NEJM 2018 paper

The

n e w e ng l a n d j o u r na l

of

m e dic i n e

Original Article

Changes in Prevalence of Health Care–
Associated Infections in U.S. Hospitals
S.S. Magill, E. O’Leary, S.J. Janelle, D.L. Thompson, G. Dumyati, J. Nadle, L.E. Wilson,
M.A. Kainer, R. Lynfield, S. Greissman, S.M. Ray, Z. Beldavs, C. Gross, W. Bamberg,
M. Sievers, C. Concannon, N. Buhr, L. Warnke, M. Maloney, V. Ocampo,
J. Brooks, T. Oyewumi, S. Sharmin, K. Richards, J. Rainbow, M. Samper,
E.B. Hancock, D. Leaptrot, E. Scalise, F. Badrun, R. Phelps, and J.R. Edwards,
for the Emerging Infections Program Hospital Prevalence Survey Team*​​

A BS T R AC T
BACKGROUND
The authors’ full names, academic degrees, and affiliations are listed in the
Appendix. Address reprint requests to
Dr. Magill at the Division of Healthcare
Quality Promotion, Centers for Disease
Control and Prevention, 1600 Clifton Rd.,
H16-3, Atlanta, GA 30329, or at s­ magill@​
­cdc​.­gov.
* A complete list of the Emerging Infections Program Hospital Prevalence Survey Team investigators is provided in the
Supplementary Appendix, available at
NEJM.org.
N Engl J Med 2018;379:1732-44.
DOI: 10.1056/NEJMoa1801550
Copyright © 2018 Massachusetts Medical Society.

A point-prevalence survey that was conducted in the United States in 2011 showed
that 4% of hospitalized patients had a health care–associated infection. We repeated
the survey in 2015 to assess changes in the prevalence of health care–associated
infections during a period of national attention to the prevention of such infections.
METHODS

At Emerging Infections Program sites in 10 states, we recruited up to 25 hospitals
in each site area, prioritizing hospitals that had participated in the 2011 survey.
Each hospital selected 1 day on which a random sample of patients was identified
for assessment. Trained staff reviewed medical records using the 2011 definitions
of health care–associated infections. We compared the percentages of patients
with health care–associated infections and performed multivariable log-binomial
regression modeling to evaluate the association of survey year with the risk of
health care–associated infections.
RESULTS

In 2015, a total of 12,299 patients in 199 hospitals were surveyed, as compared
with 11,282 patients in 183 hospitals in 2011. Fewer patients had health care–­
associated infections in 2015 (394 patients [3.2%; 95% confidence interval {CI},
2.9 to 3.5]) than in 2011 (452 [4.0%; 95% CI, 3.7 to 4.4]) (P<0.001), largely owing
to reductions in the prevalence of surgical-site and urinary tract infections. Pneumonia, gastrointestinal infections (most of which were due to Clostridium difficile
[now Clostridioides difficile]), and surgical-site infections were the most common
health care–associated infections. Patients’ risk of having a health care–associated
infection was 16% lower in 2015 than in 2011 (risk ratio, 0.84; 95% CI, 0.74 to
0.95; P = 0.005), after adjustment for age, presence of devices, days from admission
to survey, and status of being in a large hospital.
CONCLUSIONS

The prevalence of health care–associated infections was lower in 2015 than in
2011. To continue to make progress in the prevention of such infections, prevention strategies against C. difficile infection and pneumonia should be augmented.
(Funded by the Centers for Disease Control and Prevention.)

1732

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.

Health Care–Associated Infections in U.S. Hospitals

H

ealth care–associated infections
are major threats to the safety of patients
in the United States. Rates of selected
health care–associated infections have become
state and national metrics by which government
agencies and consumers evaluate health care
quality in hospitals. The National Healthcare
Safety Network of the Centers for Disease Control and Prevention (CDC) tracks state and national progress regarding the prevention of health
care–associated infections in thousands of U.S.
health care facilities,1 including approximately
3800 general, women’s, and children’s hospitals.
When reporting data regarding health care–associated infections to the National Healthcare Safety Network, hospitals prioritize selected inpatient
locations or infections that are included in federal,
state, or local reporting mandates or qualityimprovement programs.
Point-prevalence surveys of health care–associated infections in health care settings complement location- or infection-specific National
Healthcare Safety Network data, allowing public
health officials and health care leaders to conduct periodic assessments of these infections to
be considered for tracking and prevention. In
2011, the CDC conducted a hospital prevalence
survey of health care–associated infections and
the use of antimicrobial agents with the Emerging Infections Program, a network of 10 state
health departments and academic collaborators.2
A total of 4% of patients had a health care–associated infection. We used these data to generate
national estimates of 648,000 patients with
721,800 health care–associated infections in U.S.
hospitals in 2011.3
Since 2011, efforts aimed at preventing health
care–associated infections have continued to
grow nationally, with a focus on antimicrobialresistant pathogens.4-8 Although data that have
been reported by hospitals to the National Healthcare Safety Network indicate national progress
in reducing the incidence of specific health care–
associated infections that have been targeted by
prevention initiatives or reporting requirements,9
it is not clear whether reductions in the risk of
health care–associated infection have occurred
across hospital locations. We repeated the survey
in 2015 to assess changes in the prevalence of
health care–associated infections.

Me thods
Hospitals and Patients

At 10 sites in the Emerging Infections Program
(in California, Colorado, Connecticut, Georgia,
Maryland, Minnesota, New Mexico, New York,
Oregon, and Tennessee), we recruited general,
women’s, and children’s hospitals in their survey
catchment areas (Tables S1 and S2 in the Supplementary Appendix, available with the full text of
this article at NEJM.org). Sites preferentially recruited hospitals that had participated in the 2011
survey. Sites engaged additional hospitals, up to
25 per site, by recruiting from randomly sorted
hospital lists stratified according to hospital size
(small, <150 beds; medium, 150 to 399 beds; or
large, ≥400 beds) (see the Supplementary Appendix).
Each hospital selected a survey date from May 1
through September 30, 2015. Random samples
of patients in acute care locations were selected
from hospitals’ morning censuses on the survey
date with the use of the method that had been
used in the 2011 survey (see the Supplementary
Appendix).
The CDC determined the survey to be a nonresearch activity. The Emerging Infections Program site and hospital review boards either considered the survey to be a nonresearch activity or
approved the survey with a waiver of informed
consent.
Data Collection and Management

Staff at the hospitals or the Emerging Infections
Program sites reviewed medical records on the
survey date or retrospectively (see the Supplementary Appendix) to collect basic demographic
and clinical data, including information on
whether devices were present on the survey date,
and to identify patients who received or were
scheduled to receive antimicrobial agents on the
survey date or the day before the survey. Trained
staff of the Emerging Infections Program retrospectively reviewed records of patients who were
receiving or were scheduled to receive antimicrobial agents, in order to collect data regarding the
use of antimicrobial agents on the survey date
and the day before the survey.
Program staff also reviewed medical records
for health care–associated infections if patients

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.

1733

The

n e w e ng l a n d j o u r na l

were receiving antimicrobial agents for the treatment of an infection or for no documented rationale on the survey date or day before the survey.
They identified and reported health care–associated infections for which signs and symptoms
were present or for which antimicrobial treatment was given on the survey date. Two different
National Healthcare Safety Network sets of definitions of health care–associated infections were
used: the definitions used in the 2011 survey10
and the definitions in place in 201511 (see the
Supplementary Appendix). For comparisons of
the prevalence of health care–associated infections in the two surveys, we included only the
infections that were detected according to the
2011 definitions.
Program staff entered data into a Web-based
data system developed at the CDC. Staff at the
CDC reviewed the data from each site for errors
and inconsistencies, and staff from the Emerging
Infections Program re-reviewed medical records
when necessary to verify data or make corrections.
Statistical Analysis

Extracts of patient data that were generated on
November 16, 2017, were analyzed with the use
of SAS software, versions 9.3 and 9.4 (SAS Institute), and OpenEpi software, version 3.01.12 We
compared the characteristics of the patients using
chi-square or mid-P exact tests for categorical
variables and median tests for continuous variables. We compared the percentages of patients
who had health care–associated infections using
mid-P exact tests. To account for characteristics
of the patients and hospitals that might explain
differences in the prevalence of health care–associated infections, we performed multivariable logbinomial regression modeling with survey year
included as a covariate (see the Supplementary
Appendix). A two-sided P value of 0.05 or less
was considered to indicate statistical significance. National burden estimates for 2015 were
developed with the use of a process that was
similar to the method used in 2011,3 with the
2014 National Inpatient Sample data (Healthcare
Cost and Utilization Project, Agency for Healthcare Research and Quality)13 and the formula of
Rhame and Sudderth14 (see the Supplementary
Appendix).

1734

of

m e dic i n e

R e sult s
Patients

A total of 12,299 patients in 199 hospitals were
surveyed in 2015 (Table 1, and Table S3 in the
Supplementary Appendix), as compared with
11,282 patients in 183 hospitals in 2011. Hospital survey dates tended to be later in the survey
period in 2015 than in 2011 (Table 2, and Fig. S1
in the Supplementary Appendix). The distribution
of patients according to age and sex was similar
in the 2011 and 2015 surveys (Table S4 in the
Supplementary Appendix). In both surveys, approximately 15% of the patients were in critical
care units, the median time from admission to the
survey date was 3 days, and approximately 11%
of patients with a health care–associated infection died during their hospitalization (Table 2).
The percentages of patients with a urinary catheter or central catheter (known as a central line in
surveillance of the National Healthcare Safety
Network) on the survey date were lower in 2015
(urinary catheter, 18.7%; central catheter, 16.9%)
than in 2011 (urinary catheter, 23.6%; central
catheter, 18.8%) (P<0.001 for both comparisons).
In the 2015 survey, 4614 patients (37.5%) met
the criterion for review of health care–associated
infection by receiving antimicrobial agents for
the treatment of an infection or receiving antimicrobial agents for which the rationale was not
documented. This percentage was lower than that
of patients who met the same review criterion in
the 2011 survey (39.9%, P<0.001).
Prevalence of Health Care–Associated
Infections

Applying the same definitions of health care–
associated infections that had been used in 2011,
we found that 394 of 12,299 patients in the 2015
survey had one or more health care–associated
infections (3.2%; 95% confidence interval [CI],
2.9 to 3.5), as compared with 452 of 11,282
patients (4.0%; 95% CI, 3.7 to 4.4) in the 2011
survey (P<0.001). A comparison of the prevalence and distribution of health care–associated
infections according to the 2011 and 2015 definitions among patients in the 2015 survey is
presented in the Supplementary Appendix (Results section and Table S5 in the Supplementary
Appendix).

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.

Health Care–Associated Infections in U.S. Hospitals

Table 1. Selected Characteristics of Surveyed Patients, 2015.*

All Patients
(N = 12,299)

Patients without
Health Care–
Associated Infection
(N = 11,905)

Patients with
Health Care–
Associated Infection
(N = 394)

Small

3,975 (32.3)

3,889 (32.7)

86 (21.8)

Medium

5,629 (45.8)

5,459 (45.9)

170 (43.1)

Large

2,695 (21.9)

2,557 (21.5)

138 (35.0)

1,834 (14.9)

1,719 (14.4)

115 (29.2)

Unit housing patients receiving different levels of
acute care

228 (1.9)

220 (1.8)

8 (2.0)

Newborn or special care nursery

456 (3.7)

455 (3.8)

1 (0.3)

Characteristic
Hospital size — no. (%)‡

P Value†
<0.001

Location of patient in hospital on survey date — no. (%)
Critical care unit

Specialty care area
Step-down unit
Ward, excluding nursery

<0.001

60 (0.5)

58 (0.5)

2 (0.5)

547 (4.4)

525 (4.4)

22 (5.6)

9,174 (74.6)

8,928 (75.0)

246 (62.4)

Central catheter in place on survey date — no. (%)

<0.001

Any

2,081 (16.9)

1,868 (15.7)

213 (54.1)

One catheter

1,716 (14.0)

1,542 (13.0)

174 (44.2)

More than one catheter

217 (1.8)

188 (1.6)

29 (7.4)

Unknown number of catheters

148 (1.2)

138 (1.2)

10 (2.5)

9,995 (84.0)

180 (45.7)

None

10,175 (82.7)

Missing data

43 (0.3)

42 (0.4)

1 (0.3)

Urinary catheter in place on survey date — no. (%)

<0.001

Yes

2,299 (18.7)

2,164 (18.2)

135 (34.3)

No

9,959 (81.0)

9,703 (81.5)

256 (65.0)

Missing data

41 (0.3)

38 (0.3)

3 (0.8)

Ventilator in place on survey date — no. (%)
Yes

<0.001
586 (4.8)

No

11,683 (95.0)

Missing data

30 (0.2)

Receiving or scheduled to receive antimicrobial therapy
on the survey date or day before the survey, or
information not available — no. (%)

505 (4.2)
11,371 (95.5)
29 (0.2)

81 (20.6)
312 (79.2)
1 (0.3)

6,223 (50.6)

5,829 (49.0)

NA§

—

Median no. of days from admission to survey (IQR)

3 (1–6)

2 (1–6)

13 (7–21)

<0.001¶

Median hospital length of stay (IQR) — days

5 (3–11)

5 (3–10)‖

20 (11–37)**

<0.001¶

* Percentages may not total 100 because of rounding. NA denotes not applicable, and IQR interquartile range.
† The chi-square test was used for calculating the P value, unless otherwise indicated. The comparison excluded patients with missing data,
unless otherwise indicated.
‡ Hospital size was determined according to the number of beds: fewer than 150 beds indicated small size, 150 to 399 beds indicated medium
size, and 400 beds or more indicated large size.
§ By definition, all patients with a health care–associated infection were receiving antimicrobial agents at the time of the survey.
¶ The P value was calculated by a median two-sample test. The number of days from admission to survey was calculated by subtracting the admission date from the survey date; the length of stay in the hospital was calculated by subtracting the admission date from the discharge date.
‖ The analysis excluded seven patients who were still in the hospital 6 months after the survey date and one patient for whom the hospital
discharge date was unknown.
** The analysis excluded one patient who was still in the hospital 6 months after the survey date.

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.

1735

The

n e w e ng l a n d j o u r na l

of

m e dic i n e

Table 2. Comparison of Selected Characteristics of the Patients, 2011 vs. 2015 Survey.*
2011 Survey Patients
(N = 11,282)

Characteristic

2015 Survey Patients
(N = 12,299)

Survey month — no. (%)

P Value†
<0.001

May or June

5863 (52.0)

3008 (24.5)

July, August, or September

5419 (48.0)

9291 (75.5)

Small

4073 (36.1)

3975 (32.3)

Medium

4995 (44.3)

5629 (45.8)

Large

2214 (19.6)

2695 (21.9)

1707 (15.1)

1834 (14.9)

Unit housing patients receiving different levels of
acute care

119 (1.1)

228 (1.9)

Newborn or special care nursery

485 (4.3)

456 (3.7)

Hospital size — no. (%)

<0.001

Location of patient in hospital on survey date — no. (%)‡
Critical care unit

Specialty care area

<0.001

49 (0.4)

60 (0.5)

466 (4.1)

547 (4.4)

8456 (75.0)

9174 (74.6)

Yes

2121 (18.8)

2081 (16.9)

No

9140 (81.0)

10,175 (82.7)

Step-down unit
Ward, excluding nursery
Central catheter in place on survey date — no. (%)

Missing data

<0.001

21 (0.2)

43 (0.3)

Urinary catheter in place on survey date — no. (%)

<0.001

Yes

2659 (23.6)

2299 (18.7)

No

8594 (76.2)

9959 (81.0)

Missing data

29 (0.3)

41 (0.3)

Received or were scheduled to receive antimicrobial
therapy on the survey date or day before the
survey, or information not available — no. (%)

5849 (51.8)§

6223 (50.6)

0.06

Received antimicrobial therapy for infection treatment
or no documented rationale at time of survey
— no. (%)

4504 (39.9)¶

4614 (37.5)

<0.001

Median no. of days from admission to survey (IQR)

3 (1–6)

3 (1–6)

Outcome among patients with health care–associated
infection only — no./total no. (%)
Survived

0.40‖
0.99**

386/452 (85.4)

348/394 (88.3)

Died

50/452 (11.1)

45/394 (11.4)

Still in hospital or data were missing

16/452 (3.5)

1/394 (0.3)

* Percentages may not total 100 because of rounding.
† The chi-square test was used for calculating the P value, unless otherwise indicated. The comparison excluded patients
with missing data, unless otherwise indicated.
‡ The locations of the patients were defined according to the 2015 National Healthcare Safety Network categories.
Solid-organ transplantation and dialysis units were classified as specialty care areas, and bone marrow transplantation and hematology–oncology units were classified as non–nursery ward locations.
§ The analysis excluded 11 patients in the 2011 survey who were screen-positive based on a special criterion for dialysis
patients. This criterion was not implemented in the 2015 survey.
¶ The analysis included 7 patients who underwent medical record review for health care–associated infection because
they met the antimicrobial use screening criterion for patients undergoing dialysis. This criterion was not implemented in the 2015 survey.
‖ The P value was calculated by a median two-sample test. The number of days from admission to survey was calculated
by subtracting the admission date from the survey date.
** The comparison included only patients for whom the outcome was known (died vs. survived).

1736

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.

Health Care–Associated Infections in U.S. Hospitals

Table 3. Multivariable Log-Binomial Regression Model to Identify Variables Associated with Health Care–Associated
Infections, Combined 2011 and 2015 Survey Populations.*
Total No.
of Patients

No. of Patients
with Infection

Adjusted Risk Ratio
(95% CI)

12,299

394

0.84 (0.74–0.95)

0.005

Ventilator on the survey date‡

1,113

176

1.63 (1.38–1.92)

<0.001

Central catheter on the survey date§

4,202

472

1.84 (1.59–2.13)

<0.001

Urinary catheter on the survey date¶

4,958

312

1.24 (1.07–1.44)

0.004

Large hospital‖

4,909

280

1.20 (1.05–1.37)

0.007

≤1 day

7,022

27

Reference

—

2–4 days

9,013

81

2.15 (1.41–3.38)

<0.001

Variable
Survey year 2015†

P Value

Time from admission to survey

5–6 days

2,154

76

7.14 (4.67–11.26)

<0.001

7–9 days

1,834

127

12.97 (8.71–20.05)

<0.001

≥10 days

3,557

535

25.45 (17.54–38.58)

<0.001

<40 yr

7,217

172

Reference

—

40–50 yr

2,185

88

1.50 (1.17–1.89)

<0.001

51–57 yr

2,277

114

1.67 (1.33–2.08)

<0.001

58–65 yr

3,048

140

1.45 (1.17–1.78)

<0.001

66–72 yr

2,703

104

1.39 (1.10–1.75)

0.005

73–80 yr

2,815

113

1.56 (1.24–1.95)

<0.001

≥81 yr

3,335

115

1.65 (1.31–2.07)

<0.001

Age**

* The total number of patients who were included in either survey was 23,581. One patient from the 2011 survey for
whom age was unknown was excluded from the model. Other variables that were tested but found not to be sig­
nificant predictors of the risk of health care–associated infection were survey month (May or June vs. July through
September) and location of the patient in a critical care unit (yes vs. no).
† The comparator group for the risk ratio was the group of patients in the 2011 survey.
‡ The comparator group for the risk ratio was the group of patients without a ventilator or for whom the presence of a
ventilator was unknown. The presence of a ventilator was unknown for 36 patients without a health care–associated
infection and for 1 with a health care–associated infection.
§ The comparator group for the risk ratio was the group of patients without a central catheter or for whom the presence of a central catheter was unknown. The presence of a central catheter was unknown for 62 patients without a
health care–associated infection and for 2 with a health care–associated infection.
¶ The comparator group for the risk ratio was the group of patients without a urinary catheter or for whom the presence of a urinary catheter was unknown. The presence of a urinary catheter was unknown for 65 patients without a
health care–associated infection and for 5 with a health care–associated infection.
‖ The comparator group for the risk ratio was the group of patients in small or medium hospitals.
** The model excluded 1 patient without a health care–associated infection for whom age was unknown.

Because the percentage of patients who met
the criterion for review of health care–associated
infection was lower in 2015 than in 2011, we
also determined the prevalence of these infections in the subgroup of patients for whom review occurred. A total of 394 of 4614 patients
(8.5%) who met the review criterion in 2015 had
a health care–associated infection, as compared
with 452 of 4504 patients (10.0%) in 2011
(P = 0.01).

After adjustment for age, time from admission to survey, presence of devices, and status of
being in a large hospital, patients in the 2015
survey were 16% less likely to have a health
care–associated infection than patients in the
2011 survey (risk ratio, 0.84; 95% CI, 0.74 to
0.95; P = 0.005) (Table 3). We repeated the analysis in the subgroup of patients who met the review criterion. After adjustment for similar factors, patients in the 2015 survey remained less

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.

1737

The

n e w e ng l a n d j o u r na l

m e dic i n e

likely than those in the 2011 survey to have a
health care–associated infection (risk ratio, 0.84;
95% CI, 0.75 to 0.94; P = 0.003) (Table S6 in the
Supplementary Appendix).
Results were similar in an analysis that was
restricted to 148 hospitals that participated in
both surveys. In these hospitals, the percentage
of patients with a health care–associated infection was 3.2% (95% CI, 2.9 to 3.6) in 2015 (297
of 9169 patients), as compared with 4.1% (95%
CI, 3.7 to 4.6) in 2011 (383 of 9283 patients)
(P = 0.001). After adjustment for age, presence of
devices, time from admission to survey, and
status of being in a large hospital, patients in
the 2015 survey had a 22% lower risk of health
care–associated infections than patients in the
2011 survey (risk ratio, 0.78; 95% CI, 0.68 to
0.90; P<0.001) (Table S7 in the Supplementary
Appendix).
Because the inclusion of the presence of a
ventilator, central catheter, or urinary catheter
in the model neutralizes the effect of reducing
device use as a strategy for preventing health
care–associated infections, we also evaluated
the association of survey year with health care–
associated infections in a model that did not
adjust for the presence of a device. In this
model, patients in the 2015 survey had a 24%
lower risk of health care–associated infection
than patients in the 2011 survey (risk ratio, 0.76;
95% CI, 0.66 to 0.87; P<0.001) (Table S8 in the
Supplementary Appendix).

attributed to 25 different categories of National
Healthcare Safety Network operative procedures,
most commonly classified as “other” procedures
(11 infections [16%]), followed by colon procedures (7 [10%]), hip replacements (7 [10%]), and
spinal fusions (5 [7%]).
Among the 358 health care–associated infections that were not surgical-site infections, the
inpatient location to which the infection was
attributed was reported for 346 infections. Of
these, 126 infections (36.4%) were attributed to
critical care locations, 199 (57.5%) to ward or
nursery locations, and 21 (6.1%) to step-down or
specialty care units or to units that house patients receiving different levels of acute care
(known as mixed acuity locations in surveillance
of the National Healthcare Safety Network).

Types of Health Care–Associated Infection

National Estimates of Health Care–Associated
Infections in Hospitals in 2015

There were 427 health care–associated infections
in 394 patients in the 2015 survey. Pneumonia
was the most common infection, followed by
gastrointestinal infections (most of which were
due to Clostridium difficile [now Clostridioides difficile]),
and surgical-site infections (Table 4). Although
the percentages of patients with pneumonia,
gastrointestinal infection (including C. difficile
infection), or bloodstream infection did not differ significantly between 2015 and 2011, the
percentages of patients with a surgical-site infection or urinary tract infection were lower in
2015 than in 2011 (Table 4). The percentage of
patients with other health care–associated infections was also lower in 2015 than in 2011.
Of 69 surgical-site infections in the 2015 survey, 54 (78%) were deep incisional or organspace infections. Surgical-site infections were
1738

of

Pathogens Causing Health Care–Associated
Infection

At least 1 pathogen was reported for 300 of 427
health care–associated infections (70.3%). Of 392
total pathogens, C. difficile, Staphylococcus aureus,
and Escherichia coli were the most common, with
each being reported for 10% or more of all
health care–associated infections (Table 5).
Among 47 S. aureus isolates with antimicrobial
susceptibility results, 21 (45%) were methicillin
resistant (MRSA). Among 66 E. coli, klebsiella, and
enterobacter isolates with susceptibility results
that were reported for at least one carbapenem,
3 (5%) were resistant.

The age of the patients, the presence of a ventilator or central catheter, the length of stay in the
hospital, the number of beds for which the hospital was licensed, and hospital location (rural
vs. urban) were independently associated with
the prevalence of health care–associated infections in the final log-binomial regression model
(Table S9 in the Supplementary Appendix). A reduced model included factors that were present
in both the 2015 prevalence survey and the National Inpatient Sample data sets: the age of the
patient, length of stay, and hospital location.
Hospital location was removed because statistical
significance was not sustained after bootstrap
validation. The final model that was used to
obtain parameter estimates for the estimation of
burden included the age of the patient and length

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.

8

452

504

83

21

44

65

8

42

50

33

77

4.0 (3.7–4.4)

0.69 (0.55–0.86)

0.19 (0.12–0.29)

0.39 (0.29–0.52)

0.58 (0.45–0.73)

0.07 (0.03–0.14)

0.37 (0.27–0.50)

0.44 (0.34–0.58)

0.29 (0.21–0.41)

0.68 (0.55–0.85)

0.97 (0.80–1.20)

0.22 (0.15–0.33)

0.54 (0.42–0.69)

0.76 (0.62–0.94)

0.59 (0.47–0.75)

0.38 (0.28–0.51)

0.98 (0.81–1.20)

Percentage of Patients
with Infection
(95% CI)

394

61

15

24

39

14

37

51

15

54

69

25

66

91

71

39

110

No. of Patients
with Infection

427

66

15

24

39

14

38

52

15

54

69

25

66

91

71

39

110

No. of
Infections

3.2 (2.9–3.5)

0.50 (0.39–0.64)

0.12 (0.07–0.20)

0.20 (0.13–0.29)

0.32 (0.23–0.43)

0.11 (0.07–0.19)

0.30 (0.22–0.42)

0.41 (0.31–0.55)

0.12 (0.07–0.20)

0.44 (0.34–0.57)

0.56 (0.44–0.71)

0.20 (0.14–0.30)

0.54 (0.42–0.68)

0.74 (0.60–0.91)

0.58 (0.46–0.73)

0.32 (0.23–0.43)

0.89 (0.74–1.10)

Percentage of Patients
with Infection
(95% CI)

2015 Survey

<0.001

0.05

0.21

0.005

0.003

0.29

0.35

0.74

0.004

0.01

<0.001

0.76

0.97

0.84

0.87

0.41

0.52

P Value†

* A total of 11,282 patients were included in the 2011 survey, and 12,299 in the 2015 survey; these values are the denominators for the percentages of patients with infection. Patients
could have more than one health care–associated infection.
† P values were calculated by a mid-P exact test.
‡ Clostridium difficile is now known as Clostridioides difficile.
§ Other infections in the 2011 survey included the following: ear, eye, nose, and throat infections (28 infections); lower respiratory tract infection (20); skin and soft-tissue infections (16);
cardiovascular infection (6); bone and joint infections (5); central nervous system infection (4); reproductive tract infection (3); and systemic infection (1). Other infections in the 2015
survey included the following: skin and soft-tissue infections (22 infections); ear, eye, nose, and throat infections (21); lower respiratory tract infection (18); bone and joint infections
(2); central nervous system infection (1); cardiovascular infection (1); and reproductive tract infection (1).

Any infection

78

21

Other urinary tract infection

Other infection§

44

Catheter-associated urinary tract infection

65

Other primary bloodstream infection

Urinary tract infection

42

Central catheter–associated bloodstream
infection

50

33

Superficial incisional infection

Bloodstream infection

77

Deep incisional or organ-space infection

110

25

25

Other gastrointestinal infection
109

61

Surgical-site infection

86

61

Gastrointestinal infection

67

43

86

67

110

No. of
Infections

2011 Survey

Clostridium difficile infection‡

43

Other pneumonia

110

No. of Patients
with Infection

Ventilator-associated pneumonia

Pneumonia

Type of Infection

Table 4. Percentages of All Surveyed Patients with Specific Types of Health Care–Associated Infection, 2011 vs. 2015 Survey.*

Health Care–Associated Infections in U.S. Hospitals

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.

1739

1740
0
13 (12)
2 (2)

66 (15)
48 (11)
44 (10)
26 (6)
23 (5)
22 (5)

Pathogen

C. difficile

Staphylococcus aureus

Escherichia coli

Candida species

Enterococcus species

Enterobacter species††

1 (1)
1 (1)
1 (1)
0

3 (3)
3 (3)

16 (4)
11 (3)
8 (2)
8 (2)
6 (1)
6 (1)
5 (1)
5 (1)
4 (1)
4 (1)
4 (1)
4 (1)
4 (1)
3 (1)
3 (1)
2 (<1)

Coagulase-negative staphylococcus

Other gram-negative bacterium§§

Proteus mirabilis

Other gram-positive bacterium¶¶

Stenotrophomonas species

Acinetobacter baumannii

Bacteroides species‖‖

Virus***

Citrobacter freundii

Prevotella species

Serratia species

Mold

Yeast, not otherwise specified

Haemophilus influenzae, type not specified

Lactobacillus species

Other pathogen†††

64 (58)

1 (1)

1 (1)

1 (1)

3 (3)

0

0

0

1 (1)

1 (1)

16 (18)

1 (1)

0

0

0

0

0

0

0

0

0

0

1 (1)

0

0

0

2 (2)

0

19 (28)

0

1 (1)

0

0

1 (1)

1 (1)

3 (4)

1 (1)

0

2 (3)

0

0

6 (9)

3 (4)

4 (6)

6 (9)

9 (13)

3 (4)

3 (4)

10 (14)

8 (12)

1 (1)

13 (19)

12 (17)

0

0

0

0

1 (2)

0

0

1 (2)

1 (2)

0

3 (6)

2 (4)

2 (4)

1 (2)

1 (2)

1 (2)

6 (12)

6 (12)

3 (6)

0

0

6 (12)

7 (13)

4 (8)

12 (23)

0

Bloodstream
Infection
(N = 52)¶

0

0

0

0

0

0

0

0

1 (3)

0

0

0

0

0

3 (8)

1 (3)

0

0

7 (18)

5 (13)

3 (8)

4 (10)

3 (8)

18 (46)

0

0

Urinary Tract
Infection
(N = 39)‖

28 (42)

0

1 (2)

0

0

2 (3)

0

0

1 (2)

4 (6)

0

3 (5)

2 (3)

1 (2)

1 (2)

3 (5)

1 (2)

1 (2)

1 (2)

4 (6)

5 (8)

2 (3)

5 (8)

6 (9)

9 (14)

0

Other
Infection
(N = 66)**

of

127 (30)

0

21 (5)

Streptococcus species‡‡

1 (1)

2 (2)

1 (1)

2 (2)

3 (3)

1 (1)

2 (2)

66 (73)

Surgical-Site
Infection
(N = 69)§

number of infections (percent)

Gastrointestinal
Infection
(N = 91)‡

n e w e ng l a n d j o u r na l

No pathogen reported

2 (2)

21 (5)
4 (4)

8 (7)
6 (5)

22 (5)

Pseudomonas aeruginosa

Klebsiella pneumoniae or K. oxytoca

3 (3)

1 (1)

7 (6)

Pneumonia
(N = 110)†

All Infections
(N = 427)

Table 5. Pathogens Reported for Health Care–Associated Infections, 2015.*

The

m e dic i n e

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.

* Pathogens were reported for 300 of 427 health care–associated infections. Up to 3 pathogens could be reported for each infection.
† A total of 62 pathogens were reported for 46 of 110 pneumonias (42%).
‡ A total of 83 pathogens were reported for 75 of 91 gastrointestinal infections (82%).
§ A total of 89 pathogens were reported for 50 of 69 surgical-site infections (72%). Two organisms in the same genus or pathogen group were reported for each of 2 surgical-site infections.
¶ A total of 59 pathogens were reported for 52 of 52 bloodstream infections (100%). The definition of a bloodstream infection required pathogen reporting. Two organisms in the
same genus were reported for each of 2 bloodstream infections (2 streptococcus species were reported for 1 bloodstream infection, and 2 bacteroides species were reported for another bloodstream infection).
‖ A total of 45 pathogens were reported for 39 of 39 urinary tract infections (100%). The definition of a urinary tract infection required pathogen reporting.
** A total of 54 pathogens were reported for 38 of 66 other infections (58%). Two organisms in the same genus were reported for each of 2 other infections.
†† A total of 23 enterobacter were reported for 22 health care–associated infections (E. cloacae and E. aerogenes [now Klebsiella aerogenes] were each reported for 1 infection).
‡‡ A total of 24 streptococci were reported for 21 health care–associated infections (2 different streptococci were reported for each of 3 infections).
§§ Pathogens included gram-negative rod (not otherwise specified; for 2 infections), Morganella morganii (for 2), Burkholderia cepacia (for 1), capnocytophaga species (for 1),
Chryseomonas luteola (now Pseudomonas luteola; for 1), Eikenella corrodens (for 1), gram-negative coccus (not otherwise specified; for 1), Legionella pneumophila (for 1), and neisseria
species (for 1).
¶¶ Pathogens included 9 other gram-positive bacteria for 8 health care–associated infections: gram-positive coccus (not otherwise specified; for 3 infections), corynebacterium species
(for 2), gram-positive rod (not otherwise specified; for 2), Clostridium perfringens (for 1), and Rothia mucilaginosa (for 1).
‖‖ A total of 6 bacteroides were reported for 5 health care–associated infections (both B. fragilis and B. thetaiotaomicron were reported for 1 infection).
*** Pathogens included rhinovirus (for 3 infections), cytomegalovirus (for 1), and herpes simplex virus type 2 (for 1).
††† Pathogens included Pneumocystis jirovecii (for 1 infection) and other unspecified pathogen (for 1).

Health Care–Associated Infections in U.S. Hospitals

of stay (Table S9 in the Supplementary Appendix). Using National Inpatient Sample data stratified according to the categories of age and
length of stay, we estimated that there were
633,300 patients with a health care–associated
infection (95% CI, 216,000 to 1,912,700) and
687,200 health care–associated infections (95%
CI, 181,400 to 2,691,200) in U.S. hospitals in 2015
(Table S10 in the Supplementary Appendix).

Discussion
In this point-prevalence survey conducted in multiple states, we found that health care–associated
infections affected 3.2% of hospitalized patients
— a significantly lower percentage than we observed in a survey that had been conducted in
2011. These results provide evidence of national
success in preventing health care–associated
infections, particularly surgical-site and urinary
tract infections. In contrast, there was no significant reduction in the prevalence of pneumonia or C. difficile infection, nor in the percentage
of patients with health care–associated infection
who died during their hospitalization, which suggests that more work is needed to prevent these
infection types and reduce mortality among patients with health care–associated infections.
Although the prevalence of health care–associated infections was significantly lower in 2015
than in 2011, we did not directly compare the
national burden estimates from the two surveys.
Two barriers to such a comparison were present.
First, there were differences in the variables that
remained in the best-fitting multivariable regression models that were used in the 2011 and
2015 burden-estimation processes. For example,
we lacked complete data regarding the length of
stay in the hospital for patients in the 2011 survey
and therefore used a proxy measure (the number
of days from admission to the survey). In addition, the Nationwide Inpatient Sample underwent a redesign starting with 2012 data and was
renamed the National Inpatient Sample.15
Despite differences in the methods used in the
prevalence survey and in National Healthcare
Safety Network surveillance, similar signals have
emerged from these complementary systems,
providing evidence of improvements in the safety of patients in U.S. hospitals. Analyses of National Healthcare Safety Network data through
2014, before the implementation of major chang-

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.

1741

The

n e w e ng l a n d j o u r na l

es in the definitions of health care–associated
infections, showed reductions in the standardized infection ratios for central catheter–associated bloodstream infections between 2008 and
2014, selected surgical-site infections between
2008 and 2014, and MRSA bacteremia between 2011 and 2014.9 There was no reduction
in the standardized infection ratio for catheterassociated urinary tract infections in hospitals
nationally from 2009 to 2014, but a significant
decrease in the standardized infection ratio was
evident from 2013 to 2014.9
We observed significant reductions in the
prevalence of urinary tract infections and surgical-site infections. Experience has shown that
health care–associated infections can be prevented by means of evidence-based interventions;
for example, implementation of a Comprehensive Unit-based Safety Program that was focused
on catheter-associated urinary tract infection in
603 U.S. hospitals between 2011 and 2013 led to
a reduction in the rates of catheter-associated
urinary tract infection and urinary-catheter use.16
Reductions in urinary-catheter use, which we
observed in the survey, may partially explain the
lower prevalence of urinary tract infection. Although we did not collect data on urine-culturing practices, increased focus on improving the
diagnosis and treatment of urinary tract infection in recent years may also have contributed.17
The reduction in the prevalence of surgical-site
infections may reflect the uptake of preoperative
infection-prevention practices, such as the decolonization of patients with S. aureus colonization,18-20 or the use of updated surgical prophylaxis guidelines.21 A limitation of our survey is
that we do not have data to evaluate practice
changes, nor do we have information about
changes in the volume or types of operative procedures that may have affected the overall prevalence of surgical-site infections.
Our survey showed that pneumonia was the
most common health care–associated infection,
with a stable prevalence between 2011 and 2015.
Similarly, an analysis of Medicare Patient Safety
Monitoring System data showed that, between
2005 and 2013, the percentage of patients with
ventilator-associated pneumonia among eligible
Medicare patients with selected diagnoses who
were undergoing mechanical ventilation remained
the same, at approximately 10%.22 Although the
prevention of ventilator-associated pneumonia
1742

of

m e dic i n e

remains an important goal, the majority of pneumonia events in hospitals in our survey were not
ventilator-associated. The published literature
contains relatively little regarding the prevention
of non–ventilator-associated pneumonia in hospitalized patients, despite the association of this
infection with poor outcomes in some reports.23,24
Some investigators have called for increased attention and resources for this underappreciated
health care–associated infection.25-27
We also found that the prevalence of C. difficile
infection was stable between 2011 and 2015.
However, we did not collect data on changes in
the use of nucleic acid amplification tests for the
diagnosis of C. difficile infection in participating
hospitals from 2011 to 2015. Others have suggested that increasing the use of such tests may
result in an increased incidence of C. difficile infection owing to overdiagnosis.28,29 It is possible
that an increased use of nucleic acid amplification tests in survey hospitals masked actual reductions in the prevalence of C. difficile infection.
Analyses of National Healthcare Safety Network
data have begun to show progress regarding the
prevention of C. difficile infection with onset in the
hospital.9 Regardless of whether changes in testing have inflated our estimate of the burden of
C. difficile infection in hospitals, there is room for
improvement. Because the use of antibiotics is a
major driver of C. difficile infections as well as
antimicrobial resistance, continued focus on improving practices for the prescribing of antibiotics is critical, in addition to infection-control
measures to prevent transmission in hospitals.
Our survey has other potential limitations. As
in the 2011 survey, the 2015 survey included geographically diverse sites, but the results may not
be generalizable to all U.S. hospitals. Owing to the
types of data available in the National Inpatient
Sample, we were unable to account for all the
factors associated with the prevalence of health
care–associated infections in the process of developing national burden estimates. In the 2015
survey, we used the same antimicrobial screening criterion that had been used in 2011 to identify patients for review of health care–associated
infections.3,30 In 2015, the proportion of patients
who met the screening criterion was significantly
lower than in 2011. This resulted in a lower proportion of medical records being reviewed for
health care–associated infections and potentially
could have resulted in the detection of fewer

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.

Health Care–Associated Infections in U.S. Hospitals

health care–associated infections. However, analyses of the prevalence of health care–associated
infections among just those patients for whom
review was performed confirmed that a smaller
percentage of patients had a health care–associated infection in 2015 than in 2011, even after adjustment for other factors. Additional limitations
are discussed in the Supplementary Appendix.
Prevalence surveys capture the range and relative frequencies of all health care–associated infections among hospitalized patients and complement ongoing tracking of these infections. The
health care–associated infections that we identified in this survey are only one portion of the
overall burden of such infections, which includes
infections that occur in other settings, such as
nursing homes. The CDC and the Emerging
Infections Program sites are collaborating on a
large-scale nursing home prevalence survey to
address this gap.31 Collaborations among health

care facilities, public health agencies, and other
partners, bolstered by recent increases in support for programs regarding health care–associated infections, will be critical to the continued
progress toward the goal of eliminating health
care–associated infections.
The findings and conclusions in this article are those of the
authors and do not necessarily represent the official position of
the Centers for Disease Control and Prevention (CDC).
Supported by the CDC.
Dr. Dumyati reports receiving fees for serving on a data and
safety monitoring board from Seres Therapeutics; and Dr. Kainer,
receiving fees for serving on the board of directors and consulting fees from Infectious Diseases Consultation and honoraria
and travel support from Medscape. No other potential conflict
of interest relevant to this article was reported.
Disclosure forms provided by the authors are available with
the full text of this article at NEJM.org.
We thank the hospital staff who participated in each phase of
this prevalence survey effort, from 2009 to the present; colleagues at the Emerging Infections Program and the CDC who
contributed to this work (see the Supplementary Appendix); and
the staff of the Healthcare Cost and Utilization Project data
partners (www​.­hcup​-­us​.­ahrq​.­gov/​­db/​­hcupdatapartners​.­jsp).

Appendix
The authors’ full names and academic degrees are as follows: Shelley S. Magill, M.D., Ph.D., Erin O’Leary, M.P.H., Sarah J. Janelle, M.P.H.,
Deborah L. Thompson, M.D., M.S.P.H., Ghinwa Dumyati, M.D., Joelle Nadle, M.P.H., Lucy E. Wilson, M.D., Marion A. Kainer, M.B., B.S.,
M.P.H., Ruth Lynfield, M.D., Samantha Greissman, M.P.H., Susan M. Ray, M.D., Zintars Beldavs, M.S., Cindy Gross, M.T.,
S.M.(A.S.C.P.), C.I.C., Wendy Bamberg, M.D., Marla Sievers, M.P.H., Cathleen Concannon, M.P.H., Nicolai Buhr, M.P.H., Linn Warnke,
R.N., M.P.H., Meghan Maloney, M.P.H., Valerie Ocampo, R.N., B.S.N., M.I.P.H., Janet Brooks, R.N., B.S.N., C.I.C., Tolulope Oyewumi, M.B.,
B.S., M.P.H., Shamima Sharmin, M.B., B.S., M.P.H., Katherine Richards, M.P.H., Jean Rainbow, R.N., M.P.H., Monika Samper, R.N.,
Emily B. Hancock, M.S., Denise Leaptrot, M.S.A., B.S.M.T.(A.S.C.P.), C.I.C., Eileen Scalise, R.N., M.S.N., Farzana Badrun, M.D., Ruby
Phelps, B.S., and Jonathan R. Edwards, M.Stat.
The authors’ affiliations are as follows: the Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention,
(S.S.M., E.O., C.G., J.B., D.L., E.S., F.B., R.P., J.R.E.), the Department of Medicine, Emory University (S.M.R.), CACI (C.G., J.B., D.L.,
E.S.), and Eagle Medical Services (F.B.) — all in Atlanta; Colorado Department of Public Health and Environment, Denver (S.J.J., W.B.,
T.O.); New Mexico Department of Health, Santa Fe (D.L.T., M. Sievers, S.S.), and Presbyterian Healthcare Services (D.L.T.) and University of New Mexico (E.B.H.), Albuquerque; New York Emerging Infections Program and University of Rochester Medical Center, Rochester (G.D., C.C.); California Emerging Infections Program, Oakland (J.N.); Maryland Department of Health, Baltimore (L.E.W., N.B.,
K.R.); Tennessee Department of Health, Nashville (M.A.K.); Minnesota Department of Health, St. Paul (R.L., L.W., J.R.); Connecticut
Emerging Infections Program, New Haven and Hartford (S.G., M.M.); Georgia Emerging Infections Program, Decatur (S.M.R.); and
Oregon Health Authority, Portland (Z.B., V.O., M. Samper).

References
1. NHSN e-news. Vol. 12, No. 2. Atlanta:​
Centers for Disease Control and Prevention, June 2017 (https://www​.cdc​.gov/​nhsn/​
pdfs/​newsletters/​nhsn​-­nl​-­jun​-­2017​.pdf).
2. Magill SS, Dumyati G, Ray SM, Fridkin SK. Evaluating epidemiology and improving surveillance of infections associated with health care, United States.
Emerg Infect Dis 2015;​21:​1537-42.
3. Magill SS, Edwards JR, Bamberg W,
et al. Multistate point-prevalence survey of
health care–associated infections. N Engl
J Med 2014;​370:​1198-208.
4. Healthcare facility HAI reporting requirements to CMS via NHSN — current
or proposed requirements. Atlanta: Centers for Disease Control and Prevention,
September 2015 (https://www​.cdc​.gov/​nhsn/​
pdfs/​cms/​cms​-­reporting​-­requirements​.pdf).

5. What the partnership is about. Balti-

more:​Centers for Medicare & Medicaid Services (https://partnershipforpatients​.cms​
.gov/​about​-­t he​-­partnership/​what​-­is​-­t he​
-­partnership​-­about/​lpwhat​-­the​-­partnership​
-­is​-­about​.html).
6. Antibiotic resistance threats in the
United States, 2013. Atlanta: Centers for
Disease Control and Prevention (https://
www​.cdc​.gov/​drugresistance/​threat​-­report​
-­2013/​pdf/​ar​-­t hreats​-­2013​-­508​.pdf).
7. National strategy for combating antibiotic-resistant bacteria. Washington, DC:​
The White House, September 2014 (https://
www​.cdc​.gov/​drugresistance/​pdf/​c arb_
national_strategy​.pdf).
8. National action plan for combating
antibiotic-resistant bacteria. Washington,
DC:​The White House, March 2015 (https://

www​.cdc​.gov/​drugresistance/​pdf/​national
_action_plan_for_combating_antibotic​
-­resistant_bacteria​.pdf).
9. National and state healthcare associated infections: progress report. Atlanta:​
Centers for Disease Control and Prevention, 2016 (https://www​.cdc​.gov/​HAI/​pdfs/​
progress​-­report/​hai​-­progress​-­report​.pdf).
10. Horan TC, Andrus M, Dudeck MA.
CDC/NHSN surveillance definition of
health care-associated infection and criteria for specific types of infections in
the acute care setting (https://www​.cdc​
.gov/​nhsn/​pdfs/​a rchive/​17pscNosInfDef
_NOTcurrent​.pdf ). Am J Infect Control
2008;​36:​309-332.
11. National Healthcare Safety Network.
Validation manual. Atlanta:​Centers for Disease Control and Prevention, 2015 (https://

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.

1743

Health Care–Associated Infections in U.S. Hospitals

www​.cdc​.gov/​nhsn/​pdfs/​validation/​2015/​
2015​-­validation​-­manual​.pdf).
12. Dean AG, Sullivan KM, Soe MM.
OpenEpi. Open source epidemiologic statistics for public health, version 3.01.
April 2013 (www​.OpenEpi​.com).
13. Healthcare Cost and Utilization Project. HCUP National Inpatient Sample
(NIS), 2014. Rockville, MD:​Agency for
Healthcare Research and Quality, 2014
(www​.hcup​-­us​.ahrq​.gov/​nisoverview​.jsp).
14. Rhame FS, Sudderth WD. Incidence
and prevalence as used in the analysis of
the occurrence of nosocomial infections.
Am J Epidemiol 1981;​113:​1-11.
15. Houchens R, Ross D, Elixhauser A,
Jiang J. Nationwide inpatient sample (NIS)
redesign final report, 2014: HCUP methods series report #2014-04. Rockville,
MD:​U.S. Agency for Healthcare Research
and Quality (https://www​.hcup​-­us​.ahrq​
.gov/​reports/​methods/​2014​-­04​.pdf).
16. Saint S, Greene MT, Krein SL, et al.
A program to prevent catheter-associated
urinary tract infection in acute care. N Engl
J Med 2016;​374:​2111-9.
17. Garcia R, Spitzer ED. Promoting appropriate urine culture management to
improve health care outcomes and the accuracy of catheter-associated urinary tract
infections. Am J Infect Control 2017;​45:​
1143-53.
18. Bode LG, Kluytmans JA, Wertheim HF,
et al. Preventing surgical-site infections

1744

in nasal carriers of Staphylococcus aureus
N Engl J Med 2010;​362:​9-17.
19. Schweizer M, Perencevich E, McDanel
J, et al. Effectiveness of a bundled intervention of decolonization and prophylaxis
to decrease Gram positive surgical site infections after cardiac or orthopedic surgery: systematic review and meta-analysis.
BMJ 2013;​346:​f 2743.
20. Schweizer ML, Chiang HY, Septimus
E, et al. Association of a bundled intervention with surgical site infections among
patients undergoing cardiac, hip, or knee
surgery. JAMA 2015;​313:​2162-71.
21. Bratzler DW, Dellinger EP, Olsen KM,
et al. Clinical practice guidelines for antimicrobial prophylaxis in surgery. Am J
Health Syst Pharm 2013;​70:​195-283.
22. Metersky ML, Wang Y, Klompas M,
Eckenrode S, Bakullari A, Eldridge N.
Trend in ventilator-associated pneumonia
rates between 2005 and 2013. JAMA 2016;​
316:​2427-9.
23. See I, Chang J, Gualandi N, et al. Clinical correlates of surveillance events detected by National Healthcare Safety Network
pneumonia and lower respiratory infection
definitions — Pennsylvania, 2011-2012.
Infect Control Hosp Epidemiol 2016;​37:​
818-24.
24. Giuliano KK, Baker D, Quinn B. The
epidemiology of nonventilator hospitalacquired pneumonia in the United States.
Am J Infect Control 2018;​46:​322-7.

25. Ewan VC, Witham MD, Kiernan M,

Simpson AJ. Hospital-acquired pneumonia surveillance — an unmet need. Lancet
Respir Med 2017;​5:​771-2.
26. Klompas M. Hospital-acquired pneumonia in nonventilated patients: the next
frontier. Infect Control Hosp Epidemiol
2016;​37:​825-6.
27. Baker D, Quinn B. Hospital Acquired
Pneumonia Prevention Initiative-2: incidence of nonventilator hospital-acquired
pneumonia in the United States. Am J Infect Control 2018;​46:​2-7.
28. Planche TD, Davies KA, Coen PG, et al.
Differences in outcome according to Clostridium difficile testing method: a prospective multicentre diagnostic validation study
of C difficile infection. Lancet Infect Dis
2013;​13:​936-45.
29. Polage CR, Gyorke CE, Kennedy MA,
et al. Overdiagnosis of Clostridium difficile
infection in the molecular test era. JAMA
Intern Med 2015;​175:​1792-801.
30. Magill SS, Hellinger W, Cohen J, et al.
Prevalence of healthcare-associated infections in acute care hospitals in Jacksonville, Florida. Infect Control Hosp Epidemiol 2012;​33:​283-91.
31. HAI and antimicrobial use prevalence
survey: nursing home survey. Atlanta: Centers for Disease Control and Prevention
(https://www​.cdc​.gov/​hai/​eip/​antibiotic​-­use​
.html).
Copyright © 2018 Massachusetts Medical Society.

n engl j med 379;18 nejm.org  November 1, 2018

The New England Journal of Medicine
Downloaded from nejm.org at Stephen B. Thacker CDC Library on October 9, 2019. For personal use only. No other uses without permission.
Copyright © 2018 Massachusetts Medical Society. All rights reserved.