Administrative coding data, compared with CDC/NHSN criteria, are poor indicators of health care-associated infections

Measuring the Direct Medical Costs of Hospital-Onset Infections Using an Analogy Costing Framework

BACKGROUND

The majority of recent estimates on the direct medical cost attributable to hospital-onset infections (HOIs) has focused on device- or procedure-associated HOIs. The attributable costs of HOIs that are not associated with device use or procedures have not been extensively studied.

OBJECTIVE

We developed simulation models of attributable cost for 16 HOIs and estimated the total direct medical cost, including nondevice-related HOIs in the USA for 2011 and 2015.

DATA AND METHODS

We used total discharge costs associated with HOI-related hospitalization from the National Inpatient Sample and applied an analogy costing methodology to develop simulation models of the costs attributable to HOIs. The mean attributable cost estimate from the simulation analysis was then multiplied by previously published estimates of the number of HOIs for 2011 and 2015 to generate national estimates of direct medical costs.

RESULTS

After adjusting all estimates to 2017 US dollars, attributable cost estimates for select nondevice-related infections attributable cost estimates ranged from $7661 for ear, eye, nose, throat, and mouth (EENTM) infections to $27,709 for cardiovascular system infections in 2011; and from $8394 for EENTM to $26,445 for central nervous system infections in 2016 (based on 2015 incidence data). The national direct medical costs for all HOIs were $14.6 billion in 2011 and $12.1 billion in 2016. Nondevice- and nonprocedure-associated HOIs comprise approximately 26-28% of total HOI costs.

CONCLUSION

Results suggest that nondevice- and nonprocedure-related HOIs result in considerable costs to the healthcare system.

Automating detection of diagnostic error of infectious diseases using machine learning

Diagnostic error, a cause of substantial morbidity and mortality, is largely discovered and evaluated through self-report and manual review, which is costly and not suitable to real-time intervention. Opportunities exist to leverage electronic health record data for automated detection of potential misdiagnosis, executed at scale and generalized across diseases. We propose a novel automated approach to identifying diagnostic divergence considering both diagnosis and risk of mortality. Our objective was to identify cases of emergency department infectious disease misdiagnoses by measuring the deviation between predicted diagnosis and documented diagnosis, weighted by mortality. Two machine learning models were trained for prediction of infectious disease and mortality using the first 24h of data. Charts were manually reviewed by clinicians to determine whether there could have been a more correct or timely diagnosis. The proposed approach was validated against manual reviews and compared using the Spearman rank correlation. We analyzed 6.5 million ED visits and over 700 million associated clinical features from over one hundred emergency departments. The testing set performances of the infectious disease (Macro F1 = 86.7, AUROC 90.6 to 94.7) and mortality model (Macro F1 = 97.6, AUROC 89.1 to 89.1) were in expected ranges. Human reviews and the proposed automated metric demonstrated positive correlations ranging from 0.231 to 0.358. The proposed approach for diagnostic deviation shows promise as a potential tool for clinicians to find diagnostic errors. Given the vast number of clinical features used in this analysis, further improvements likely need to either take greater account of data structure (what occurs before when) or involve natural language processing. Further work is needed to explain the potential reasons for divergence and to refine and validate the approach for implementation in real-world settings.

Perioperative Antibiotics and Other Factors Associated with Postcesarean Infections: A Case-Control Study

OBJECTIVE

Our objective was to determine modifiable risk factors associated with surgical site infection (SSI) and postpartum endometritis. We hypothesized that inappropriate surgical antibiotic prophylaxis would be a risk factor for both types of infections.

STUDY DESIGN

This was a single-center case-control study of SSI and endometritis after cesarean delivery over a 2-year period from 2016 to 2017. Cases were identified by International Classification of Diseases, 10th Revision diagnosis codes, infection control surveillance, and electronic medical records search and were subsequently confirmed by chart review. Three controls were randomly selected for each case from all cesareans ± 48 hours from case delivery. Demographic, pregnancy, and delivery characteristics were abstracted. Separate multivariable logistic regression models were used to assess factors associated with SSI and endometritis. Postpartum outcomes, including length of stay and readmission, were also compared.

RESULTS

We identified 141 cases of SSI and endometritis with an overall postpartum infection rate of 4.0% among all cesarean deliveries. In adjusted analysis, factors associated with both SSI and endometritis were intrapartum delivery, classical or other (non-low-transverse) uterine incision, and blood transfusion. Factors associated with SSI only included inadequate antibiotic prophylaxis, public insurance, hypertensive disorder of pregnancy, and nonchlorhexidine abdominal preparation; factors only associated with endometritis included β-lactam allergy, anticoagulation therapy, and chorioamnionitis. Among cases, 34% of those with SSI and 25% of those with endometritis did not receive adequate antibiotic prophylaxis, compared with 12.9 and 13.5% in control groups, respectively. Failure to receive appropriate antibiotic prophylaxis was associated with an increased risk of SSI (adjusted odds ratio [aOR]: 4.4, 95% confidence interval [CI]: 1.3-15.6) but not endometritis (aOR 0.9, 95% CI 0.4-2.0).

CONCLUSION

Inadequate surgical antibiotic prophylaxis was associated with an increased risk of SSI but not postpartum endometritis, highlighting the different mechanisms of these infections and the importance of prioritizing adequate surgical prophylaxis. Additional potentially modifiable factors which emerged included blood transfusion and chlorhexidine skin preparation.

KEY POINTS

· Inadequate antibiotic prophylaxis is associated with a four-fold risk in surgical site infections.. · The most common cause for failure to achieve adequate surgical prophylaxis was inappropriate timing of antibiotics at or after skin incision.. · Blood transfusions are strongly associated (>10-fold risk) with both SSI and endometritis..

Performance of ICD-10-AM codes for quality improvement monitoring of hospital-acquired pneumonia in a haematology-oncology casemix in Victoria, Australia

BACKGROUND

The Australian hospital-acquired complication (HAC) policy was introduced to facilitate negative funding adjustments in Australian hospitals using ICD-10-AM codes.

OBJECTIVE

The aim of this study was to determine the positive predictive value (PPV) of the ICD-10-AM codes in the HAC framework to detect hospital-acquired pneumonia in patients with cancer and to describe any change in PPV before and after implementation of an electronic medical record (EMR) at our centre.

METHOD

A retrospective case review of all coded pneumonia episodes at the Peter MacCallum Cancer Centre in Melbourne, Australia spanning two time periods (01 July 2015 to 30 June 2017 [pre-EMR period] and 01 September 2020 to 28 February 2021 [EMR period]) was performed to determine the proportion of events satisfying standardised surveillance definitions.

RESULTS

HAC-coded pneumonia occurred in 3.66% (n = 151) of 41,260 separations during the study period. Of the 151 coded pneumonia separations, 27 satisfied consensus surveillance criteria, corresponding to an overall PPV of 0.18 (95% CI: 0.12, 0.25). The PPV was approximately three times higher following EMR implementation (0.34 [95% CI: 0.19, 0.53] versus 0.13 [95% CI: 0.08, 0.21]; p = .013).

CONCLUSION

The current HAC definition is a poor-to-moderate classifier for hospital-acquired pneumonia in patients with cancer and, therefore, may not accurately reflect hospital-level quality improvement. Implementation of an EMR did enhance case detection, and future refinements to administratively coded data in support of robust monitoring frameworks should focus on EMR systems.

IMPLICATIONS

Although ICD-10-AM data are readily available in Australian healthcare settings, these data are not sufficient for monitoring and reporting of hospital-acquired pneumonia in haematology-oncology patients.

The National Healthcare Safety Network's digital quality measures: CDC's automated measures for surveillance of patient safety

OBJECTIVE

This article presents the National Healthcare Safety Network (NHSN)'s approach to automation for public health surveillance using digital quality measures (dQMs) via an open-source tool (NHSNLink) and piloting of this approach using real-world data in a newly established collaborative program (NHSNCoLab). The approach leverages Health Level Seven Fast Healthcare Interoperability Resources (FHIR) application programming interfaces to improve data collection and reporting for public health and patient safety beginning with common, clinically significant, and preventable patient harms, such as medication-related hypoglycemia, healthcare facility-onset Clostridioides difficile infection, and healthcare-associated venous thromboembolism.

CONCLUSIONS

The NHSN's FHIR dQMs hold the promise of minimizing the burden of reporting, improving accuracy, quality, and validity of data collected by NHSN, and increasing speed and efficiency of public health surveillance.

Healthcare-associated infections and conditions in the era of digital measurement

As the third edition of the Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals is released with the latest recommendations for the prevention and management of healthcare-associated infections (HAIs), a new approach to reporting HAIs is just beginning to unfold. This next generation of HAI reporting will be fully electronic and based largely on existing data in electronic health record (EHR) systems and other electronic data sources. It will be a significant change in how hospitals report HAIs and how the Centers for Disease Control and Prevention (CDC) and other agencies receive this information. This paper outlines what that future electronic reporting system will look like and how it will impact HAI reporting.

Incidence and risk factors of surgical site infection in patients with head and neck cancer: A meta-analysis

We systematically review the incidence and risk factors of surgical site infection (SSI) in patients with head and neck cancer. PubMed, Embase, Cochrane Library, and Web of Science databases were searched to obtain studies on the risk factors for SSI in patients with HNC. The retrieval time was from the establishment of the database to February 2023. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias in included studies. Meta-analysis was performed by using Stata 15.1 software. A total of 32 articles including 128 919 patients with head and neck cancer and 2949 cases of SSI were included in this meta-analysis. The incidence rate of SSI in head and neck cancer ranges from 19% to 29%, and the overall infection rate was 24%. Meta-analysis indicated that BMI < 20 kg/m2 (OR, 2.64; 95% CI, 1.74-4.00; I2 , 0%), diabetes (OR, 3.00; 95% CI, 2.12-4.16; I2 , 60.6%), ASA score (OR, 1.51; 95% CI, 1.29-1.77; I2 , 0%), radiotherapy (OR, 2.27; 95% CI, 1.87-2.77; I2 , 44.8%), chemotherapy (OR, 2.36; 95% CI, 1.64-3.40; I2 , 0%), clindamycin antibiotic (OR, 2.99; 95% CI, 1.82-2.93; I2 , 36.5%), deficit repair (OR, 3.76; 95% CI, 1.22-11.59; I2 , 91.4%), neck dissection (OR, 2.13; 95% CI, 1.63-2.79; I2 , 16.4%), blood transfusion (OR, 2.29; 95% CI, 1.52-3.45; I2 , 66.2%), mandibular (OR, 3.17; 95% CI, 1.85-5.42; I2 , 73%), tracheostomy (OR, 2.51; 95% CI, 1.74-3.62; I2 , 86.4%), operation time (OR, 1.42; 95% CI, 1.16-1.74; I2 , 86.4%), ALB (OR, 2.48; 95% CI, 1.95-3.15; I2 , 5.3%) were risk factors of surgical site infection in patients with head and neck cancer (p < 0.05). The results of the sensitivity analysis showed good agreement in all risk factors and the results had stability. The present meta-analysis suggests that BMI < 20 kg/m2 , diabetes, ASA score, radiotherapy, chemotherapy, clindamycin antibiotic, deficit repair, neck dissection, blood transfusion, mandibular, tracheostomy, operation time, and ALB were significant risk factors for SSI.

Delayed Presentation and Referral Time from General Practitioners Contribute to Increased Complicated Appendicitis during the Initial COVID-19 Pandemic Period in Japan

Objectives

This study aims to investigate the impact of the coronavirus disease 2019 (COVID-19) pandemic on the situation of acute appendicitis (AA) with respect to patients' and general practitioners' behaviors in a general community hospital in Japan.

Methods

The surgical outcomes and periods from symptom onset to medical presentation besides practitioners' referral time for consecutive AA patients were compared between the control (January 2016 to March 2020) and COVID-19 periods (April 2020 to April 2021).

Results

Eighty-three patients who underwent emergency surgery for AA were reviewed. Complicated appendicitis significantly increased in the COVID-19 period (63.6% vs. 31.2%, P = 0.023). In the COVID-19 period, the time from symptom onset to the medical presentation (2.2 vs. 0.9 days, P < 0.001) was significantly longer than in the control period. Among the patients who first presented to a general practitioner, the referral time from the practitioner to our hospital was significantly longer in the COVID-19 period (1.6 vs. 0.7 days, P = 0.017). Furthermore, among patients with a fever of higher than 38°C at medical presentation, the time from symptom onset to medical presentation was significantly longer in the COVID-19 period (3.0 vs. 0.7 days, P = 0.015). There was no difference in severe postoperative complications.

Conclusions

Hesitation to seek surgical treatment for AA was seen in both the patients and practitioners in the COVID-19 period. The delay in surgical treatment presumably led to the increase in severe AA. In a pandemic era, timely care for emergent conditions is a crucial challenge.

Validating administrative data to identify complex surgical site infections following cardiac implantable electronic device implantation: a comparison of traditional methods and machine learning

Background

Cardiac implantable electronic device (CIED) surgical site infections (SSIs) have been outpacing the increases in implantation of these devices. While traditional surveillance of these SSIs by infection prevention and control would likely be the most accurate, this is not practical in many centers where resources are constrained. Therefore, we explored the validity of administrative data at identifying these SSIs.

Methods

We used a cohort of all patients with CIED implantation in Calgary, Alberta where traditional surveillance was done for infections from Jan 1, 2013 to December 31, 2019. We used this infection subgroup as our “gold standard” and then utilized various combinations of administrative data to determine which best optimized the sensitivity and specificity at identifying infection. We evaluated six approaches to identifying CIED infection using administrative data, which included four algorithms using International Classification of Diseases codes and/or Canadian Classification of Health Intervention codes, and two machine learning models. A secondary objective of our study was to assess if machine learning techniques with training of logistic regression models would outperform our pre-selected codes.

Results

We determined that all of the pre-selected algorithms performed well at identifying CIED infections but the machine learning model was able to produce the optimal method of identification with an area under the receiver operating characteristic curve (AUC) of 96.8%. The best performing pre-selected algorithm yielded an AUC of 94.6%.

Conclusions

Our findings suggest that administrative data can be used to effectively identify CIED infections. While machine learning performed the most optimally, in centers with limited analytic capabilities a simpler algorithm of pre-selected codes also has excellent yield. This can be valuable for centers without traditional surveillance to follow trends in SSIs over time and identify when rates of infection are increasing. This can lead to enhanced interventions for prevention of SSIs.

High Mortality After Total Knee Arthroplasty Periprosthetic Joint Infection is Related to Preoperative Morbidity and the Disease Process but Not Treatment

BACKGROUND

Periprosthetic joint infection (PJI) mortality rate is approximately 20%. The etiology for high mortality remains unknown. The objective of this study was to determine whether mortality was associated with preoperative morbidity (frailty), sequalae of treatment, or the PJI disease process itself.

METHODS

A multicenter observational study was completed comparing 184 patients treated with septic revision total knee arthroplasty (TKA) to a control group of 38 patients treated with aseptic revision TKA. Primary outcomes included time and the cause of death. Secondary outcomes included preoperative comorbidities and Charlson Comorbidity Index (CCMI) measured preoperatively and at various postoperative timepoints.

RESULTS

The septic revision TKA cohort experienced earlier mortality compared to the aseptic cohort, with a higher mortality rate at 90 days, 1, 2, and 3 years after index revision surgery (P = .01). There was no significant difference for any single cause of death (P > .05 for each). The mean preoperative CCMI was higher (P = .005) in the septic revision TKA cohort. Both septic and aseptic cohorts experienced a significant increase in CCMI from the preoperative to 3 years postoperative (P < .0001 and P = .002) and time of death (P < .0001 both) timepoints. The septic revision TKA cohort had a higher CCMI 3 years postoperatively (P = .001) and at time of death (P = .046), but not one year postoperatively (P = .119).

CONCLUSION

Compared to mortality from aseptic revision surgery, septic revision TKA is associated with earlier mortality, but there is no single specific etiology. As quantified by changes in CCMI, PJI mortality was associated with both frailty and the PJI disease process, but not treatment.

Strategies to prevent ventilator-associated pneumonia, ventilator-associated events, and nonventilator hospital-acquired pneumonia in acute-care hospitals: 2022 Update

The purpose of this document is to highlight practical recommendations to assist acute care hospitals to prioritize and implement strategies to prevent ventilator-associated pneumonia (VAP), ventilator-associated events (VAE), and non-ventilator hospital-acquired pneumonia (NV-HAP) in adults, children, and neonates. This document updates the Strategies to Prevent Ventilator-Associated Pneumonia in Acute Care Hospitals published in 2014. This expert guidance document is sponsored by the Society for Healthcare Epidemiology (SHEA), and is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America, the American Hospital Association, the Association for Professionals in Infection Control and Epidemiology, and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise.

Measuring the economic impact of hospital-acquired complications on an acute health service

Objective This study determined the economic impact of 16 'high-priority' hospital-acquired complications (HACs), as defined by the Australian Commission on Safety and Quality in Health Care, from the perspective of an individual Australian health service. Methods A retrospective cohort study was performed using a deidentified patient dataset containing 93056 in-patient separations in Northern Health (Victoria, Australia) from 1 July 2016 to 30 June 2017. Two log-linked generalised linear regression models were used to obtain additional costs and additional length of stay (LOS) for 16 different HACs, with the main outcome measures being the additional cost and LOS for all 16 HACs. Results In all, 1700 separations involving HACs (1.83%) were identified. The most common HAC was health care-associated infections. Most HACs were associated with a statistically significant risk of increased cost (15/16 HACs) and LOS (11/16 HACs). HACs involving falls resulting in fracture or other intracranial injury were associated with the highest additional cost (A$17173). The biggest increase in additional LOS was unplanned admissions to the intensive care unit (5.42 days). Conclusions This study shows the economic impact of HACs from the perspective of an individual health service. The methodology used demonstrates how other health services could determine safety priorities corresponding to their own casemix. What is known about the topic? HACs are a major issue in Australian health care; however, their effect on cost and LOS at the individual health service level is not well quantified. What does this paper add? Additional cost and LOS implications for 16 high-priority HACs have been quantified within an Australian health service. There is substantial variation in terms of the number of HACs and the economic impact of each HAC. What are the implications for practitioners? This study provides a template for other health services to assess the economic impact of HACs corresponding to their own casemix and to inform targeted patient safety programs.

Predicting ventilator-associated pneumonia with machine learning

Ventilator-associated pneumonia (VAP) is the most common and fatal nosocomial infection in intensive care units (ICUs). Existing methods for identifying VAP display low accuracy, and their use may delay antimicrobial therapy. VAP diagnostics derived from machine learning (ML) methods that utilize electronic health record (EHR) data have not yet been explored. The objective of this study is to compare the performance of a variety of ML models trained to predict whether VAP will be diagnosed during the patient stay.A retrospective study examined data from 6126 adult ICU encounters lasting at least 48 hours following the initiation of mechanical ventilation. The gold standard was the presence of a diagnostic code for VAP. Five different ML models were trained to predict VAP 48 hours after initiation of mechanical ventilation. Model performance was evaluated with regard to the area under the receiver operating characteristic (AUROC) curve on a 20% hold-out test set. Feature importance was measured in terms of Shapley values.The highest performing model achieved an AUROC value of 0.854. The most important features for the best-performing model were the length of time on mechanical ventilation, the presence of antibiotics, sputum test frequency, and the most recent Glasgow Coma Scale assessment.Supervised ML using patient EHR data is promising for VAP diagnosis and warrants further validation. This tool has the potential to aid the timely diagnosis of VAP.

Evaluation of the accuracy of diagnostic coding for influenza compared to laboratory results: the availability of test results before hospital discharge facilitates improved coding accuracy

Background

Assessing the accuracy of diagnostic coding is essential to ensure the validity and reliability of administrative coded data. The aim of the study was to evaluate the accuracy of assigned International Classification of Diseases version 10-Australian Modification (ICD-10-AM) codes for influenza by comparing with patients’ results of their polymerase chain reaction (PCR)-based laboratory tests.

Method

A retrospective study was conducted across seven public hospitals in New South Wales, Australia. A total of 16,439 patients who were admitted and tested by either cartridge-based rapid PCR or batched multiplex PCR between January 2016 and December 2017 met the inclusion criteria. We calculated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of ICD-10-AM coding using laboratory results as a gold standard. Separate analyses were conducted to determine whether the availability of test results at the time of hospital discharge influenced diagnostic coding accuracy.

Results

Laboratory results revealed 2759 positive influenza cases, while ICD-10-AM coding identified 2527 patients. Overall, 13.7% (n = 378) of test positive patients were not assigned an ICD-10-AM code for influenza. A further 5.8% (n = 146) patients with negative test results were incorrectly assigned an ICD-10-AM code for influenza. The sensitivity, specificity, PPV and NPV of ICD-10-AM coding were 93.1%; 98.9%; 94.5% and 98.6% respectively when test results were received before discharge and 32.7%; 99.2%; 87.8% and 89.8% respectively when test results were not available at discharge. The sensitivity of ICD-10-AM coding varied significantly across hospitals. The use of rapid PCR or hospitalisation during the influenza season were associated with greater coding accuracy.

Conclusion

Although ICD-10-AM coding for influenza demonstrated high accuracy when laboratory results were received before discharge, its sensitivity was substantially lower for patients whose test results were not available at discharge. The timely availability of laboratory test results during the episode of care could contribute to improved coding accuracy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-021-01531-9.

Changes in the accuracy of administrative data for the detection of surgical site infections

We performed a retrospective analysis of the changes in accuracy of International Classification of Diseases, Clinical Modification (ICD-CM) diagnosis codes for colectomy and hysterectomy surgical site infection surveillance. After the transition from ICD-CM ninth edition to tenth edition codes, there was no significant change in the accuracy of these codes for SSI surveillance.

Total cost of surgical site infection in the two years following primary knee replacement surgery

Objective:

The disease burden of surgical site infection (SSI) following total knee (TKA) replacement is considerable and is expected to grow with increased demand for the procedure. Diagnosing and treating SSI utilizes both inpatient and outpatient services, and the timing of diagnosis can affect health service requirements. The purpose of this study was to estimate the health system costs of infection and to compare them across time-to-diagnosis categories.

Methods:

Administrative data from 2005–2016 were used to identify cases diagnosed with SSI up to 1 year following primary TKA. Uninfected controls were selected matched on age, sex and comorbidities. Costs and utilization were measured over the 2-year period following surgery using hospital and out-of-hospital data. Costs and utilization were compared for those diagnosed within 30, 90, 180, and 365 days. A subsample of cases and controls without comorbidities were also compared.

Results:

We identified 238 SSI cases over the study period. On average, SSI cases cost 8 times more than noninfected controls over the 2-year follow-up period (CaD$41,938 [US$29,965] vs CaD$5,158 [US$3,685]) for a net difference of CaD$36,780 (US$26,279). The case-to-control ratio for costs was lowest for those diagnosed within 30 days compared to those diagnosed later. When only patients without comorbidities were included, costs were >7 times higher.

Conclusion:

Our results suggest that considerable costs result from SSI following TKA and that those costs vary depending on the time of diagnosis. A 2-year follow-up period provided a more complete estimate of cost and utilization.

Early Enteral Nutrition in Patients Undergoing Sustained Neuromuscular Blockade: A Propensity-Matched Analysis Using a Nationwide Inpatient Database

OBJECTIVES

Whether enteral nutrition should be postponed in patients undergoing sustained treatment with neuromuscular blocking agents remains unclear. We evaluated the association between enteral nutrition initiated within 2 days of sustained neuromuscular blocking agent treatment and in-hospital mortality.

DESIGN

Retrospective administrative database study from July 2010 to March 2016.

SETTING

More than 1,200 acute care hospitals covering approximately 90% of all tertiary-care emergency hospitals in Japan.

PATIENTS

Mechanically ventilated patients, who had undergone sustained treatment with neuromuscular blocking agents in an ICU, were retrospectively reviewed. We defined patients who received sustained treatment with neuromuscular blocking agents as those who received either rocuronium at greater than or equal to 250 mg/d or vecuronium at greater than or equal to 50 mg/d for at least 2 consecutive days.

INTERVENTIONS

Enteral nutrition started within 2 days from the initiation of neuromuscular blocking agents (defined as early enteral nutrition).

MEASUREMENTS AND MAIN RESULTS

We identified 2,340 eligible patients during the 69-month study period. Of these, 378 patients (16%) had received early enteral nutrition. One-to-three propensity score matching created 374-1,122 pairs. The in-hospital mortality rate was significantly lower in the early than late enteral nutrition group (risk difference, -6.3%; 95% CI, -11.7% to -0.9%). There was no significant difference in the rate of hospital pneumonia between the two groups (risk difference, 2.8%; 95% CI, -2.7% to 8.3%). Length of hospital stay among survivors was significantly shorter in the early compared with the late enteral nutrition group (risk difference, -11.4 d; 95% CI, -19.1 to -3.7 d). There was no significant difference between the two groups in length of ICU stay or length of mechanical ventilation among survivors.

CONCLUSIONS

According to this retrospective database study, early enteral nutrition may be associated with lower in-hospital mortality with no increase in-hospital pneumonia in patients undergoing sustained treatment with neuromuscular blocking agents.

Burden and clinical outcomes of hospital-coded infections in patients with cancer: an 11-year longitudinal cohort study at an Australian cancer centre

PURPOSE

Patients with cancer are at increased risk for infection, but the relative morbidity and mortality of all infections is not well understood. The objectives of this study were to determine the prevalence, incidence, time-trends and risk of mortality of infections associated with hospital admissions in patients with haematological- and solid-tumour malignancies over 11 years.

METHODS

A retrospective, longitudinal cohort study of inpatient admissions between 1 January 2007 and 31 December 2017 at the Peter MacCallum Cancer Centre was conducted using administratively coded and patient demographics data. Descriptive analyses, autoregressive integrated moving average, Kaplan-Meier and Cox regression modelling were applied.

RESULTS

Of 45,116 inpatient hospitalisations consisting of 3033 haematological malignancy (HM), 18,372 solid tumour neoplasm (STN) patients and 953 autologous haematopoietic stem cell transplantation recipients, 67%, 29% and 88% were coded with ≥ 1 infection, respectively. Gastrointestinal tract and bloodstream infections were observed with the highest incidence, and bloodstream infection rates increased significantly over time in both HM- and STN-cohorts. Inpatient length of stay was significantly higher in exposed patients with coded infection compared to unexposed in HM- and STN-cohorts (22 versus 4 days [p < 0.001] and 15 versus 4 days [p < 0.001], respectively). Risk of in-hospital mortality was higher in exposed than unexposed patients in the STN-cohort (adjusted hazard ratio [aHR] 1.61 [95% CI 1.41-1.83]; p < 0.001)) and HM-cohort (aHR 1.30 [95% CI 0.90-1.90]; p = 0.166).

CONCLUSION

Infection burden among cancer patients is substantial and findings reflect the need for targeted surveillance in high-risk patient groups (e.g. haematological malignancy), in whom enhanced monitoring may be required to support infection prevention strategies.

Use of Computerized Provider Order Entry Events for Postoperative Complication Surveillance

Importance

Conventional approaches for tracking postoperative adverse events requires manual medical record review, thus limiting the scalability of such efforts.

Objective

To determine if a surveillance system using computerized provider order entry (CPOE) events for selected medications as well as laboratory, microbiologic, and radiologic orders can decrease the manual medical record review burden for surveillance of postoperative complications.

Design, Setting, and Participants

This cohort study reviewed the medical records of 21 775 patients who underwent surgical procedures at a university-based tertiary referral center (University of Utah, Salt Lake City) from July 1, 2007, to August 31, 2017. Patients were included if their case was selected for review by a surgical clinical reviewer as part of the National Surgical Quality Improvement Program. Patients were excluded if they had incomplete follow-up data.

Main Outcomes and Measures

Thirty-day postoperative occurrences of superficial surgical site infection, deep surgical site infection, organ space surgical site infection, urinary tract infection, pneumonia, sepsis, septic shock, deep vein thrombosis requiring therapy, and pulmonary embolism, as defined by the National Surgical Quality Improvement Program. A logistic regression model was developed for each postoperative complication using CPOE features as predictors on a development set, and performance was measured on a holdout internal validation set. The models were internally validated using bootstrapping with 10 000 replications to determine the sensitivity, specificity, positive predictive value, and negative predictive value of CPOE-based surveillance system.

Results

The study included 21 775 patients who underwent surgical procedures. Among these patients, 11 855 (54.4%) were women and 9920 (45.6%) were men, with a mean (SD) age of 51.7 (16.8) years. Overall, the prevalence of postoperative complications was low, ranging from 0.2% (pulmonary embolism) to 2.6% (superficial surgical site infection). Use of CPOE events to detect patients who experienced at least 1 complication had a sensitivity of 74.8% (95% CI, 71.1%-78.4%), specificity of 86.8% (95% CI, 85.5%-88.3%), positive predictive value of 33.8% (95% CI, 31.2%-36.4%), negative predictive value of 97.5% (95% CI, 97.1%-97.8%), and area under the curve of 0.808 (95% CI, 0.791-0.824). The negative predictive value for individual complications ranged from 98.7% to 100%. Use of CPOE events to screen for adverse events was estimated to diminish the burden of manual medical record review by 55.4% to 90.3%. A CPOE-based surveillance system performed well for both inpatient and outpatient procedures.

Conclusions and Relevance

A CPOE-based surveillance of postoperative complications has high negative predictive value, which demonstrates that this approach can augment the currently used, resource-intensive manual medical record review process.

Measuring Surgical Site Infection From Linked Administrative Data Following Hip and Knee Replacement

BACKGROUND

Surgical site infections (SSIs) in hip and knee arthroplasty are increasing internationally. Current trends in SSI monitoring use single source administrative databases with data collection points commonly at 30 or 90 days. We hypothesize that SSI rates are being under-reported due to methodological biases.

METHODS

Data from multiple administrative data sets were contrasted and compared to look at the 90-day SSI rates for hip and knee arthroplasty in a single province from 2001 to 2015. SSI rates were calculated over time by year, and the differences in infection rates between single and multiple administrative data sets were calculated as an estimate of under reporting rates of SSIs. Days until diagnosis was measured for those diagnosed with an infection within 1 year.

RESULTS

Combining administrative data sets indicates that hospital-based data underestimate SSI rates by 0.44 (P < .0001) of a percentage point over all years, a clinically significant result given the overall infection rate of 2.2% over the period. Less than 50% of hip and knee arthroplasty was recorded as infected by 30 days and approximately 75% of cases were recorded as infected by 90 days.

CONCLUSION

Single source administrative data sets and short follow-up periods underestimate SSI rates. Administrative data sets should be combined and a minimum follow-up period of 90 days should be used to more accurately track SSI rates in hip and knee arthroplasty.

Early enteral nutrition in patients with severe traumatic brain injury: a propensity score-matched analysis using a nationwide inpatient database in Japan

BACKGROUND

Whether enteral nutrition (EN) should be administered early in severe traumatic brain injury (TBI) patients has not been fully addressed.

OBJECTIVE

The present study aimed to evaluate whether early EN can reduce mortality or nosocomial pneumonia among severe TBI patients.

METHODS

Using the Japanese Diagnosis Procedure Combination inpatient database from April 2014 to March 2017 linked with the Survey for Medical Institutions, we identified patients admitted for intracranial injury with Japan Coma Scale scores ≥30 (corresponding to Glasgow Coma Scale scores ≤8) at admission. We designated patients who started EN within 2 d of admission as the early EN group, and those who started EN at 3-5 d after admission as the delayed EN group. The primary outcome was in-hospital mortality. The secondary outcome was nosocomial pneumonia. Propensity score-matched analyses were performed to compare the outcomes between the 2 groups.

RESULTS

We identified 3080 eligible patients during the 36-mo study period, comprising 1100 (36%) in the early EN group and 1980 (64%) in the delayed EN group. After propensity score matching, there was no significant difference in in-hospital mortality (difference: -0.3%; 95% CI: -3.7%, 3.1%) between the 2 groups. The proportion of nosocomial pneumonia was significantly lower in the early EN group than in the delayed EN group (difference: -3.2%; 95% CI: -5.9%, -0.4%).

CONCLUSIONS

Early EN may not reduce mortality, but may reduce nosocomial pneumonia in patients with severe TBI.

The association of burn patient volume with patient safety indicators and mortality in the US

INTRODUCTION

Clinical volume has been associated with rate of complications and mortality for various conditions and procedures. We aim to analyze the relationship between annual hospital burn admission, patient safety indicators (PSI), line infections, and inpatient mortality. We hypothesize that high facility volume will correlate with better outcomes.

METHODS

All burn admissions with complete data for total body surface area (TBSA) and depth were extracted from the Nationwide Inpatient Sample from 2002-2011. Predictor variables included age, gender, comorbidities, %TBSA, burn depth, and inhalation injury. Surgically relevant PSIs were drawn from the Healthcare Cost & Utilization Project and included: sepsis, venous thromboembolic disease, hemorrhage, pneumonia, and wound complications. Outcomes were analyzed with regression models.

RESULTS

Of the 57,468 encounters included, 3.1% died, 6.3% experienced >1 PSI event, and 0.3% experienced a catheter-associated urinary tract infections or central line associated blood stream infections. The most frequent PSI was pneumonia followed by sepsis and VTE. Annual hospital burn admission volume was independently associated with decreased odds of mortality (OR 0.99, 95% CI 0.99-0.99, p < 0.001) and PSIs (OR 0.99, 95% CI 0.99-0.99, p = 0.031). There was no significant correlation with line infections. In both mortality and PSI models, age, %TBSA, inhalation injuries, and Elixhauser comorbidity score were significantly associated with adverse outcomes (p < 0.05).

CONCLUSION

There was a significant association between higher hospital volume and decreased likelihood of patient safety indicators and mortality. There was no observed relationship with line infections. These findings could inform future verification policies of US burn centers.

Nurse Staffing and Healthcare-Associated Infection, Unit-Level Analysis

OBJECTIVE

To examine whether healthcare-associated infections (HAIs) and nurse staffing are associated using unit-level staffing data.

BACKGROUND

Previous studies of the association between HAIs and nurse staffing are inconsistent and limited by methodological weaknesses.

METHODS

Cross-sectional data between 2007 and 2012 from a large urban hospital system were analyzed. HAIs were diagnosed using the Centers for Disease Control and Prevention's National Healthcare Safety Network definitions. We used Cox proportional-hazards regression model to examine the association of nurse staffing (2 days before HAI onset) with HAIs after adjusting for individual risks.

RESULTS

Fifteen percent of patient-days had 1 shift understaffed, defined as staffing below 80% of the unit median for a shift, and 6.2% had both day and night shifts understaffed. Patients on units with both shifts understaffed were significantly more likely to develop HAIs 2 days later.

CONCLUSIONS

Understaffing is associated with increased risk of HAIs.

The Cost of Surgical Site Infections after Colorectal Surgery in the United States from 2001 to 2012: A Longitudinal Analysis

Surgical site infections (SSIs) are among the most common types of postoperative complications in the United States and are associated with significant prevalence of morbidity and mortality in patients undergoing surgical interventions, especially in colorectal surgery (CRS) where SSI rates are significantly higher than those of similar operative sites. SSIs were identified from the National Inpatient Sample-Healthcare Cost and Utilization Project database from 2001 to 2012 based on the specification of an ICD-9 code. Propensity score matching was used to compare costs associated with SSI cases with those of non-SSI controls among elective and nonelective admissions. Results were projected nationally using Healthcare Cost and Utilization Project sampling methodology to evaluate the incidence of SSIs and ascertain the national cost burden retrospectively. Among 4,851,359 sample-weighted hospitalizations, 4.2 per cent (203,597) experienced SSI. Elective admissions associated with SSI-stayed hospitalized for an average of 7.8 days longer and cost $18,410 more than their counterparts who did not experience an SSI. Nonelective admissions that experienced an SSI had an 8.5-day longer hospital stay and cost $20,890 more than counterparts without perioperative infections. This represents a 3 per cent annual growth in costs for SSIs and seems to be largely driven by cost increases in treatment of SSIs for elective surgeries. Current efforts of SSI management after CRS focused on compliance with guidelines and tracking of infection rates would benefit from some improvements. Considering the growing costs and increase in resource utilization associated with SSIs from 2001 to 2012, further research on costs associated with management of SSIs specific to CRS is necessary.

Comparison of hospital surgical site infection rates and rankings using claims versus National Healthcare Safety Network surveillance data

National policies target healthcare-associated infections using medical claims and National Healthcare Safety Network surveillance data. We found low concordance between the 2 data sources in rates and rankings for surgical site infection following colon surgery in 155 hospitals, underscoring the limitations in evaluating hospital quality by claims data.

Validity of administrative data in identifying complex surgical site infections from a population-based cohort after primary hip and knee arthroplasty in Alberta, Canada

BACKGROUND

Surgical site infections (SSIs) are a substantial burden to healthcare systems in North America. Administrative data is one method though which these may be identified, but the accuracy of using such data is uncertain.

METHODS

We followed a population-based cohort of patients who received primary hip/knee arthroplasty in Alberta, Canada, for whom a comprehensive Infection Prevention and Control (IPC) prospective surveillance methodology was used to track SSIs. Patients were also followed using International Classification of Diseases, Tenth Revision (ICD-10) codes. We assessed the sensitivity/specificity and positive/negative predictive values of ICD-10 codes compared to IPC surveillance.

RESULTS

Between April 1, 2012, and March 31, 2015, 24,512 people received hip/knee arthroplasty. Of these, 258 (1.05%) had a complex SSI found by IPC surveillance. Sensitivity and specificity of ICD-10 codes in identifying complex SSIs after hip/knee arthroplasty were 85.3% (95% confidence interval [CI] 80.3%-89.4%) and 99.5% (95% CI 99.4%-99.6%), respectively. Positive and negative predictive values were 63.6% (95% CI 58.3%-68.7%) and 99.8% (95% CI 99.8%-99.9%), respectively.

DISCUSSION

Administrative data have reasonable testing characteristics for identifying complex SSIs after arthroplasty. For centers without prospective surveillance programs, this could be useful in identifying hospitals with frequent complex SSIs after arthroplasty.

CONCLUSIONS

A comprehensive IPC surveillance program is superior at detecting SSIs after arthroplasty.

Increased Risk of Complications After Pancreatoduodenectomy in Uninephrectomized Patients

Objective:

The study objective is to investigate the impact of unilateral nephrectomy on the complications after pancreatoduodenectomy (PD).

Summary of background data:

Preoperative renal insufficiency is a risk factor for postoperative complications and mortality after various types of surgery. However, the specific postoperative risks in uninephrectomized (UN) patients are largely unknown.

Methods:

Between January 2010 and June 2014, a total of 177 patients underwent PD at the Department of Surgery, Nara Medical University. Among them, 7 patients (4.0%) were UN. We retrospectively evaluated the influence of the UN status on the postoperative complications.

Results:

The rate of acute kidney injury in the UN group was significantly higher than that in the control group (28.6% versus 1.2%; P = 0.017). In addition, the rates of surgical site infection of the organ/space (57.1% versus 9.0%; P = 0.006) and sepsis (42.9% versus 3.5%; P = 0.003) in UN group were significantly higher. Even on a reanalysis of only patients with soft pancreas, the significance remained.

Conclusions:

The UN status has a significant impact on the rate of morbidities, such as acute kidney injury and various infectious complications, including surgical site infections of organ/space, sepsis, and cholangitis after PD. Appropriate intervention should be implemented to decrease the morbidity rate for UN patients.

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.

Validation of an electronic tool for flagging surgical site infections based on clinical practice patterns for triaging surveillance: Operational successes and barriers

BACKGROUND

Surveillance is an effective strategy for reducing surgical site infections (SSIs); however, current identification methods are resource-intensive. Therefore, we sought to validate an electronic SSI triaging tool for detection of probable infections and identify operational barriers and challenges.

METHODS

A retrospective cohort study was conducted among all Veterans Affairs Surgical Quality Improvement Program (VASQIP)-reviewed surgeries at 2 Veterans Affairs medical centers from October 1, 2011-September 30, 2014. During the postoperative period, clinical and administrative variables associated with SSI (relevant microbiology order, antibiotic order, radiology order, and administrative codes) were extracted from the electronic medical record and used to score the probability (high, intermediate, and low) that an SSI occurred. VASQIP manual chart review was used as the gold standard of comparison.

RESULTS

VASQIP manual review identified 118 SSIs out of 3,700 surgeries (3.2%). There were 2,041, 1,428, and 231 surgeries that met criteria for low, intermediate, and high probability for SSI. The tool's area under the curve was 0.86 (95% confidence interval, 0.82-0.89). The sensitivity among low-probability surgeries was 92.4%, and the specificity among high-probability surgeries was 95.1%.

CONCLUSIONS

The electronic SSI tool has the potential to be used for triaging VASQIP surveillance toward the high-probability surgeries and to avoid manual review of surgeries with low probability of SSI.

The Implications of Inaccuracy: Comparison of Coding in Heterotopic Ossification and Associated Trauma

Retrospective studies using large databases serve a major purpose in providing evidence in the current literature. However, the quality of medical coding is highly variable. This retrospective cohort study aimed to evaluate the documentation regarding the diagnosis of heterotopic ossification (HO) and the implications it may have for conducting retrospective research using electronic medical records (EMRs). A retrospective chart review using the EMR was performed to identify all patients with a diagnosis of HO within 7 university-affiliated hospital facilities. A limited data set request was conducted for all patients with HO-specific International Classification of Diseases, Ninth Revision (ICD-9) codes and additional nonspecific musculoskeletal codes to capture patients with HO who were improperly coded. A total of 522 patients were identified-26 patients with specific HO codes and 496 patients with nonspecific codes. Imaging and clinical notes were inspected for evidence and location of HO, and histories were reviewed for traumatic injury mechanism. Two-thirds of the patients with HO were discovered by reviewing miscellaneous musculoskeletal ICD-9 codes. Thirty-eight percent of the patients with an HO-specific ICD-9 code had no evidence of HO in their EMR. Thirty-three patients had a clinical history of a traumatic injury preceding HO formation, but only 16 of the 33 had documented ICD-9 codes for the injury. The utility of databases in retrospective research is dependent on the integrity of the coding. This study questions the use of retrospective reviews for patients with uncommon diagnoses and shows how painstaking verification may be necessary to ensure that research conclusions are based on accurate data. [Orthopedics. 2017; 40(4):237-241.].

[The use of administrative health databases in infectious disease epidemiology and public health]

BACKGROUND

The public health burden resulting from infectious diseases requires efforts in surveillance and evaluation of health care. The use of administrative health databases (AHD) and in particular the French national health insurance database (SNIIRAM) is an opportunity to improve knowledge in this field. The SNIIRAM data network (REDSIAM) workshop dedicated to infectious diseases conducted a narrative literature review of studies using French AHD. From the results, benefits and limits of these new tools in the field of infectious diseases are presented.

METHODS

Publications identified by the members of the workgroup were collected using an analytical framework that documented the pathology of interest, the aim of the study, the goal of the developed algorithm, the kind of data, the study period, and the presence of an evaluation or a discussion of the performance of the performed algorithm.

RESULTS

Fifty-five articles were identified. A majority focused on the field of vaccination coverage and joint infections. Excluding vaccine coverage field, the aim of 28 studies was epidemiological surveillance. Twenty-six studies used hospital databases exclusively, 18 used ambulatory databases exclusively and 4 used both. Validation or discussion of the performed algorithm was present in 18 studies.

CONCLUSIONS

The literature review confirmed the interest of the French AHD in the infectious diseases field. The AHD are additional tools of the existing surveillance systems and their use will probably be more frequent in the coming years given their advantage and reliability. However, incoming users need to be assisted. Thus, the workgroup will contribute to a reasonable use of AHD and support future developments.

The Seasonal Variability in Surgical Site Infections and the Association With Warmer Weather: A Population-Based Investigation

OBJECTIVE To determine whether the seasonality of surgical site infections (SSIs) can be explained by changes in temperature. DESIGN Retrospective cohort analysis. SETTING The National Inpatient Sample database. PATIENTS All hospital discharges with a primary diagnosis of SSI from 1998 to 2011 were considered cases. Discharges with a primary or secondary diagnoses of specific surgeries commonly associated with SSIs from the previous and current month served as our "at risk" cohort. METHODS We modeled the national monthly count of SSI cases both nationally and stratified by region, sex, age, and type of institution. We used data from the National Climatic Data Center to estimate the monthly average temperatures for all hospital locations. We modeled the odds of having a primary diagnosis of SSI as a function of demographics, payer, location, patient severity, admission month, year, and the average temperature in the month of admission. RESULTS SSI incidence is highly seasonal, with the highest SSI incidence in August and the lowest in January. During the study period, there were 26.5% more cases in August than in January (95% CI, 23.3-29.7). Controlling for demographic and hospital-level characteristics, the odds of a primary SSI admission increased by roughly 2.1% per 2.8°C (5°F) increase in the average monthly temperature. Specifically, the highest temperature group, >32.2°C (>90°F), was associated with an increase in the odds of an SSI admission of 28.9% (95% CI, 20.2-38.3) compared to temperatures <4.4°C (<40°F). CONCLUSIONS At population level, SSI risk is highly seasonal and is associated with warmer weather. Infect Control Hosp Epidemiol 2017;38:809-816.

In-Hospital Mortality in Patients With Periprosthetic Joint Infection

BACKGROUND

While periprosthetic joint infection (PJI) has a huge impact on patient function and health, only a few studies have investigated its impact on mortality. The purpose of this large-scale study was to (1) determine the rate and trends of in-hospital mortality for PJI and (2) compare the in-hospital mortality rate of patients with PJI and those undergoing revision arthroplasty for aseptic failure and patients undergoing other nonorthopedic major surgical procedures.

METHODS

Data from the Nationwide Inpatient Sample from 2002 to 2010 were analyzed to determine the risk of in-hospital mortality for PJI patients compared with aseptic revision arthroplasty. The Elixhauser comorbidity index was used to obtain patient comorbidities. Multiple logistic regression analyses were used to examine whether PJI and other patient-related factors were associated with mortality.

RESULTS

PJI was associated with an increased risk (odds ratio, 2.05; P < .0001) of in-hospital mortality (0.77%) compared with aseptic revisions (0.38%). The in-hospital mortality rate of revision total hip arthroplasties with PJI was higher than those for interventional coronary procedures (1.22%; 95% confidence interval [CI], 1.20-1.24), cholecystectomy (1.13%; 95% CI, 1.11-1.15), kidney transplant (0.70%; 95% CI, 0.61-0.79), and carotid surgery (0.89%; 95% CI, 0.86-0.93).

CONCLUSION

Patients undergoing treatment for PJI have a 2-fold increase in in-hospital mortality for each surgical admission compared to aseptic revisions. Considering that PJI cases often have multiple admissions and that this analysis is by surgical admission, the risk of mortality will accumulate for every additional surgery. Surgeons should be cognizant of the potentially fatal outcome of PJI and the importance of infection control to reduce the risk of mortality.

Potentially Preventable Hospitalizations and the Burden of Healthcare-Associated Infections

BACKGROUND

An estimated 4% of hospital admissions acquired healthcare-associated infections (HAIs) and accounted for $9.8 (USD) billion in direct cost during 2011. In 2010, nearly 140 000 of the 3.5 million potentially preventable hospitalizations (PPHs) may have acquired an HAI. There is a knowledge gap regarding the co-occurrence of these events.

AIMS

To estimate the period occurrences and likelihood of acquiring an HAI for the PPH population.

METHODS

Retrospective, cross-sectional study using logistic regression analysis of 2011 Texas Inpatient Discharge Public Use Data File including 2.6 million admissions from 576 acute care hospitals. Agency for Healthcare Research and Quality Prevention Quality Indicator software identified PPH, and existing administrative data identification methodologies were refined for Clostridium difficile infection, central line-associated bloodstream infection, catheter-associated urinary tract infection, and ventilator-associated pneumonia. Odds of acquiring HAIs when admitted with PPH were adjusted for demographic, health status, hospital, and community characteristics.

FINDINGS

We identified 272 923 PPH, 14 219 HAI, and 986 admissions with PPH and HAI. Odds of acquiring an HAI for diabetic patients admitted for lower extremity amputation demonstrated significantly increased odds ratio of 2.9 (95% confidence interval: 2.16-3.91) for Clostridium difficile infection. Other PPH patients had lower odds of acquiring HAI compared to non-PPH patients, and results were frequently significant.

CONCLUSIONS

Clinical implications include increased risk of HAI among diabetic patients admitted for lower extremity amputation. Methodological implications include identification of rare events for inpatient subpopulations and the need for improved codification of HAIs to improve cost and policy analyses regarding allocation of resources toward clinical improvements.

Validation of ICD-9-CM Diagnosis Codes for Surgical Site Infection and Noninfectious Wound Complications After Mastectomy

BACKGROUND Few studies have validated ICD-9-CM diagnosis codes for surgical site infection (SSI), and none have validated coding for noninfectious wound complications after mastectomy. OBJECTIVES To determine the accuracy of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes in health insurer claims data to identify SSI and noninfectious wound complications, including hematoma, seroma, fat and tissue necrosis, and dehiscence, after mastectomy. METHODS We reviewed medical records for 275 randomly selected women who were coded in the claims data for mastectomy with or without immediate breast reconstruction and had an ICD-9-CM diagnosis code for a wound complication within 180 days after surgery. We calculated the positive predictive value (PPV) to evaluate the accuracy of diagnosis codes in identifying specific wound complications and the PPV to determine the accuracy of coding for the breast surgical procedure. RESULTS The PPV for SSI was 57.5%, or 68.9% if cellulitis-alone was considered an SSI, while the PPV for cellulitis was 82.2%. The PPVs of individual noninfectious wound complications ranged from 47.8% for fat necrosis to 94.9% for seroma and 96.6% for hematoma. The PPVs for mastectomy, implant, and autologous flap reconstruction were uniformly high (97.5%-99.2%). CONCLUSIONS Our results suggest that claims data can be used to compare rates of infectious and noninfectious wound complications after mastectomy across facilities, even though PPVs vary by specific type of postoperative complication. The accuracy of coding was highest for cellulitis, hematoma, and seroma, and a composite group of noninfectious complications (fat necrosis, tissue necrosis, or dehiscence). Infect Control Hosp Epidemiol 2017;38:334-339.

Research Methods in Healthcare Epidemiology and Antimicrobial Stewardship: Use of Administrative and Surveillance Databases

Administrative and surveillance data are used frequently in healthcare epidemiology and antimicrobial stewardship (HE&AS) research because of their wide availability and efficiency. However, data quality issues exist, requiring careful consideration and potential validation of data. This methods paper presents key considerations for using administrative and surveillance data in HE&AS, including types of data available and potential use, data limitations, and the importance of validation. After discussing these issues, we review examples of HE&AS research using administrative data with a focus on scenarios when their use may be advantageous. A checklist is provided to help aid study development in HE&AS using administrative data.

Infect Control Hosp Epidemiol 2016;1–10

Can additional information be obtained from claims data to support surgical site infection diagnosis codes?

OBJECTIVE

International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes are increasingly used to identify healthcare-associated infections, often with insufficient evidence demonstrating validity of the codes used. Absent medical record verification, we sought to confirm a claims algorithm to identify surgical site infections (SSIs) by examining the presence of clinically expected SSI treatment.

METHODS

We performed a retrospective cohort study, using private insurer claims data from persons less than 65 years old with ICD-9-CM procedure or Current Procedure Terminology (CPT-4) codes for anterior cruciate ligament (ACL) reconstruction from January 2004 through December 2010. SSIs occurring within 90 days after ACL reconstruction were identified by ICD-9-CM diagnosis codes. Antibiotic utilization, surgical treatment, and microbiology culture claims within 14 days of SSI codes were used as evidence to support the SSI diagnosis.

RESULTS

Of 40,702 procedures, 401 (1.0%) were complicated by SSI, 172 (0.4%) of which were specifically identified as septic arthritis. Most SSIs were associated with an inpatient admission (232/401 [58%]), and/or surgical procedure(s) for treatment (250/401 [62%]). Temporally associated antibiotics, surgical treatment procedures, and cultures were present for 84% (338/401), 61% (246/401), and 59% (238/401), respectively. Only 5.7% (23/401) of procedures coded for SSI after the procedure had no antibiotics, surgical treatments, or cultures within 14 days of the SSI claims.

CONCLUSIONS

More than 94% of patients identified by our claims algorithm as having an SSI received clinically expected treatment for infection, including antibiotics, surgical treatment, and culture, suggesting that this algorithm has very good positive predictive value. This method may facilitate retrospective SSI surveillance and comparison of SSI rates across facilities and providers.

Quality Assessment of Hospital Discharge Database for Routine Surveillance of Hip and Knee Arthroplasty–Related Infections

Objective.

Surgical site infection (SSI) surveillance represents a key method of nosocomial infection control programs worldwide. However, most SSI surveillance systems are considered to be poorly cost effective regarding human and economic resources required for data collection and patient follow up. This study aims to assess the efficacy of using hospital discharge databases (HDDs) as a routine surveillance system for detecting hip or knee arthroplasty–related infections (HKAIs).

Methods.

A case-control study was conducted among patients hospitalized in the Centre region of France between 2008 and 2010. HKAI cases were extracted from the HDD with various algorithms based on the International Classification of Diseases, Tenth Revision, and procedure codes. The control subjects were patients with hip or knee arthroplasty (HKA) without infection selected at random from the HDD during the study period. The gold standard was medical chart review. Sensitivity (Se), specificity (Spe), positive predictive value (PPV), and negative predictive value (NPV) were calculated to evaluate the efficacy of the surveillance system.

Results.

Among 18,265 hospital stays for HKA, corresponding to 17,388 patients, medical reports were checked for 1,010 hospital stays (989 patients). We identified 530 cases in total (incidence rate, 1% [95% confidence interval (CI), 0.4%–1.6%), and 333 cases were detected by routine surveillance. As compared with 480 controls, Se was 98%, Spe was 71%, PPV was 63%, and NPV was 99%. Using a more specific case definition, based on a sample of 681 hospital stays, Se was 97%, Spe was 95%, PPV was 87%, and NPV was 98%.

Conclusions.

This study demonstrates the potential of HDD as a tool for routine SSI surveillance after low-risk surgery, under conditions of having an appropriate algorithm for selecting infections.

Infect Control Hosp Epidemiol 2014;35(6):646–651

Strategies to Prevent Ventilator-Associated Pneumonia in Acute Care Hospitals: 2014 Update

Previously published guidelines are available that provide comprehensive recommendations for detecting and preventing healthcare-associated infections (HAIs). The intent of this document is to highlight practical recommendations in a concise format to assist acute care hospitals in implementing and prioritizing strategies to prevent ventilator-associated pneumonia (VAP) and other ventilator-associated events (VAEs) and to improve outcomes for mechanically ventilated adults, children, and neonates. This document updates "Strategies to Prevent Ventilator-Associated Pneumonia in Acute Care Hospitals," published in 2008. This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA) and is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America (IDSA), the American Hospital Association (AHA), the Association for Professionals in Infection Control and Epidemiology (APIC), and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise. The list of endorsing and supporting organizations is presented in the introduction to the 2014 updates.

Surgical site infection: comparing surgeon versus patient self-report

BACKGROUND

To compare the rate of surgical site infection (SSI) using surgeon versus patient report.

MATERIALS AND METHODS

A prospective observational study of surgical patients in four hospitals within one private health-care system was performed. Surgeon report consisted of contacting the surgeon or staff 30 d after procedure to identify infections. Patient report consisted of telephone contact with the patient and confirmation of infections by a trained surgical clinical reviewer.

RESULTS

Between February 2011 and June 2012, there were 2853 surgical procedures that met inclusion criteria. Surgeon-reported SSI rate was significantly lower (2.4%, P value < 0.01) compared with patient self-report (4.3%). The rate was lower across most infection subtypes (1.3% versus 3.0% superficial, 0.3% versus 0.5% organ/space) except deep incisional, most procedure types (2.3% versus 4.4% general surgery) except plastics, most patient characteristics (except body mass index < 18.5), and all hospitals. There were disagreements in 3.4% of cases; 74 cases reported by patients but not surgeons and 21 cases vice versa. Disagreements were more likely in superficial infections (59.8% versus 1.0%), C-sections (22.7% versus 17.7%), hospital A (22.7% versus 17.7%), age < 65 y (74.2% versus 68.3%), and body mass index ≥ 30 (54.2% versus 39.9%).

CONCLUSIONS

Patient report is a more sensitive method of detection of SSI compared with surgeon report, resulting in nearly twice the SSI rate. Fair and consistent ways of identifying SSIs are essential for comparing hospitals and surgeons, locally and nationally.

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.