Context.—Early diagnosis of gram-negative bloodstream infections, prompt identification of the infecting organism, and appropriate antibiotic therapy improve patient care outcomes and decrease health care expenditures. In an era of increasing antimicrobial resistance, methods to acquire and rapidly translate critical results into timely therapies for gram-negative bloodstream infections are needed.

Objective.—To determine whether mass spectrometry technology coupled with antimicrobial stewardship provides a substantially improved alternative to conventional laboratory methods.

Design.—An evidence-based intervention that integrated matrix-assisted laser desorption and ionization time-of-flight mass spectrometry, rapid antimicrobial susceptibility testing, and near–real-time antimicrobial stewardship practices was implemented. Outcomes in patients hospitalized prior to initiation of the study intervention were compared to those in patients treated after implementation. Differences in length of hospitalization and hospital costs were assessed in survivors.

Results.—The mean hospital length of stay in the preintervention group survivors (n = 100) was 11.9 versus 9.3 days in the intervention group (n = 101; P = .01). After multivariate analysis, factors independently associated with decreased length of hospitalization included the intervention (hazard ratio, 1.38; 95% confidence interval, 1.01–1.88) and active therapy at 48 hours (hazard ratio, 2.9; confidence interval, 1.15–7.33). Mean hospital costs per patient were $45 709 in the preintervention group and$26 162 in the intervention group (P = .009).

Conclusions.—Integration of rapid identification and susceptibility techniques with antimicrobial stewardship significantly improved time to optimal therapy, and it decreased hospital length of stay and total costs. This innovative strategy has ramifications for other areas of patient care.

Prompt and aggressive initiation of antimicrobial therapy is the mainstay of treatment for patients with bloodstream infections (BSIs).13  Moreover, increasing rates of drug resistance have forced clinicians to expose patients with presumed bacterial infection to treatment with empiric combination broad-spectrum antibiotics.48  It follows that the time required for bacterial identification and drug susceptibility testing has a critical impact on guiding therapy.

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis of microbial proteins is a new method for rapid and reliable species identification of bacteria and yeast grown on agar media, and more recently has been used to identify gram-negative organisms directly from positive blood culture bottles within minutes.912  Further, testing of specimens taken directly from positive blood cultures has been reported to decrease the time required for antimicrobial susceptibility testing results.12

With the enhanced speed and technical advances made possible by MS, in principle, opportunities exist for antimicrobial stewardship practices to enhance antimicrobial management.8,13,14  However, the clinical and health care cost implications of integrating new molecular diagnostic microbiology techniques with antimicrobial stewardship practices have not been well established. Here, we tested the hypothesis that patient care would be enhanced by combining new rapid methods to obtain identification and susceptibility results with real-time clinical interpretation and action by an infectious diseases pharmacist.

### Study Location and Patient Population

We implemented our study intervention at The Methodist Hospital in Houston, Texas, a 1000-bed quaternary care academic hospital on February 1, 2012. Eligibility screening was conducted among consecutive patients ages 18 years and older with 1 or more blood cultures with a gram-negative organism who were hospitalized between August 15, 2011, and November 30, 2011 (preintervention period), and February 1, 2012, through May 25, 2012 (intervention period). For simplicity, only the first BSI episode was evaluated for each patient; subsequent episodes that occurred in the study period were excluded from the analysis. Patients were excluded if the pathogen ultimately identified was not a facultative anaerobic or aerobic gram-negative bacillus; if the patient had a polymicrobial BSI, experienced prior or subsequent BSIs with an organism(s) other than the study pathogen, or died prior to the index blood culture becoming positive; and/or if criteria for discharge were determined by institutional policies rather than at the treating physician's discretion (ie, medical circumstances other than the BSI required extended hospitalization). This study was approved by the Institutional Review Board of The Methodist Hospital Research Institute (IRB1011-0200). No private sector funds were used in support of this study. The authors vouch for the accuracy and completeness of the reported data and the fidelity of this report to the study protocol.

### Data Collection

Patients were identified through the clinical microbiology laboratory records for the designated study periods. We collected data on demographic characteristics, manifestations of BSI, microbiology results, antibiotic therapy, and severity of illness.15,16  Cost data were obtained from the institution's financial management department. The Acute Physiology and Chronic Health Evaluation II (APACHE II) score was calculated based on clinical data present during the 24 hours preceding the index blood culture. Underlying illnesses, recent hospitalizations (previous 90 days), and reason for admission were noted. Immunosuppressive therapy was defined as receipt of cytotoxic agents within 6 weeks, corticosteroids at a dosage of 15 mg or more of prednisolone daily for longer than 1 week within 4 weeks, or other immunosuppressive agents within 2 weeks before bacteremia onset. Bloodstream infection onset was defined as the time the first blood sample yielding the study isolate (index blood culture) was collected. Infection-related characteristics examined were infection source; pathogen species and susceptibility data; and time, dose, and route of therapy with individual antimicrobial agents relative to time of index culture collection. The source of bacteremia was determined according to the definitions published by the Centers for Disease Control and Prevention.17  In each case, an effort was made to establish a primary focus of infection.

Appropriateness of antibiotic therapy was assessed on a case-by-case basis by an infectious diseases–trained pharmacist and was evaluated at BSI onset, at the index culture time-to-positivity (TTP), and at 24 and 48 hours after BSI onset in the 2 groups. Active therapy was defined as when the regimen included 1 or more antimicrobial agents to which the causative pathogen was susceptible in vitro. Therapy was appropriate when the administered regimen was active and, when available, was in accordance with current clinical guidelines regarding dosing and route of administration.16  Therapy was defined as inactive if the blood isolate was resistant to the agent(s) used or in the absence of any antibacterials.

Empiric therapy refers to antimicrobial agents administered during the period before identification of the blood culture isolate and susceptibility results were available. De-escalation was defined as switching to a narrower-spectrum agent or decreasing the number of antibiotics from 2 or more agents to a single agent when clinically appropriate. Unnecessary gram-positive coverage was defined as empiric use of an anti–gram-positive agent (eg, glycopeptides) without subsequent microbiologic or clinical indication. Therapy was considered optimized when antibiotics were de-escalated based on available identification and susceptibility testing results, when dosing or administration route modifications were made based on organ function, or if antimicrobial spectrum was expanded based on patient-specific history or local antibiogram in the absence of final pathogen susceptibility testing results. Patients who initially received broad-spectrum or combined empiric therapy were considered candidates for treatment de-escalation.

Duration of hospital and intensive care unit stays were determined as the difference in days between admission and discharge. Inasmuch as death can artificially decrease length of stay (LOS), LOS analysis was done solely with patients who survived to hospital discharge.

### Study Design

All blood specimens obtained in each of the 2 study periods were processed identically using the BACTEC FX automated blood culture system (BD Diagnostics, Sparks, Maryland) and standard aerobic and anaerobic blood culture media. Specimens were Gram stained when the blood culture bottle became positive. In the preintervention phase, microbiology laboratory personnel directly notified the nursing staff with the Gram stain result. Additionally, if an infectious diseases physician was recorded on the provider list, the individual was called with the result. Positive blood culture specimens were inoculated on appropriate solid agar media and subsequently identified by conventional clinical microbiology procedures. The final organism identification and antimicrobial susceptibilities were performed using the BD Phoenix system (BD Diagnostics). Once obtained, the results were reported to the electronic medical record without additional active notification of the patient care team. Multidrug resistant organisms (MDROs) and/or extended-spectrum beta-lactamase producing (ESBL) organisms were telephoned to the appropriate nursing unit during both study periods. Susceptibility testing was performed according to guidelines and breakpoints established by the Clinical Laboratory and Standards Institute.18

### The Intervention

After a validation process we published recently,12  the clinical microbiology laboratory implemented MALDI-TOF MS (Bruker Daltonics, Fremont, California) for routine species identification of gram-negative bacteria directly from early-positive blood cultures. Immediately after the Gram stain results were obtained, the microbiology laboratory staff telephoned the appropriate member of the patient care team, a procedure identical to that used before the intervention. If a gram-negative isolate was identified, the specimen was then analyzed by the MALDI-TOF MS and simultaneously set up for antimicrobial susceptibility testing by the BD Phoenix system. Positive blood culture specimens also were inoculated on appropriate agar media for identification by conventional bacteriologic methods, if necessary. Species identification based on the BD Phoenix result was considered to be the reference standard. Microbiology laboratory personnel called the infectious diseases pharmacist with each result obtained for every hospitalized patient, 24 hours a day and 7 days a week. The on-call infectious diseases pharmacist had remote access privileges to patients' electronic medical records. After review, and when necessary, the infectious diseases pharmacist would contact the treating physician to discuss the results and formulate the most effective, targeted antimicrobial therapy. The pharmacist recommended de-escalation to targeted therapy when the final bacterial identification and/or susceptibility test results were available. Recommendations related to dosing/route modifications or to escalate therapy were made when clinically indicated after review of the medical record. The MALDI-TOF MS analysis was initially performed 3 times daily (at ∼1000, 1300, and 1900 hours), but on March 20, 2012, an additional run was instituted on the night shift (0500 hours; 4 times daily) every day.

### Outcomes

We modeled exposure to the study intervention according to clinically relevant temporal variables, comparing values collected prior to and during the invention period. Clinical outcomes evaluated included differences in time to final identification and susceptibilities results, de-escalation rates, time to active therapy when initial therapy was inactive, hospital LOS, total hospital costs, and 30-day mortality rates between the 2 study periods.

### Cost Analysis

Total hospital costs were calculated by adding up the costs incurred across all cost centers, including room and board, pharmacy, radiology, and laboratory. Cost data were obtained from an individual in The Methodist Hospital accounting department who was independent of the team. All reported costs represent actual costs for the administration of patient care as determined by the individual departmental finance sections. No changes were made in how these costs were calculated during the period of the preintervention and intervention protocols.

### Statistical Analysis

Summary statistics for continuous variables were reported as mean ± SD, and results for categoric variables were presented as frequencies. The Mann-Whitney test was employed to identify significantly different central locations between groups for continuously scaled variables, whereas the χ2 test was used to determine significantly different configurations across groups of categoric data. All tests were 2-tailed, and a P value ≤.05 represented statistical significance. P values for χ2 test were based on Fisher exact test. To evaluate the independent impact of the study intervention on LOS, we performed univariate and multivariate Cox proportional hazards regression using LOS as the time-to-event and discharge as the failure, and we included predictor covariates likely to affect LOS, regardless of diagnosis timing. These included age, sex, comorbidities, severity of illness, in vitro antibiotic activity at 24 and 48 hours from BSI onset, preinfection LOS (for nosocomial infections), and hospital mortality. The expectation for Cox proportional hazards modeling is that if the intervention shortens LOS, the resulting hazard ratio will be greater than 1, reflecting a beneficial outcome. Kaplan-Meier survival analysis was performed by partitioning LOS into groups representing preintervention and intervention study periods, and the equality of LOS was tested using the log-rank test.

Patients (N = 317) with gram-negative BSIs were evaluated for inclusion between August 2011 and November 2011 (preintervention) and February 2012 and May 2012 (intervention). After the defined criteria were applied, 219 patients with gram-negative BSIs were included in the final analysis. Of these, 112 patients were included in the preintervention study group and 107 patients were in the intervention study group (Figure 1).

Figure 1.

Eligibility and inclusion of the study participants. The most common reasons for ineligibility among patients were medical circumstances requiring prolonged hospitalization unrelated to the patient's bloodstream infection (BSI; 24.4%), including patients receiving extracorporeal membrane oxygenation (ECMO) for cardiorespiratory failure; advanced heart failure requiring ventricular assist devices (VADs) or an artificial heart; and elective admissions for bone marrow transplantation (BMT). Length of stay (LOS) and hospital cost analyses were conducted in those patients surviving to hospital discharge. Abbreviation: TTP, time-to-positivity of index blood culture.

Figure 1.

Eligibility and inclusion of the study participants. The most common reasons for ineligibility among patients were medical circumstances requiring prolonged hospitalization unrelated to the patient's bloodstream infection (BSI; 24.4%), including patients receiving extracorporeal membrane oxygenation (ECMO) for cardiorespiratory failure; advanced heart failure requiring ventricular assist devices (VADs) or an artificial heart; and elective admissions for bone marrow transplantation (BMT). Length of stay (LOS) and hospital cost analyses were conducted in those patients surviving to hospital discharge. Abbreviation: TTP, time-to-positivity of index blood culture.

Close modal

Among the 219 evaluable patients, the mean age of participants was 66.1 ± 15.3 years (range, 25–100 years), with 112 men (51.1% Table 1). The overall mean APACHE II score was 14.8 ± 5.7 (range, 3–39). The most common infection source was the urinary tract, accounting for 42.9% of BSIs in the preintervention group and 34.6% in the intervention group, followed by intravascular catheter–associated (20% versus 22.4%, respectively). Escherichia coli was isolated most frequently (in 50% of preintervention and 43% of intervention study groups), followed by Klebsiella spp (in 23.3% and 19.7%, respectively). Nosocomial infections accounted for 20.5% of BSIs in the preintervention group and 14% in the intervention group.

Table 1.

Demographics and Baseline Characteristicsa

### Outcomes

The average time from the blood culture TTP to final species identification and antimicrobial susceptibility results was 47.1 ± 13.7 hours for the preintervention study group versus 24.4 ± 11.4 hours for the intervention study group (P < .001). The mean TTP was 15.6 ± 12 hours (range, 4–109 hours) for both groups and was not significantly different. The mean time to gram-negative organism identification was significantly longer in the preintervention group versus the intervention arm (36.6 ± 15.3 versus 11.1 ± 10.2 hours, respectively; P < .001; Figure 2).

Figure 2.

Timeline comparison of preintervention and intervention study periods depicting the differences in laboratory procedure and their respective impact on adjusted therapy. Adjusted therapy included, when clinically indicated, de-escalation/escalation of antibiotic therapy, dosing/route modifications, and/or discontinuation of unnecessary gram-positive coverage. White boxes denote the average times (hours) until the corresponding information was obtained or action implemented in the preintervention (PI) and intervention (Int) groups. The bottom horizontal line represents the global study/patient timeline (hours) and includes point measurements (below) for patients on inactive therapy at 0, 24, and 48 hours in both groups. Abbreviations: EMR, electronic medical record; MALDI-TOF MS, matrix-assisted laser desorption and ionization time-of-flight mass spectrometry.

Figure 2.

Timeline comparison of preintervention and intervention study periods depicting the differences in laboratory procedure and their respective impact on adjusted therapy. Adjusted therapy included, when clinically indicated, de-escalation/escalation of antibiotic therapy, dosing/route modifications, and/or discontinuation of unnecessary gram-positive coverage. White boxes denote the average times (hours) until the corresponding information was obtained or action implemented in the preintervention (PI) and intervention (Int) groups. The bottom horizontal line represents the global study/patient timeline (hours) and includes point measurements (below) for patients on inactive therapy at 0, 24, and 48 hours in both groups. Abbreviations: EMR, electronic medical record; MALDI-TOF MS, matrix-assisted laser desorption and ionization time-of-flight mass spectrometry.

Close modal

During the intervention study period, a total of 246 interventions were recommended to the prescribing physician by the infectious diseases pharmacist, of which 225 were accepted. Overall, efforts to adjust and optimize antimicrobial management occurred, on average, at 75 hours from TTP in 80% of eligible patients during the preintervention period compared with 29 hours, on average, in 94% of eligible patients in the intervention study group (79 of 99 and 86 of 92 patients, respectively; P = .004; Figure 2).

At TTP, similar proportions of patients on inactive therapy were identified in the 2 groups (22 of 112 preintervention patients and 16 of 107 intervention patients; Figure 2). At 24 hours from BSI onset, 22 patients (19.6%) in the preintervention period were on inactive therapy compared with 5 patients (4.7%) in the intervention group. The average time to initiation of an active agent was 73.2 hours in the preintervention group (n = 22) compared with 36.5 hours in the intervention group (n = 5; P < .001). At 48 hours, inactive therapy was only identified in 15 of 112 patients from the preintervention study period (P < .001).

The mean hospital LOS for survivors (n = 100) in the preintervention group was 11.9 days, and this was significantly decreased to 9.3 days for the intervention group (n = 101; P = .01; Table 2). The Kaplan-Meier analysis (Figure 3) showed a significantly decreased probability of remaining hospitalized after BSI onset as a function of the study intervention (P = .02). Multivariate Cox proportional hazards regression analysis revealed that our study intervention remained independently associated with a decreased length of hospitalization in patients with gram-negative BSIs. Patients in the intervention study group had a 38% greater rate of discharge compared with the preintervention group (hazard ratio for intervention group, 1.38; 95% confidence interval, 1.01–1.88). Additionally, receipt of active antimicrobial therapy at 48 hours was independently associated with decreased LOS (hazard ratio, 2.9; 95% confidence interval, 1.15–7.33). Preexisting pulmonary disease, preinfection LOS, and APACHE II score were independent predictors of prolonged hospitalization (Table 3). All-cause 30-day mortality rates were lower in the intervention period compared with the preintervention period (5.6% versus 10.7%, respectively; P = .19).

Table 2.

Length of Stay and Cost Outcomes in Survivorsa

Figure 3.

Impact of combining matrix-assisted laser desorption and ionization time-of-flight mass spectrometry with antimicrobial stewardship on hospital length of stay after bloodstream infection onset. Kaplan-Meier curves compare time to hospital discharge between preintervention and intervention study periods for hospital survivors (P = .02, log-rank test).

Figure 3.

Impact of combining matrix-assisted laser desorption and ionization time-of-flight mass spectrometry with antimicrobial stewardship on hospital length of stay after bloodstream infection onset. Kaplan-Meier curves compare time to hospital discharge between preintervention and intervention study periods for hospital survivors (P = .02, log-rank test).

Close modal
Table 3.

Independent Factors Associated with Length of Staya

### Limitations

Our study has several limitations. First, we analyzed a limited sample size at a single academic quaternary care hospital, which means that the results may not be applicable to other settings. However, as noted above, the findings from other investigations corroborate the role of timely, appropriate antibiotics as a determinant of improved outcomes in patients with gram-negative BSIs. Second, patients in the preintervention study period were analyzed retrospectively, creating the possibility of information bias. Third, we did not examine all aspects of care that may have influenced the clinical outcomes (eg, training and experience of the treating physicians). Fourth, when the study started, we had not yet validated the MALDI-TOF MS for identification of yeasts, gram-positive anaerobic organisms, or gram-negative anaerobic organisms directly from blood culture bottles, thereby preventing inclusion of patients with infections caused by these organisms. Future analyses warrant their evaluation for potential impact.3,6,13,25,35

In an era of increasing resistance to bacterial antimicrobial agents, optimal and timely management of patients with gram-negative BSIs is essential. Many strategies have been proposed and tried to further improve the consequences of these detrimental infections. However, our study is the first to demonstrate that integrating rapid molecular analysis by novel application of MS with antimicrobial stewardship in near real time significantly enhanced clinical care and financial outcomes. Our interdisciplinary collaborative study provides an important framework for productively addressing many other clinical care problems.

We thank the Clinical Microbiology Laboratory staff and the Clinical Pharmacy Services for assistance with the study; D. Meuth, MBA (The Methodist Hospital [TMH], Houston, Texas), for providing institutional financial data; J. O. Ikwuagwu, PharmD (TMH), for advice and assistance; and P. Cagle, MD (TMH), A. Drews, MD (TMH), V. Fainstein, MD (TMH), R. Harris, MD (TMH), M. Liebl, PharmD (TMH), D. Low, MD (Mt Sinai Hospital, Toronto, Ontario, Canada), A. McGeer, MD (Mt. Sinai Hospital, Toronto), I. Nachamkin, DrPH, MPH (University of Pennsylvania, Philadelphia, Pennsylvania), R. Rapp, PharmD (University of Kentucky, Lexington, Kentucky), E. Septimus, MD (Hospital Corporation of America Inc, Houston, Texas), S. Shelburne, MD, PhD (MD Anderson Cancer Center, Houston, Texas), and K. Traugott, PharmD (Ochsner Health System, New Orleans, Louisiana), for critical review of the manuscript. We gratefully acknowledge K. E. Stockbauer, PhD, Office of Academic Development, Department of Pathology and Genomic Medicine, TMH, for assistance with manuscript preparation.

1
Ibrahim
EH
,
Sherman
G
,
Ward
S
,
Fraser
VJ
,
Kollef
MH
.
The influence of inadequate antimicrobial treatment of bloodstream infections on patient outcomes in the ICU setting
.
Chest
.
2000
;
118
(
1
):
146
155
.
2
Harbarth
S
,
Garbino
J
,
Pugin
J
,
Romand
JA
,
Lew
D
,
Pittet
D
.
Inappropriate initial antimicrobial therapy and its effect on survival in a clinical trial of immunomodulating therapy for severe sepsis
.
Am J Med
.
2003
;
115
(
7
):
529
535
.
3
Garey
KW
,
Rege
M
,
Pai
MP
,
et al
.
Time to initiation of fluconazole therapy impacts mortality in patients with candidemia: a multi-institutional study
.
Clin Infect Dis
.
2006
;
43
(
1
):
25
31
.
4
Micek
ST
,
Lloyd
AE
,
Ritchie
DJ
,
Reichley
RM
,
Fraser
VJ
,
Kollef
MH
.
Pseudomonas aeruginosa bloodstream infection: importance of appropriate initial antimicrobial treatment
.
Antimicrob Agents Chemother
.
2005
;
49
(
4
):
1306
1311
.
5
Hidron
AI
,
Edwards
JR
,
Patel
J
,
et al
.
NHSN annual update: antimicrobial-resistant pathogens associated with healthcare-associated infections: annual summary of data reported to the national healthcare safety network at the centers for disease control and prevention, 2006–2007
.
Infect Control Hosp Epidemiol
.
2008
;
29
(
11
):
996
1011
.
6
Gaynes
R
,
Edwards
JR
;
National Nosocomial Infections Surveillance System. Overview of nosocomial infections caused by gram-negative bacilli
.
Clin Infect Dis
.
2005
;
41
(
6
):
848
854
.
7
Peleg
AY
,
Hooper
DC
.
Hospital-acquired infections due to gram-negative bacteria
.
N Engl J Med
.
2010
;
362
(
19
):
1804
1813
.
8
Dellit
TH
,
Owens
RC
,
McGowan
JE
Jr,
et al
.
Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America guidelines for developing an institutional program to enhance antimicrobial stewardship
.
Clin Infect Dis
.
2007
;
44
(
2
):
159
177
.
9
Seng
P
,
Drancourt
M
,
Gouriet
F
,
et al
.
Ongoing revolution in bacteriology: routine identification of bacteria by matrix-assisted laser desorption ionization time-of-flight mass spectrometry
.
Clin Infect Dis
.
2009
;
49
(
4
):
543
551
.
10
Prod'hom
G
,
Bizzini
A
,
Durussel
C
,
Bille
J
,
Greub
G
.
Matrix-assisted laser desorption ionization-time of flight mass spectrometry for direct bacterial identification from positive blood culture pellets
.
J Clin Microbiol
.
2010
;
48
(
4
):
1481
1483
.
11
Schubert
S
,
Weinert
K
,
Wagner
C
,
et al
.
Novel, improved sample preparation for rapid, direct identification from positive blood cultures using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry
.
J Mol Diagn
.
2011
;
13
(
6
):
701
706
.
12
Wimmer
JL
,
Long
SW
,
Cernoch
P
,
et al
.
Strategy for rapid identification and antibiotic susceptibility testing of gram-negative bacteria directly recovered from positive blood cultures using the Bruker MALDI Biotyper and the BD Phoenix system
.
J Clin Microbiol
.
2012
;
50
(
7
):
2452
2454
.
13
Bauer
KA
,
West
JE
,
JM
,
Pancholi
P
,
Stevenson
KB
,
Goff
DA
.
An antimicrobial stewardship program's impact with rapid polymerase chain reaction methicillin-resistant Staphylococcus aureus/S. aureus blood culture test in patients with S. aureus bacteremia
.
Clin Infect Dis
.
2010
;
51
(
9
):
1074
1080
.
14
Boucher
HW
,
Talbot
GH
,
JS
,
et al
.
Bad bugs, no drugs: no ESKAPE!: an update from the Infectious Diseases Society of America
.
Clin Infect Dis
.
2009
;
48
(
1
):
1
12
.
15
Knaus
WA
,
Draper
EA
,
Wagner
DP
,
Zimmerman
JE
.
APACHEII: a severity of disease classification system
.
Crit Care Med
.
1985
;
13
(
10
):
818
829
.
16
McGregor
JC
,
Rich
SE
,
Harris
,
et al
.
A systematic review of the methods used to assess the association between appropriate antibiotic therapy and mortality in bacteremic patients
.
Clin Infect Dis
.
2007
;
45
(
3
):
329
337
.
17
Garner
JS
,
Jarvis
WR
,
Emori
TG
,
Horan
TC
,
Hughes
JM
.
CDC definitions for nosocomial infections, 1988
.
Am J Infect Control
.
1988
;
16
(
3
):
128
140
.
18
Clinical and Laboratory Standards Institute
.
Performance Standards for Antimicrobial Susceptibility Testing: Twenty-First Informational Supplement
.
Wayne, PA
:
Clinical and Laboratory Standards Institute;
2011
.
CLSI document M100-S21
.
19
Kang
CI
,
Kim
SH
,
Kim
HB
,
et al
.
Pseudomonas aeruginosa bacteremia: risk factors for mortality and influence of delayed receipt of effective antimicrobial therapy on clinical outcome
.
Clin Infect Dis
.
2003
;
37
(
6
):
745
751
.
20
Lee
YT
,
Kuo
SC
,
Yang
SP
,
et al
.
Impact of appropriate antimicrobial therapy on mortality associated with Acinetobacter baumannii bacteremia: relation to severity of infection
.
Clin Infect Dis
.
2012
;
55
(
2
):
209
215
.
21
Shorr
AF
,
Micek
ST
,
Welch
EC
,
Doherty
JA
,
Reichley
RM
,
Kollef
MH
.
Inappropriate antibiotic therapy in gram-negative sepsis increases hospital length of stay
.
Crit Care Med
.
2011
;
39
(
1
):
46
51
.
22
Lodise
TP
Jr,
Patel
N
,
Kwa
A
,
et al
.
Predictors of 30-day mortality among patients with Pseudomonas aeruginosa bloodstream infections: impact of delayed appropriate antibiotic selection
.
Antimicrob Agents Chemother
.
2007
;
51
(
10
):
3510
3515
.
23
Tumbarello
M
,
Spanu
T
,
Di Bidino
R
,
et al
.
Costs of bloodstream infections caused by Escherichia coli and influence of extended-spectrum-beta-lactamase production and inadequate initial antibiotic therapy
.
Antimicrob Agents Chemother
.
2010
;
54
(
10
):
4085
4091
.
24
Shorr
AF
,
Micek
ST
,
Kollef
MH
.
Inappropriate therapy for methicillin-resistant Staphylococcus aureus: resource utilization and cost implications
.
Crit Care Med
.
2008
;
36
(
8
):
2335
2340
.
25
Lodise
TP
,
McKinnon
PS
,
Swiderski
L
,
Rybak
MJ
.
Outcomes analysis of delayed antibiotic treatment for hospital-acquired Staphylococcus aureus bacteremia
.
Clin Infect Dis
.
2003
;
36
(
11
):
1418
1423
.
26
Kollef
KE
,
Schramm
GE
,
Wills
AR
,
Reichley
RM
,
Micek
ST
,
Kollef
MH
.
Predictors of 30-day mortality and hospital costs in patients with ventilator-associated pneumonia attributed to potentially antibiotic-resistant gram-negative bacteria
.
Chest
.
2008
;
134
(
2
):
281
287
.
27
Schwaber
MJ
,
Carmeli
Y
.
Mortality and delay in effective therapy associated with extended-spectrum beta-lactamase production in Enterobacteriaceae bacteraemia: a systematic review and meta-analysis
.
J Antimicrob Chemother
.
2007
;
60
(
5
):
913
920
.
28
Martin
GS
,
Mannino
DM
,
Eaton
S
,
Moss
M
.
The epidemiology of sepsis in the United States from 1979 through 2000
.
N Engl J Med
.
2003
;
348
(
16
):
1546
1554
.
29
Camins
BC
,
King
MD
,
Wells
JB
,
et al
.
Impact of an antimicrobial utilization program on antimicrobial use at a large teaching hospital: a randomized controlled trial
.
Infect Control Hosp Epidemiol
.
2009
;
30
(
10
):
931
938
.
30
Forrest
GN
,
Mehta
S
,
Weekes
E
,
Lincalis
DP
,
Johnson
JK
,
Venezia
RA
.
Impact of rapid in situ hybridization testing on coagulase-negative staphylococci positive blood cultures
.
J Antimicrob Chemother
.
2006
;
58
(
1
):
154
158
.
31
Holtzman
C
,
Whitney
D
,
Barlam
T
,
Miller
NS
.
Assessment of impact of peptide nucleic acid fluorescence in situ hybridization for rapid identification of coagulase-negative staphylococci in the absence of antimicrobial stewardship intervention
.
J Clin Microbiol
.
2011
;
49
(
4
):
1581
1582
.
32
Roberts
RR
,
Hota
B
,
I
,
et al
.
Hospital and societal costs of antimicrobial-resistant infections in a Chicago teaching hospital: implications for antibiotic stewardship
.
Clin Infect Dis
.
2009
;
49
(
8
):
1175
1184
.
33
Charani
E
,
Edwards
R
,
Sevdalis
N
,
et al
.
Behavior change strategies to influence antimicrobial prescribing in acute care: a systematic review
.
Clin Infect Dis
.
2011
;
53
(
7
):
651
662
.
34
Singh
N
,
Rogers
P
,
Atwood
CW
,
Wagener
MM
,
Yu
VL
.
Short-course empiric antibiotic therapy for patients with pulmonary infiltrates in the intensive care unit: a proposed solution for indiscriminate antibiotic prescription
.
Am J Respir Crit Care Med
.
2000
;
162
(
2, pt 1
):
505
511
.
35
Neidell
MJ
,
Cohen
B
,
Furuya
Y
,
et al
.
Costs of healthcare- and community-associated infections with antimicrobial-resistant versus susceptible organisms
.
Clin Infect Dis
.
2012
;
55
(
6
):
807
815
.

## Author notes

The authors have no relevant financial interest in the products or companies described in this article.