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Synopsis
Systematic Review of Antimicrobial
Drug Prescribing in Hospitals
Peter Davey,*†
Erwin Brown,‡ Lynda Fenelon,§ Roger Finch,¶# Ian Gould,** Alison Holmes,††
Craig Ramsay,‡‡ Eric Taylor,§§ Phil Wiffen,¶¶ and Mark Wilcox,##***
*University of Dundee Medical School, Dundee, United Kingdom; †Ninewells
Hospital, Dundee, United Kingdom; ‡Frenchay Hospital, Bristol, United
Kingdom; §St Vincent's University Hospital, Dublin, Ireland; ¶Nottingham
City Hospital, Nottingham, United Kingdom; #University of Nottingham,
Nottingham, United Kingdom; **Aberdeen Royal Infirmary, Aberdeen, United
Kingdom; ††Hammersmith Hospital, London, United Kingdom; ‡‡University
of Aberdeen Health Services Research Unit, Aberdeen, United Kingdom; §§Inverclyde
Royal Hospital, Greenock, United Kingdom; ¶¶United Kingdom Cochrane Centre,
Oxford, United Kingdom; ##Leeds General Infirmary, Leeds, United Kingdom;
and ***University of Leeds, Leeds, United Kingdom
Suggested
citation for this article
Prudent prescribing
of antimicrobial drugs to hospital inpatients may reduce incidences
of antimicrobial drug resistance and healthcare-associated infection.
We reviewed the literature from January 1980 to November 2003 to identify
rigorous evaluations of interventions to improve hospital prescribing
of antimicrobial drugs. We identified 66 studies with interpretable
data, of which 16 reported 20 microbiologic outcomes: gram-negative
resistant bacteria, 10 studies; Clostridium difficile–associated
diarrhea, 5 studies; vancomycin-resistant enterococci, 3 studies; and
methicillin-resistant Staphylococcus aureus, 2 studies. Four
studies provided strong evidence that the intervention changed microbial
outcomes with low risk for alternative explanations, 8 studies provided
less convincing evidence, and 4 studies provided no evidence. The strongest
and most consistent evidence was for C. difficile–associated
diahrrea, but we were able to analyze only the immediate impact of interventions
because of nonstandardized durations of follow-up. The ability to compare
results of studies could be substantially improved by standardizing
methods and reporting.
Despite strenuous efforts to control antimicrobial drug use and promote
optimal prescribing, practitioners continue to prescribe excessively;
it is estimated that up to 50% of antimicrobial drug use in hospitals
is inappropriate (1–3). Antimicrobial drug resistance
is largely a consequence of the selective pressures of antimicrobial drug
use. Reducing these pressures by the judicious administration of these
drugs should facilitate a return of susceptible bacteria or, at least,
prevent or slow the pace of the emergence of drug-resistant strains (4,5).
Furthermore, Clostridium difficile–associated diarrhea (CDAD) is
a hospital-acquired infection associated with use of antimicrobial drugs
(6–8) and reducing the incidences of CDAD is an
additional potential benefit of improving hospital antimicrobial drug
prescribing.
Implementing and monitoring interventions to optimize prescribing of
antimicrobial drugs place a burden on hospital resources and their efficacies
need to be confirmed (9). We have conducted a
systematic review of interventions to improve antimicrobial drug–prescribing
practices for hospital inpatients using the methods of the Cochrane Effective
Practice and Organization of Care Group to assess validity (10).
In this study, our primary objective was to evaluate the impact of interventions
on reducing the incidence of colonization with or infection caused by
antimicrobial drug–resistant pathogens or CDAD. In addition to the usual
threats to the validity of interventions to change health care, infection
control interventions are particularly prone to regression to the mean
(11). This refers to the natural tendency of
extreme observations to return towards the average (mean) over time. An
epidemic or outbreak is a sequence of unusually large number of cases
of infection, so that the natural history of an epidemic is to increase,
peak, and then decrease. Consequently, regression to the mean is always
a threat to the validity of evaluations of unplanned interventions that
are initiated in response to an outbreak.
Methods
The full protocol is available in the Cochrane Library (10).
We searched Medline, EMBASE, the Cochrane database, and the Effective
Practice and Organisation of Care specialized register for studies from
January 1, 1980, to November 30, 2003, relating to prescribing of antimicrobial
drugs to hospital inpatients. Additional studies were obtained from the
bibliographies of retrieved articles, the Scientific Citation Index, and
personal files. We requested additional data from the authors when necessary.
There were no language limitations for the literature review. We included
all randomized and controlled clinical trials (RCT/CCT, designs where
allocation to the intervention is determined either by an explicit random
process [RCT] or by a nonrandom process such as date of birth or case
note number) before and after studies (a design with contemporaneous data
collection before and after the intervention and an appropriate control
site or activity) and interrupted time series (ITS, a clearly defined
point in time when the intervention occurred and at least 3 data points
before and 3 after the intervention). Data about microbiologic outcomes
were considered reliable if they met the same criteria. For example, if
a paper included prescribing data that met the criteria for an ITS but
provided only mean data about microbiologic outcomes before and after
the intervention, then the microbiologic data were not considered reliable.
Two reviewers independently extracted data and assessed the quality of
each study with the standardized criteria.
Statistical Considerations
Many statistical methods can be used to analyze ITS designs (e.g., ARIMA
modeling or time series regression). However, the design is often analyzed
inappropriately, which makes interpretation of individual studies difficult
(12). Methods of analyzing ITS data were examined
critically (12). The preferred method for short
time series is segmented time series regression analysis, which is a statistical
comparison of time trends before and after the intervention to identify
either an immediate change in the level of the regression line or a sustained
change in the slope of the line (12,13).
In this report, we have distinguished 2 intervention effects: immediate
(a sudden change in the level of the regression line at the point of intervention)
and sustained (a sustained change in the slope of the regression line
from the start of the intervention phase). If the original report did
not include an appropriate analysis, data were reanalyzed by using segmented
time series regression.
The following model was specified: Yt = B0
+ B1 × preslope + B2 ×
postslope + B3 × intervention + et,
where Yt is the outcome (e.g., CDAD incidence) in month
t, preslope is a continuous variable indicating time from the start
of the study up to the last point in the preintervention phase and coded
constant thereafter, postslope is coded 0 to and including the first point
postintervention and coded sequentially from 1 thereafter, and intervention
is coded 0 for preintervention time points and 1 for postintervention
time points. In this model, B1 estimates the slope of
the preintervention data, B2 estimates the slope of
the postintervention data, and B3 estimates the change
in level of outcome as the difference between the estimated first point
postintervention and the extrapolated first point postintervention if
the preintervention line was continued into the postintervention phase.
The difference in slope is calculated by B2 – B1.
The error term et was assumed to be first-order autoregressive.
Confidence intervals (95%) were calculated for all effect measures.
Formal metaanalysis of results was not attempted given the differences
in context, setting, and type of outcomes. However, to gain an overall
summary picture of the heterogeneity of effect sizes we standardized all
measures so that they were all on the same scale. To do this, we divided
the change in level and the change in slope by the preintervention standard
deviation (SD) in each study. The resulting metric has no unit, it is
known in standard metaanalysis as the standardized mean difference. Standardized
effect sizes of 2 to 3 SD were considered large, whereas an effect size
<0.5 SD was considered of questionable clinical significance even if
statistically significant (14). To visually display
the heterogeneity of the standardized effect sizes, graphic plots of level
effects versus slope effects for each study (with associated 95% confidence
intervals) were generated.
Other Criteria for Assessing
Evidence
The statistical analysis assessed how likely it was that study results
could simply have happened by chance, and the Cochrane quality criteria
assessed common threats to the validity of interventions to change practice
or organization of care. To assess other threats to the validity of infection
control interventions, we used the format for reporting the results of
included studies recommended by guidelines derived from a recent systematic
review of isolation measures to control methicillin-resistant Staphylococcus
aureus (MRSA) (15). We required studies to
provide reliable data about the effect of interventions on both microbial
and drug outcomes with clear case definition, description of infection
control measures, and other variables such as bed occupancy or staffing
levels that could provide plausible alternative explanations for changes
in microbial outcomes. We have provided a summary of detailed information
from the included studies (Appendix Table [ 74
KB, 5 pages]). Additional
information is available from the British Society for Antimicrobial Chemotherapy
(http://www.bsac.org.uk). We
classified case definitions into colonization, infection or clinical isolates,
or a combination of >2 with the following definitions.
Colonization was defined as a microorganism, usually detected by screening,
at a host site (normally nonsterile, although the urine of a catheterized
patient may be an exception) without causing systemic signs of infection
or a specific immune response. Colonization by case note review was established
by excluding infection diagnosed according to criteria adopted by the
authors or defined by appropriate bodies, e.g., the Centers for Disease
Control and Prevention criteria for diagnosing nosocomial infections.
Infection was established by case note review according to criteria adopted
by the authors or defined by appropriate bodies or by recording specific
symptoms and/or signs, such as diarrhea in patients with CDAD. Clinical
isolates were defined as the recovery of a microorganism after culture
of a clinical (not screening) specimen without specifying whether it represents
colonization or infection.
Results
We identified 66 intervention studies to improve prescribing of antimicrobial
drugs to hospital inpatients that met our inclusion criteria (16)
and excluded 243 studies that were uncontrolled before and after studies
(n = 164) or inadequate ITS studies (n = 79). Of the 66 studies, 16 reported
reliable data about 20 microbiologic outcomes: gram-negative resistant
bacteria (GNRB), 10 studies; CDAD, 5 studies; vancomycin-resistant enterococci
(VRE), 3 studies; and MRSA, 2 studies (Appendix Table [ 74
KB, 5 pages]).
The setting for the intervention was the entire hospital in 8 studies
(17–24), a single service in 2 studies (25,26),
and a unit or ward in 6 studies (27–32). One
intervention was educational with advice about changes in antimicrobial
drugs (17); the other 15 interventions were restrictive
(Appendix Table [ 74
KB, 5 pages]). Two studies were RCTs (31,32)
and 1 study was a CCT (30); the remaining 13
studies used an ITS design.
Statistical Validity
All 3 clinical trials reported appropriate statistical analysis (30–32),
whereas only 2 of the 13 ITS studies reported appropriate statistical
analysis (17,27). Of the remaining
11 ITS studies, 5 did not report statistical analysis; 6 reported inappropriate
statistical analysis by using tests such as χ2 or t
tests that assume independence between observations and do not account
for time trends. Data from these 11 studies were reanalyzed.
Effectiveness of Interventions
Overall, 4 studies provided strong evidence of control of the microbial
outcome by change in prescribing (17,27,30,31).
All of these studies provided reliable data about antimicrobial drug prescribing,
with significant changes in both microbial and drug outcomes after planned
interventions. In addition, 2 studies provided further protection against
regression to the mean by using a crossover design (27,30).
Three of these studies have rigorous case definitions based on prospective
screening cultures plus full description of infection control measures.
Eight studies provided less convincing evidence. Two studies showed significant
changes in prescribing that were associated with nonsignficant changes
in CDAD (20,26). An additional
6 studies reported statistically significant improvement in microbial
outcome but without reliable data about the effect of the intervention
on prescribing (18,19,23,24,28,29).
The importance of this omission is confirmed by the 6 studies that included
reliable data about prescribing because all showed that there was some
prescription of restricted drugs during the intervention phase (17,20,26,27,30,31).
Four studies had negative results (21,22,25,32).
One study provided strong evidence of failure to control microbial outcomes
despite a successful change in prescribing (32).
One study reported an intervention that failed to change use of vancomycin
(22). The remaining 2 studies showed no change
in microbial outcome but did not provide reliable data about the effect
of the intervention on prescribing (21,25).
CDAD
The most consistent evidence was for the 5 interventions designed to
reduce the incidence of CDAD. Four were implemented throughout the hospital
(17,18,20,24) and 1 was implemented
in the elderly care service (26); all 5 targeted
prescribing of cephalosporin or clindamycin. All of the interventions
were associated with a change in the expected direction (Figure
part A), which was a change in the incidence of CDAD in the same direction
to a change in use of cephalosporin or clindamycin. For 1 intervention,
the expected direction was an increase in CDAD incidence after the introduction
of ceftriaxone (20); for all other interventions
a decrease in CDAD incidence was expected to accompany a decrease in use
of cephalosporin or clindamycin. These 5 studies reported 7 interventions.
The immediate effect after 6 of the 7 interventions was at least 0.5 SDs;
5 of these 7 immediate effects were statistically significant (Figure,
part A). Sustained changes after the intervention were more modest,
but all were in the expected directions and 4 of 7 were statistically
significant (Figure, part A). The 5 CDAD studies
had results expressed in different units: cases per month (24,26);
cases per quarter (18,20); or cases per 1,000
admissions per year (17). Consequently, we were
only able to compare effect sizes in numbers of CDAD cases per quarter
by recalculating results from 2 studies (24,26).
The antimicrobial drug intervention was associated with a mean immediate
reduction of 15.0 CDAD cases per quarter (range 6–26) and a median sustained
reduction of 3.2 CDAD cases per quarter (range 1–6).
Resistant Gram-negative Bacteria
The results of the 10 interventions designed to reduce the incidences
of GNRB were less consistent. Three were implemented throughout the hospital
(19,21,23), 1 was implemented
in the neurology and neurosurgery service (25),
and 5 were implemented in a single intensive care unit (ICU), which included
4 with pediatric patients (28–30,32)
and 1 with adult patients (31). One intervention
was designed to reduce the duration of treatment with any antimicrobial
drug for ICU patients at low risk for pneumonia; this was associated with
a significant reduction in the incidence of colonization by any GNRB and
exposure to antimicrobial drugs (31). The remaining
9 interventions involved changes in antimicrobial drug treatment, mainly
aminoglycosides or cephalosporins. One RCT provided no evidence that antimicrobial
drug cycling reduced the incidence of GNRB in a neonatal ICU (32).
The 8 ITS studies reported 9 outcomes (Figure, part
B). The expected direction of effect from a change in aminoglycoside
or cephalosporin prescribing was usually a reduction in GNRB. For 1 intervention,
the expected direction of effect was an increase in the incidence of GNRB
after gentamicin was reintroduced (19). The expected
direction for all 9 outcomes changed, but the effect size was <0.5
SD in 2 studies and not statistically significant in 5 studies (Figure,
part B). In 3 studies the changes in slope were in the expected direction
and in 1 the changes were both statistically significant and >0.5 SD,
which is likely clinically important. Unlike with CDAD data, effects cannot
be expressed in a common unit. Some studies measured colonization and
others examined infection. Units of measurement were also variable (e.g.,
number of isolates, percentage of isolates, number of cases, and number
of cases per time period).
Gram-positive Bacteria
Data for gram-positive bacteria were very limited. One study provided
strong evidence that restricting ceftazidime in a hematology unit was
associated with significant reduction in risk for colonization by VRE
(27). However, reduction of cephalosporin use
in a hospital was not associated with any change in the prevalence of
VRE isolates (17). A third study targeted at
VRE showed that implementation of a vancomycin order form had no significant
impact on vancomycin prescribing, with a trend in the unintended direction
(22). Two studies report effects on MRSA prevalence
(17,21). Our segmented regression
analysis showed no significant change in response to a reduction in use
of third-generation cephalosporins (Appendix Table [ 74 KB, 5 pages]),
although 1 of the reports claimed that a change did occur (21).
Discussion
Our primary conclusion is that 4 of the 16 studies provided strong evidence
that changes in prescribing antimicrobial drugs to hospital inpatients
can improve microbial outcomes (17,27,30,31).
Eight of the remaining studies provided some evidence that antimicrobial
drug–prescribing interventions can improve microbial outcomes, but flaws
in their design indicated that there were plausible alternative explanations
for the results (18–20,23,24,26,28,29).
The remaining 4 studies were unequivocally negative (21,22,25,32).
Estimation of overall effect size was only possible for reduction in
CDAD, where the evidence suggested that restriction of clindamycin or
third-generation cephalosporins resulted in an immediate reduction in
prevalence by 15 cases per quarter, with an additional sustained reduction
by 3 cases per quarter. Prevalence is usually adjusted for clinical activity,
e.g., cases per 1,000 admissions per quarter (7),
but only 1 study provided this information (17).
Furthermore, potentially important differences in the case definitions
of CDAD occurred between the studies in our review.
Finding valid studies required painstaking analysis of a huge volume
of literature, most of which is fundamentally flawed (16).
The included studies could be dramatically improved by following guidelines
for standardized reporting (15). In particular,
the unequal duration of postintervention phases made it difficult to reliably
compare the sustained effects of interventions, these being the most important
outcome measures. The short and unequal duration of preintervention phases
provides limited information about underlying preintervention trends.
To understand how much of a change in prescribing is required to change
outcome, the intervention must be independent of other control measures
and be accompanied by reliable data about both prescribing and microbial
outcomes.
Only 1 of the interventions was designed to reduce overall exposure to
antimicrobial drugs (31). All of the other studies
targeted the choice of antimicrobial drug (e.g., by restricting access
to third-generation cephalosporins in favor of drugs recommended by the
hospital antimicrobial drug policy) but did not aim to shorten the duration
of treatment. This intervention (31) shortened
the duration of antimicrobial drug treatment for ICU patients at low risk
for ventilator-associated pneumonia. This study was conducted in an ICU
with adult patients. However, the same principle of using clinical scores
to identify low-risk patients, in whom antimicrobial drug therapy could
be stopped, has been developed in other clinical settings (33–35),
and the impact on microbiologic outcomes should be investigated.
None of the studies provided evidence for cost-effectiveness or clinical
outcome. The study designs likely did not have sufficient power to measure
these outcomes. Few studies provided data about multiple microbiologic
species and 1 of these endpoints (incidence of cefotaxime-resistant Acinetobacter
spp.) was opposite to that which was expected (21).
Future studies should provide more data about cost and clinical outcomes.
Notably, evidence is needed to show that interventions do not have adverse
outcomes.
The potential for the success of antimicrobial drug interventions likely
varies by organism (36,37). Antimicrobial drugs
are likely to play a large role in the selection of enterobacteria expressing
extended-spectrum β-lactamases, a minimal role in the selection and
transmission of MRSA, and an intermediate role in VRE. However, the available
evidence is not sufficient to investigate these hypotheses.
Implications for Practice
The evidence supports the theory that limiting the use of specific antimicrobial
drugs will reduce the prevalences of resistant gram-negative bacteria
and CDAD. For gram-positive bacteria, there is a lack of evidence rather
than evidence of no effect. Hospitals would like to know how much they
should limit their antimicrobial drug prescriptions and what is the minimum
that will show a real effect. Unfortunately, the available evidence is
too limited to provide definitive answers to these issues. Thus, hospitals
must estimate the effect of their own interventions. The good news is
that the data required for ITS analysis of the incidences of drug-resistant
bacteria or CDAD should be readily available in most hospitals. Healthcare
providers need to invest in data analysis so that evaluation of antimicrobial
drug control in hospitals becomes a routine measure of the quality of
care rather than a research project.
Standardized reporting of outbreaks and interventions to control the
incidence of antimicrobial drug resistance or hospital-acquired infection
would greatly enhance the ability to combine results from hospitals in
metaanalyses. Key issues include full description of other infection control
measures, consistent and reproducible case definitions, the length of
preintervention and postintervention phases, and the intervals between
data points (15). Ideally, data should be made
available in a way that allows reanalysis and, where appropriate, metaanalysis.
Metaanalysis of single hospital studies is no substitute for good multicenter
studies, but it could be used to provide some evidence of reproducibility
and thus to prioritize targets for definitive trials.
Priorities for Research
The research agenda needs to move to multicenter studies with randomized
allocation to interventions. This will provide better evidence of external
validity as well as the power to measure cost-effectiveness and exclude
important unintended adverse clinical outcomes. Development and pilot
testing of the effectiveness of clinical decisions for reducing unnecessary
exposure to antimicrobial drugs should be a priority for research in hospitals.
This study was supported
by a working party grant from the British Society for Antimicrobial
Chemotherapy and the Hospital Infection Society.
Dr Davey is honorary
consultant in infectious diseases at the Acute Services Division of
National Health Service Tayside and director of the Health Informatics
Centre, a multidisciplinary group developing innovative methods for
linkage and application of information from health records. His main
research interests are epidemiology of antimicrobial drug prescribing
or resistance and quality improvement of prescribing practices.
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Appendix Table. Summary
of included studies* (Download PDF 74
KB, 5 pages) |
|
Study, y (reference) |
Setting and population |
Design |
Main interventions |
Outcomes |
Assessment of evidence |
|
Bradley et al., 1999 (27) |
Adult hematology unit in UK, 261 patients who were
not carriers of VRE at the start of the study |
Prospective ITS with 3 phases of 4, 6, and 5 months.
Planned intervention. Case definition: colonization. Other infection
control measures consistent through study. |
Phase 1: ceftazidime for empiric antimicrobial drug
treatment
Phase 2: antimicrobial drug policy changed to piperacillin tazobactam.
Phase 3: antimicrobial drug policy changed back to ceftazidime. |
Microbial: % of patients colonized with VRE fell
from 57% in Phase 1 to 19% in Phase 2, then rose again to 36% in
Phase 3: significant by log rank test.
Drug: significant reduction in ceftazidime use in Phase 2: immediate
–227.8 patient days per month, p<0.001; sustained –19.3 patient
days per month, p = 0.037. |
Statistically significant reduction in risk of colonization
with VRE associated with reduction in antimicrobial drug prescribing.
No major weaknesses in the study design. |
Calil et al., 2001 (28) |
Neonatal unit in Brazil, 342 patients in a 30-bed
unit (8 intensive care and 22 intermediate care beds) |
Prospective ITS with 2 phases of 3 months each.
Unplanned intervention. Case definition: colonization. Other infection
control measures were introduced during the study and it is not
clear how they related to the antimicrobial drug intervention. |
Phase 1: usual care.
Phase 2: implementation of infection control measures emphasizing
hand washing and contact precautions plus an antimicrobial drug
policy restricting use of third-generation cephalosporins. |
Microbial: cases of multi-resistant Enterobacter
cloacae colonization per month decreased in Phase 2: immediate
–15.51 cases per month (p = 0.054); sustained –2.73 cases per month
(p = 0.138). Drug: no reliable data. |
Significant reduction in colonization but it is
not possible to separate the effects of the infection control measures
from the change in antimicrobial drug policy. Several other potentially
important weaknesses. |
Carling et al., 2003 (17) |
Single medium-sized community teaching hospital
(affiliated with a University) in US. No obstetric unit or pediatric
ICU. |
Hybrid retrospective and prospective ITS with 2
phases of 36 and 84 months. Planned intervention. Case definition:
infection with CDAD or resistant gram-negative bacteria, MRSA, or
VRE. Other infection control measures consistent through study. |
Phase 1: automatic 7-day stop order on all antimicrobial
drugs, limited reporting of susceptibility tests, and educational
program. Phase 2: as Phase 1 plus review of patients receiving target
antimicrobial drugs by pharmacist and ID physician, recommendations
placed in the case notes. |
Microbial: CDAD and resistant Enterobacteriaceae
in cases per 1,000 admissions. MRSA and VRE as % clinical isolates.
Postintervention: there were significant reductions for CDAD: immediate
–1.47 cases, p<0.001; sustained –0.81 cases, p = 0.05. Resistant
Enterobacteriaceae also reduced: immediate –2.34 cases, p = 0.03;
sustained –1.34 cases, p = 0.01. There was no significant change
in the % isolates of MRSA or VRE. Drug: authors' regression analysis
shows significant reduction in target antimicrobial drugs in Phase
2. |
Significant reduction in CDAD cases and resistant
Enterobaceriaceae associated with planned antimicrobial drug intervention
that resulted in significant changes in antimicrobial drug use.
Main weaknesses were the lack of detail about infection control
and the case definition for resistant Enterobacteriaceae. |
Climo et al., 1998 (18) |
Single 703-bed tertiary care hospital in USA |
Hybrid retrospective and prospective ITS with 2
phases of 27 and 33 months. Unplanned intervention. Case definition:
infection, CDAD. Other infection control measures consistent through
study. |
Phase 1: infection control only
Phase 2: infection control plus restriction of clindamycin. |
Microbial: CDAD cases per quarter.
The intervention was associated with significant reduction in CDAD
cases per quarter: immediate –26.3 cases, p<0.001; sustained
–3.8 cases, p<0.001. Drug: no reliable data. |
Significant reduction in CDAD cases in phase 2.
However, this was an unplanned intervention, there were no reliable
data about drug use, and the study had several other potentially
important weaknesses. |
de Champs et al., 1994 (29) |
Single pediatric ICU with 15 ventilator beds and
28 intermediate-care beds in France |
Prospective ITS with 2 phases of 7 and 12 months.
Unplanned intervention. Case definition: infection by resistant
E cloacae.
Other infection control measures consistent through study. |
Phase 1: barrier precautions only.
Phase 2: barrier precautions plus removal of gentamicin from the
unit and replacement with amikacin. |
Microbial: The intervention was associated with
significant reduction in resistant E cloacae cases per month,
immediate –7.47 cases, p<0.001; sustained –1.00 cases, p = 0.002.
Drug: no reliable data. |
Significant reduction in E cloacae cases
in phase 2.
However, this was an unplanned intervention, there were no reliable
data about drug use, and the study had several other potentially
important weaknesses. |
de Man et al., 2001 (30) |
Two similar neonatal ICUs in the same hospital.
The study enrolled 436 patients with a mean of 33 weeks gestation. |
Prospective cluster controlled clinical trial with
crossover with 2 phases of 6 months each. Planned intervention.
Case definition: colonization plus clinical isolates. Other infection
control measures: consistent through study. |
Phase 1: unit A used amoxicillin plus cefotaxime,
unit B used penicillin plus tobramycin.
Phase 2: antimicrobial drug policies were switched: unit A used
penicillin plus tobramycin, unit B used amoxicillin plus cefotaxime. |
Microbial: the cefotaxime and amoxicillin regimen
was associated with a relative risk of colonization by gram-negative
bacteria resistant to cefotaxime or tobramycin of 2.98 (95% CI 1.64–5.38).
Drug: cefotaxime plus amoxicillin exposure was 26%–32% of patient
days when that regimen was in place vs. 1% when penicillin
plus tobramycin was used. |
Significantly increased risk of colonization associated
with the cefotaxime and amoxicillin regimen. However, risk of colonization
was also related to length of stay and was significantly shorter
in the penicillin plus tobramycin phase. |
Gerding et al., 1985 (19) |
Single Veterans Administration hospital in US |
Prospective ITS with 4 phases of 4, 26, 12, and
12 months. Planned intervention. Case definition: clinical isolates.
Other infection control measures not described. |
Phase 1: no restriction.
Phase 2: gentamicin restricted.
Phase 3: amikacin restricted.
Phase 4: gentamicin restricted. |
Microbial: % of all gram-negative aerobic bacilli
resistant to gentamicin.
Figure 1 shows resistance to gentamicin varied
between 15% and 2% over the study, falling and rising with no clear
relationship to changes in antimicrobial drug policy. Drug: no reliable
data. |
Little evidence that the fluctuations in resistance
to gentamicin were related to antimicrobial drug policy changes.
Several potentially important design weaknesses. |
Khan and Cheesbrough, 2003 (20) |
Single 800-bed nonteaching hospital in UK |
Prospective ITS with 3 phases of 6, 13, and 5 months.
Phase 2 planned, Phase 3 unplanned. Case definition: CDAD infection.
Other infection control measures consistent through study. |
Phase 1: cefotaxime.
Phase 2: ceftriaxone.
Phase 3: levofloxacin. |
Microbial: Phase 2 was associated with increase
in CDAD cases per quarter: immediate +19.7 cases, p = 0.07; sustained
+4.7 cases p = 0.07. Phase 3 was associated with sustained reduction
in CDAD by –5.8 cases per quarter, p = 0.08. Drug: no reliable data
for Phase 1, significant reduction in ceftriaxone use (g per quarter)
in Phase 3. |
Non significant changes in CDAD were associated
with the introduction and restriction of ceftriaxone. Regression
to the mean was a plausible alternative explanation for changes
in phase 3 and reliable drug data were provided only for phases
2 and 3. |
Landman et al., 1990 (21) |
Single university hospital in US with 569 discharges
per month from medical and surgical services |
Retrospective ITS with 2 phases of 29 and 23 months.
Planned intervention. Case definition: clinical isolates of resistant
bacteria. Other infection control measures: none specific to the
bacteria under study. |
Phase 1: unrestricted.
Phase 2: restriction of third-generation cephalosporins, clindamycin,
and vancomycin by requiring approval by an ID physician. |
Microbial: intervention was not associated with
a significant reduction in the incidence of either ceftazidime-resistant
Klebsiella pneumoniae or MRSA. However, there was a significant
sustained increase in cefotaxime-resistant Acinetobacter
spp: by +0.337 new cases per 1,000 discharges.
Drug: no reliable data. |
The intervention was associated with a significant
but unintended increase in one of the outcomes and no significant
changes in the other. However, there were important weaknesses in
the study design. |
Lautenbach et al., 2003 (22) |
Single 725-bed University hospital in US |
Hybrid retrospective and prospective ITS with 2
phases of 36 and 84 months. Unplanned intervention. Case definition:
clinical isolates of VRE. Other infection control measures not described. |
Phase 1: unrestricted use of antimicrobial drugs.
Phase 2: use of vancomycin or third-generation cephalosporins for
>72 h required approval by the antimicrobial drug management
team. After 24 months any use of vancomycin required approval. |
Microbial: regression analysis suggests that the
intervention was associated with significant reduction in % VRE
but this result was an artifact caused by the first point in the
data (1% VRE) and only having 3 preintervention points. Drug: no
significant change in vancomycin use (DDD/1,000 patient days) |
No evidence supporting control by antimicrobial
drug restriction because the restriction did not reduce the use
of vancomycin.
No data about infection control measures and there were other important
weaknesses in the study design. |
Leverstein-van Hall et al., 2001 (25) |
Neurology and neurosurgery wards in a single 858-bed
university hospital in the Netherlands. |
Prospective ITS with 2 phases of 1 and 2 months.
Unplanned intervention. Case definition: colonization. Other infection
control measures consistent through study but only implemented 4
weeks before the start of antimicrobial drug restriction. |
Phase 1: stringent barrier precautions.
Phase 2: restriction of all antimicrobial drugs by requiring approval
by microbiology or ID. Only amikacin or carbapenems used for treatment
of gram-negative infection. |
Microbial: % prevalence of intestinal colonization
by gentamicin-resistant Enterobacteraiaceae was decreasing
preintervention: by –1.3 % per week and there was no significant
change postintervention. Drug: no reliable data. |
No evidence supporting control by antimicrobial
drug restriction. There were several important weaknesses in the
study design. |
McNulty et al., 1997 (26) |
Care of the elderly unit in a single nonteaching
hospital in UK. |
Prospective ITS with 2 phases of 7 and 16 months.
Unplanned intervention. Case definition: infection, CDAD. Other
infection control measures consistent through study. |
Phase 1: increased ward cleaning and patient isolation.
Phase 2: restriction of cephalosporins by removal from ward stock;
infection control measures as in Phase 1. |
Microbial: phase 2 was associated with nonsignificant
reduction in CDAD: immediate –3.22, cases per month, p = 0.120;
sustained –0.50 cases per month, p = 0.230.
Drug: intervention was associated with significant reduction in
cefuroxime cost: immediate –£501.78 per month, p = 0.015. |
Nonsignificant reduction in CDAD cases. This was
an unplanned intervention and the study had several other potentially
important weaknesses. |
Meyer et al., 1993 (23) |
A single 487-bed university hospital in US |
Hybrid retrospective and prospective ITS with 2
phases of 14 and 11 months. Unplanned intervention. Case definition:
infection plus colonization.
Other infection control measures: barrier precautions implemented
at the same time as ceftazidime restriction. |
Phase 1: usual care.
Phase 2: barrier precautions for infected or colonized patients
plus restriction of ceftazidime. Case notes were reviewed for 133
of the 142 patients with resistant isolates, of whom 52 (39%) met
CDC criteria for nosocomial infection. |
Microbial: number of cases of ceftazidime-resistant
K. pneumoniae per 1,000 average daily census. Phase 2 was
associated with significant reduction: immediate –38.6 cases, p<0.0001;
sustained –6.2 cases, p<0.0001.
Drug: drug data are provided for different periods (22 months preintervention
and 6 months postintervention) but do show a significant reduction
in the number of patients receiving ceftazidime: immediate –26.4
patients, p =0.003; sustained –10.21 patients, p<0.001. |
Significant reduction in ceftazidime-resistant K.
pneumoniae in phase 2 with significant reduction in ceftazidime
use. However, it is impossible to separate the effect of ceftazidime
restriction from the infection control measures. Regression to the
mean was another plausible explanation. |
Pear et al., 1994 (24) |
A single university hospital in the US with an average
daily census of 168 patients |
Hybrid retrospective and prospective ITS with 2
phases of 40 and 14 months. Unplanned intervention. Case definition:
infection, CDAD. Other infection control measures consistent across
study. |
Phase 1: hospital staff education, increased use
of gloves and improved environmental hygiene.
Phase 2: restriction of clindamycin by prior approval by ID physician;
infection control measures maintained as in Phase 1. |
Microbial: number of CDAD cases per month. Phase
2 was associated with significant reduction, immediate –3.68 cases
per month, p = 0.041, sustained –0.32 cases per month, p = 0.134).
Drug: no reliable data. |
Significant reduction in CDAD in phase 2 but this
was an unplanned intervention and there were no reliable data about
drug use. |
Singh et al., 2000 (31) |
Adult surgical and medical ICUs in a single university-affiliated
Veterans Administration hospital in US. 81 patients included, mean
age 69 years. |
Randomized trial with followup of patients until
they were discharged from ICU or died.
Planned intervention. Case definition: colonization plus clinical
isolates. Other infection control measures not described but it
is reasonable to assume that they were consistent for the intervention
and control patients. |
Control group: choice, number, and duration of antimicrobial
drugs at the discretion of the care providers. Intervention group:
patients received standardized initial therapy (ciprofloxacin IV
for 3 days) with assessment at 3 days when antimicrobial drugs were
stopped if the patient was judged to be at low risk of pneumonia
based on the CPIS score. |
Microbial: % patients colonized or infected with
resistant bacteria. RR for intervention vs. control: 0.36,
95% CI 0.14–0.89. Drug: RR of receiving antimicrobial drugs for
> 3 days, intervention vs. control: 0.29, 95% CI 0.17–0.48.
Clinical: length of ICU stay (9.4 days intervention vs. 14.7 days
control; p = 0.04); Nonsignificant reduction in deaths: RR of 30-day
death: 0.41, 95% CI 0.16–1.05 |
Statistically significant reduction in risk of colonization
and infection with resistant bacteria associated with reduction
in antimicrobial drug prescribing.
Clinical noninferiority of the intervention regimen was confirmed.
No major weaknesses. |
Toltzis et al., 2002 (32) |
Single 38-bed neonatal intensive care unit in a
University hospital in US. 1,062 episodes of care in infants with
mean age 35 weeks |
Randomized trial with followup of patients until
they were discharged from ICU or died. Planned intervention. Case
definition: colonization. Other infection control measures not described
but it is reasonable to assume that they were consistent for the
intervention and control patients. |
Control group: prescribing according to individual
preference of physicians. Intervention group: monthly rotation between
gentamicin, followed by piperacillin-tazobactam, followed by ceftazidime,
followed by gentamicin again. |
Microbial: % of patients colonized with resistant
bacteria. RR was greater in the Intervention group: 1.40, 95% CI
0.95–2.05.
Drug: control patients received predominantly gentamicin. The intervention
group received the intended antimicrobial drugs on 84% of all antimicrobial
days. No difference in total antimicrobial drug use. Clinical: all
cause death was similar: 3.2% intervention vs. 2.3% control. |
No evidence supporting control of resistance by
antimicrobial drug cycling. No major weaknesses.
The authors provide 4 alternative explanations other than failure
of cycling: NICU population, rotation too rapid, inclusion of ceftazidime,
use of ampicillin in all regimens. |
|
*VRE, vancomycin-resistant enterococci; ITS, interrupted
time series; ICU, intensive care unit; CDAD, Clostridium difficile–associated
diarrhea; MRSA, methicillin-resistant Staphylococcus aureus;
ID, infectious disease; CI, confidence interval; DDD, defined daily
dose; CDC, Centers for Disease Control and Prevention; IV, intravenous;
RR, relative risk; CPIS, clinical pulmonary infection score; NICU,
neonatal intensive care unit. Additional information is available
from http://www.bsac.org.uk |
Suggested citation
for this article:
Davey P, Brown E, Fenelon
L, Finch R, Gould I, Holmes A, et al. Systematic review of antimicrobial
drug prescribing in hospitals. Emerg Infect Dis [serial on the Internet].
2006 Feb [date cited]. Available from http://www.cdc.gov/ncidod/EID/vol12no02/05-0145.htm
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