A comparison of two methods for identifying surgical site infections following orthopaedic surgery

Does public report card matter? A 10-year interrupted time series analysis on total knee replacement

BACKGROUND

There is a lack of evidence that shows whether a report card can improve health outcomes in terms of infection rates or unscheduled readmission by using rigorous methods to evaluate its impact.

METHODS

We used the National Health Insurance Administration's claims database from 1 January 2004 to 30 December 2013 and a time series analysis to evaluate the impact of the quality report card initiative on three negative outcomes of total knee replacement for each quarter of the year, including the rates of superficial infection of a knee replacement, deep infection of knee arthroplasty and unplanned readmissions for surgical site infection.

RESULTS

These negative outcomes (original scale) do not show significant decreases in terms of superficial infection (-0.05‰, -0.63 to 0.53‰, P = 0.87), deep infection (-0.003‰, -0.19 to 0.18‰, P = 0.97) and unscheduled readmission (0.02‰, -0.21 to 0.25‰, P = 0.88).

CONCLUSION

The total knee replacement public report card initiative did not improve the rate of infection and unscheduled readmission for surgical site infection. This report card in Taiwan should involve physicians' participation in the design and be tailored to be suitable for reading by patients in order to further enhance the chance of improvement in these negative outcomes.

Accuracy of using natural language processing methods for identifying healthcare-associated infections

OBJECTIVE

There is a growing interest in using natural language processing (NLP) for healthcare-associated infections (HAIs) monitoring. A French project consortium, SYNODOS, developed a NLP solution for detecting medical events in electronic medical records for epidemiological purposes. The objective of this study was to evaluate the performance of the SYNODOS data processing chain for detecting HAIs in clinical documents.

MATERIALS AND METHODS

The collection of textual records in these hospitals was carried out between October 2009 and December 2010 in three French University hospitals (Lyon, Rouen and Nice). The following medical specialties were included in the study: digestive surgery, neurosurgery, orthopedic surgery, adult intensive-care units. Reference Standard surveillance was compared with the results of automatic detection using NLP. Sensitivity on 56 HAI cases and specificity on 57 non-HAI cases were calculated.

RESULTS

The accuracy rate was 84% (n = 95/113). The overall sensitivity of automatic detection of HAIs was 83.9% (CI 95%: 71.7-92.4) and the specificity was 84.2% (CI 95%: 72.1-92.5). The sensitivity varies from one specialty to the other, from 69.2% (CI 95%: 38.6-90.9) for intensive care to 93.3% (CI 95%: 68.1-99.8) for orthopedic surgery. The manual review of classification errors showed that the most frequent cause was an inaccurate temporal labeling of medical events, which is an important factor for HAI detection.

CONCLUSION

This study confirmed the feasibility of using NLP for the HAI detection in hospital facilities. Automatic HAI detection algorithms could offer better surveillance standardization for hospital comparisons.

Validity and Reliability of Administrative Coded Data for the Identification of Hospital-Acquired Infections: An Updated Systematic Review with Meta-Analysis and Meta-Regression Analysis

OBJECTIVE

To conduct an updated assessment of the validity and reliability of administrative coded data (ACD) in identifying hospital-acquired infections (HAIs).

METHODS

We systematically searched three libraries for studies on ACD detecting HAIs compared to manual chart review. Meta-analyses were conducted for prosthetic and nonprosthetic surgical site infections (SSIs), Clostridium difficile infections (CDIs), ventilator-associated pneumonias/events (VAPs/VAEs) and non-VAPs/VAEs, catheter-associated urinary tract infections (CAUTIs), and central venous catheter-related bloodstream infections (CLABSIs). A random-effects meta-regression model was constructed.

RESULTS

Of 1,906 references found, we retrieved 38 documents, of which 33 provided meta-analyzable data (N = 567,826 patients). ACD identified HAI incidence with high specificity (≥93 percent), prosthetic SSIs with high sensitivity (95 percent), and both CDIs and nonprosthetic SSIs with moderate sensitivity (65 percent). ACD exhibited substantial agreement with traditional surveillance methods for CDI (κ = 0.70) and provided strong diagnostic odds ratios (DORs) for the identification of CDIs (DOR = 772.07) and SSIs (DOR = 78.20). ACD performance in identifying nosocomial pneumonia depended on the ICD coding system (DORICD-10/ICD-9-CM  = 0.05; p = .036). Algorithmic coding improved ACD's sensitivity for SSIs up to 22 percent. Overall, high heterogeneity was observed, without significant publication bias.

CONCLUSIONS

Administrative coded data may not be sufficiently accurate or reliable for the majority of HAIs. Still, subgrouping and algorithmic coding as tools for improving ACD validity deserve further investigation, specifically for prosthetic SSIs. Analyzing a potential lower discriminative ability of ICD-10 coding system is also a pending issue.

Appropriateness of ICD-coded Diagnostic Inpatient Hospital Discharge Data for Medical Practice Assessment

Objectives: We performed a systematic review to investigate the quality of diagnostic hospital discharge data (DHDD) in order to gain insight in the usefulness of these data for medical practice assessment. We investigated the methods used to evaluate data quality, factors that determine data quality and its consequences for medical practice assessment.

Methods: We selected studies in which both completeness (or sensitivity: SENS) and correctness (or positive predictive value: PPV) were measured. We used the random-effects model to calculate mean SENS and PPV and to explore the effect of a number of covariates.

Results: The 101 included studies were very heterogeneous. We distinguished six typical study designs. We found a mean SENS of 0.67 (95%CI: 0.62– 0.73) and PPV of 0.76 (95%CI: 0.73– 0.79); SENS was significantly lower for comorbidity and complication studies than for some single disease studies. PPV was significantly higher for Scandinavian countries than for other countries. Recoding compared to re-abstracting of the medical record as a gold standard gave a significantly lower PPV. Diagnostic data were considered appropriate by the authors of the studies for quality of care purposes when both SENS and PPV were at least 0.85. Only 13% of the studies fulfilled this criterion.

Conclusions: Variability in quality of care between settings can easily be overshadowed by variability in data quality. However, the use of DHDD by physicians to evaluate their own medical practice may be useful. But only if physicians are willing to critically interpret the meaning of the information for their medical practice assessment.

Measuring Surgical Site Infections in Children: Comparing Clinical, Electronic, and Administrative Data

BACKGROUND

Surgical site infections (SSIs) are an important end point and measure of quality of care. Surgical site infections can be identified using clinical registries, electronic surveillance, and administrative claims data. This study compared measurements of SSIs using these 3 different methods and estimated their implication for health care costs.

STUDY DESIGN

Data were obtained from 5,476 surgical patients treated at a single academic children's hospital (January 1, 2010 through August 31, 2014). Surgical site infections within 30 days were identified using a clinical registry in the NSQIP Pediatric, an electronic surveillance method (Nosocomial Infection Marker; MedMined), and billing claims. Infection rates, diagnostic characteristics, and attributable costs were estimated for each of the 3 measures of SSI.

RESULTS

Surgical site infections were observed in 2.24% of patients per NSQIP Pediatric definitions, 0.99% of patients per the Nosocomial Infection Marker, and 2.34% per billing claims definitions. Using NSQIP Pediatric as the clinical reference, Nosocomial Infection Marker had a sensitivity of 31.7% and positive predictive value of 72.2%, and billing claims had a sensitivity of 48.0% and positive predictive value of 46.1% for detection of an SSI. Nosocomial Infection Marker and billing claims overestimated the costs of SSIs by 108% and 41%, respectively.

CONCLUSIONS

There is poor correlation among SSIs measured using electronic surveillance, administrative claims, and clinically derived measures of SSI in the pediatric surgical population. Although these measures might be more convenient, clinically derived data, such as NSQIP Pediatric, may provide a more appropriate quality metric to estimate the postoperative burden of SSIs in children.

Predicting Infections After Total Joint Arthroplasty Using a Prescription Based Comorbidity Measure

This study evaluated the association and predictive ability of co-morbidities measured by RxRisk-V, Elixhauser and Charlson measures and post-total hip (THA) and total knee arthroplasties (TKA) infection. THAs and TKAs (2001-2012) were identified using the Australian Department of Veterans' Affairs data. Infections within 90 days post-surgery were the study endpoint. Co-morbidities were identified using pharmacy (RxRisk-V) and hospitalization history (Elixhauser, Charlson). Of the 11,848 THAs, 3.1% (N = 364) had infections and out of 18,972 TKAs 3.4% (N = 648). Comorbidity burden and specific conditions were associated with infection likelihood. RxRisk-V performed better than other measures, but none had high predictive ability and differences were small. The best performing infection prediction models resulted when a combination of conditions identified by all measures was used.

Accuracy of administrative data for surveillance of healthcare-associated infections: a systematic review

OBJECTIVE

Measuring the incidence of healthcare-associated infections (HAI) is of increasing importance in current healthcare delivery systems. Administrative data algorithms, including (combinations of) diagnosis codes, are commonly used to determine the occurrence of HAI, either to support within-hospital surveillance programmes or as free-standing quality indicators. We conducted a systematic review evaluating the diagnostic accuracy of administrative data for the detection of HAI.

METHODS

Systematic search of Medline, Embase, CINAHL and Cochrane for relevant studies (1995-2013). Methodological quality assessment was performed using QUADAS-2 criteria; diagnostic accuracy estimates were stratified by HAI type and key study characteristics.

RESULTS

57 studies were included, the majority aiming to detect surgical site or bloodstream infections. Study designs were very diverse regarding the specification of their administrative data algorithm (code selections, follow-up) and definitions of HAI presence. One-third of studies had important methodological limitations including differential or incomplete HAI ascertainment or lack of blinding of assessors. Observed sensitivity and positive predictive values of administrative data algorithms for HAI detection were very heterogeneous and generally modest at best, both for within-hospital algorithms and for formal quality indicators; accuracy was particularly poor for the identification of device-associated HAI such as central line associated bloodstream infections. The large heterogeneity in study designs across the included studies precluded formal calculation of summary diagnostic accuracy estimates in most instances.

CONCLUSIONS

Administrative data had limited and highly variable accuracy for the detection of HAI, and their judicious use for internal surveillance efforts and external quality assessment is recommended. If hospitals and policymakers choose to rely on administrative data for HAI surveillance, continued improvements to existing algorithms and their robust validation are imperative.

Validation of a Modified Version of the National Nosocomial Infections Surveillance System Risk Index for Health Services Research

Objective.

To validate the National Nosocomial Infections Surveillance system risk index through administrative data to predict surgical site infections.

Design.

Retrospective cohort study.

Setting.

Population-based analysis in Ontario, Canada.

Patients.

All elderly patients who underwent elective surgery from April 1, 1992, through March 31, 2006 (n = 469,349).

Methods.

Data on procedural and patient outcomes were gathered from linked population-wide hospital discharge records and physician claims. The 75th percentile of surgical duration was estimated through anesthesiologist billing fees recorded in 15-minute increments; the American Society of Anesthesiology score of at least 3 out of 5 was estimated by diagnostic codes for severe systemic illness; and all surgeries were classified as clean or clean-contaminated because of their elective nature (thus, the maximum score on the modified index was 2).

Results.

A total of 147,216 surgeries (31%) had a score of 0;246,592 (53%) had a score of 1; and 75,541 (16%) had a score of 2 on the modified index. The 30-day risk of surgical site infection increased with each increment in the modified index (score of 0, 5.4%; score of 1, 8.0%; score of 2, 14.3%; P < .001). The association was evident for surgical site infection diagnosed during the index admission (score of 0, 2.0%; score of 1, 3.7%; score of 2, 8.9%; P < .001), as well as that associated with reoperation or death (score of 0, 0.04%; score of 1, 0.23%; score of 2, 0.73%; P < .001). The modified index predicted increases in surgical site infection risk within each of 11 surgical subgroups. In accord with past research, the modified index had modest discrimination (C statistic, 0.59), and the majority of surgical site infections (72%) occurred within lower risk strata.

Conclusions.

The modified index predicts surgical site infection in population-based analyses and is associated with incremental increases in risk.

Leveraging Electronic Medical Records for Surveillance of Surgical Site Infection in a Total Joint Replacement Population

Objective.

TO evaluate whether a hybrid electronic screening algorithm using a total joint replacement (TJR) registry, electronic surgical site infection (SSI) screening, and electronic health record (EHR) review of SSI is sensitive and specific for SSI detection and reduces chart review volume for SSI surveillance.

Design.

Validation study.

Setting.

A large health maintenance organization (HMO) with 8.6 million members.

Methods.

Using codes for infection, wound complications, cellullitis, procedures related to infections, and surgeon-reported complications from the International Classification of Diseases, Ninth Revision, Clinical Modification, we screened each TJR procedure performed in our HMO between January 2006 and December 2008 for possible infections. Flagged charts were reviewed by clinical-content experts to confirm SSIs. SSIs identified by the electronic screening algorithm were compared with SSIs identified by the traditional indirect surveillance methodology currently employed in our HMO. Positive predictive values (PPVs), negative predictive values (NPVs), and specificity and sensitivity values were calculated. Absolute reduction of chart review volume was evaluated.

Results.

The algorithm identified 4,001 possible SSIs (9.5%) for the 42,173 procedures performed for our TJR patient population. A total of 440 case patients (1.04%) had SSIs (PPV, 11.0%; NPV, 100.0%). The sensitivity and specificity of the overall algorithm were 97.8% and 91.5%, respectively.

Conclusion.

An electronic screening algorithm combined with an electronic health record review of flagged cases can be used as a valid source for TJR SSI surveillance. The algorithm successfully reduced the volume of chart review for surveillance by 90.5%.

Identifying colon and open reduction of fracture surgical site infections using a partially automated electronic algorithm

BACKGROUND

Algorithms leveraging electronic data may reduce manual review burden for surgical site infection (SSI) surveillance with little to no reduction in sensitivity. We developed an algorithm to identify colon and open reduction of fracture (FX) SSIs to reduce manual chart review.

METHODS

A retrospective cohort of colon and FX procedures and associated SSIs was constructed. Potential SSIs were identified by positive microbiologic cultures or administrative data for diagnosis or treatment of wound infection. Sensitivity and specificity of the algorithm were assessed. The number of charts needing review to identify 1 SSI, and the potential time-savings from the algorithm, were calculated.

RESULTS

Four hundred seventy-three colon (SSI rate = 7%) and 1081 FX (SSI rate = 3%) procedures were identified. The algorithm was 91% and 97% sensitive and 76% and 93% specific for colon and FX procedures, respectively. Overall, chart review would have been reduced by 24.3 hours per 100 procedures, decreasing the number of charts to review to identify 1 SSI from 23.9 for manual review to 3.9 with the algorithm.

CONCLUSIONS

The algorithm identified SSIs with excellent sensitivity and specificity, resulting in substantial reductions in manual chart review. This algorithm could be tailored and applied to other hospitals.

Data use and effectiveness in electronic surveillance of healthcare associated infections in the 21st century: a systematic review

OBJECTIVE

As more electronic health records have become available during the last decade, we aimed to uncover recent trends in use of electronically available patient data by electronic surveillance systems for healthcare associated infections (HAIs) and identify consequences for system effectiveness.

METHODS

A systematic review of published literature evaluating electronic HAI surveillance systems was performed. The PubMed service was used to retrieve publications between January 2001 and December 2011. Studies were included in the review if they accurately described what electronic data were used and if system effectiveness was evaluated using sensitivity, specificity, positive predictive value, or negative predictive value. Trends were identified by analyzing changes in the number and types of electronic data sources used.

RESULTS

26 publications comprising discussions on 27 electronic systems met the eligibility criteria. Trend analysis showed that systems use an increasing number of data sources which are either medico-administrative or clinical and laboratory-based data. Trends on the use of individual types of electronic data confirmed the paramount role of microbiology data in HAI detection, but also showed increased use of biochemistry and pharmacy data, and the limited adoption of clinical data and physician narratives. System effectiveness assessments indicate that the use of heterogeneous data sources results in higher system sensitivity at the expense of specificity.

CONCLUSIONS

Driven by the increased availability of electronic patient data, electronic HAI surveillance systems use more data, making systems more sensitive yet less specific, but also allow systems to be tailored to the needs of healthcare institutes' surveillance programs.

Epidemiology of surgical site infections after total hip and knee joint replacement during 2007-2009: a report from the VINCat Program

The VINCat Program is a system for epidemiological surveillance of healthcare-related infections in which the majority of Catalan hospitals participate. It has a specific module for surgical site infections (SSI) surveillance. Primary hip and knee arthroplasties are basic indicators of the program due to their high frequency and the important morbidity of SSI of these sites. Results are presented for surgical site infection (SSI) surveillance of primary hip and knee arthroplasties for the first three years of the VINCat Program. The program requires SSI surveillance to be performed in a standardized, prospective and continuous manner by an infection control team from the centers. With primary arthroplasties, as with all procedures involving implants, the surveillance is maintained for 1 year after the intervention. The VINCat Program uses the SSI definitions of the Centers for Disease Control (CDC) and patients are stratified by surgical risk, following the classification of the National Healthcare Safety Network (NHSN). During the period 2007-2009, 51 Catalan hospitals participated in the SSI surveillance of prosthetic orthopedic surgery. The overall SSI rate in the interventions for total primary hip prosthesis (7,804 procedures) was 3.0% (IC 95%: 2.6-3.4) and for total primary knee prosthesis (16,781 procedures) was 3.3% (IC95%: 3.0-3.6). During the period 2007-2009, the overall SSI rates for total primary hip and knee arthroplasty were higher than those published by some surveillance systems in our environment. There were significant differences in the infection rates by procedure and in those adjusted by risk among the different hospitals.

Evaluation study of different strategies for detecting surgical site infections using the hospital information system at Lyon University Hospital, France

OBJECTIVE

To evaluate different strategies for detecting surgical site infections (SSIs) using different sources (notification by the surgeon, bacteriological results, antibiotic prescription, and discharge diagnosis codes).

BACKGROUND

Surveillance plays a role in reducing the risks of SSIs but the performance of case reports by surgeons is insufficient. Indirect methods of SSI detection are an alternative to increase the quality of surveillance.

METHODS

A retrospective cohort study of 446 patients operated consecutively during the first half of 2007 was set up in a 56-bed general surgery unit in Lyon University Hospital, France. Patients were followed up 30 days after intervention. Different methods of detection were established by combining different data sources. The sensitivity and specificity of these methods were calculated by using, as reference method, the manual review of the medical records.

RESULTS

The sensitivity and specificity of SSI detection were, respectively, 18.4% (95% confidence interval [CI]: 7.9-31.6) and 100% for surgeon notification; 63.2% (95% CI: 47.3-78.9) and 95.1% (95% CI: 92.9-97.1) for detection based on positive cultures; 68.4% (95% CI: 52.6-81.6) and 87.5% (95% CI: 84.3-90.7) using antibiotic prescription; 26.3% (95% CI: 13.2-42.1) and 99.5% (95% CI: 98.8-100) using discharge diagnosis codes. By combining the latter 3 sources, the sensitivity increased at 86.8% (95% CI: 76.3-97.4) and the specificity was lowered at 85.5% (95% CI: 82.1-89.0).

CONCLUSIONS

SSI detection based on the combination of data extracted automatically from the hospital information system performed well. This strategy has been implemented gradually in Lyon University Hospital.

Electronic measures of surgical site infection: implications for estimating risks and costs

OBJECTIVE

Electronic measures of surgical site infections (SSIs) are being used more frequently in place of labor-intensive measures. This study compares performance characteristics of 2 electronic measures of SSIs with a clinical measure and studies the implications of using electronic measures to estimate risk factors and costs of SSIs among surgery patients.

METHODS

Data included 1,066 general and vascular surgery patients at a single academic center between 2007 and 2008. Clinical data were from the National Surgical Quality Improvement Program (NSQIP) database, which includes a nurse-derived measure of SSI. We compared the NSQIP SSI measure with 2 electronic measures of SSI: MedMined Nosocomial Infection Marker (NIM) and International Classification of Diseases, Ninth Revision (ICD-9) coding for SSIs. We compared infection rates for each measure, estimated sensitivity and specificity of electronic measures, compared effects of SSI measures on risk factors for mortality using logistic regression, and compared estimated costs of SSIs for measures using linear regression.

RESULTS

SSIs were observed in 8.8% of patients according to the NSQIP definition, 2.6% of patients according to the NIM definition, and 5.8% according to the ICD-9 definition. Logistic regression for each SSI measure revealed large differences in estimated risk factors. NIM and ICD-9 measures overestimated the cost of SSIs by 134% and 33%, respectively.

CONCLUSIONS

Caution should be taken when relying on electronic measures for SSI surveillance and when estimating risk and costs attributable to SSIs. Electronic measures are convenient, but in this data set they did not correlate well with a clinical measure of infection.

Use of diagnosis codes and/or wound culture results for surveillance of surgical site infection after mastectomy and breast reconstruction

We compared surveillance of surgical site infection (SSI) after major breast surgery by using a combination of International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes and microbiology-based surveillance. The sensitivity of the coding algorithm for identification of SSI was 87.5%, and the sensitivity of wound culture for identification of SSI was 78.1%. Our results suggest that SSI surveillance can be reliably performed using claims data.

Validity of electronic surveillance systems: a systematic review

Electronic surveillance that utilises information held in databases is more efficient than conventional infection surveillance methods. Validity is not well-defined, however. We systematically reviewed studies comparing the utility of electronic and conventional surveillance methods. Publications were identified using Medline (1980-2007) and bibliographic review. The sensitivity and specificity of electronic compared with conventional surveillance was reported. Twenty-four studies were included. Six studies reported that nosocomial infections could be detected utilising microbiology data alone with good overall sensitivity (range: 63-91%) and excellent specificity (range: 87 to >99%). Two studies used three laboratory-based algorithms for the detection of infection outbreaks yielding variable utility measures (sensitivity, range: 43-91%; specificity, range: 67-86%). Seven studies using only administrative data including discharge coding (International Classification of Diseases, 9th edn, Clinical Modification) and pharmacy data claimed databases had good sensitivity (range: 59-96%) and excellent specificity (range: 95 to >99%) in detecting nosocomial infections. Six studies combined both laboratory and administrative data for a range of infections, and overall had higher sensitivity (range: 71-94%) but lower specificity (range: 47 to >99%) than with use of either alone. Three studies evaluated community-acquired infections with variable results. Electronic surveillance has moderate to excellent utility compared with conventional methods for nosocomial infections. Future studies are needed to refine electronic algorithms further, especially with community-onset infections.

Proposition d’un protocole de suivi des infections avérées de site opératoire en chirurgie orthopédique et traumatologique

PURPOSE OF THE STUDY

A program for the prevention of nosocomial infections, including operative site infections (OSI) is a legal obligation in France. According to the CDC, in orthopedic surgery, nosocomial infection is defined as any infection occurring within 30 days of operation, or within one year in the event of material implantation. No surveillance system has been validated and the rate of OSI is unknown in orthopedic surgery. We report the number of OSI observed during a three year period in our unit and describe the characteristic features.

MATERIAL AND METHODS

Data were collected from the bacteriology reports on operative site samples with a positive culture. A group of specialists determined the infective nature of the germ and the nosocomial nature of the OSI. Clinical and bacteriological data were noted on a standard datasheet used for prospective follow-up of the number of cases and data processing. During a three-year period (2000, 2001, 2002), among 9397 orthopedic and traumatology operations performed, 86 OSI were identified. Mean patient age was 58 years and mean body mass index was 25.7. The ASA score was >or=II for 72% of patients.

RESULTS

The OSI involved an arthroplasty in 23 cases, a traumatology procedure in 21, and tumor treatment in 24. The diagnosis was established within 30 days of operation for 75% and after discharge from hospital in 65.4%. Single-germ infections predominated (n=59). Staphylococcus aureus was isolated in 80.23% of infections. For tumor surgery, the statistically more frequent multiple-germ infections associated coagulase negative Staphylococcus and Gram-negative bacilli. There were six OSI-related deaths.

DISCUSSION

Two criticisms can be formulated concerning our surveillance system. First, infections with no identified germ could be missed. The frequency of such infections has been estimated at 2.8 to 19% by different authors. Although patients are automatically recalled for consultation, we were unable to determine the number of patients lost to follow-up at one year. It was thus not possible to determine a precise rate of OSI. Data in the literature have not demonstrated any system providing an exhaustive surveillance, particularly because of the long postoperative period after material implantation. Excepting tumor surgery, Staphylococcus aureus infections predominated. Factors of risk of OSI include the patient's general status, particularly for arthroplasty. We had a mortality rate of 7% for our OSI, corroborating earlier studies and illustrating the severity of such infections.

CONCLUSION

Surveillance of OSI in orthopedic surgery requires the development of a system responding to the problem of a long observation period. It would be important to know the precise number of OSI and their characteristic features in order to develop comparison tools.

Surgical-site infections after orthopaedic surgery: statewide surveillance using linked administrative databases

Prospective surveillance programmes to monitor the incidence of surgical-site infection (SSI) in patients who have had orthopaedic implant surgery can be difficult to implement due to limited human and technical resources. In addition, prolonged patient follow-up, up to one year, may be required. Traditional methods of surveillance can be enhanced by using administrative databases to assist in case finding and facilitate overall surveillance activities. The aim of this study was to identify the incidence of SSI in patients who had undergone total hip replacement (THR) or total knee replacement (TKR) surgery in all Western Australian (WA) hospitals during 1999 using the Western Australian Data Linkage System. The WA Data Linkage System links several population-based administrative health datasets within the state, including the Hospital Morbidity Data System (HMDS), containing International Classification of Disease-coded discharge information, and mortality records. A total of 1476 THR and 1875 TKR procedures was identified from 21 WA hospitals during 1999. The incidence of SSI after these procedures was 5% (95% CI 4.3-5.7) [THR (4.86%, 95% CI 3.77-5.95) and TKR (5.15%, 95% CI 4.15-6.15)]. The incidence was 33.72 infections per 1000 person-years. Patients aged over 80 years experienced a significantly higher rate of infection after THR compared with patients aged 80 or less (z-test, z = 2.56, P = 0.015), but not for TKR. No patients with an SSI died during follow-up. The WA Data Linkage System provided a unique opportunity to review the incidence of SSIs in patients undergoing THR or TKR surgery in WA hospitals.

Linkage of microbiology reports and hospital discharge diagnoses for surveillance of surgical site infections

Surveillance of surgical site infections (SSIs) with feedback to surgical personnel is pivotal in decisions regarding infection control. Prospective surveillance is time and resource consuming, so we aimed to evaluate a method based on data collected routinely during care delivery. The study was carried out at three acute hospitals in North-eastern Italy, from 1 January 2001 to 31 December 2001. Hospital discharge diagnoses (selected codes from the International Classification of Diseases, 9th Revision--Clinical Modification) and electronic microbiology reports (positive cultures from surgical wounds and drainages) were linked to identify suspected SSIs. A random sample of tracked events was submitted to total chart review in order to confirm the presence of SSIs retrospectively according to Centers for Disease Control and Prevention definitions. Of 865 suspected SSIs, 64.5% were identified from the microbiological database, 27.1% from discharge codes, and 8.4% from both. Four hundred and three admissions were sampled for review; the overall positive predictive value was 72% (95%CI=69-76%). Since inpatient individual antibiotic exposure is not registered in Italy, the combined use of discharge codes and microbiology reports represents the most feasible automated method for surveillance of SSIs developing during hospital stay.

Can hospital discharge diagnoses be used for surveillance of surgical-site infections?

The aim of this study was to assess the data quality of postoperative infections in a hospital discharge registry in the Emilia-Romagna region of Italy. Data from a prospective regional study of postoperative infections in 6158 patients from 31 of the 36 public hospitals of the region were compared with data from the regional hospital discharge registry, using different classes of ICD-9-CM codes. The sensitivity of the hospital discharge database for postoperative surgical infections was 10% when ICD-9-CM codes directly indicative of postoperative infectious complications were used. When non-specific codes of postoperative complications, not necessarily of infectious origin, were added, the sensitivity reached 21%. At present, the hospital discharge registry is not suited for surveillance of hospital-acquired infection.

A comparison of competing methods for the detection of surgical-site infections in patients undergoing total arthroplasty of the knee, partial and total arthroplasty of hip and femoral or similar vascular bypass

Recent research suggests that the retrospective review of the International Classification of Disease (ICD-9-CM) codes assigned to a patient episode will identify a similar number of healthcare-acquired surgical-site infections as compared with prospective surveillance by infection control practitioners (ICP). We tested this finding by replicating the methods for 380 surgical procedures. The sensitivity and specificity of the ICP undertaking prospective surveillance was 80% and 100%, and the sensitivity and specificity of the review of ICD-10-AM codes was 60% and 98.9%. Based on these results we do not support retrospective review of ICD-10-AM codes in preference prospective surveillance for SSI.

Prevention of postsurgical infections: some like it hot

PURPOSE OF THE REVIEW

The present review covers the literature on prevention of surgical site infections published during 2001. Only papers that offer new insights or question current recommendations are included.

RECENT FINDINGS

The most interesting advances have been made in the preoperative preparation of the patient. In particular, the effects of preoperative warming of the patient, either generally or locally at the incision site, on the rate of surgical site infections are impressive and warrant further investigation. Also, the effects of strict control of perioperative blood glucose levels and of preoperative eradication of nasal carriage of Staphylococcus aureus should be studied in greater detail.

SUMMARY

The protective effect of local and systemic warming before surgical procedures has been described in two well designed studies. Although a final judgement regarding effectiveness can only be made after more extensive investigations have been conducted, there appear to be few arguments against application of this cheap and safe measure. Thus, implementation of preoperative warming can be justified in settings associated with high rates of surgical site infections.