Cases & Commentaries

The Forgotten Med

Commentary By Russ Cucina, MD, MS

The Case

A 78-year-old woman with a history of chronic
obstructive pulmonary disease (COPD) came to the hospital with
increasing shortness of breath and chest pain. Although she had no
history of diabetes, her glucose level on admission was nearly 300
mg/dL. Along with initial treatment, the admitting physician
prescribed once-daily insulin (glargine) and ordered finger-stick
glucose checks four times daily (QID), with sliding-scale coverage
for persistently elevated glucose values.

The patient ruled out for a myocardial
infarction, and her COPD exacerbation improved after initial
treatment. After 3 days, she was transferred to a skilled nursing
facility (SNF) for continued observation and intensive respiratory
treatments. Medication orders from the acute care ward were
continued at the SNF.

Three days later, a physician evaluated the
patient and reviewed her progress. He noted that, while glucose
values in the hospital ranged from 150-250 mg/dL, glucose levels
currently ranged from 90-140 mg/dL (essentially normal). Therefore,
thinking that the patient’s glycemic control had improved, he
discontinued the QID glucose checks and insulin sliding-scale
orders. However, he failed to notice the existing order for
glargine, a long-acting insulin.

Four days later, the patient became unresponsive.
The physician ordered stat blood cultures, electrolytes, and a head
CT scan. As staff prepared to transport the patient to radiology,
the lab called to report a critical value—a glucose level of
22 mg/dL. The physician immediately ordered intravenous dextrose
followed by an infusion, which led to a rapid improvement in the
patient’s mental status. Luckily, the patient suffered no
subsequent events, her glargine was discontinued, and she continued
her rehabilitation at the SNF.

The incident led to an internal review of the
case. The physician acknowledged that he had seen the glargine
order earlier in her SNF stay but had forgotten about it when he
discontinued the glucose checks and sliding-scale insulin orders.
Also, as in most hospitals, the nursing medication administration
record (MAR) listed the once-daily dose of insulin in a different
location than the sliding-scale insulin, because one is a regular
medication and the other given as needed. This seemingly added to
the confusion among the day and night nursing staff—since it
was the latter who administered the evening glargine and the former
who performed the glucose checks and would have administered the
sliding-scale insulin therapy.

The Commentary

While it is tempting to blame the physician for a
lack of vigilance or the nurse for failure to recognize discordant
orders, this case presents an opportunity to systematically improve
safety. Creating a new hospital policy that mandates glucose checks
in any patient receiving hypoglycemic agents (either insulin or
oral agents) is a simple and common response. Though such policies
can help raise awareness, they merely reinforce the
providers’ existing clinical practice, which relies (to an
unsafe degree) on human vigilance. Although heightened awareness
may decrease error in the short term, the benefits extinguish
rapidly, and the safety risks may exceed the capacities of human
vigilance, regardless of training or reinforcement.(1)

A second common preventive approach aims to
redesign workflow and build in safety checks. For example, a
hospital might develop specialized documentation that integrates
hypoglycemic medication orders, records of administration of those
medications, and records of glucose measurements in a uniform place
within the patient’s record. Custom documentation is common
for higher-risk nursing tasks, such as documenting
patient-controlled analgesia or the use of restraints. While these
practices are an improvement over strategies that rely on vigilance
alone, they increase already burdensome paperwork responsibilities
in nursing care (recently estimated at 16% of nursing time
[2])
and either fragment the nursing record or require redundant
documentation. Furthermore, although potentially effective for
specific problems, the technique scales poorly, since it is
impractical to implement on paper task-specific documentation for
every potential safety issue involved in medication ordering or
administration.

A more powerful solution is a system that
actively prevents orders for hypoglycemics from existing on the
medication list without the presence of glucose checks. A
“forcing
function” prevents an action from being performed or
allows it only if another specific action is performed first or
concurrently. Paper-based order sets employ this strategy when they
bundle corollary orders, such as glucose checks with insulin
orders, so they are ordered as a unit. However, paper-based systems
to bundle corollary orders continue to suffer from poor
scalability. Computerized provider order entry (CPOE) systems make
implementing forcing functions straightforward and far more
scalable. Research demonstrated a 25% improvement in completeness
of corollary orders (reduction in errors of omission) with a basic
CPOE system.(3)
Beyond corollary orders, a second study showed an 81% decrease in
all medication errors and an 86% decrease in nonintercepted serious
medication errors (harmful errors that reached the patient)
(4) in
a home-grown CPOE system with integrated decision support.

In human–computer interaction design (the
design of the communication and cognitive tasks of working with
software, including the visual user interface), forcing functions
are divided into triggers and constraints. A
trigger is a design element where an initial user action
automatically results in another action, such as when closing a
software application prompts the user to first save her work. A
constraint is a rule stating under what conditions an action
is allowed, and prevents actions that would violate a constraint.
Requiring a driver to have his foot on the brake before shifting
into reverse is a constraint, as is graying out menu items in a
software application inapplicable to its current state. Returning
to this case, having a new hypoglycemic order (the glargine
insulin) prompt a corollary order for glucose checks within a CPOE
system (a trigger) is simple. It is more subtle, however, to detect
conditions arising other than when an order is placed, such as when
an existing order is discontinued or expires, as in this case, when
the discontinuation of the glucose checks failed to prompt
providers to reconsider the existing insulin order. Building in
this type of forcing function requires an if-then rule,
stating “if a hypoglycemic is on the medication list,
then glucose checks must be on the nurses’ work
list.” Each time the orders are altered, the decision support
rules must be scanned to see if the new state resulting from the
proposed action violates any constraint; if so, an appropriate
remedy is suggested to the ordering clinician. Systems that permit
an unsafe action under current conditions, such as administering
insulin in the absence of glucose checks, are termed
underconstrained.

While building a rule-based decision support
system might appear straightforward, the number of interactions
among rules becomes very large when implemented in systems of even
moderate complexity. Unanticipated interactions become difficult to
predict and control.(5) The
labor of producing and maintaining the rule base is large, and
interruptions to clinician workflow become frequent. Interruptions
in the form of alerts decrease user acceptance, and “alert
fatigue” develops quickly (6),
rendering the safety checks ineffective.
“Noninterruptive” decision support, which alerts the
user about a potential issue without diverting him or her from the
current task, may enjoy better user acceptance and cause less alert
fatigue. Examples of noninterruptive support are few in currently
available clinical software but exist in other applications, such
as a word processor that indicates a spelling error with red
underlining but does not stop the user from typing. Institutions,
however, would face the difficult choice of what constraint
violations are sufficiently worrisome to warrant interruption, how
to interrupt, and what medicolegal ramifications those decisions
might have.

Even when finely honed, a single set of decision
support rules will not satisfy all users. Although it is useful to
remind many clinicians of the interaction between
angiotensin-converting enzyme inhibitors and spironolactone
(additive potassium retention)(7),
cardiologists who order these medications daily and are intimately
familiar with them will find an interruptive alert very unwelcome.
Unfortunately, tailoring decision support by department, or even by
individual, multiplies the cost and labor.

The benefits of CPOE depend on details of
software design, user training, and institutional
factors.(8)
Weakness in any of these elements can create opportunities for
error that did not exist in paper-based systems.(9) While many successful home-grown CPOE systems have
highly customized clinician interfaces, interface design for CPOE
has received insufficient attention from commercial vendors and
lags well behind that found in other software applications, despite
the critical human factors requirements on which safe clinical use
depends. Beyond software, vendors should develop their expertise in
the organizational factors necessary for successful health
information technology applications and bring this expertise to
customers as part of their sales package. Several studies have
demonstrated the power of specific CPOE systems to reduce error at
individual institutions, but the benefits may not apply to all CPOE
systems in all places. CPOE is undoubtedly among our most powerful
tools to enhance patient safety, but its optimal implementation
remains an unfinished science, and an active area of research,
commercial development, and entrepreneurial activity.

Take-Home Points

  • Policy- and paper-based medication
    safety improvement strategies, while useful, are limited in their
    scope, flexibility, scalability, and power.
  • Computerized provider order entry (CPOE) is a
    powerful tool to address a range of patient safety issues and a
    subject of intense national interest among payors and regulatory
    agencies.
  • Implementing CPOE is
    complex and resource intensive, holds many challenges outside the
    technical issues of implementation, and may introduce new
    risks.
  • Software design for CPOE systems is an unfinished
    science.
  • Much of the utility
    of CPOE comes from clinical decision support, the implementation
    and maintenance of which is a separate
    challenge.

Russ Cucina, MD,
MS
Assistant Professor of Medicine
Hospitalist Group & Medical Informatics
University of California, San Francisco

References

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