The Biggest Mistake Doctors Make
harmful and costly. But they're often preventable.
By Laura Landro,
assistant managing editor for The Wall Street Journal
Not only are
diagnostic problems more common than other medical
mistakes—and more likely to harm patients—but they're
also the leading cause of malpractice claims, accounting
for 35% of nearly $39 billion in payouts in the U.S.
from 1986 to 2010, measured in 2011 dollars, according
to Johns Hopkins.
The good news is that
diagnostic errors are more likely to be preventable than
other medical mistakes. And now health-care providers
are turning to a number of innovative strategies to fix
the complex web of errors, biases and oversights that
stymie the quest for the right diagnosis.
Part of the solution
is automation—using computers to sift through medical
records to look for potential bad calls, or to prompt
doctors to follow up on red-flag test results. Another
component is devices and tests that help doctors
identify diseases and conditions more accurately, and
online services that give doctors suggestions when they
aren't sure what they're dealing with.
Finally, there's a
push to change the very culture of medicine. Doctors are
being trained not to latch onto one diagnosis and stick
with it no matter what. Instead, they're being taught to
keep an open mind when confronted with conflicting
evidence and opinion.
"Diagnostic error is
probably the biggest patient-safety issue we face in
health care, and it is finally getting on the radar of
the patient quality and safety movement," says Mark
Graber, a longtime Veterans Administration physician and
a fellow at the nonprofit research group RTI
Software-Guided Insulin Dosing: Tight
Glycemic Control and Decreased Glycemic
Derangements in Critically
Clin Proc. n September 2013
determine whether glycemic derangements are more
effectively controlled using softwareguided
insulin dosing compared with paper-based protocols.
Patients and Methods: We prospectively evaluated
consecutive critically ill patients treated in a
tertiary hospital surgical intensive care unit (ICU)
between January 1 and June 30, 2008, and between January
1 and September 30, 2009. Paper-based protocol insulin
dosing was evaluated as a baseline during the first
period, followed by software-guided insulin dosing in
the second period. We compared glycemic metrics related
to hyperglycemia, hypoglycemia, and glycemic variability
during the 2 periods.
Results: We treated 110 patients by the
paper-based protocol and 87 by the software-guided
protocol during the before and after periods,
respectively. The mean ICU admission blood glucose (BG)
level was higher in patients receiving software-guided
intensive insulin than for those receiving paper-based
intensive insulin (181 vs 156 mg/dL; P¼.003, mean of the
per-patient mean). Patients treated with software-guided
intensive insulin had lower mean BG levels (117 vs 135
mg/dL; P¼.0008), sustained greater time in the desired
BG target range (95-135 mg/dL; 68% vs 52%; P¼.0001), had
less frequent hypoglycemia (percentage of time BG level
was <70 mg/dL: 0.51% vs 1.44%; P¼.04), and showed
decreased glycemic variability (BG level per-patient
standard deviation from the mean: 29 vs 42 mg/ dL;
Conclusion: Surgical ICU patients whose intensive
insulin infusions were managed using the softwareguided
program achieved tighter glycemic control and fewer
glycemic derangements than those managed with the
paper-based insulin dosing regimen.
Committee: Development, Successful Implementation, and
Impact on Patient Safety
Journal, Volume 13, Number 3, Fall 2013
Hypoglycemia is a major and preventable cause of
morbidity and mortality in the hospital setting.
hypoglycemia in hospitalized patients relates to the
practice climates and prescribing patterns of
physicians, the development of safe and effective
protocols, and the education of providers and nursing
staff on hypoglycemia and its consequences.
Many hospitals use multidisciplinary committees to
address issues of healthcare quality and patient safety.
article describes the creation of a subspecialty
Hypoglycemia Committee, its design and function, and the
steps taken to reduce hypoglycemia in a large, tertiary
acute care hospital.
The committee’s initiatives included a systematic
investigation of all severe hypoglycemic events, the
development of a standalone hypoglycemia treatment
protocol, reduction of sliding scale insulin therapy,
revision of insulin order sets, and education of
physicians and house staff. Hypoglycemic events have
The Hypoglycemia Committee is unique in that every case
of severe hypoglycemia is reviewed by physicians,
endocrinologists, and diabetes specialists. This
multidisciplinary approach can effect measurable
decreases in preventable hypoglycemic events.
AND THE INTERPRETATION OF
INPATIENT GLUCOSE CONTROL DATA
Objective: To introduce a statistical method of
assessing hospital-based non–intensive care unit
(non-ICU) inpatient glucose control.
Methods: Point-of-care blood glucose (POC-BG)
data from non-ICU hospital units was extracted for
January 1 through December 31, 2011. Glucose data
distribution was examined before and after Box-Cox
transformations and compared to normality. Different
subsets of data were used to establish upper and lower
control limits, and exponentially weighted moving
average (EWMA) control charts were constructed from
June, July, and October data as examples to determine if
out-of-control events were identified differently in
nontransformed vs transformed data.
Results: A total of 36,381 POC-BG values were
analyzed. In all 3 monthly test samples, glucose
distributions in nontransformed data were skewed but
approached normal distribution once transformed.
Interpretation of out-of-control events from EWMA
control chart analysis also revealed differences. In the
June test data, an out-of-control process was identified
at sample 53 with nontransformed data, while the
transformed data remained in control for the duration of
the observed period. Analysis of July data demonstrated
an out-of-control process sooner in the transformed data
(sample 55) than the nontransformed (sample 111), while
for October, transformed data remained in control longer
than nontransformed data.
Conclusion: Statistical transformations increase
the normal behavior of inpatient non-ICU glycemic data
sets. The decision to transform glucose data could
influence the interpretation and conclusions about the
status of inpatient glycemic control. Further study is
required to determine whether transformed vs
nontransformed data influence point-of-care decisions or
evaluation of interventions.
Pathways to Quality Inpatient
Management of Hyperglycemia and Diabetes:
Call to Action
Care 36:1807–1814, 2013
Currently patients with diabetes comprise up to 25–30%of
the census of adult wards and critical care units in our
hospitals. Although evidence suggests that avoidance of
hyperglycemia (.180 mg/dL) and hypoglycemia (,70 mg/dL)
is beneficial for positive outcomes in the hospitalized
patient, much of this evidence remains controversial and
at times somewhat contradictory. We have recently formed
a consortium for Planning Research in Inpatient Diabetes
(PRIDE) with the goal of promoting clinical research in
the area of management of hyperglycemia and diabetes in
In this article, we outline eight aspects of inpatient
glucose management in which randomized clinical trials
are needed.We refer to four as system-based issues and
four as patient-based issues.We urge further progress in
the science of inpatient diabetes management. We hope
this call to action is supported by the American
Diabetes Association, The Endocrine Society, the
American Association of Clinical Endocrinologists, the
American Heart Association, the European Association for
the Study of Diabetes, the International Diabetes
Federation, and the Society of Hospital Medicine.