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BACKGROUND:Universal skin and nasal decolonisation reduces multidrug-resistant pathogens and bloodstream infections in intensive care units. The effect of universal decolonisation on pathogens and infections in non-critical-care units is unknown. The aim of the ABATE Infection trial was to evaluate the use of chlorhexidine bathing in non-critical-care units, with an intervention similar to one that was found to reduce multidrug-resistant organisms and bacteraemia in intensive care units. METHODS:The ABATE Infection (active bathing to eliminate infection) trial was a cluster-randomised trial of 53 hospitals comparing routine bathing to decolonisation with universal chlorhexidine and targeted nasal mupirocin in non-critical-care units. The trial was done in hospitals affiliated with HCA Healthcare and consisted of a 12-month baseline period from March 1, 2013, to Feb 28, 2014, a 2-month phase-in period from April 1, 2014, to May 31, 2014, and a 21-month intervention period from June 1, 2014, to Feb 29, 2016. Hospitals were randomised and their participating non-critical-care units assigned to either routine care or daily chlorhexidine bathing for all patients plus mupirocin for known methicillin-resistant Staphylococcus aureus (MRSA) carriers. The primary outcome was MRSA or vancomycin-resistant enterococcus clinical cultures attributed to participating units, measured in the unadjusted, intention-to-treat population as the HR for the intervention period versus the baseline period in the decolonisation group versus the HR in the routine care group. Proportional hazards models assessed differences in outcome reductions across groups, accounting for clustering within hospitals. This trial is registered with ClinicalTrials.gov, number NCT02063867. FINDINGS:There were 189 081 patients in the baseline period and 339 902 patients (156 889 patients in the routine care group and 183 013 patients in the decolonisation group) in the intervention period across 194 non-critical-care units in 53 hospitals. For the primary outcome of unit-attributable MRSA-positive or VRE-positive clinical cultures (figure 2), the HR for the intervention period versus the baseline period was 0·79 (0·73-0·87) in the decolonisation group versus 0·87 (95% CI 0·79-0·95) in the routine care group. No difference was seen in the relative HRs (p=0·17). There were 25 (

Background Current sedation guidelines recommend avoiding benzodiazepines but express no preference for propofol vs dexmedetomidine. In addition, few data exist on whether randomized controlled trials of sedatives can be successfully generalized to routine practice, in which conditions tend to be more varied and complex. Methods Data regarding daily sedative exposure were gathered from all patients undergoing mechanical ventilation for ≥ 3 days over a 7-year period in a large academic medical center. Hazard ratios (HRs) were compared for ventilator-associated events (VAEs), extubation, hospital discharge, and hospital death among patients receiving benzodiazepines, propofol, and dexmedetomidine. Proportional subdistribution hazard models with competing risks were used for analysis. All analyses were adjusted for ICU type, demographic characteristics, comorbidities, procedures, severity of illness, hypotension, oxygenation, renal function, opioids, neuroleptic agents, neuromuscular blockers, awakening and breathing trials, and calendar year. Results A total of 9,603 consecutive episodes of mechanical ventilation were evaluated. Benzodiazepines and propofol were associated with increased VAE risk, whereas dexmedetomidine was not. Propofol was associated with less time to extubation compared with benzodiazepines (HR, 1.4; 95% CI, 1.3-1.5). Dexmedetomidine was associated with less time to extubation compared with benzodiazepines (HR, 2.3; 95% CI, 2.0-2.7) and propofol (HR, 1.7; 95% CI, 1.4-2.0), but relatively few dexmedetomidine exposures were available for analysis. There were no differences between any two agents in HRs for hospital discharge or mortality. Conclusions In this large, real-world cohort, propofol and dexmedetomidine were associated with less time to extubation compared with benzodiazepines, but dexmedetomidine was also associated with less time to extubation vs propofol. These possible differences merit further study.

OBJECTIVETo determine the effect of graft choice (allograft, bone-patellar tendon-bone autograft, or hamstring autograft) on deep tissue infections following anterior cruciate ligament (ACL) reconstructions.DESIGNRetrospective cohort study.SETTING AND POPULATIONPatients from 6 US health plans who underwent ACL reconstruction from January 1, 2000, through December 31, 2008.METHODSWe identified ACL reconstructions and potential postoperative infections using claims data. A hierarchical stratified sampling strategy was used to identify patients for medical record review to confirm ACL reconstructions and to determine allograft vs autograft tissue implanted, clinical characteristics, and infection status. We estimated infection rates overall and by graft type. We used logistic regression to assess the association between infections and patients’ demographic characteristics, comorbidities, and choice of graft.RESULTSOn review of 1,452 medical records, we found 55 deep wound infections. With correction for sampling weights, infection rates varied by graft type: 0.5% (95% CI, 0.3%-0.8%) with allografts, 0.6% (0.1%–1.5%) with bone-patellar tendon-bone autografts, and 2.5% (1.9%–3.1%) with hamstring autograft. After adjusting for potential confounders, we found an increased infection risk with hamstring autografts compared with allografts (odds ratio, 5.9; 95% CI, 2.8–12.8). However, there was no difference in infection risk among bone-patellar tendon-bone autografts vs allografts (odds ratio, 1.2; 95% CI, 0.3–4.8).CONCLUSIONSThe overall risk for deep wound infections following ACL reconstruction is low but it does vary by graft type. Infection risk was highest in hamstring autograft recipients compared with allograft recipients and bone-patellar tendon-bone autograft recipients.Infect Control Hosp Epidemiol 2016;37:827–833

Background Universal decolonization with daily chlorhexidine (CHG) bathing with and without nasal decolonization has significantly reduced positive MRSA clinical cultures and bloodstream infections in adult ICUs in several clinical trials. We evaluated whether decolonization was similarly effective in a lower risk hospitalized population. Methods We conducted a 2 arm cluster-randomized trial involving a 1-year baseline period (April 2013–March 2014) and a 21-month intervention period (June 2014–February 2016). All noncritical care units in a hospital were assigned to the same strategy. These were (1) Routine Care: routine bathing product and frequency and (2) Decolonization: CHG for routine daily bathing (2% leave-on CHG) or showering (4% rinse-off CHG) for all patients plus mupirocin for 5 days for known MRSA. Universal ICU decolonization was in place in both arms by September 2013. Differences between the arms in the outcome rates between the baseline and intervention periods were assessed with proportional hazards models, using shared frailties to account for clustering by hospital. The primary analysis was as-randomized and unadjusted. Primary outcome was any MRSA or VRE clinical isolate attributable to the unit. Secondary outcome was all-cause bloodstream infections. Additional analyses adjusted for age, gender, race, Medicaid insurer, surgery, and comorbidities. Results We randomized 53 hospitals in 15 states. There were 194 adult units with 189,616 admissions in the baseline period and 340,350 in the intervention period. Common unit types included mixed medical surgical (30%), cardiac (20%), step-down (11%), medical (10%), surgical (10%), and oncology (4%). There were no significant differences between arms in the relative hazards for intervention vs. baseline for either outcome (Table and Figure). Adjusted analyses yielded similar results. Conclusion Universal daily CHG bathing or showering plus targeted mupirocin for MRSA+ patients in non-critical care units did not reduce the combination of positive MRSA and VRE clinical cultures or bloodstream infections due to all pathogens. Further analyses to assess for any differential effects in high-risk subpopulations will be important. Disclosures S. S. Huang, Sage Products: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Clorox: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; 3M: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; E. Septimus, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; K. Kleinman, Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Moody, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Hickok, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L. Heim, Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; A. Gombosev, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; T. Avery, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; received research funds from Clorox, but Clorox has no role in the design K. Haffenreffer, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; receive research funds from Clorox, but Clorox has no role in the design; L. Shimelman, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; receive research funds from Clorox, but Clorox has no role in the design; M. K. Hayden, OpGen, Inc.: Receipt of donated laboratory services for project, Research support; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. A. Weinstein, Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; OpGen Inc.: Receipt of donated laboratory services for project, Research support; C. Spencer-Smith, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. E. Kaganov, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; M. V. Murphy, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; T. Forehand, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Lankiewicz, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; M. H. Coady, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; received research funds from Clorox, but Clorox has no role in the design.; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L. M. Portillo, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Patel Sarup, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Perlin, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. Platt, Clorox: Receipt of contributed product, Conducting clinical studies in which participating healthcare facilities are receiving contributed product; receive research funds from Clorox, but Clorox has no role in the design; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product

BackgroundQuality improvement (QI) campaigns appear to increase use of evidence-based practices, but their effect on health outcomes is less well studied.ObjectiveTo assess the effect of a multistate QI campaign (Project JOINTS, Joining Organizations IN Tackling SSIs) that used the Institute for Healthcare Improvement’s Rapid Spread Network to promote adoption of evidence-based surgical site infection (SSI) prevention practices.MethodsWe analysed rates of SSI among Medicare beneficiaries undergoing hip and knee arthroplasty during preintervention (May 2010 to April 2011) and postintervention (November 2011 to September 2013) periods in five states included in a multistate trial of the Project JOINTS campaign and five matched comparison states. We used generalised linear mixed effects models and a difference-in-differences approach to estimate changes in SSI outcomes.Results125 070 patients underwent hip arthroplasty in 405 hospitals in intervention states, compared with 131 787 in 525 hospitals in comparison states. 170 663 patients underwent knee arthroplasty in 397 hospitals in intervention states, compared with 196 064 in 518 hospitals in comparison states. After the campaign, patients in intervention states had a 15% lower odds of developing hip arthroplasty SSIs (OR=0.85, 95% CI 0.75 to 0.96, p=0.01) and a 12% lower odds of knee arthroplasty SSIs than patients in comparison states (OR=0.88, 95% CI 0.78 to 0.99, p=0.04).ConclusionsA larger reduction of SSI rates following hip and knee arthroplasty was shown in intervention states than in matched control states.

Background: Universal skin and nasal decolonization reduces multidrug-resistant pathogens and bloodstream infections in intensive care units. The effect of universal decolonization on pathogens and infections in non-critical care units is unknown. Methods: A two-arm cluster-randomized trial was conducted in 53 hospitals in the Hospital Corporation of America Healthcare system. Hospitals were randomized and their participating non-critical care units assigned to either routine care or daily chlorhexidine bathing for all patients plus mupirocin for known methicillin-resistant Staphylococcus aureus (MRSA) carriers. The trial involved a 12-month baseline (Mar 2013-Feb 2014) and 21-month intervention (Jun 2014-Feb 2016). Primary outcome was MRSA or vancomycin-resistant enterococcus (VRE) clinical cultures attributed to participating units, and secondary outcome was all-pathogen bloodstream infection. Proportional hazards models assessed differences in outcome reductions across arms, accounting for clustering by hospital. Post-hoc subgroup analyses were performed. Findings: There were 189,081 patients in the baseline period and 339,902 patients in the intervention period across 194 non-critical care units in 53 hospitals. Hazard ratios for MRSA/VRE clinical isolates during intervention vs. baseline periods were 0·87 (CI:0·79, 0·95) for routine care, and 0·79 (CI:0·73, 0·87) for decolonization (p=0·17), and 0·96 (CI:0·85, 1·08) and 0·90 (0·81, 1·01) for all-pathogen bloodstream infection, respectively (p=0·44). Among patients with central venous catheters, midline catheters, or lumbar drains, the hazard ratio for MRSA/VRE clinical cultures was 1·17 (CI:1·00, 1·37) for routine care and 0·80 (CI:0·69, 0·92) for decolonization, (p=0·0004), and the hazard ratio for all-pathogen bloodstream infections was 1·13 (CI:0·96, 1·33) for routine care and 0·82 (CI:0·71, 0·94) for decolonization, p=0·004. Interpretation: Decolonization with universal chlorhexidine bathing and targeted mupirocin for MRSA carriers did not reduce multidrug-resistant organisms or all-pathogen bloodstream infection in all non-critical care patients, but patients with invasive devices experienced 37% reduction in MRSA/VRE and 31% reduction in bloodstream infections. Clinical Trial Registration Number: clinicaltrials.gov Identifier: NCT0206386 Funding Statement: This project was funded by the National Institutes of Health Common Fund and administered by the National Institute of Allergy and Infectious Diseases (UH2/UH3 AT007769‐01 (Huang)). Declaration of Interest: Sage Products and Molnlycke contributed antiseptic chlorhexidine product to this trial. Investigators are also conducting other studies in which contributed antiseptic product is provided to participating hospitals and nursing homes from Stryker (Sage Products) (KK, LH, MHC, MKH, RAW, SSH), 3M (LH, SSH), Clorox (CS, ES, JH, JM, JP, KH, KK, LH, LS, MHC, MKH, RAW, RP, SSH, TRA), Xttrium (LH, SSH), and Medline (CS, ES, JH, JM, JP, KH, KK, LH, LS, MHC, MKH, RAW, RP, SSH, TRA). Investigator-initiated grant funds were received from Clorox (MKH, MHC, LS, KH, RP). Companies contributing product or providing grant funds have no role in the design, conduct, analysis, or publication of the ABATE Infection Trial or other studies conducted by these investigators. All other authors have no disclosures. Ethics Approval Statement: Central IRB approval was obtained from Harvard Pilgrim Health Care with a waiver of informed consent. All participating hospitals formally ceded IRB oversight to the HPHC IRB, except for the designated medical center IRB (Chippenham & Johnston Willis Hospitals) that provided prisoner oversight for the trial.

The Centers for Disease Control and Prevention recently released new surveillance definitions for ventilator-associated events, including the new entities of ventilator-associated conditions and infection-related ventilator-associated complications. Both ventilator-associated conditions and infection-related ventilator-associated complications are associated with prolonged mechanical ventilation and hospital death, but little is known about their risk factors and how best to prevent them. We sought to identify risk factors for ventilator-associated conditions and infection-related ventilator-associated complications.Retrospective case-control study.Medical, surgical, cardiac, and neuroscience units of a tertiary care teaching hospital.Hundred ten patients with ventilator-associated conditions matched to 110 controls without ventilator-associated conditions on the basis of age, sex, ICU type, comorbidities, and duration of mechanical ventilation prior to ventilator-associated conditions.None.We compared cases with controls with regard to demographics, comorbidities, ventilator bundle adherence rates, sedative exposures, routes of nutrition, blood products, fluid balance, and modes of ventilatory support. We repeated the analysis for the subset of patients with infection-related ventilator-associated complications and their controls.Case and control patients were well matched on baseline characteristics. On multivariable logistic regression, significant risk factors for ventilator-associated conditions were mandatory modes of ventilation (odds ratio, 3.4; 95% CI, 1.6-8.0) and positive fluid balances (odds ratio, 1.2 per L positive; 95% CI, 1.0-1.4). Possible risk factors for infection-related ventilator-associated complications were starting benzodiazepines prior to intubation (odds ratio, 5.0; 95% CI, 1.3-29), total opioid exposures (odds ratio, 3.3 per 100 μg fentanyl equivalent/kg; 95% CI, 0.90-16), and paralytic medications (odds ratio, 2.3; 95% CI, 0.79-80). Traditional ventilator bundle elements, including semirecumbent positioning, oral care with chlorhexidine, venous thromboembolism prophylaxis, stress ulcer prophylaxis, daily spontaneous breathing trials, and sedative interruptions, were not associated with ventilator-associated conditions or infection-related ventilator-associated complications.Mandatory modes of ventilation and positive fluid balance are risk factors for ventilator-associated conditions. Benzodiazepines, opioids, and paralytic medications are possible risk factors for infection-related ventilator-associated complications. Prospective studies are needed to determine if targeting these risk factors can lower ventilator-associated condition and infection-related ventilator-associated complication rates.

Objective.The Centers for Disease Control and Prevention implemented new surveillance definitions for ventilator-associated events (VAEs) in January 2013. We describe the epidemiology, attributable morbidity, and attributable mortality of VAEs.Design.Retrospective cohort study.Setting.Academic tertiary care center.Patients.All patients initiated on mechanical ventilation between January 1, 2006, and December 31, 2011.Methods.We calculated and compared VAE hazard ratios, antibiotic exposures, microbiology, attributable morbidity, and attributable mortality for all VAE tiers.Results.Among 20,356 episodes of mechanical ventilation, there were 1,141 (5.6%) ventilator-associated condition (VAC) events, 431 (2.1%) infection-related ventilator-associated complications (IVACs), 139 (0.7%) possible pneumonias, and 127 (0.6%) probable pneumonias. VAC hazard rates were highest in medical, surgical, and thoracic units and lowest in cardiac and neuroscience units. The median number of days to VAC onset was 6 (interquartile range, 4–11). The proportion of IVACs to VACs ranged from 29% in medical units to 42% in surgical units. Patients with probable pneumonia were more likely to be prescribed nafcillin, ceftazidime, and fluroquinolones compared with patients with possible pneumonia or IVAC-alone. The most frequendy isolated organisms were Staphylococcus aureus (29%), Pseudomonas aeruginosa (14%), and Enterobacter species (7.9%). Compared with matched controls, VAEs were associated with more days to extubation (relative rate, 3.12 [95% confidence interval (CI), 2.96–3.29]), more days to hospital discharge (relative rate, 1.46 [95% CI, 1.37–1.55]), and higher hospital mortality risk (odds ratio, 1.98 [95% CI, 1.60–2.44]).Conclusions.VAEs are common and morbid. Prevention strategies targeting VAEs are needed.

Author(s): Calderwood, Michael S; Kleinman, Ken; Huang, Susan S; Murphy, Michael V; Yokoe, Deborah S; Platt, Richard | Abstract: BackgroundSurgical site infection (SSI) rates are publicly reported as quality metrics and increasingly used to determine financial reimbursement.ObjectiveTo evaluate the volume-outcome relationship as well as the year-to-year stability of performance rankings following coronary artery bypass graft (CABG) surgery and hip arthroplasty.Research designWe performed a retrospective cohort study of Medicare beneficiaries who underwent CABG surgery or hip arthroplasty at US hospitals from 2005 to 2011, with outcomes analyzed through March 2012. Nationally validated claims-based surveillance methods were used to assess for SSI within 90 days of surgery. The relationship between procedure volume and SSI rate was assessed using logistic regression and generalized additive modeling. Year-to-year stability of SSI rates was evaluated using logistic regression to assess hospitals' movement in and out of performance rankings linked to financial penalties.ResultsCase-mix adjusted SSI risk based on claims was highest in hospitals performing l50 CABG/year and l200 hip arthroplasty/year compared with hospitals performing ≥200 procedures/year. At that same time, hospitals in the worst quartile in a given year based on claims had a low probability of remaining in that quartile the following year. This probability increased with volume, and when using 2 years' experience, but the highest probabilities were only 0.59 for CABG (95% confidence interval, 0.52-0.66) and 0.48 for hip arthroplasty (95% confidence interval, 0.42-0.55).ConclusionsAggregate SSI risk is highest in hospitals with low annual procedure volumes, yet these hospitals are currently excluded from quality reporting. Even for higher volume hospitals, year-to-year random variation makes past experience an unreliable estimator of current performance.

Introduction Claims-based analyses report that the incidence of sepsis-associated organ dysfunction is increasing. We examined whether coding practices for acute organ dysfunction are changing over time and if so, whether this is biasing estimates of rising severe sepsis incidence and severity. Methods We assessed trends from 2005 to 2013 in the annual sensitivity and incidence of discharge ICD-9-CM codes for organ dysfunction (shock, respiratory failure, acute kidney failure, acidosis, hepatitis, coagulopathy, and thrombocytopenia) relative to standardized clinical criteria (use of vasopressors/inotropes, mechanical ventilation for ≥2 consecutive days, rise in baseline creatinine, low pH, elevated transaminases or bilirubin, abnormal international normalized ratio or low fibrinogen, and decline in platelets). We studied all adult patients with suspected infection (defined by ≥1 blood culture order) at two US academic hospitals. Results Acute organ dysfunction codes were present in 57,273 of 191,695 (29.9 %) hospitalizations with suspected infection, most commonly acute kidney failure (60.2 % of cases) and respiratory failure (28.9 %). The sensitivity of all organ dysfunction codes except thrombocytopenia increased significantly over time. This was most pronounced for acute kidney failure codes, which increased in sensitivity from 59.3 % in 2005 to 87.5 % in 2013 relative to a fixed definition for changes in creatinine (p = 0.019 for linear trend). Acute kidney failure codes were increasingly assigned to patients with smaller creatinine changes: the average peak creatinine change associated with a code was 1.99 mg/dL in 2005 versus 1.49 mg/dL in 2013 (p p Conclusions Coding for acute organ dysfunction is becoming increasingly sensitive and the clinical threshold to code patients for certain kinds of organ dysfunction is decreasing. This accounts for much of the apparent rise in severe sepsis incidence and severity imputed from claims.

OBJECTIVETo compare the accuracy of surveillance of severe sepsis using electronic health record clinical data vs claims and to compare incidence and mortality trends using both methods.DESIGNWe created an electronic health record–based surveillance definition for severe sepsis using clinical indicators of infection (blood culture and antibiotic orders) and concurrent organ dysfunction (vasopressors, mechanical ventilation, and/or abnormal laboratory values). We reviewed 1,000 randomly selected medical charts to characterize the definition’s accuracy and stability over time compared with a claims-based definition requiring infection and organ dysfunction codes. We compared incidence and mortality trends from 2003–2012 using both methods.SETTINGTwo US academic hospitals.PATIENTSAdult inpatients.RESULTSThe electronic health record–based clinical surveillance definition had stable and high sensitivity over time (77% in 2003–2009 vs 80% in 2012, P=.58) whereas the sensitivity of claims increased (52% in 2003–2009 vs 67% in 2012, P=.02). Positive predictive values for claims and clinical surveillance definitions were comparable (55% vs 53%, P=.65) and stable over time. From 2003 to 2012, severe sepsis incidence imputed from claims rose by 72% (95% CI, 57%–88%) and absolute mortality declined by 5.4% (95% CI, 4.6%–6.7%). In contrast, incidence using the clinical surveillance definition increased by 7.7% (95% CI, −1.1% to 17%) and mortality declined by 1.7% (95% CI, 1.1%–2.3%).CONCLUSIONSSepsis surveillance using clinical data is more sensitive and more stable over time compared with claims and can be done electronically. This may enable more reliable estimates of sepsis burden and trends.Infect. Control Hosp. Epidemiol. 2016;37(2):163–171

Serum lactate monitoring is central to risk stratification and management of sepsis and is now part of a potential quality measure. We examined 11-year trends in lactate testing and predictors of failure to measure lactates in patients with severe sepsis.Retrospective cohort study.Two U.S. academic hospitals.Adult patients admitted from 2003 to 2013.Annual rates of lactate measurement were assessed in patients who had blood cultures ordered and patients with severe sepsis, as defined by concomitant International Classification of Diseases, Ninth Revision codes for infection and organ dysfunction. The approximate time of suspected sepsis was determined by the first blood culture order with concurrent antibiotic initiation. Multivariate analysis was performed to identify predictors of failure to measure lactates in severe sepsis cases in 2013.Among hospitalizations with blood culture orders, rates of lactate measurement increased from 11% in 2003 to 48% in 2013 (p0.001 for linear trend). Rates of repeat lactate measurement within 6 hours after lactate levels greater than or equal to 4.0 mmol/L increased from 23% to 69% (p0.001). Patients were progressively less likely to be on vasopressors at the time of first lactate measurement (49% in 2003 vs 21% in 2013; p0.001). Despite these trends, lactates were measured at the time of suspected sepsis in only 65% of patients with severe sepsis in 2013. On multivariate analysis, hospital-onset sepsis and hospitalization on a nonmedical service were significant predictors of failure to measure lactates (adjusted odds ratio, 7.56; 95% CI, 6.31-9.06 and adjusted odds ratio, 2.08; 95% CI, 1.76-2.24, respectively).Lactate testing has increased dramatically over time and is being extended to patients without overt shock. However, rates of serial lactate testing are still suboptimal, and lactates are not being measured in many patients with severe sepsis. Hospital-onset sepsis and nonmedical units may be high-yield targets for quality improvement initiatives.

BACKGROUNDValid comparison between hospitals for benchmarking or pay-for-performance incentives requires accurate correction for underlying disease severity (case-mix). However, existing models are either very simplistic or require extensive manual data collection.OBJECTIVETo develop a disease severity prediction model based solely on data routinely available in electronic health records for risk-adjustment in mechanically ventilated patients.DESIGNRetrospective cohort study.PARTICIPANTSMechanically ventilated patients from a single tertiary medical center (2006–2012).METHODSPredictors were extracted from electronic data repositories (demographic characteristics, laboratory tests, medications, microbiology results, procedure codes, and comorbidities) and assessed for feasibility and generalizability of data collection. Models for in-hospital mortality of increasing complexity were built using logistic regression. Estimated disease severity from these models was linked to rates of ventilator-associated events.RESULTSA total of 20,028 patients were initiated on mechanical ventilation, of whom 3,027 deceased in hospital. For models of incremental complexity, area under the receiver operating characteristic curve ranged from 0.83 to 0.88. A simple model including demographic characteristics, type of intensive care unit, time to intubation, blood culture sampling, 8 common laboratory tests, and surgical status achieved an area under the receiver operating characteristic curve of 0.87 (95% CI, 0.86–0.88) with adequate calibration. The estimated disease severity was associated with occurrence of ventilator-associated events.CONCLUSIONSAccurate estimation of disease severity in ventilated patients using electronic, routine care data was feasible using simple models. These estimates may be useful for risk-adjustment in ventilated patients. Additional research is necessary to validate and refine these models.Infect. Control Hosp. Epidemiol. 2015;36(7):807–815

The CDC introduced ventilator-associated event (VAE) definitions in January 2013. Little is known about VAE prevention. We hypothesized that daily, coordinated spontaneous awakening trials (SATs) and spontaneous breathing trials (SBTs) might prevent VAEs.To assess the preventability of VAEs.We nested a multicenter quality improvement collaborative within a prospective study of VAE surveillance among 20 intensive care units between November 2011 and May 2013. Twelve units joined the collaborative and implemented an opt-out protocol for nurses and respiratory therapists to perform paired daily SATs and SBTs. The remaining eight units conducted surveillance alone. We measured temporal trends in VAEs using generalized mixed effects regression models adjusted for patient-level unit, age, sex, reason for intubation, Sequential Organ Failure Assessment score, and comorbidity index.We tracked 5,164 consecutive episodes of mechanical ventilation: 3,425 in collaborative units and 1,739 in surveillance-only units. Within collaborative units, significant increases in SATs, SBTs, and percentage of SBTs performed without sedation were mirrored by significant decreases in duration of mechanical ventilation and hospital length-of-stay. There was no change in VAE risk per ventilator day but significant decreases in VAE risk per episode of mechanical ventilation (odds ratio [OR], 0.63; 95% confidence interval [CI], 0.42-0.97) and infection-related ventilator-associated complications (OR, 0.35; 95% CI, 0.17-0.71) but not pneumonias (OR, 0.51; 95% CI, 0.19-1.3). Within surveillance-only units, there were no significant changes in SAT, SBT, or VAE rates.Enhanced performance of paired, daily SATs and SBTs is associated with lower VAE rates. Clinical trial registered with www.clinicaltrials.gov (NCT 01583413).

Background. National reports of a dramatic rise in sepsis incidence are largely based on analyses of administrative databases. It is unclear if these estimates are biased by changes in coding practices over time. Methods. We calculated linear trends in the annual incidence of septicemia, sepsis, and severe sepsis at 2 academic hospitals from 2003 to 2012 using 5 different claims methods and compared case identification rates to selected objective clinical markers, including positive blood cultures, vasopressors, and/or lactic acid levels. Results. The annual incidence of hospitalizations with sepsis claims increased over the decade, ranging from a 54% increase for the method combining septicemia, bacteremia, and fungemia codes (P< .001 for linear trend) to a 706% increase for explicit severe sepsis/septic shock codes (P= .001). In contrast, the incidence of hospitalizations with positive blood cultures decreased by 17% (P= .006), and hospitalizations with positive blood cultures with concurrent vasopressors and/or lactic acidosis remained stable (P= .098). The sensitivity of sepsis claims for capturing hospitalizations with positive blood cultures with concurrent vasopressors and/or lactic acidosis increased (P< .001 for all methods), whereas the proportion of septicemia hospitalizations with positive blood cultures decreased from 50% to 30% (P< .001). Conclusions. The incidence of hospitalizations with sepsis codes rose dramatically while hospitalizations with corresponding objective clinical markers remained stable or decreased. Coding for sepsis has become more inclusive, and septicemia diagnoses are increasingly being applied to patients without positive blood cultures. These changes likely explain some of the apparent rise in sepsis incidence and underscore the need for more reliable surveillance methods.

Objective.To explore the feasibility of identifying anterior cruciate ligament (ACL) allograft implantations and infections using claims.Design.Retrospective cohort study.Methods.We identified ACL reconstructions using procedure codes at 6 health plans from 2000 to 2008. We then identified potential infections using claims-based indicators of infection, including diagnoses, procedures, antibiotic dispensings, specialty consultations, emergency department visits, and hospitalizations. Patients’ medical records were reviewed to determine graft type, validate infection status, and calculate sensitivity and positive predictive value (PPV) for indicators of ACL allografts and infections.Results.A total of 11,778 patients with codes for ACL reconstruction were identified. After chart review, PPV for ACL reconstruction was 96% (95% confidence interval [CI], 94%–97%). Of the confirmed ACL reconstructions, 39% (95% CI, 35%–42%) used allograft tissues. The deep infection rate after ACL reconstruction was 1.0% (95% CI, 0.7%–1.4%). The odds ratio of infection for allografts versus autografts was 0.41 (95% CI, 0.19–0.78). Sensitivity of individual claims-based indicators for deep infection after ACL reconstruction ranged from 0% to 75% and PPV from 0% to 100%. Claims-based infection indicators could be combined to enhance sensitivity or PPV but not both.Conclusions.While claims data accurately identify ACL reconstructions, they poorly distinguish between allografts and autografts and identify infections with variable accuracy. Claims data could be useful to monitor infection trends after ACL reconstruction, with different algorithms optimized for different surveillance goals.Infect Control Hosp Epidemiol 2014;35(6):652–659

Objectives Several studies have noted the impact of socioeconomic factors on access to expensive medical care, but none of those studies controlled for self-reported health and functional status or attitudes about treatment alternatives when analyses were completed. Because these factors may be correlated with socioeconomic status, the failure to control for them may have led to bias in other studies. The authors merged data from secondary sources with telephone survey data from a national sample of 456 end-stage renal disease patients to show how estimates of the effects of socioeconomic factors change when self-reported health and functional status and attitudes about treatment are incorporated into statistical models. The authors also showed how kidney transplant rates would change if socioeconomic factors no longer influences organ allocation decisions. Methods Weibull proportional hazard analyses were used to show relationships between socioeconomic measures and waiting list entry and kidney transplant rates, before versus after accounting for self-reported health and functional status, attitudes about treatment, and other variables. Simulation analyses were used to estimate the number of waiting list spots and transplant operations that would move from economically advantaged to disadvantaged persons if socioeconomics no longer influenced organ allocation decisions. Results Incorporating information about health and functional status, attitudes about treatment, and other factors into the hazard models often reduced the estimated impact of socioeconomic measures on the odds of (1) being on a waiting list for a cadaver kidney transplant and (2) receiving a transplant. Simulations showed that 30 to 65 waiting list spots or transplant operations per 1,000 patients would shift from economically advantaged to disadvantaged persons if socioeconomics no longer influenced organ allocation decisions. Conclusions Successful efforts to level the playing field would result in substantial redistributions of kidney transplants from economically advantaged to disadvantaged persons.