Point prevalence survey of healthcare-associated infections and antimicrobial use in European acute care hospitals : ECDC PPS validation protocol version 3.1.2.
Date: 2019-01-11
Institutions: European Centre for Disease Prevention and Control
Subjects: antimicrobial resistance, data collection, disease prevention, health care, health care system, infectious disease, medical institution

TECHNICAL REPORT

Point prevalence survey of 
healthcare-associated infections 
and antimicrobial use in 
European acute care hospitals

ECDC PPS validation protocol version 3.1.2

www.ecdc.europa.eu

ECDC TECHNICAL REPORT 

Point prevalence survey of healthcare-
associated infections and antimicrobial 
use in European acute care hospitals 
ECDC PPS validation protocol version 3.1.2 

 
 
Suggested citation: European Centre for Disease Prevention and Control. Point prevalence survey of 
healthcare-associated infections and antimicrobial use in European acute care hospitals – ECDC PPS validation 
protocol version 3.1.2. Stockholm: ECDC; 2019. 

Stockholm, January 2019 

PDF 
ISBN: 978-92-9498-276-6 
DOI: 10.2900/444036 
Catalogue number: TQ-01-19-007-EN-N 

© European Centre for Disease Prevention and Control, 2019 

Cover picture: © iStock 

Reproduction is authorised, provided the source is acknowledged. 

For any use or reproduction of photos or other material that is not under the EU copyright, permission must be 
sought directly from the copyright holders. 

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TECHNICAL REPORT 

Point prevalence survey of healthcare-associated infections and antimicrobial use in acute care hospitals 

Contents 
Abbreviations ............................................................................................................................................... iv 
Background and objectives ............................................................................................................................. 1 
Conditions for participation ............................................................................................................................. 1 
Methodology ................................................................................................................................................. 1 
Timing and blinding .................................................................................................................................. 1 
Sample size .............................................................................................................................................. 2 
Selection of hospitals, wards and patients ................................................................................................... 2 
Composition of the validation team (VT) ..................................................................................................... 3 
Data collection ............................................................................................................................................... 3 
Data collection process .............................................................................................................................. 3 
Which data should be collected? ................................................................................................................ 4 
Hospital data ............................................................................................................................................ 4 
Ward data ................................................................................................................................................ 6 
Data entry and transfer ................................................................................................................................ 11 
References .................................................................................................................................................. 12 

Figures 

Figure 1. Variation of the confidence interval around a sensitivity of 80% according to the number of patients 
included in the validation sample, for an outcome with prevalence of 7% and for an outcome with prevalence of 
2%, with 10% of false positives ...................................................................................................................... 2 

Tables 
Table 1. Sample form of a single patient list to be used by primary and validation PPS data collectors ................... 4 

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TECHNICAL REPORT 

Abbreviations 

FTE 
HAI 
HAI-Net 
ICU 
PPS 
TESSy 

VT 

Full-time equivalent 
Healthcare associated infections 
ECDC-coordinated network for the surveillance of healthcare-associated infections 
Intensive care unit 
Point prevalence survey 
The European Surveillance System (ECDC’s web-based data reporting system for the 
surveillance of communicable diseases) 
Validation team 

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TECHNICAL REPORT 

Point prevalence survey of healthcare-associated infections and antimicrobial use in acute care hospitals 

Background and objectives 

In accordance with article II.8.c of Council Recommendation 2009/C 151/01 of 9 June 2009 on patient safety, 
including the prevention and control of healthcare-associated infections (HAIs) [1], ECDC developed a methodology 
for repeated point prevalence surveys (PPS) of HAIs and antimicrobial use in acute care hospitals [2]. The main 
objective of the ECDC PPS of HAIs and antimicrobial use in acute care hospitals is to estimate the total burden of 
HAIs and antimicrobial use in acute care hospitals in the EU. 

During the first EU-wide PPS in 2011–2012, a validation protocol developed by ECDC with Member State experts 
was tested in 10 countries [3]. After the 2011 pilot study, the protocol was adapted [4] and implemented by five 
countries in 2012. The results of these five validation surveys showed that a large number of HAIs were not 
detected or reported by hospital PPS staff (false negatives), resulting in a low sensitivity (country average 71.9%). 
False positives, or low specificity, was less of a problem, except in the country that reported the highest 
prevalence. The results suggested that the observed large differences in HAI prevalence between countries 
(ranging from 2.3% to 10.8%) were in reality less important because of low sensitivity and high specificity in low-
prevalence countries and high sensitivity and low specificity in high prevalence countries [5]. The results also 
showed that performing validation during a national PPS is crucial in order to interpret PPS results, in particular for 
the main outcome of such a survey, i.e. to estimate the burden of HAIs in Europe. 

It was therefore strongly recommended by the ECDC Advisory Forum that all countries must perform validation 
studies during future prevalence surveys. Accordingly, all Member States were expected to perform a validation 
study of their national PPS during the second ECDC PPS in 2016–2017. The objectives of the validation study are to 
assess the validity, reliability and inter-country comparability of the data collected during the national/regional PPS 
of HAI and antimicrobial use in acute care hospitals, and to assess the data accuracy of selected process and 
structure indicators at the hospital level. 

The current protocol version 3.2.1 is the ECDC PPS validation protocol used during the second EU-wide PPS of HAIs 
and antimicrobial use in 2016–2017. This protocol version is an accompanying document to the ECDC protocol for 
the point prevalence survey of healthcare-associated infections and antimicrobial use in European acute care 
hospitals version 5.3 [2]. 

Conditions for participation 

• 

• 

• 

• 

The PPS validation study needs to be performed at the same time as a national or regional PPS. The 
national/regional PPS is hereafter referred to as the primary PPS. 
The national PPS coordinating centre should train and coordinate a national/regional PPS validation team 
(VT). 
The validation study should be performed in a minimum sample of five randomly selected hospitals and 
re-examine 250 patients (50 patients per hospital). In order to obtain representative data at the 
national/regional level, a sample of 25 hospitals and 750 patients (30 patients re-examined per hospital) is 
recommended. If the total number of hospitals included in the primary PPS is five or lower, all hospitals 
should be validated (50 patients per hospital). 
Validation data collected by the national/regional validation team should be entered in the software 
provided by ECDC (HelicsWin.Net) or in another software compatible with the current protocol. Data should 
be made available to ECDC in HelicsWin.Net or TESSy format, together with the primary PPS data collected 
by the hospital PPS staff. The specifications of the data format and file names are described elsewhere. 

Methodology 

Timing and blinding 
Based on the results of the pilot PPS validation study in 2011 [3], it is recommended to perform the validation PPS 
survey on the same day as the primary PPS, at the same time or shortly after the primary data collection, using 
blinded data collection. The VT member(s) is/are not allowed to look at the primary PPS forms during the data 
collection. Exceptionally, retrospective validation is allowed within one week after primary PPS data collection. 
Participants should also specify if data collection was unblinded (e.g. if blinded data collection was impossible). 
Data on timing and blinding should be reported at the ward level. 

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Point prevalence survey of healthcare-associated infections and antimicrobial use in acute care hospitals 

TECHNICAL REPORT 

Sample size 
The minimum sample size is five hospitals and 250 patients (50 patients re-examined per hospital). If the total 
number of hospitals included in the primary PPS is five or lower, all hospitals should be included. 

In order to obtain representative data at the national/regional level, a sample of 25 hospitals and 750 patients (30 
patients re-examined per hospital) is recommended. Countries preferring better precision of the sensitivity at the 
national level may consider including more patients. For example, a sample size of 2 000 patients in at least 25 
hospitals would result in precision of approximately +/-5% around an estimated sensitivity of 80% for a HAI 
prevalence of 7% (Figure 1). 

Figure 1. Variation of the confidence interval around a sensitivity of 80% according to the number of 
patients included in the validation sample, for an outcome with prevalence of 7% and for an 
outcome with prevalence of 2%, with 10% of false positives 

y
t
i
v
i
t
i
s
n
e
S

100%

90%

80%

70%

60%

50%

40%

Se

LL (Pr 7%)

UL (Pr 7%)

LL (Pr 2%)

UL (Pr 2%)

250

500

750 1000 1250 1500 1750 2000

Se: sensitivity 
LL: 95% confidence interval lower limit 
UL: 95% confidence interval upper limit 
Pr: prevalence percentage 

Selection of hospitals, wards and patients 
Hospitals taking part in validation should be selected randomly from the list of hospitals participating in the primary 
PPS, e.g. using systematic sampling after sorting the hospital list by hospital type and size. 

Wards for validation should be selected among wards in which the primary PPS is done on the same day. 

There are three possible methods for the sampling of wards and patients for the validation survey: 

• 

Wards with an expected higher HAI prevalence (e.g. intensive care units – ICU; HIPREV). This method is 
referred to as purposive sampling and results in HAI oversampling. All patients of a ward should be 
included. 
Advantages: 
− 

best precision of the validation results (specificity and sensitivity) due to higher number of HAI 
cases, therefore recommended method; and 
can be used for validation of ‘standard’ (patient-based) and ‘light’ (unit-based) data. 

− 
Disadvantages: 
− 

− 

requires careful planning of the validation visit on a day that at least one high-prevalence ward is 
surveyed for the primary PPS 
availability of HAI-related data in high-prevalence wards may not be representative of data 
availability in the entire hospital. 

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TECHNICAL REPORT 

Point prevalence survey of healthcare-associated infections and antimicrobial use in acute care hospitals 

• 

• 

easier planning; and 
can be used for validation of ‘standard’ (patient-based) and ‘light’ (unit-based) data. 

Wards included in the PPS on the day of the validation study (until the required number of validation 
records per hospital is obtained) without purposive sampling (PPSDAY), i.e. the choice of the validation day 
did not take into account the inclusion of high-prevalence wards. The order/choice of the wards can follow 
the normal planning of the primary PPS. All patients of a ward should be included. 
Advantages: 
− 
− 
Disadvantages: 
− 
Random selection of patients from all wards included in the primary PPS (RANDOM). 
Advantages: 
− 
Disadvantages: 
− 

requires several days of (same-day) validation and collecting more ward data (more 
labour-intensive) 
cannot be used if primary PPS data were collected using ‘light’ (unit-based) protocol option; and 
lower precision of validation results than in purposive sampling because of a lower number of HAIs. 

produces the most representative results. 

lower precision of validation results. 

− 
− 

Composition of the validation team (VT) 
The PPS coordinating centre should compose and train a national/regional VT. VT surveyors will visit the selected 
hospitals and do a repeated collection of basic demographic, HAI and antimicrobial use data for the patients 
included in the validation study, applying the exact definitions of the ECDC PPS protocol (‘gold standard’ data 
collection). Hospital staff do not participate in the validation process/data collection as such. 

The national/regional VT should be composed of at least one senior expert with experience in HAI surveillance 
(especially case definitions). Less experienced surveillance staff or clinicians who were recruited and trained can 
join the VT to speed up the data collection process. The VT should ideally be the same for all validated hospitals to 
ensure consistency of the gold standard. If large numbers of hospitals are validated with different validation teams, 
the training of VT members should ensure that all teams perform the validation in the same way. It is 
recommended to test the inter-rater reliability (IRR) of VT members prior to the validation survey. Standard case 
studies to perform this IRR testing can be obtained from ECDC by contacting HAI-Net 
(HAI-Net@ecdc.europa.eu). 

In case the primary data collection in all included hospitals is performed by the national PPS coordination team 
(e.g. in smaller countries), the national team should be composed of at least two data collectors so that data 
collector A can repeat the primary PPS data collection performed by data collector B and vice versa. In this case, 
only IRR can be calculated (kappa statistic) since there is no gold standard. Alternatively, the validation survey in 
these countries may be performed by an external expert trained for this purpose. 

Data collection 

Data collection process 
The estimated time needed for data collection is on average approximately 10 minutes per validated patient or 8.3 
person-hours for 50 patients. The recommended method for data collection by the validation team is blinded data 
collection on the same day as the primary PPS, so that the availability of the data is as similar as possible [3]. 

In order to ensure that the same patients are included in the primary and validation survey, it is recommended to 
prepare a list of eligible patients used by both primary and validation PPS data collectors. The list should also 
contain the anonymised patient counter (number) that will be entered in the primary database. In addition, it is 
useful to add the time when the data collection for each patient (in the primary survey) was completed on the list 
so that the validation team can verify the availability of information at the time of the primary survey. This also 
applies in the case of validation of primary data collected using the ‘light’ (unit-based) protocol option, since 
surveyors should go through the notes for every patient in both protocol options. Such a list contains patient 
identifiers and should therefore never leave the hospital. 

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Point prevalence survey of healthcare-associated infections and antimicrobial use in acute care hospitals 

TECHNICAL REPORT 

Table 1. Sample form of a single patient list to be used by primary and validation PPS data collectors 

Primary data collector should collect these data for each patient on ward. 

THIS SHEET SHOULD NOT LEAVE THE HOSPITAL 

FORM REQUIRED FOR DATA VALIDATION 

In order to cross validate patient level data, please pre-number each patient on the ward in the column 
'Patient Counter', record unique hospital patient number/identifier and record the end time of primary data 
collection for each patient. The patient counter for these patients should be manually filled in on the database. 
End time of data collection (primary PPS) 
Patient counter (primary PPS) 

Hospital patient identifier 

Sample form to pre-assign patient counters to PPS patients in the primary data collection (these should be entered manually in 
the software) and to ensure that the same patients are included in the primary and validation surveys. 

The validation results should not be cross-checked with the results of the primary PPS nor discussed with the 
hospital PPS data collector(s) to avoid bias due to possible corrections of the primary data by the hospital PPS staff 
following a discussion with the validation team. The results of the validation study should therefore not be 
communicated to the hospital PPS staff on the day of the validation survey. The primary PPS data should never be 
corrected following the findings of the VT as this would completely invalidate the validation study results. 

Which data should be collected? 
Data to be collected in the validation study can be summarised as follows: 

• 
• 
• 

data regarding the methodology of validation at hospital and ward level 
repeated data collection of selected variables at the patient level; and 
data accuracy on selected structure and process indicators at the hospital level. To perform the assessment 
of the selected indicators, it is recommended to ask the hospital PPS staff to collect the indicator data prior 
to the validation visit. 

Hospital data 

Definition of variables 

PPS survey variables, validation methods 

• 

• 

• 

Hospital code primary PPS: hospital code used for primary PPS data to be entered in validation tab (sub-
screen) of hospital survey screen in HelicsWin.Net. 
Hospital code validation survey: use primary PPS hospital code with ‘v’ added to it. Hospital code should be 
defined in hospital definition screen of HelicsWin.Net. 
Start date primary PPS: start date of primary PPS in this hospital to be entered in the validation tab of 
hospital survey screen in HelicsWin.Net. 

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TECHNICAL REPORT 

Point prevalence survey of healthcare-associated infections and antimicrobial use in acute care hospitals 

• 

• 

• 

• 

• 

Validation survey dates: From ... to ...: start and end dates of validation survey to be entered in general tab 
of hospital survey screen in HelicsWin.Net (‘Survey start date’ and ‘Survey end date’).  Start and end date of 
validation survey for one hospital will be the same, particularly if VT is composed of more than one person. 
Hospital size: total number of beds in hospital as re-assessed by VT – general tab of hospital survey screen; 
mandatory field in HelicsWin.Net. 
Protocol validation survey: validation survey must be carried out using the ‘standard’ protocol – enter 
‘standard’ in ‘PPS Protocol’ field of general tab of the hospital survey screen in HelicsWin.Net. 
Protocol primary PPS: protocol option used for primary PPS in the hospital (‘standard’ or ‘light’) – enter in 
validation tab of hospital survey screen in HelicsWin.Net. 
Sampling validation survey: sampling design used for validation survey – enter in the validation tab of 
hospital survey screen in HelicsWin.Net. 
− 

Wards included on day of visit only, high prevalence wards privileged. Recommended method. Order 
in which wards are visited and/or choice of validation day(s) are dependent on expected prevalence 
of HAI in these wards (e.g. ICUs – haematology) to improve precision of validation results (purposive 
sampling). 
Wards included on day of visit only, no selection of wards. Order in which wards are visited and 
choice of validation day(s) independent on expected prevalence of HAI in these wards, no ‘HAI 
oversampling’/purposive sampling. 
Random selection of patients in all wards included in primary PPS. This method, which yields the 
most representative sample of patients, can only be applied if hospital is visited on all primary PPS 
days for same-day validation or in combination with retrospective validation within one week after 
primary PPS (not recommended). Timing of validation should be specified for each ward at ward PPS 
data level. 
Other (please specify in comments): other selection method of wards – describe in comments field. 

− 

− 

− 

Data accuracy of selected structure and process indicators (interview of hospital 
PPS coordinator) 

• 

• 

• 

• 

Are hospital indicator data reported for the same hospital population as HAI, antimicrobial use and 
denominator data? 
− 

Yes: Only reply yes if all indicator data, HAI, antimicrobial use and denominator data and risk factors 
were collected for the same population, e.g. as recommended: all wards in hospital except day cases 
for one hospital site (not for the entire administrative hospital group). 
Partially, please specify: Specify which indicator data were not available for the same population as 
the main PPS (HAI/AM/patient/denominator) data and which population they were reported or 
estimated. 
No, please specify: All indicator data concern another hospital population, e.g. the administrative 
hospital group, while the main PPS data were collected and reported for a single hospital site. 
Specify for which population the indicator data were reported or estimated. 

− 

− 

PHADIS: pharmacy, quantity dispensed/delivered to wards in one year period 
PHAPUR: pharmacy, quantity purchased by hospital in one year period 
WARD: wards, quantity actually used in one year period 
OTH: other, please specify (in comment field); and 
NA: data not available. 

Alcohol hand rub consumption, data source: Who provided the data on alcohol hand rub consumption and 
what do they represent? 
− 
− 
− 
− 
− 
Correct reporting of full-time equivalents (FTEs): Assess accuracy of the reported FTEs (infection control 
staffing levels, antimicrobial stewardship, registered nurses, nursing assistants) by checking the following 
questions: 
− 
− 
− 

Correct reporting of partial FTEs ? (e.g. 10% of full-time = 0.1 FTE) 
FTE antimicrobial stewardship included in job description? 
Correct distinction between FTEs for infection prevention and control (IPC) and antimicrobial 
stewardship? 

Other validation team comments/data quality issues: Free text. Other validation team comments on data 
quality issues at the hospital level, such as: 
− 

factors that may have influenced the reported quantity of alcohol hand rub, e.g. how much alcohol 
hand rub is used for other purposes than hand hygiene, use of other hand hygiene products than 
alcohol hand rub, etc. 
deviations from ECDC PPS protocol, e.g. different HAI case definitions or inclusion criteria 
existence of disincentives or incentives for reporting HAIs; and 
other elements that should be taken into account when interpreting data for this hospital. 

− 
− 
− 

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Point prevalence survey of healthcare-associated infections and antimicrobial use in acute care hospitals 

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European Prevalence Survey of Healthcare-Associated Infections and Antimicrobial Use 
Form VTH. Validation study. Hospital data.

Hospital code primary PPS: 

Hospital code validation survey: 

Add a  s ma l l  'v' to the pri ma ry hos pi ta l  code

Protocol option (standard/light)

STD

Va l i da ti on s urvey MUST us e s ta nda rd

Start date primary PPS

Start date validation survey:

End date validation survey:

Hospital size

___/___/___

___/___/___

___/___/___

Hos pi ta l  s i ze a s  re-a s s es s ed by VT

Sampling of wards for validation survey

Wards on PPS day, high prevalence wards privileged

  (recommended)

Wards on PPS day, no selection of wards

All PPS wards, random patient selection

Other method, please specify: 

   ________________________________________________________

Are the reported numbers of the hospital indicator data for the same hospital population as HAI and AM use data?

    O  Yes  O  Partially, please specify:  O  No, please specify:

Alcohol hand rub (AHR) consumption/year represents:

Qua nti ty di s pens ed to wa rds  i n one yea r peri od

Qua nti ty purcha s ed by hos pi ta l  i n one yea r peri od

Qua nti ty a ctua l l y us ed i n the wa rds  i n one yea r peri od

Other, pl ea s e s peci fy:  _____________________________________

Are FTEs (full-time equivalents) correctly reported? 

Correct interpretation of the term FTE? (e.g. 10% of full-time = 0.1 FTE)                                                                O  Yes          O  No

FTE Antimicrobial Stewardship: included in job description?                                                                                O  Yes          O  No

Correct distinction between FTE Infection Control (IPC) and antimicrobial stewardship?                               O  Yes          O  No

Other validation team comments/data quality issues for the current hospital:

Ward data 

Ward PPS and validation methodology 
• 

• 

• 

Ward name (abbreviated)/unit ID: abbreviated name of validated hospital ward. Ensure spelling is exactly 
the same as in primary PPS data. To be entered in the general tab of the ward PPS data screen in 
HelicsWin.Net. 
Ward specialty: main ward specialty (≥ 80% of patients requiring this specialty) as re-assessed by VT. If 
lower than 80%, choose mixed ward (MIX).  GER=geriatrics, GO=gynecology/obstetrics, ICU=intensive 
care, LTC=long-term care, MED=medicine, MIX=mixed, NEO=neonatal, OTH=other, PED=paediatric, 
PSY=psychiatry, RHB=eehabilitation, SUR=surgery. Allows combination with patient specialty to refine 
specialties, e.g. paediatrics: ward specialty PED + patient specialty: PEDICU=paediatric ICU, 
NEOICU=neonatal ICU, SURCARD=paediatric cardiac surgery). A ward with healthy newborns either must 
be allocated to GO (GOBAB) when located in obstetrics or PED (PEDBAB) if located in paediatrics. To be 
entered in the general tab of the ward PPS data screen in HelicsWin.Net. 
Ward validation survey date: date validation survey was carried out in this ward. To be entered in general 
screen of ward PPS data screen in HelicsWin.Net. It is recommended to collect data from a single ward on 
the same day. 

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TECHNICAL REPORT 

Point prevalence survey of healthcare-associated infections and antimicrobial use in acute care hospitals 

• 

• 

Ward primary PPS date: date primary survey was carried out in this ward. To be entered in the validation 
screen of the ward PPS data screen in HelicsWin.Net. 
Patients included in the validation survey: method of selection of patients in the ward. To be entered in 
validation screen of ward PPS data screen in HelicsWin.Net. 
− 
− 

All eligible patients included: all eligible patients were included for this ward. Recommended. 
Selection of patients: selection of eligible patients made, e.g. a random selection of x patients in y 
(systematic sampling) or not all patients validated. Specify reason for patient selection in ward VT 
comments field. 

Note: If primary PPS was performed using the ‘light' (unit-based) protocol, all patients in ward should be validated 
with or without HAI and/or antimicrobial use. Selection of patients is not allowed for validation of ‘light’ protocol. 

• 

• 

• 

• 

Timing: Timing of validation survey in this ward. To be entered in validation screen of ward PPS data form 
in HelicsWin.Net. The first two options (same day as primary PPS) are recommended. Retrospective 
validation in the week after primary PPS (third option) is not recommended, but allowed. 
− 

Simultaneous (same day, same time): validation done at same time as primary PPS collection. To 
ensure blinded data collection, communication between VT member(s) and primary PPS data 
collector(s) should be minimised. Select this answer if only part of data collection occurred 
simultaneously. 
Same day, after PPS: validation done on same day as the primary PPS collection, but after primary 
PPS completely finalised. 
Retrospective (PPS <+/- 1 week ago):primary PPS data collection occurred less than one week ago, 
most patients are still in the hospital. Not recommended. 
Other: other timing of validation (e.g. > 1 month after the primary PPS) not recommended. Specify 
in comments field which timing was chosen and why. 

− 

− 

− 

Validation method. Blinded or unblinded data collection. To be entered in validation screen of ward PPS 
data form in HelicsWin.Net. Recommended method is blinded. If data collection was considered un-blinded, 
specify why in comments field. 
− 
Blinded: HAI or antimicrobial use status of patient not disclosed to VT before start of data collection. 
− 
Unblinded: HAI or antimicrobial use status of patient disclosed to VT before start of data collection. 
Who collected primary PPS data in this ward? ICN=infection control nurse; ICP=infection control physician 
or equivalent; WN=ward nurse; WP=ward physician; IDP=infectious disease physician; MIC=hospital 
microbiologist; MDST=MD specialist trainee; PHA=hospital pharmacist; LINK=infection control link nurse; 
DNU=data nurse; AID=nurse aid/nursing assistant; MDSTU=MD students; NUSTU=nursing students; 
PSQUAL=hospital patient safety or quality of care staff; CONAT=national PPS coordination staff; 
COREG=regional PPS coordination staff; OTH=other (specify). In HelicsWin.Net, data collectors should be 
defined in hospital survey screen. This will create a dropdown list from which the data collector for the 
current ward can be selected in the ward PPS data screen. 
Validation team comments for this ward: other validation team comments, data quality issues at the ward 
level (e.g. deviations from ECDC PPS protocol) or elements that should be taken into account when 
interpreting the data for this ward (e.g. existence of disincentives or incentives for reporting HAIs). Specify 
reasons for deviations from recommended validation method here. 

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European Prevalence Survey of Healthcare-Associated Infections and Antimicrobial Use 
Form VTW. Validation study. Ward data.

Hospital code

Ward name (abbreviated) /Unit  ID

Exactly the same ward code/ID as in primary PPS data

Ward Specialty :     O PED   O NEO   O ICU   O MED   O SUR  O GO   O GER   O PSY   O RHB   O LTC   O OTH   O MIX

Ward validation survey date

___/___/___

Ward primary PPS  date              ___/___/ ____

Patients included in the ward validation survey:  O All eligible patients      O Selection of patients 



(Note: selection of patients not allowed if primary PPS used LIGHT protocol)

Validation timing:   O Simultaneous   O Same day after PPS     O Retrospective (Within one week)    O Other

Validation method:   O Blinded  O Unblinded  (not recommended)

Who collected the primary PPS data in this ward? (more than one answer possible)

O Infection control nurse   O Infection control physician   O Ward nurse   O Ward physician/Consultant

O Infectious diseases physician   O Hospital microbiologist   O MD specialist trainee   O Hospital pharmacist

O Infection control link nurse   O Data nurse   O Nurse aid   O MD student   O Nurse student 

O National PPS coordination staff   O Regional PPS coordination staff   O Other, specify: ____________________

Other validation team comments for the current ward:

Patient, HAI and antimicrobial use 
Files for all patients present at 8:00 am on the PPS day need to be re-examined (with or without 
HAI/antimicrobial). For each patient, collect and enter the following data: 

• 

• 

• 

• 

• 
• 

• 
• 

• 

• 

Hospital code: hospital identifier/code assigned by national/regional PPS coordinating centre; unique code 
per surveillance/PPS network. 
Ward name (abbr.)/Unit ID:. abbreviated name of validated hospital ward. Ensure spelling is exactly the 
same as in primary PPS data. 
Patient Counter validation: patient counter for this patient in the validation survey. Not necessarily be the 
same as patient counter of primary PPS (which is collected in a separate variable). Enter in main field 
‘Patient Counter’ on the general screen of the patient screen in HelicsWin.Net. 
Patient Counter primary PPS: patient counter (not internal patient identifier) of patient for which data are 
validated. This field is mandatory for validation because it is needed to make the link with primary PPS 
patient data. Enter in field ‘Patient Counter Primary PPS’ on validation tab (sub-screen) of patient screen in 
HelicsWin.Net. If this field is missing, the link with the primary PPS file can only be made by the 
combination of other fields (age, gender), which is not 100% precise, or using information from one of the 
optional text fields in HelicsWin.Net. 
Age in years: patient age in years. Enter in the general tab of the patient screen in HelicsWin.Net. 
Age in months: patient’s age in months if the patient is less than two years old. Enter in the general tab of 
the patient screen in HelicsWin.Net. 
Sex: gender of patient – M (male), F (female). Enter in general tab of patient screen in HelicsWin.Net. 
Date of hospital admission: date patient was admitted to hospital for current hospitalisation (dd/mm/yyyy). 
Enter in general tab of the patient screen in HelicsWin.Net. 
Consultant/patient specialty: specialty of physician in charge of the patient or specialty of main disease of 
the patient. If consultant specialty differs from patient specialty, give priority to patient specialty. For 
paediatric patients on PED ward, use subspecialty (MEDGEN, MEDSUR, etc.). LTC is in principle a ward 
specialty and should only exceptionally be used as a consultant/patient specialty. Enter in field on general 
screen of patient screen in HelicsWin.Net. 
McCabe score (optional): classification of severity of underlying medical conditions. Enter in field on general 
screen of patient screen in HelicsWin.Net. See primary PPS protocol for details. 

8 

 
TECHNICAL REPORT 

Point prevalence survey of healthcare-associated infections and antimicrobial use in acute care hospitals 

• 

• 

• 

• 

Patient receives at least one antimicrobial on PPS day: patient receives at least one systemic antimicrobial 
agent on date of the survey (given or planned treatment, including intermittent treatments, e.g. alternate 
day, or medical prophylaxis). For surgical antimicrobial prophylaxis, check whether any surgical prophylaxis 
was given in the 24 hours prior to 8:00 a.m. on day of the survey (yes/no). Enter in field on general screen 
of patient screen in HelicsWin.Net. If yes, collect antimicrobial use data (optional). See primary PPS protocol 
for details. 
Patient has active HAI: patient has active HAI on survey date (yes/no). Enter in field on general screen of 
patient screen in HelicsWin.Net. If yes, collect all HAI data. See primary PPS protocol for details. 
If PN: number of X-rays (additional field in HAI data). How many chest x-rays or CT-scans with suggestive 
image of pneumonia are available for the current pneumonia episode? To be filled only in case of 
healthcare-associated pneumonia (PN1-5) in patients with underlying cardiac or pulmonary disease. This 
variable is added to estimate the number of cases of pneumonia that would not have been reported using 
the PPS 2011–2012 case definition since in the PPS 2016–2017 protocol, the following note was added: 
‘One definitive chest X-ray or CT-scan for the current pneumonia episode may be sufficient in patients with 
underlying cardiac or pulmonary disease if comparison with previous X-rays is possible’. Enter in validation 
tab of patient screen in HelicsWin.Net (not in HAI screen). 
VT comments for this patient/AM/HAI: free text. Possible comments or encountered problems with the data 
collection for the current patient. Enter in the validation tab of the patient screen in HelicsWin.Net. 

9 

 
TECHNICAL REPORT 

Point prevalence survey of healthcare-associated infections and antimicrobial use in acute care hospitals 

European Prevalence Survey of Healthcare-Associated Infections (HAIs) and Antimicrobial Use (AU) 
Form VTP. Patient validation form

Patient data

Hospital code

[__________]

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

Patient Counter validation:  [___________________________]

Patient Counter primary PPS: [_________________________]

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

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

Consultant/Patient Specialty: [__________]

dd / mm / yyyy

McCabe score (optional):  

O Non-fatal disease
O Rapidly fatal disease

O Ultimately fatal disease
O Unknown

Patient receives antimicrobial(s)(1):    

Patient has active HAI(2): 

 No 

 No 

 Yes

 Yes

Antimicrobial 
(AM)
(generic or 
brand name)

R
o
u
t
e

I

n
d
i
c
a
t
i
o
n

(
s
i
t
e
)

D
i
a
g
n
o
s
i
s

n
o
t
e
s

R
e
a
s
o
n

i

n

n
o
i
t
a
d

i
l

a
v

l

a
n
o
i
t
p
O

:
a
t
a
d
U
A

Case definition code

If PN(3): Number of x-rays 

r
e
a
s
o
n
)

C
h
a
n
g
e
d
?
(
+

A
M

I
f
c
h
a
n
g
e
d
:

D
a
t
e
s
t
a
r
t
1
s
t

/       /

/       /

/       /

D
a
t
e
s
t
a
r
t

A
M

/       /

/       /

/       /

HAI 1

Dosage per day
m
g
g

/

Strength    
of 1 dose

/
I

U

N
u
m
b
e
r

d
o
s
e
s

o
f

HAI 2

Relevant device (4)

O Yes  O No  O Unknown

O Yes  O No  O Unknown

Present on admission

O Yes   O No

IF YES

Date of onset (5)

/          / 

O Yes   O No

/          / 

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

(2)

(3)

survey;  if yes, fill antimicrobial use data; if patient receives  >3 antimicrobials, add a new form;
[nfection with onset  ≥ Day 3, OR SSI criteria met (surgery  in previous  30/90d, 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.
If pneumonia: only record  number of x-rays/ct-scans  for pneumonia  episode  in patients  with 
underlying  cardiac or pulmonary  disease

(4) Relevant  device  use before  onset  infection  (intubation for  PN, CVC/PVC for BSI, urinary catheter 

for UTI); 

Origin of infection

O current  hospital     O other 
hospital    O other  origin/  unk

O current  hospital     O other 
hospital    O other  origin/  unk

HAI associated to current 
ward

If BSI: source (6)

O Yes  O No  O Unknown

O Yes  O No  O Unknown

AMR

MO code

AB (7)

SIR

P
D
R MO code

AMR

AB (7)

SIR

P
D
R

(5) Only for infections  not present/active  on admission  (dd/mm/yyyy);
(6) C-CVC, C-PVC, S-PUL, S-UTI, S-DIG, S-SSI, S-SST, S-OTH, UO, UNK;
(7) AB: tested  antibiotic(s):  STAAUR: oxacillin/meticillin (OXA) + glycopeptides (GLY); Enterococci: 
GLY; Enterobacteriaceae:  3rd-gen cephalosporins (C3G) + carbapenems (CAR); PSEAER and 
ACIBAU: CAR; SIR: S=sensitive,  I=intermediate,  R=resistant,  U=unknown;  PDR: Pan-drug 
resistant:  N=no, P=possible,  C=confirmed,  U=Unknown

Microorganism 1

Microorganism 2

Validation team comments for this patient:___________________________________________________________________________________________________ 

_____________________________________________________________________________________________________________________________________

_____________________________________________________________________________________________________________________________________

Please  do NOT communicate  the validation  results to the  primary  data  collector(s)

10 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
TECHNICAL REPORT 

Point prevalence survey of healthcare-associated infections and antimicrobial use in acute care hospitals 

Data entry and transfer 

Validation data should in principle be entered in the HelicsWin.Net software (see HelicsWin.Net manual). If a 
national software package is used to enter data, they should be exported to the TESSy ‘HAIPPSVAL’ format and 
.csv files submitted as a compressed Zip file. Validation teams will as a rule enter validation data for validated 
hospitals in a different HelicsWin.Net database than the primary PPS data. Data for several validated hospitals can 
be entered in a single validation database. 

After completion of the validation data entry, validation data will be transmitted by the national VT (usually the PPS 
coordinating centre) to ECDC. The primary PPS data of the validated hospital will either only be submitted to TESSy 
as part of the national PPS database (TESSy .csv format) or separately in HelicsWin.Net format (.mdb export 
format). Separate TESSy submission of the primary hospital PPS data is always required if the national PPS 
database cannot be submitted by the same date as submission of the validation data. 

The following files should be transmitted to ECDC. It is recommended that HelicsWin.Net files are renamed as 
follows: 

Validation data: export of original hospital database from HelicsWin.Net (automatically named as 
‘HWN_yyyymmdd_hhmmss.zip’). Rename this .zip file to ‘HWN_yyyymmdd_country(+region if 
applicable)code_hospitalid.zip’ (i.e. ‘HWN_20111001_UKEN_1234v.zip’). Note that hospital codes for 
validation hospitals should end with a small “v”. 
Primary PPS data: 
− 

Submit primary PPS data in TESSy format to TESSy by the same date as submission of validation 
data. 
If an HelicsWin.Net Access data file is available: export of the original hospital database from 
HelicsWin.Net (automatically named as ‘HWN_yyyymmdd_hhmmss.zip’). Rename this file to 
‘HWN_yyyymmdd_country(+region if applicable)code_hospitalid.zip’ (i.e. 
‘HWN_20111001_UKEN_1234.zip’) and transfer file together with validation data. Hospital codes for 
primary data hospital identifiers should be the same as in validation data, but without a small ‘v’. 

− 

• 

• 

11 

 
 
Point prevalence survey of healthcare-associated infections and antimicrobial use in acute care hospitals 

TECHNICAL REPORT 

References 

1. 

2. 

3. 

4. 

5. 

6. 

7. 

8. 

9. 

Council of the European Union. Council Recommendation of 9 June 2009 on patient safety, including the 
prevention and control of healthcare associated infections (2009/C 151/01). Brussels: Council of the 
European Union; 2009. Available from: http://eur-
lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:C:2009:151:0001:0006:EN:PDF. 

European Centre for Disease Prevention and Control. Point prevalence survey of healthcare-associated 
infections and antimicrobial use in European acute care hospitals – Protocol version 5.3. Stockholm: ECDC; 
2016. Available from: http://ecdc.europa.eu/publications-data/point-prevalence-survey-healthcare-
associated-infections-and-antimicrobial-use-3. 

Reilly JS, Price L, Godwin J, Cairns S, Hopkins S, Cookson B, et al. National Participants in the ECDC pilot 
validation study. A pilot validation in 10 European Union Member States of a point prevalence survey of 
healthcare-associated infections and antimicrobial use in acute hospitals in Europe, 2011. Euro Surveill. 
2015 Feb 26;20(8). Available from: http://www.eurosurveillance.org/content/10.2807/1560-
7917.ES2015.20.8.21045. 

European Centre for Disease Prevention and Control. Point prevalence survey validation protocol – Version 
2.1. Point prevalence survey of healthcare-associated infections and antimicrobial use in European acute 
care hospitals. Stockholm: ECDC; 2014. Available from: http://ecdc.europa.eu/publications-data/point-
prevalence-survey-validation-protocol-version-21-point-prevalence-survey. 

European Centre for Disease Prevention and Control. Point prevalence survey of healthcare-associated 
infections and antimicrobial use in European acute care hospitals – 2011–2012. Stockholm: ECDC; 2013. 
Available from: http://ecdc.europa.eu/healthcare-associated-infections-acute-care-hospitals/surveillance-
disease-data/report. 

Fabry J, Morales I, Metzger MH, Russell I, Gastmeier P. Quality of information: a European challenge. 
J Hosp Infect. 2007 Jun;65 Suppl 2:155-8. 

Machin D, Campbell MJ, Tan SB, Tan SH. Sample Size Tables for Clinical Studies. Third Edition. Oxford: 
Wiley-Blackwell; 2009. 

Sim J, Wright CC. The Kappa Statistic in Reliability Studies: Use, Interpretation, and Sample Size 
Requirements. Phys Ther. 2005 Mar;85(3):257-68. 

Shoukri MM, Donner A. Efficiency considerations in the analysis of inter-observer agreement. Biostatistics. 
2001 Sep;2(3):323-36. 

12 

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