While there is a wealth of literature dealing with the
association between workload and patient outcomes and costs for nurses and housestaff, there has been relatively little literature on
the impact of attending physician workload.
A new study has looked at the impact of hospitalist workload
on quality and efficiency of care (Elliott
2014). They found clinically meaningful increases in length of stay and
costs associated with increased hospitalist workloads. They found that LOS and
cost increased exponentially above a hospitalist census value of about 15
patients per day. Length of stay accounted for most of the excess cost but even
after adjustment for length of stay cost increased by $205 per unit increase in
hospitalist census.
Hospital occupancy was also a factor. For occupancies less
than 75%, LOS increased linearly from 5.5 to 7.5 days from low to high
workloads. At occupancies between 75-85% LOS was stable across lower workloads
but increased to 8.0 days at higher workloads.
Importantly, they did not find associations between
hospitalist workload and in-hospital mortality, rapid response team activation,
30-day readmissions, or patient satisfaction.
While the Elliott study found no adverse effects on patient
safety issues related to higher hospitalist workloads, in a previous survey of
hospitalists (Michtalik
2013) respondents strongly felt that excessive workloads did impact
patient safety and outcomes. In that survey 40% of hospitalists responding felt
that their typical inpatient workload exceeded “safe” levels at least monthly.
The hospitalists felt that excess workload frequently interfered with full
discussion of treatment options, led to delays in discharges (or admissions), more
testing and consults, worsened patient satisfaction, and probably also
contributed to patient transfers, morbidity and mortality. Keep in mind,
however, that this study had no objective measurements of quality and patient
safety and was based on the perceptions of the responding hospitalists.
In an editorial accompanying the Elliott study, Bob Wachter (Wachter
2014) notes that there are considerations other than simply patient
census that need be taken into account. For example, hospitalists in most
institutions play key roles in some of the quality improvement and patient
safety initiatives. They may also have other administrative and/or teaching
responsibilities. He, therefore, notes that the number 15 patients per
hospitalist may not apply at all settings and in all circumstances.
The key is probably consideration of models to better
intervene when physician workloads approach such thresholds.
References:
Elliott DJ, Young RS, Brice J, et al. Effect of HospitalistWorkload on the Quality and Efficiency of Care. JAMA Intern Med 2014; Published
online March 31, 2014
http://archinte.jamanetwork.com/article.aspx?articleid=1847571
Wachter RM. HospitalistWorkload:
The Search for the Magic Number. JAMA
Intern Med 2014; Published online March 31, 2014
http://archinte.jamanetwork.com/article.aspx?articleid=1847567
Michtalik HJ, Yeh
H-C, Pronovost PJ, Brotman
DJ. Impact of Attending Physician Workload on Patient Care: A Survey of
Hospitalists. JAMA Intern Med 2013; 173(5): 375-377
http://archinte.jamanetwork.com/article.aspx?articleid=1566604
Print “May
2014 Hospitalist Workload Impact on Care and Cost”
Our What’s New in
the Patient Safety World columns for September 2012 “FDA
Warning on Codeine Use in Children Following Tonsillectomy” and March 2013 “Further
Warning on Codeine in Children Following Tonsillectomy” described cases of
death and serious adverse effects in children treated with codeine following adenotonsillectomy for obstructive sleep apnea. Those cases
led to the FDA issuing a safety alert (FDA 2012) and
additional cases led to a subsequent black box warning for products containing codeine (FDA 2013).
The original FDA
alert was issued after reviewing reports in the literature of 3 deaths and one
near-miss case of respiratory depression in young children (ages 2-5) following
tonsillectomy and/or adenoidectomy for obstructive sleep apnea (Ciszkowski
2009, Kelly
2012). The most interesting facet
is the data presented on unusual metabolism of codeine as a root cause.
Ingested codeine is converted into morphine in the liver by cytochrome
P450 2D6 (CYP2D6). It turns out there are genetic variations that cause some
people to be “ultra-rapid metabolizers” which leads to higher concentrations of
morphine earlier. Apparently all the children in the above reports were
“ultra-rapid metabolizers”. The original FDA alert (FDA 2012)
estimates the number of “ultra-rapid metabolizers” as generally 1 to 7
per 100 people, but may be as high as 28 per 100 people in some ethnic groups
(the FDA site has a table of these rates by ethnic group).
In addition to those
rapid metabolizers who are at risk for toxicity from codeine, up to a third of
children are poor metabolizers of codeine and subsequently get little or no
benefit of codeine for pain or other conditions such as cough (Kaiser
2014). For many years the American
Academy of Pediatrics has recommended against use of codeine in children for
either analgesia or cough. The American College of Chest Physicians has
recommended against the use of codeine for cough in children since 2006. And
the World Health Organization and health ministries in Canada and Europe
likewise have recommended against use of codeine in children.
So one would
anticipate that use of codeine in children would have almost stopped
completely. Not so. A recent study (Kaiser
2014) has demonstrated that codeine continues to be prescribed to children
in significant numbers. They analyzed emergency department visits for children
between the ages of 3 and 17 from 2001 to 2010. Though the percentage of visits
resulting in codeine prescriptions did drop from 3.7% to 2.9% over the study
period, there was no decline in prescription rates after the 2006 guidelines recommending
against use of codeine for cough or URI. For subgroups, the rate of codeine
prescriptions did decrease significantly in the 3-7 year age group but not
others. Overall, codeine continued to be prescribed to 500,000 to almost
900,000 children per year.
The authors note some potential interventions that might
decrease the prescription of codeine in children including:
It’s pretty clear that guidelines and provider education
have been inadequate in stopping use of codeine in children. If you do
educational interventions, remember that stories
are better than statistics. Be sure to include descriptions of cases in the original literature of 3 deaths and one
near-miss case of respiratory depression (Ciszkowski 2009,
Kelly
2012). But remember that education
and training are what we consider to be weak actions. In our March 27, 2012
Patient Safety Tip of the Week “Action
Plan Strength in RCA’s” we included some slides
to help you remember which actions are strong and which are weak. Forcing
functions and constraints that make it difficult to order or
prescribe codeine for children are much more likely to be successful.
References:
FDA. FDA Drug Safety
Communication: Codeine use in certain children after tonsillectomy and/or
adenoidectomy may lead to rare, but life-threatening adverse events or death.
8/15/12
http://www.fda.gov/Drugs/DrugSafety/ucm313631.htm
FDA. FDA Drug Safety Communication: Safety review update of
codeine use in children; new Boxed Warning and Contraindication on use after
tonsillectomy and/or adenoidectomy. Update February 20, 2013
http://www.fda.gov/Drugs/DrugSafety/ucm339112.htm
Ciszkowski C, Madadi
P, Phillips MS, Lauwers AE, Koren
G. Codeine, ultrarapid-metabolism genotype, and
postoperative death. N Engl J Med 2009; 361(8):
827-828
http://www.nejm.org/doi/full/10.1056/NEJMc0904266
Kelly LE, Rieder M, van den Anker
J, Malkin B, Ross C, Neely MN, et al. More codeine
fatalities after tonsillectomy in North American children. Pediatrics 2012;
129:5 e1343-e1347; published ahead of print April 9, 2012
Kaiser SV, Asteria-Penaloza R, Vittinghoff E, et al. National Patterns of Codeine
Prescriptions for Children in the Emergency Department. Pediatrics 2014; 133(5): e1139-e1147 Published
online April 21, 2014
http://pediatrics.aappublications.org/content/early/2014/04/16/peds.2013-3171.full.pdf+html
Print “May
2014 Pediatric Codeine Prescriptions in the ER”
In the past 3 years we’ve done multiple columns (see list at the end of today’s column) highlighting
some of the detrimental effects related to red blood cell transfusions and the
trend toward more restrictive transfusion strategies in many different
scenarios. Unnecessary transfusions
have not only clinical untoward effects but add to health care costs.
One of the untoward side effects of transfusion is the risk
of infection. A new systematic review and meta-analysis on the relative risk of
infection in restrictive vs. liberal transfusion strategies was just published (Rohde 2014).
It showed the risk of serious infections was 11.8% with a restricted
transfusion strategy vs. 16.9% with a liberal strategy. The number needed to
treat (NNT) with the restrictive strategy to prevent one infection was 38. For
every 1000 patients in which transfusion is under consideration 26 serious
infections could be avoided by using the restrictive transfusion strategy.
The accompanying editorial by Jeffrey Carson (Carson 2014),
author of several studies on the detrimental aspects of transfusion and lead
author of the revised AABB guidelines on transfusion (see our April 2012 What’s New in the Patient Safety
World column “New
Transfusion Guidelines from the AABB”), highlights some of the other
outcomes that benefit from a restricted transfusion strategy. He further
highlights, however, that we still don’t know the optimal transfusion
threshold/trigger, noting some evidence to suggest that may be even lower than
the current guidelines (Carson
2012) suggest.
Have your
organization’s transfusion policies and practices kept up-to-date with current
trends and recommendations?
Prior columns on
potential detrimental effects related to red blood cell transfusions:
References:
Rohde JM, Dimcheff DE, Blumberg N.
et al. Health Care–Associated Infection After Red
Blood Cell Transfusion. A Systematic Review and Meta-analysis. JAMA 2014;
311(13): 1317-1326
http://jama.jamanetwork.com/article.aspx?articleid=1853162
Carson JL. Blood Transfusion and Risk of InfectionNew
Convincing Evidence (editorial). JAMA 2014; 311(13): 1293-1294
http://jama.jamanetwork.com/article.aspx?articleid=1853139
Carson JL, Grossman BJ, Kleinman
S, et al. for the Clinical Transfusion Medicine Committee of the AABB. Clinical
Guidelines.Red Blood Cell Transfusion: A Clinical
Practice Guideline From the AABB. Ann Intern Med 2012;
157(1): 49-58
http://annals.org/data/Journals/AIM/24329/0000605-201207030-00008.pdf
Print “May
2014 Blood Transfusion and Infection Risk”
A new easy-to-use scoring system for severity of delirium has
been developed and validated (Inouye 2014). The
tool, CAM-S, is based on the Confusion Assessment Method (CAM) which is already
widely used as a screening tool for delirium. There are actually 2 forms, one a
4-item tool and the other a 10-item tool. Both were validated in 2 independent
populations and have good inter-rater reliability. Increasing severity on these
two scores is associated with worse outcomes (length of stay, hospital costs,
nursing home placement, cognitive decline, death within 90 days, and functional
decline at 30 days). Previous systems for scoring severity of delirium have not
been widely adopted. The new system will likely be better utilized because of
its relationship to the CAM and it doesn’t require special training to
administer. The short form takes only 5 minutes to complete. The tool(s) may
help follow the clinical progress of patients with delirium, determine whether
the patient is improving and responding to management interventions, and be of
prognostic value. They likely will also play a key role in future research and
clinical trials.
The accompanying editorial (Eubank 2014) notes
that delirium has a risk of death similar to that for myocardial infarction and
severity of complications and costs similar to diabetes yet has never received
the amount of attention that either of those 2 conditions have.
This is a welcome scoring system and we expect you’ll hear a
lot more about its use in the next few years.
Some of our prior
columns on delirium assessment and management:
·
October
21, 2008 “Preventing
Delirium”
·
October
14, 2009 “Managing
Delirium”
·
February
10, 2009 “Sedation
in the ICU: The Dexmedetomidine Study”
·
March
31, 2009 “Screening
Patients for Risk of Delirium”
·
June 23,
2009 “More
on Delirium in the ICU”
·
January
26, 2010 “Preventing
Postoperative Delirium”
·
August
31, 2010 “Postoperative
Delirium”
·
September
2011 “Modified
HELP Helps Outcomes in Elderly Undergoing Abdominal Surgery”)
·
December
2010 “The
ABCDE Bundle”
·
February
28, 2012 “AACN
Practice Alert on Delirium in Critical Care”
·
April 3, 2012 “New
Risk for Postoperative Delirium: Obstructive Sleep Apnea”
·
August
7, 2012 “Cognition,
Post-Op Delirium, and Post-Op Outcomes”
·
September
2013 “Disappointing
Results in Delirium”
·
October
29, 2013 “PAD:
The Pain, Agitation, and Delirium Care Bundle”
·
February
2014 “New
Studies on Delirium”
·
March
25, 2014 “Melatonin
and Delirium”
References:
Inouye SK, Kosar CM, Tommet D, et al. The CAM-S: Development and Validation of a
New Scoring System for Delirium Severity in 2 Cohorts. Ann Intern Med 2014;
160(8):526-533
http://annals.org/article.aspx?articleid=1860529
Eubank KJ, Covinsky KE. Delirium
Severity in the Hospitalized Patient: Time to Pay Attention. Ann Intern Med
2014; 160(8): 574-575
http://annals.org/article.aspx?articleid=1860540
Print “May
2014 New Delirium Severity Score”
A new review shows that over 5% of outpatients have errors
in diagnosis, about half of which may be potentially harmful (Singh
2014). The authors estimate that such errors in diagnosis may affect 12
million outpatients annually in the US.
In our March 2013
What’s New in the Patient Safety World column “Diagnostic
Error in Primary Care” and our January 2014 What’s New in the Patient
Safety World column “Trigger
Tools to Prevent Diagnostic Delays” we highlighted previous studies by
Singh and colleagues (Singh
2013, Murphy 2014)
on diagnostic errors in primary care that used
trigger tool methodology. The new study included the previous work and a total
of 3 studies using the same definitions and methodologies.
AHRQ, which partially funded the study, did a press release (AHRQ
2014) that also calls attention to the AHRQ toolkit
“Improving Your Office Testing Process. A Toolkit for Rapid-Cycle Patient
Safety and Quality Improvement” (see our October 2013 What’s New in the Patient
Safety World column “New
AHRQ Toolkit: Improving Your Office Testing”) and a new set of guides and interactive
tools from the ONC to help health care providers more safely use electronic
health information technology products, including test results reporting and
follow up.
Diagnostic error, and specifically diagnostic error on the
outpatient side, is finally receiving the attention it merits. It is important
both in its frequent occurrence and the harm that results from it.
Some of our prior
columns on diagnostic error:
References:
Singh H, Meyer AND, Thomas EJ. The frequency of diagnostic
errors in outpatient care: estimations from three large observational studies
involving US adult populations. BMJ Qual Saf 2014; published online
April 17, 2014
http://qualitysafety.bmj.com/content/early/2014/04/04/bmjqs-2013-002627.short?g=w_qs_ahead_tab
Singh H, Giardina TD, Meyer AND,
et al. Types and Origins of Diagnostic Errors in Primary Care Settings. JAMA
Intern Med 2013; published online February 25, 2013
http://archinte.jamanetwork.com/article.aspx?articleid=1656540
Murphy DR, Laxmisan A, Reis BA, et
al. Electronic health record-based triggers to detect potential delays in
cancer diagnosis. BMJ Qual Saf 2014; 23: 8-16
Published Online First: 19 July 201
http://qualitysafety.bmj.com/content/23/1/8.full.pdf+html
AHRQ. Diagnostic Errors Study Findings. Press Release April
16, 2014
http://www.ahrq.gov/news/newsroom/press-releases/2014/diagnostic_errors.html
AHRQ. Improving Your Office Testing Process. A Toolkit for
Rapid-Cycle Patient Safety and Quality Improvement. August 2013
ONC (Office of the National Coordinator for Health
Information Technology). Safer Guides. HealthIT.gov
http://www.healthit.gov/safer/safer-guides
Print “May
2014 Frequency of Diagnostic Errors in Outpatients”
Print “May
2014 What's New in the Patient Safety World (full
column)”
Print “May
2014 Hospitalist Workload Impact on Care and Cost”
Print “May
2014 Pediatric Codeine Prescriptions in the ER”
Print “May
2014 Blood Transfusion and Infection Risk”
Print “May
2014 New Delirium Severity Score”
Print “May
2014 Frequency of Diagnostic Errors in Outpatients”
Print “May
2014 What's New in the Patient Safety World (full
column in PDF version)”
http://www.patientsafetysolutions.com/