Identification of risk factors by systematic review and development of risk-adjusted models for ...

172 Pages·2011·1.51 MB·English

by  Gibbons C

Health Technology Assessment 2011; Vol. 15: No.301
References
Health Technology Assessment 2011; Vol. 15: No. 30 ISSN 1366-5278
ISSN 1366-5278 Appendix 1
AbSsttruadcyt protocol
1.1 Details of the proposed research
Lis1t .o2f P aubrbporesvei aotf itohnes research
1.3 Plan of investigation
Executive summary
1.4 Likely outputs from the study
Background to the research
1.5 Proposal for an extension
Aim and objectives of the research
1.6 References
How the research was conducted
ARpepseenadricxh 2 fi ndings
Identification of risk factors by DCatoanbcalussei osnesarches 111
SFuurgnedriyn-gspecific search: colon surgery
systematic review and development of Surgery-specific search: hip and knee replacement surgery
ChSapeatercrh 1 f o r generic risk factors for surgical site infections
risk-adjusted models for surgical site SIenatrrcohd fuocr triioskn ftaoc ttohres rfoers seuarrgcichal site infections identified by postdischarge surveillance
Background
infection ARpipsekn-addixju 3s t ing rates of surgical site infection
MDeathtaobdass feosr cdoenrisviidnegr esdurgical site infection definitions based upon CDC, NINSS and
ARSeEsPeSaIrSc hc raitimersia ainn dth oeb UjeCcLtivHe swound monitoring data set 117
Introduction
ChDapaitlye rs u2m mary: Centers for Disease Control and Prevention
C Gibbons, J Bruce, J Carpenter, AP Wilson,
DSayilys tseummamtiacr yr:e AvSieEwPsS IoSf literature
J Wilson, A Pearson, DL Lamping, FIonltlorowd-uucpt iponre tpoa rsaytsiotenm aantdic f orellvoiwew-usp summary (surgical site infection definitions)
FSinyasl toeumtpautict firleeview methods
ZH Krukowski and BC Reeves Results
ASpupmenmdaixr y4 o f findings
Risk factors excluded from modelling 129
ChSapumtemr 3ar y of actions taken to exclude some risk factors from surgery-specific models
Definitions of surgical site infection
AApgpreenedmixe 5n t of alternative surgical site infection definitions
UDneivfianriinabg lea ssuumrgmicaalr iseiste o ifn rfiesckt ifoanctors measured as continuous variables 131
TaVbaulidlaattioionns ooff scuartgeicgaolr issiateti oinnfse cotfio pno dteenfitniaitli orinssk factors other than components of National
NOovseorcvoiemwia ol fI nfifnedcitniognss o Sf usruvregiilclaanl cseit eri sinkf eincdtieoxn, dagefien aitniodn gsender
ACphpaepntdeixr 46
ASltuerrgniactaivl essit eto i ntfheec Ntioanti orinsakl mNoosdoeclloinmgi a(Nl aIntifoencatilo Nnso sSoucrovmeililaaln Icnefe rcistiko nin Sduerxv: eai ltlaensct e
uSsicnhge lmareg dea btoa)wel surgery data
InNtraotdiouncatli oNnosocomial Infection Surveillance Scheme
LDogaitsat icm raengargeessmioenn ta pnraiolyrs tiso faonr alalyrsgies bowel surgery
CRoensculultssi oonf univariable analyses of risk factors
Methods for multivariable and multilevel risk modelling
HealtRhi sTke mchondoellolinggy rAessusletss bsym ceantet gpororyg oraf smumrgeical procedure
Chapter 5
Discussion and conclusions
Summary of findings
Limitations
Implications of findings
September 2011
Research recommendations
10.3310/hta15300
Conclusions
Acknowledgements
Contributions of authors
Publication
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Identification of risk factors by systematic
review and development of risk-adjusted
models for surgical site infection
C Gibbons,1 J Bruce,2 J Carpenter,1 AP Wilson,3
J Wilson,4 A Pearson,5 DL Lamping,1† ZH Krukowski6
and BC Reeves7*
1London School of Hygiene and Tropical Medicine, London, UK
2University of Aberdeen, Aberdeen, UK
3University College London, London, UK
4Imperial College Healthcare NHS Trust, London, UK
5Health Protection Agency, London, UK
6Aberdeen Royal Infirmary, Aberdeen, UK
7University of Bristol, Bristol, UK
*Corresponding author
†In memoriam
Declared competing interests of authors: Barnaby C Reeves was awarded a grant by the National
Institute for Health Research to carry out this research. The grant was awarded to the London School
of Hygiene and Tropical Medicine (Barnaby C Reeves’ employer until 2005). James Carpenter has
consultancy and grants. A Peter Wilson has consultancy (Roche, drug safety monitoring board) and a
grant with the Department of Health (trial of cleaning on hospital wards).
Published September 2011
DOI: 10.3310/hta15300
This report should be referenced as follows:
Gibbons C, Bruce J, Carpenter J, Wilson AP, Wilson J, Pearson A, et al. Identification of risk factors by
systematic review and development of risk-adjusted models for surgical site infection. Health Technol
Assess 2011;15(30).
Health Technology Assessment is indexed and abstracted in Index Medicus/MEDLINE, Excerpta
Medica/EMBASE, Science Citation Index Expanded (SciSearch) and Current Contents/
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DOI: 10.3310/hta15300 Health Technology Assessment 2011; Vol. 15: No. 30 iii
Abstract
Identification of risk factors by systematic review and
development of risk-adjusted models for surgical
site infection
C Gibbons,1 J Bruce,2 J Carpenter,1 AP Wilson,3 J Wilson,4 A Pearson,5
DL Lamping,1† ZH Krukowski6 and BC Reeves7*
1London School of Hygiene and Tropical Medicine, London, UK
2University of Aberdeen, Aberdeen, UK
3University College London, London, UK
4Imperial College Healthcare NHS Trust, London, UK
5Health Protection Agency, London, UK
6Aberdeen Royal Infirmary, Aberdeen, UK
7University of Bristol, Bristol, UK
*Corresponding author
†In memoriam
Background: Surgical site infections (SSIs) are complications of surgery that cause
significant postoperative morbidity. SSI has been proposed as a potential indicator of the
quality of care in the context of clinical governance and monitoring of the performance of
NHS organisations against targets.
Objectives: We aimed to address a number of objectives. Firstly, identify risk factors for
SSI, criteria for stratifying surgical procedures and evidence about the importance of
postdischarge surveillance (PDS). Secondly, test the importance of risk factors for SSI in
surveillance databases and investigate interactions between risk factors. Thirdly,
investigate and validate different definitions of SSI. Lastly, develop models for making risk-
adjusted comparisons between hospitals.
Data sources: A single hospital surveillance database was used to address objectives 2
and 3 and the UK Surgical Site Infection Surveillance Service database to address
objective 4.
Study design: There were four elements to the research: (1) systematic reviews of risk
factors for SSI (two reviewers assessed titles and abstracts of studies identified by the
search strategy and the quality of studies was assessed using the Newcastle Ottawa
Scale); (2) assessment of agreement between four SSI definitions; (3) validation of
definitions of SSI, quantifying their ability to predict clinical outcomes; and (4) development
of operation-specific risk models for SSI, with hospitals fitted as random effects.
Results: Reviews of SSI risk factors other than established SSI risk indices identified other
risk; some were operation specific, but others applied to multiple operations. The factor
most commonly identified was duration of preoperative hospital stay. The review of PDS for
SSI confirmed the need for PDS if SSIs are to be compared meaningfully over time within
an institution. There was wide variation in SSI rate (SSI%) using different definitions. Over
twice as many wounds were classified as infected by one definition only as were classified
as infected by both. Different SSI definitions also classified different wounds as being
infected. The two most established SSI definitions had broadly similar ability to predict the
© Queen’s Printer and Controller of HMSO 2011. This work was produced by Gibbons et al. under the terms of a commissioning contract issued by the
Secretary of State for Health.
iv Abstract
chosen clinical outcomes. This finding is paradoxical given the poor agreement between
definitions. Elements of each definition not common to both may be important in predicting
clinical outcomes or outcomes may depend on only a subset of elements which are
common to both. Risk factors fitted in multivariable models and their effects, including age
and gender, varied by surgical procedure. Operative duration was an important risk factor
for all operations, except for hip replacement. Wound class was included least often
because some wound classes were not applicable to all operations or were combined
because of small numbers. The American Association of Anesthesiologists class was a
consistent risk factor for most operations.
Conclusions: The research literature does not allow surgery-specific or generic risk factors
to be defined. SSI definitions varied between surveillance programmes and potentially
between hospitals. Different definitions do not have good agreement, but the definitions
have similar ability to predict outcomes influenced by SSI. Associations between
components of the National Nosocomial Infections Surveillance risk index and odds of SSI
varied for different surgical procedures. There was no evidence for effect modification by
hospital. Estimates of SSI% should be disseminated within institutions to inform infection
control. Estimates of SSI% across institutions or countries should be interpreted cautiously
and should not be assumed to reflect quality of medical care. Future research should focus
on developing an SSI definition that has satisfactory psychometric properties, that can be
applied in everyday clinical settings, includes PDS and is formulated to detect SSIs that are
important to patients or health services.
Funding: The National Institute for Health Research Technology Assessment programme.
DOI: 10.3310/hta15300 Health Technology Assessment 2011; Vol. 15: No. 30 v
Contents
List of abbreviations vii
Executive summary ix
1. Introduction to the research 1
Background 1
Risk-adjusting rates of surgical site infection 1
Databases considered 3
Research aims and objectives 4
2. Systematic reviews of literature 5
Introduction to systematic reviews 5
Systematic review methods 6
Results 8
Summary of findings 19
3. Definitions of surgical site infection 21
Agreement of alternative surgical site infection definitions 21
Defining a surgical site infection 21
Validation of surgical site infection definitions 27
Overview of findings of surgical site infection definitions 35
4. Surgical site infection risk modelling (National Nosocomial Infection
Surveillance Scheme data) 37
National Nosocomial Infection Surveillance Scheme 37
Data management prior to analysis 38
Results of univariable analyses of risk factors 39
Methods for multivariable and multilevel risk modelling 54
Risk modelling results by category of surgical procedure 57
5. Discussion and conclusions 77
Summary of findings 77
Limitations 78
Implications of findings 79
Research recommendations 80
Conclusions 81
Acknowledgements 83
References 85
Appendix 1 Study protocol 93
Appendix 2 Database searches 111
Appendix 3 Methods for deriving surgical site infection definitions based upon CDC,
NINSS and ASEPSIS criteria in the UCLH wound monitoring data set 117
© Queen’s Printer and Controller of HMSO 2011. This work was produced by Gibbons et al. under the terms of a commissioning contract issued by the
Secretary of State for Health.
vi Contents
Appendix 4 Risk factors excluded from modelling 129
Appendix 5 Univariable summaries of risk factors measured as continuous variables 131
Appendix 6 Alternatives to the National Nosocomial Infections Surveillance risk index:
a test using large bowel surgery data 145
Health Technology Assessment programme 151
DOI: 10.3310/hta15300 Health Technology Assessment 2011; Vol. 15: No. 30 vii
List of abbreviations
ASA American Society of Anesthesiologists
ASEPSIS Additional treatment, the presence of Serous discharge, Erythema, Purulent
exudate, and Separation of the deep tissues, the Isolation of bacteria and the
duration of inpatient Stay
CABG coronary artery bypass graft
CDC Centers for Disease Control and Prevention
CI confidence interval
HR hazard ratio
HTA health technology assessment
IGLS iterative generalised least squares
IQR interquartile range
LOS length of stay
MeSH medical subject heading
MQL marginal quasi-likelihood
NIHR National Institute for Health Research
NINSS Nosocomial Infection National Surveillance Scheme
NNIS National Nosocomial Infections Surveillance
NOS Newcastle Ottawa Scale
NRC National Research Council
OR odds ratio
PAB prescription of antibiotics in hospital or after discharge
PDS postdischarge surveillance
PLOS protracted length of hospital stay
Pneg number of negative predictions
Ppos number of positive predictions
PQL penalised quasi-likelihood
PWH patient-reported problem with wound healing
RCT randomised controlled trial
ROC receiver operating characteristic
RR rate ratio
SENIC Study of the Efficacy of Nosocomial Infection Control
SSI surgical site infection
SSI% surgical site infection rate
SSISS Surgical Site Infection Surveillance Service
STROBE Strengthening the Reporting of Observational studies in Epidemiology
UCLH University College London Hospitals
WBC white blood cell
WRTX wound retreatment in hospital or after discharge
All abbreviations that have been used in this report are listed here unless the abbreviation is well
known (e.g. NHS), or it has been used only once, or it is a non-standard abbreviation used only
in figures/tables/appendices, in which case the abbreviation is defined in the figure legend or in
the notes at the end of the table.
© Queen’s Printer and Controller of HMSO 2011. This work was produced by Gibbons et al. under the terms of a commissioning contract issued by the
Secretary of State for Health.