Point prevalence surveys of healthcare-associated infections and antimicrobial use in healthcare facilities

European Centre for Disease Prevention and Control

Carl Suetens, Tommi Karki, Diamantis Plachouras, Pete Kinross (HAI-Net), Antimicrobial Resistance and Healthcare-Associated Infections (ARHAI) Programme, ECDC

ECDC point prevalence surveys (PPSs), 2016-2017

2Source: Plachouras D, et al.; Ricchizzi E, et al.; Suetens C, Latour K. et al. Eurosurveillance 15 November 2018.

• 2nd ECDC PPS of healthcare-associated infections and antimicrobial use in European acute care hospitals

• 3rd ECDC PPS of healthcare-associated infections and antimicrobial use in European long-term care facilities

Objectives

• To estimate the prevalence and burden of healthcare-associated infections (HAIs, all types) and antimicrobial use

• To describe key structures and processes for the prevention of HAIs and antimicrobial resistance at the hospital and ward level in hospitals in EU/EEA countries

• To describe patients/residents, infections (sites, micro-organisms including markers of antimicrobial resistance) and antimicrobials prescribed (compounds, indications)

• To disseminate results to those who need to know at local, regional, national and EU level

Raise awareness

Train and reinforce surveillance structures and skills

Identify common EU problems and set up priorities accordingly

Evaluate the effect of strategies and guide policies (repeated PPS)

• To provide a standardised tool to identify targets for quality improvement

3

Protocols and tools

http://ecdc.europa.eu/en/healthtopics/Healthcare-associated_infections/point-prevalence-survey/Pages/Point-prevalence-survey.aspx 4

• PPS II protocol v5.3, HALT-3 (v2.1)

• Extranet: Q&A (MS Excel), training materials, validation protocol

• Train-the-trainers: face-to-face + webinars

• HelicsWin.Net/HALT software

• Hospital/LTCF feedback reports

Methods

PPS in acute care hospitals(ECDC PPS-2)

PPS in long-term care facilities (HALT-3 PPS)

Where? All EU/EEA countries and (potential) candidate countries invited

When? 4 possible periods 2016 and 2017, April-June & September-November

Data collection duration One ward one day, hospital 2-3 weeks One day, larger facilities >1 day

Who? All patients on ward at 8:00 am All residents present at 8:00 am and living in the LTCF

Exclusion Accident and emergency wards,Day cases

e.g. hospitalised residents

HAI case definitions EU case definitions (PN, BSI, SSI, UTI, CDI, neonatal HAIs), other CDC 2008

case definitions

Modified CDC/SHEA/Mc Geer case definitions for HAIs in LTCFs

Active HAI Signs and symptoms present on day PPS or were present and patient/resident is still receiving treatment for that infection on day PPS

National validation `Mandatory’, + ECDC support, min. 250 pts in 5 hospitals

Voluntary, min 1 LTCF

5

Healthcare facilities in Europe (EU/EEA)

Source: ECDC point prevalence surveys in acute care hospitals and long-term care facilities, 2016-2017 6

Acute care hospitals Long-term care facilities (LTCF)

Total number of facilities in EU/EEA

8 300 62 000

Number of occupied beds every day

1.5 million patients 3.3 million residents

Number of new admissions/year

90 million ?

Median age 66 years 85 years

Median length of stay 6 days > 1 year

M:F ratio 1:1.1 1:1.8

Representative sample of hospitals or long-term care facilities

Recommended: systematic random sampling1. Obtain a list of all acute-care hospitals/LTCFs in the country + number of beds

2. Sort list by number of beds (+ hospital/LTCF type … if available)

3. Calculate number of patients/residents and facilities to be sampled, e.g. 14 000 patients / 280 beds on average = 50 hospitals

4. Divide the total number of hospitals by the number to be sampled = sampling interval k, e.g. k = 500 hospitals / 50 = 10

5. Choose a random number between 1 and k = i.

6. Select the ith hospital, ith +k hospital, the ith+2k hospital etc.

7. Foresee substitution in case of refusal of the first selected hospital: select the next hospital on the list (ith +1 hospital, ith +k +1 hospital, etc.)

8. Invite the hospitals selected in step 6 to participate; replace them in case of refusal to participate.

9. Alternatively: first identify list of representative hospitals, then invite all hospitals in country to participate => evaluate representativeness => adjust if needed/possible

ECDC point prevalence surveys (PPSs) in acute care hospitals and LTCFs, 2016-2017: prevalence and estimated incidence of healthcare-associated infections (HAIs)

*Percentage of patients/residents with at least one HAI + 95% confidence interval, country-weighted and corrected after validation 8

PPS in acute care hospitals

PPS in long-term care facilities

Number of facilities, EU/EEA countries1209 hospitals, 28 countries

1788 LTCFs, 23 countries

Number of included patients/residents 310 755 102 301

HAI prevalence %*6.5 (5.4-7.8)

1 in 15 patients3.9 (2.4-6.0)

1 in 26 residents

Estimated number of patients/residents with HAI on any day

98 000 130 000

Estimated number of patients acquiring at least one HAI each year

3.8 million ?

Number of HAI episodes per year 4.5 million 4.4 million

Total : 8.9 million HAIs per year Estimated attributable deaths/year3 (PPS 2011-2012) : 91 310 (in acute care hospitals only)

PPS-1: Comparing the burden of HAIs with other infectious diseases

HAIsaccount for twice the burdenof 31 other infectious diseases

Burden of HAIs – 2011-2012 *Burden of 5 top ranking infectious diseases from BCoDE 2009-2013 **

Source: *Cassini A, et al. PLoS Med 2016;13(10):e1002150

** Cassini A, et al. Euro Surveill. 2018;23(16):pii=17-00454

AT

BE

BG

CY

CZ

DE

EE

ES

FI

FR

HR

HU

IEIS

IT

LT

LU

LV

MT

NO

PL

PT

RO

RS

SI

SK

UK-ENUK-NI

UK-SC

UK-WA

24

68

10

Patie

nts

with

at

least

one

HA

I (%

)

0 20 40 60 80 100

Blood cultures (No. per 1000 patient-days)

Correlation between observed prevalence of healthcare-associated infections (HAIs) and number of blood cultures per 1000 patient-days, acute care hospitals, EU/EEA and Serbia, 2016-2017

Source: ECDC PPS in European acute care hospitals, 2016-2017 (preliminary, unpublished results). Norway: national protocol 10

AT: Austria; BE: Belgium; BG: Bulgaria; CY: Cyprus; CZ: Czech Republic; DE: Germany; EE: Estonia; EL: Greece; ES: Spain; FI: Finland; FR: France; HR: Croatia; HU: Hungary; IE: Ireland; IS: Iceland; IT: Italy; LT: Lithuania; LU: Luxembourg; LV: Latvia; MT: Malta; NL: the Netherlands; NO: Norway; PL: Poland; PT: Portugal; RO: Romania; RS: Serbia; SI: Slovenia; SK: Slovakia; UK-EN: United Kingdom-England; UK-NI: UK-Northern Ireland; UK-SC: UK-Scotland; UK-WA: UK-Wales.

Patients

with a

t le

ast

one H

AI

(%)

Blood cultures (No. per 1000 patient-days)

ρ=0.75p<0.0001

Types of HAI by type of healthcare facility

Gastro-intestinal infections: including Clostridium difficile infections 11

• More severe infections (pneumonia, bloodstream infections) are transferred to hospital for treatment

• 9% of HAIs in LTCF are imported (e.g. surgical site infections)

0 10 20 30 40

Systemic/other infection

Eye, ear, nose or mouthinfection

Skin and soft tissueinfection

Gastrointestinal infection

Bloodstream infection

Surgical site infection

Urinary tract infection

Common cold/flu

Other lower respiratorytract

Pneumonia

Percentage of all HAIs

Types of HAI by type of healthcare facility

Acute carehospitals

Long-term carefacilities

Site of infection in antimicrobial treatment by origin

12

34%

16%2%

13%

6%

15%

7%6%

27%

18%

8%11%

9%

19%

5%4%

40%

24%

4%

8%

7%

12%2%4%

32%

17%4%

12%

7%

16%

6%5%

Community infection (n=54347) Hospital infection (n=21328)

LTCF HAI (n=2159) Total

Respiratory tract Urinary tract

Bacteremia Gastrointestinal

Systemic Skin, soft tissue, bone/joint

Other sites Undefined/unknown

Percentage HAIs with microbiological results

13

Acute care hospitals

**

*

*

Liechtenstein

Luxembourg

Malta

Non-visible countries

<45

45 to <50

50 to <55

55 to <65

>=65

No data

Not invited

HAIs with microbiologicalresults (%)

Long-term care facilities

14

Most frequently isolated microorganisms isolated in HAIs, acute care hospitals (n=13 683 isolates)

14*CNS: coagulase-negative staphylococci

0 5 10 15 20

ACINETOBACTER SPP.

PROTEUS SPP.

ENTEROBACTER SPP.

CANDIDA SPP.

CNS*

C. DIFFICILE

P. AERUGINOSA

ENTEROCOCCUS SPP.

KLEBSIELLA SPP.

S. AUREUS

E. COLI

Percentage of microorganisms

10.7% (PPS-1 rank 5: 8.7%)

7.5% (PPS-1 rank 8: 5.4%)

Composite index* of antimicrobial resistance (AMR) in healthcare-associated infections from acute care hospitals, EU/EEA countries and Serbia, 2016-2017

15

**

*

*

Liechtenstein

Luxembourg

Malta

Non-visible countries

<5

5 to <20

20 to <35

35 to <50

>=50

No data

Not invited

Resistantisolates (%)

*Percentage of isolates resistant to first-level antimicrobial resistance markers in healthcare-associated infections, i.e.:- Staphylococcus aureus resistant to meticillin

(MRSA), - Enterococcus faecium and Enterococcus faecalis

resistant to vancomycin, - Enterobacteriaceae resistant to third-generation

cephalosporins, - Pseudomonas aeruginosa and Acinetobacter

baumannii resistant to carbapenems.

Adapted from: Suetens C, et al. Eurosurveillance 15 November 2018;

* Bulgaria and the Netherlands: poor national representativeness of acute care hospital sample; ** Norway: national protocol; Norway and UK-Scotland did not collect microbiological data..

Correlations between composite indices of antimicrobial resistance (AMR) from ECDC data

Adapted from: Suetens C, et al. Eurosurveillance 15 November 2018. 16

PPS long-term care facilities 2016-2017EARS-Net 2016

PP

S a

cu

te c

are

ho

sp

ita

ls 2

01

6-2

01

7

PP

S a

cu

te c

are

ho

sp

ita

ls 2

01

6-2

01

7

Estimated burden of infections with antibiotic-resistant bacteria, age-group standardised, EU/EEA, 2015

Source: Cassini A, et al. Lancet Infectious Diseases. 5 November 2018.

671 689 infections with antibiotic-resistant bacteria

33 110 attributable deaths

170 DALYs* per 100 000 population

• 63% of cases were HAIs,representing 75% of total burden (DALYs)

• 70% due to 4 top-ranking antibiotic-resistant bacteria

• 39% due to carbapenem- and/or colistin resistance

*DALYS, Disability-adjusted life years

Prevalence of antimicrobial use, 2016-2017

Eurosurveillance 15 November 2018 18

**

*

*

Liechtenstein

Luxembourg

Malta

Non-visible countries

<30

30 to <35

35 to <40

40 to <45

>=45

Did not participate

Not invited

Patients onantimicrobials (%)

**

*

*

Liechtenstein

Luxembourg

Malta

Non-visible countries

<30

30 to <35

35 to <40

40 to <45

>=45

Did not participate

Not invited

Patients onantimicrobials (%)

* Bulgaria, the Netherlands: poor national representativeness of acute care hospital sample; ** Norway: national protocol.

Acute care hospitals Long-term care facilities

19Source: Plachouras D, et al. Eurosurveillance 15 November 2018.

Proportion of broad-spectrum antibiotics in acute care hospitals, EU/EEA countries & Serbia, 2016–2017

Percentage of antibiotics (%)

Surgical antibiotic prophylaxis in acute care hospitals, by duration (single dose, one day, more than one day), EU/EEA countries and Serbia, 2016-2017

20

54% surgical antibiotic prophylaxis

courses in EU/EEA countrieswere prescribed for

more than one day

1 dose

1 day

more than 1 day

Source: Plachouras D, et al. Eurosurveillance 15 November 2018.

Correlation of the composite index of AMR* with prevalence of antimicrobial use in acute care hospitals, EU/EEA countries and Serbia, 2016-2017

Adapted from Suetens C, et al. Eurosurveillance 15 November 2018; Plachouras D, et al. Eurosurveillance 15 November 2018 (unpublished results). 21

Patients

with a

least

one a

ntim

icro

bia

l (%

)Patients

with a

t le

ast

one a

ntim

icro

bia

l (%

)

Composite index of AMR (%)

*Percentage of isolates resistant to first-level antimicrobial resistance markers in healthcare-associated infections, i.e.:- Staphylococcus aureus resistant to meticillin (MRSA), - Enterococcus faecium and Enterococcus faecalis

resistant to vancomycin, - Enterobacteriaceae resistant to third-generation

cephalosporins, - Pseudomonas aeruginosa and Acinetobacter baumannii

resistant to carbapenems.

Multiple regression (preliminary results):% AMR significantly associated with:- Antimicrobial use (% of patients)- Presence of AHR dispensers at point of care

(% of beds)- Single(-room) beds (%)- FTE ICN (>0.4-0.5 IPCN/250 beds)- Case mix

Percentage antimicrobial use for prophylaxis in LTCFs

22

ECDC PPS indicators of WHO core components of infection prevention and control (IPC) programmes

Source: ECDC, 2018 (see ECDC point prevalence survey of healthcare-associated infections and antimicrobial use in European acute care hospitals. Protocol version 5.3. 23

WHO Core Component Description ECDC PPS hospital indicators

1Infection prevention and control (IPC) programme

An effective IPC programme in an acute care hospital must include at least: one full-time specifically trained IPC-nurse ≤ 250 beds; a dedicated physician trained infection control; microbiological support; data management support

FTE IPC nurses and doctors IPC plan and report approved by hospital CEO Number of blood cultures, stool tests for CDI Microbiology services during weekends

2 IPC guidelinesEvidence-based guidelines + education, training of relevant health care workers and monitoring of adherence with guidelines

Presence of guidelines, audit and checklist for prevention of PN, BSI, UTI, SSI and for antimicrobial stewardship (as part of multimodal strategy, in ICU and hospital-wide)

3 IPC education and trainingIPC education and training involves frontline staff, and is team- and task-oriented

Presence of training in prevention of PN, BSI, UTI, SSI and antimicrobial stewardship (as part of multimodal strategy, ICU and hospital-wide)

4 SurveillanceParticipating in prospective surveillance and offering active feedback, preferably as part of a network

Participation in ICU, SSI, CDI, AMR and AMC surveillance networks

Surveillance as part of multimodal strategy

5 Multimodal strategiesImplementing infection control programmes follow a multimodal strategy including tools such as bundles and checklists developed by multidisciplinary teams and taking into account local conditions

Presence of guideline, bundle, training, checklist, audit, surveillance, feedback for prevention of PN, BSI, UTI, SSI and for antimicrobial stewardship

6Monitoring/audit of IPC practices and feedback

Organising audits as a standardized (scored) and systematic review of practice with timely feedback

Number of hand hygiene observations Alcohol hand rub consumption Audit and feedback as part of multimodal strategy

7Workload, staffing and bed occupancy

To make sure that the ward occupancy does not exceed the capacity for which it is designed and staffed; staffing and workload of frontline health-care workers must be adapted to acuity of care; and the number of pool/agency nurses and physicians minimized

Bed occupancy at midnight FTE registered nurses, hospital-wide and ICU FTE nursing assistants, hospital-wide and ICU

8Built environment, materials and equipment for IPC at the facility level

Sufficient availability of and easy access to material and equipment and optimized ergonomics; adequate number of single rooms (preferably with private toilet facilities) and/or rooms suitable for patient cohorting for the isolation of suspected /infected patients, including those with TB and multidrug-resistant organisms, to prevent transmission to other patients, staff and visitors

Alcohol hand rub dispensers at point of care+ carriage of AHR bottles by health-care workers

Number of single rooms Number of single rooms with toilet and shower Number of airborne infection isolation rooms

Core component 1: Infection prevention and control nurses, FTE per 250 beds (hospitals) and availability of IPCN nurse in LTCFs

Acute care hospitals

*poor representativeness, **Norway 2017: national PPS protocol

**

*

*

Liechtenstein

Luxembourg

Malta

Non-visible countries

<0.50

0.50 to <0.75

0.75 to <1.00

1.00 to <1.25

>=1.25

No data

Not included

Infection preventionand control nurses(Median FTE/250 beds)

2016-2017 data are preliminary.

LTCFs

Core component 6. monitoring of practices:Alcohol hand rub consumption (L/1000 patient-days)

Source: ECDC PPSs in European acute care hospitals, 2011-2012 & 2016-2017 (preliminary, unpublished results). 25

2011-2012

*poor country representativeness, **Norway 2017: national PPS protocol.

2016-2017

**

*

*

Liechtenstein

Luxembourg

Malta

Non-visible countries

<10

10-19.9

20-29.9

30-39.9

>=40

No data

Not included

Alcohol hand rubconsumption(L/1000 patient days)

Core component 8: environment – Beds with alcohol hand rub dispensers at point of care (%)

**

*

*

Liechtenstein

Luxembourg

Malta

Non-visible countries

<10

10 to <20

20 to <50

50 to <90

>=90

No data

Not invited

Beds with AHR dispenserat point of care (%)

05

10

15

20

25

Me

dia

n A

HR

con

sum

ption

(L

/100

0 p

atie

nt-

da

ys)

<50% beds with AHR >=50% beds with AHR

<25% HCW >=25% HCW <25% HCW >=25% HCW

Core component 8: environment, isolation capacity –Beds in single rooms (%)

Source: ECDC PPSs in European acute care hospitals, 2011-2012 & 2016-2017 (preliminary, unpublished results). 27

2011-2012

**

*

*

Liechtenstein

Luxembourg

Malta

Non-visible countries

<5

5 to <10

10 to <20

20 to <30

>=30

No data

Not invited

Single-room beds (%)

2016-2017

*poor country representativeness, **Norway 2017: national PPS protocol.

Core component 8: environment, isolation capacity –Beds in single rooms (%)

Source: ECDC PPSs in European acute care hospitals and HALT-3 PPS in LTCFs, 2016-2017 (preliminary, unpublished results). 28

**

*

*

Liechtenstein

Luxembourg

Malta

Non-visible countries

<5

5 to <10

10 to <20

20 to <30

>=30

No data

Not invited

Single-room beds (%)

*poor country representativeness, **Norway 2017: national PPS protocol.

Acute care hospitals Long-term care facilities

2nd ECDC point prevalence survey (PPS) of healthcare-associated infections and antimicrobial use in European acute care hospitals, 2016-2017

Source: ECDC, 2018. 29

MRSA

Carb-R

kpn

VRE

CDI

3GC-R

eco3GC-R

kpn

ALERT

MDRO

Carb-R

aci

MRSA

guidance

CDI

guidance

CPE/CRE

guidance

ABS

guidance

IPC prog.

guidanceHand hygiene

guidance

Outcome

indicators

(HAI,

composite index

of AMR)Structure and

process indicators

(incl. antimicrobial

consumption)

Guidance

(directory of online

resources)

Hospital

indicators

(tbd)

IPC

SPIsHand

hygiene

ABS

SPIs

AMC

Thank you

30

Active HAI

ONSET OF HAI CASE DEFINITION

Day 3 onwards AND Meets the case definition on the dayof surveyOR

Day 1 (day of admission) or day 2: SSI criteria met at any time after admission (including previous surgery 30 d/ 90 d)

ORORDay 1 or day 2 AND patient

discharged from acute care hospital in preceding 48 hours

ORDay 1 or day 2 AND patient discharged from acute care hospital in preceding 28

days if CDI present

Patient is receiving treatment* AND HAI has previously met the case definition between day 1 of treatment and survey day

OR

Day 1 or day 2 AND patient has relevant device inserted on this admission prior

to onset

OR

Day 1 or day 2 after birth for neonates

Representativeness

Optimal:• systematic random sample of 25–60 hospitals (depending on hospital size in the

country) and inclusion of at least 75% of these hospitals;

• inclusion of ≥75% of all acute care hospitals or occupied beds in country, required sample size achieved

Good:• < 75% of hospitals, required sample size achieved

• required sample size not achieved, but inclusion of ≥75% of all acute care hospitals or occupied acute care hospital beds in the country.

Poor: • 5-25 hosp. in countries with >25 hospitals, required sample size not achieved;

• < 5 hosp. in countries with > 5 hospitals, inclusion of 50–75% of all acute care hospitals or occupied acute care hospital beds in the country.

Very poor:• inclusion of < 5 hospitals and < 50% of all acute care hospitals and < 50% of all

occupied acute care hospital beds.

Sample representativeness in ECDC PPS, 2011-2012

Liechtenstein

Luxembourg

Malta

Non-visible countries

Very poor

Poor

Good

Optimal

Not included

Optimal or good

representativeness:

25/33 (76%)

countries

General Guidelines

All patients present on the ward at 8am and not discharged at the time of survey should be included

Complete each ward within one day

Complete the hospital within 2-3 weeks

Units where patients are admitted for elective procedures on a Monday should preferably be surveyed between Tuesday and Thursday

Included/Excluded?INCLUDED

• Hospitals

• All acute care hospitals/ facilities

• All sizes

• Wards

• All hospital wards, both acute and long-term care (including psychiatric wards & neonatal units)

• Include wards attached to A&E/ ER departments where patients are monitored >24 hours

• Patients

• All admitted to ward before 8 a.m. & not discharged at the time of the survey

EXCLUDED

• Hospitals

• Long term care facilities without acute care beds

• Wards

• accident & emergency department

• Patients

• Day cases including: same day treatment or surgery, outpatient, or emergency room (A&E) episode, renal dialysis day attenders

Inclusion and exclusion criteria by 8am rule

Legend:

W1: ward 1

W2: ward 2

Include those who are temporarily off the ward for investigations, procedures or on Patient Administration system but at home for a number of hours

Include all patients admitted to the ward before or at (≤) 8:00 AM and not discharged from the ward at the time of the survey

Distribution of PPS coordination activities (estimated % of total patient-days)

13%

5%

12%

9%

11%9%

8%

6%

11%

9%

7%1%

Prepare PPS tools/materials, excl. translation

Recruit/select. hospitals, nat. denom data

Prepare training, excl. translation

Translation

Delivering training course(s)

Helpdesk

Data collection in hosp. by national PPS team

Hospital data entry by national PPS team

Data management/prepare national database

Data quality check, feedback to hospitals

Prepare national data for TESSy and upload

Other

National PPS coordination: PPS workload

AT

BE

BG

CZDK EE

ES

FR

HR

HU

IE

ISLT

MT

NOPL

PT

SE

SK

UK-NI

UK-SC

UK-WA

0

100

200

300

400

500

Est

imate

d n

of

pers

on-d

ays

PPS c

oord

ination

0 5 10 15N of staff involved in PPS coordination

• Mean n of staff: 4.8 (median: 4 [IQR 2-7])

• Mean n of person-days: 116 (median: 59 [IQR 32-131])

Time span of data collection in hospitals by country (days) – Start date End date PPS

AT

BE

BG

CY

CZ

DE

DK

EE

ES

FI

FR

GRHR

HU

IE

IS

IT

LT

LU

LV

MTNL

NO

PL

PT

RO

SE

SI

SK

UK-EN

UK-NI

UK-SCO

UK-WLS

05

01

00

150

Dura

tion

natio

na

l P

PS

(d

ays)

0 20 40 60N of hospitals

Median 50 days

Data collection days per 100 patients*

02

.75

10

15

20

N o

f da

ys/1

00

patie

nts

ATBE

BGCY

CZDE

DKEE

ENES

FIFR

GRHR

HUIE

ISIT

LTLU

LVMT

NINL

NOPL

PTRO

SCSE

SISK

WA

median

*excluding data entry and checking

European Prevalence Survey of Healthcare-Associated Infections and Antimicrobial Use

Form A. Standard protocol: Patient data, Antimicrobial (AM) use and HAI data

HAI 1 HAI 2

Case definition code

Relevant device (3) O Yes O No O Unknown O Yes O No O Unknown

Present on admission O Yes O No O Yes O No

Date of onset (4) / / / /

Origin of infectionO current hospital O other

hospital O other origin/ unk

O current hospital O other

hospital O other origin/ unk

HAI associated to

current wardO Yes O No O Unknown O Yes O No O Unknown

If BSI: source (5)

MO code

AMR PDR MO code

AMR PDRAM (6) SIR AM (6) SIR

Microorganism 1

Microorganism 2

Microorganism 3

Hospital code [__________] Ward name (abbr.)/Unit Id [__________]

Survey date: ___ / ___ / 20___ (dd/mm/yyyy)

Patient Counter: [_________________________________]

Age in years: [____] yrs; Age if < 2 year old: [_____] months

Sex: M / F Date of hospital admission: ___ / ___ / _____

Consultant/Patient Specialty: [__________]

Surgery since admission:

O No surgery O Minimal invasive/non-NHSN surgery

O NHSN surgery -> specify (optional): [__________] O Unknown

McCabe score:

O Non-fatal disease O Ultimately fatal disease

O Rapidly fatal disease O Unknown

If neonate, birth weight: [______] grams

Central vascular catheter: No Yes Unk

Peripheral vascular catheter: No Yes Unk

Urinary catheter: No Yes Unk

Intubation: No Yes Unk

Patient receives antimicrobial(s)(1): No Yes

Patient has active HAI(2): No Yes

(1) At the time of the survey, except for surgical prophylaxis 24h before 8:00 AM on the day

of the survey; if yes, fill antimicrobial use data; if patient receives >3 antimicrobials, add a

new form; (2) [infection with onset ≥ Day 3, OR SSI criteria met (surgery in previous

30d/90d), OR discharged from acute care hospital <48h ago, OR CDI and discharged from

acute care hospital < 28 days ago OR onset < Day 3 after invasive device/procedure on D1

or D2] AND [HAI case criteria met on survey day OR patient is receiving (any) treatment

for HAI AND case criteria are met between D1 of treatment and survey day]; if yes, fill HAI

data; if patient has > 2 HAIs, add new form.

Patient data (to collect for all patients)

IF YES

dd / mm / yyyy

X

(3) relevant device use before onset infection (intubation for PN, CVC/PVC for BSI, urinary catheter for UTI);

(4) Only for infections not present/active on admission (dd/mm/yyyy); (5) C-CVC, C-PVC, S-PUL, S-UTI, S-DIG,

S-SSI, S-SST, S-OTH, UO, UNK; (6) AB: tested antibiotic(s): STAAUR: OXA+ GLY; Enterococci: GLY;

Enterobacteriaceae: C3G + CAR; PSEAER and Acinetobacter: CAR; SIR: S=sensitive, I=intermediate,

R=resistant, U=unknown; PDR: Pan-drug resistant: N=no, P=possible, C=confirmed, U=Unknown

Antimicrobial

(generic or

brand name)

Ro

ute

Ind

icatio

n

Dia

gn

os

is

(site

)

Reaso

n in

no

tes

Date

sta

rt

AM

Ch

an

ged

?

(+ re

aso

n)

If ch

an

ged

:

Date

sta

rt

1stA

M

Dosage per day

Nu

mb

er

of d

oses

Strength

of 1 dose

mg

/g/IU

/ / / /

/ / / /

/ / / /

Route: P: parenteral, O: oral, R: rectal, I: inhalation; Indication: treatment intention for community (CI), long-

term care (LI) or acute hospital (HI) infection; surgical prophylaxis: SP1: single dose, SP2: one day, SP3: >1

day; MP: medical prophylaxis; O: other; UI: Unknown indication; Diagnosis: see site list, only for CI-LI-HI;

Reason in notes: Y/N; AM Changed? (+ reason): N=no change; E=escalation; D=De-escalation; S=switch IV

to oral; A=adverse effects; OU=changed, other/unknown reason; U=unknown; If changed, date start 1st AM

given for the indication; Dose/day e.g. 3 x 1 g; g=gram, mg=milligram, IU=international units, MU=million IU

Patient-based data (standard)

ALL PATIENTS

European Prevalence Survey of Healthcare-Associated Infections and Antimicrobial Use

Form H1. Hospital data 1/3

Hospital code:

Survey dates: From __ / __ /____ To: __ / __ / ____

dd / mm / yyyy dd / mm / yyyy

Hospital size (total number of beds)

Number of acute care beds

Number of ICU beds

Exclusion of wards for PPS? No

Yes, please specify which ward types were excluded:

_______________________________________________

Total number of beds in included wards:

Total number of patients included in PPS:

Hospital type Primary Secondary Tertiary

Specialised, specify : ______________________

Hospital ownership: Public Private, not-for-profit

Private, for profit Other/unknown

Number

Year

data

Inc./

Total (1)

Number of discharges/admissions in yearInc Tot

Number of patient-days in year

Alcohol hand rub consumption liters/year Inc Tot

N observed hand hygiene opportunities/year Inc Tot

Number of blood culture sets/year Inc Tot

Number of stool tests for CDI/year Inc Tot

Number of FTE infection control nurses

Inc TotNumber of FTE infection control doctors

Number of FTE antimicrobial stewardship

Number of FTE registered nurses

Inc TotNumber of FTE nursing assistants

Number of FTE registered nurses in ICU

Number of FTE nursing assistants in ICU

N of airborne infection isolation rooms

PPS Protocol: Standard Light

Is the hospital part of a national representative sample of hospitals ? No Yes Unknown

(1) Data were collected for Included wards only (Inc , = recommended) or for the total

hospital (Tot); if all wards were included in PPS (Inc=Tot), mark “Inc”; N=Number

Hospital is part of administrative hospital group (AHG):

No Yes if yes:

Data apply to: Hospital site only All hospitals in AHG

AHG code: AHG type: Prim Sec Tert Spec

N of beds AHG: Total Acute care beds

Hospital data 1/3 p.10