additional work required
5. ED group finan cials vs. hospital financial
repercussions
Our community hospital functions with a fourbed CDU with a yearly ED volume of 26,700
patients. Of all hospital admissions, 5.5% were
placed in observation – with the ED managing
58% of those observation patients in an ED CDU
and 42% placed in observation status throughout
the hospital.
Prior to implementation of the ED observa-
tion unit (OU), the average length of stay (LOS)
for all hospital observation patients was 27 hours.
The LOS for patients managed through the ED
OU averaged 15 hours and the LOS for observation patients in the hospital (e.g., non-ED OU
observation patients) remained at 27 hours. Over
12 months of operation, 848 patients were evaluated in the CDU, saving the hospital the equivalent of 424 patient days. The implementation of
the CDU resulted in improvement in the backend ED processing of patients and ED patient
flow or turnaround time, as well as adding value
to the hospital by increasing bed availability for
higher-acuity patients.
Tantamount to our successful operation was
the idea that the bed was the most valuable
commodity in the flow equation. We employed
24-hour CDU management, meaning discharg es
occur more promptly in an attempt to improve
turnaround time. Although consideration was
given to the time of day discharges occurred,
patients were given the option to be discharged
late in the evening if their workup was complete.
Also, our CDU was designated a closed unit
which eliminated the dependence and delays that
occur from waiting on “non-ED physicians” to
evaluate or discharge patients.
We initially reviewed the information from
ACEP’s observation medicine section for a menu
of common observation conditions (www. acep.
org/Clinical–Practice-Management/ObservationMedicine) and selected those conditions that would
be optimally treated with the resources available at
our facility. As the comfort level of both physicians
and observation nursing staff increased, we began
to expand the services provided in the CDU. We
selected chest pain, asthma, and COPD initially
because the patients could be continually monitored and treated as if they would be on the hospital floor. We believe the proximity of the CDU to
the ED adds an advantage to patients by providing
access to emergency physicians for rapid response
if a patient’s condition deteriorates or they do not
respond as desired to medical management.
Initiation of clinical care pathways was instituted for those conditions placed in the OU,
which allows for consistent high-quality care and
limited treatment variability. We used established
care plans as the framework for those conditions
selected for evaluation in the OU. Through close
collaboration with the available subspecialists, we
created site-specific protocols leveraging the facility’s available resources. We also established
inclusion and exclusion criteria for each care plan.
Conversely, we excluded patient conditions
requiring a high amount of social resources,
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which can monopolize CDU staff and detract from
the management of observation patients. For
example, a patient under the influence of chemical
substances or having psychiatric issues can have
high demands on the CDU staff. Additionally we
found that patients who could not ambulate or
perform activities of daily living or with severe
dementia were failures for treatment in the CDU.
These failures were due to other ancillary services
needed to be involved in their medical care and the
additional time needed to coordinate follow-up.
This is consistent with the findings of a recent
study regarding the types of CDU patients that will
need inpatient admission from the CDU. In this
study, frailty and sociodemographic factors were
the greatest predictors of inpatient admission from
the CDU.
1
As a general rule, patients placed in the
OU should have only a few discrete issues that can
be addressed simply, and should be able to walk in
and out of the CDU.
The number of observation services that EDs
can potentially provide is growing and determining which services are right for your facility may
be dependent on what ancillary services or diagnostic services are available. Overall, observation
medicine has been a success at our facility and our
CDU continues to expand services – most
recently in the form of Pediatric Observation.
Pediatric Observation in the
Community Setting
Observation of pediatric patients improves compliance w ith therapy, decreases patient bounce
backs and allows for the closer monitoring of
patients. Since management of both adult and
pediatric patients (“hybrid unit”; see hybrid units
in Chapter 1) occurred in the four-bed CDU, we
found the variable experience of nursing staff
and the requirements of young children/toddlers
increased staff an xiety. We addressed staffing
concerns by treating only school-aged children,
that is, children 5 years and above. In addition,
we required at least one parent to remain in the
OU with the child at all times. This allows for
the patient’s family to be updated on any changes
in c ondition, decreases delays in locating the
guardian in the event that the patient is decompensated and requires transfer, and allows
patients to be discharged in real time. (See Pediatric Observation Chapters 53 and 54, and The
Evidence Basis for Age-Related Observation care
Chapter 81. )
With the assistance of our local pediatricians,
we limited our services to high-yield complaints
such as asthma, dehydration, non-differentiated
abdominal pain, cellulitis, and urinary tract
infections. Aggressive treatment and frequent
reevaluation allowed for faster disposition and
turnaround. This is important in the rural community setting where the pediatrician is often
not available 24 hours a day.
We have had success with the selected patient
populations and complaints chosen for observation treatment. We have decreased the patients’
overall LOS, improved hospital resource utilization, and increased hospital bed availability.
References
1. Zdradzinski MJ, Phelan MP, Mace SE. Impact of
fraility and sociodemographic factors on hospital
admission from an emergency department
observation unit. AJMQ (accepted for publication
2016)
Ryan Prudoff and Stephen Sayles
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