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Hu X, Chen J, Zheng X, Li J, Zhou M. Establishment and application of TSDPSO-SVM model combined with multi-dimensional feature fusion method in the identification of fracture-related infection. Sci Rep 2023; 13:19632. [PMID: 37949929 PMCID: PMC10638378 DOI: 10.1038/s41598-023-46526-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 11/02/2023] [Indexed: 11/12/2023] Open
Abstract
Fracture-related infection (FRI) is one of the most common and intractable complications in orthopedic trauma surgery. This complication can impose severe psychological burdens and socio-economic impacts on patients. Although the definition of FRI has been proposed recently by an expert group, the diagnostic criteria for FRI are not yet standardized. A total of 4761 FRI patients and 4761 fracture patients (Non-FRI) were included in the study. The feature set of patients included imaging characteristics, demographic information, clinical symptoms, microbiological findings, and serum inflammatory markers, which were reduced by the Principal Component Analysis. To optimize the Support Vector Machine (SVM) model, the Traction Switching Delay Particle Swarm Optimization (TSDPSO) algorithm, a recognition method was proposed. Moreover, five machine learning models, including TSDPSO-SVM, were employed to distinguish FRI from Non-FRI. The Area under the Curve of TSDPSO-SVM was 0.91, at least 5% higher than that of other models. Compared with the Random Forest, Backpropagation Neural Network (BP), SVM and eXtreme Gradient Boosting (XGBoost), TSDPSO-SVM demonstrated remarkable accuracy in the test set ([Formula: see text]). The recall of TSDPSO-SVM was 98.32%, indicating a significant improvement ([Formula: see text]). Compared with BP and SVM, TSDPSO-SVM exhibited significantly superior specificity, false positive rate and precision ([Formula: see text]. The five models yielded consistent results in the training and testing of FRI patients across different age groups. TSDPSO-SVM is validated to have the maximum overall prediction ability and can effectively distinguish between FRI and Non-FRI. For the early diagnosis of FRI, TSDPSO-SVM may provide a reference basis for clinicians, especially those with insufficient experience. These results also lay a foundation for the intelligent diagnosis of FRI. Furthermore, these findings exhibit the application potential of this model in the diagnosis and classification of other diseases.
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Affiliation(s)
- Xiaofeng Hu
- Department of Orthopaedics, Jinling Hospital, School of Medicine, Nanjing University, No. 34, Lot 34, Changfu Street, Qinhuai District, Nanjing, Jiangsu Province, China
| | - Jianmin Chen
- Department of Orthopaedics, Jinling Hospital, School of Medicine, Nanjing University, No. 34, Lot 34, Changfu Street, Qinhuai District, Nanjing, Jiangsu Province, China.
| | - Xiaofei Zheng
- Department of Orthopaedics, Jinling Hospital, School of Medicine, Nanjing University, No. 34, Lot 34, Changfu Street, Qinhuai District, Nanjing, Jiangsu Province, China
| | - Jianmei Li
- Department of Orthopaedics, Jinling Hospital, School of Medicine, Nanjing University, No. 34, Lot 34, Changfu Street, Qinhuai District, Nanjing, Jiangsu Province, China
| | - Mingwei Zhou
- Department of Orthopaedics, Jinling Hospital, School of Medicine, Nanjing University, No. 34, Lot 34, Changfu Street, Qinhuai District, Nanjing, Jiangsu Province, China
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Verberk JDM, Aghdassi SJS, Abbas M, Nauclér P, Gubbels S, Maldonado N, Palacios-Baena ZR, Johansson AF, Gastmeier P, Behnke M, van Rooden SM, van Mourik MSM. Automated surveillance systems for healthcare-associated infections: results from a European survey and experiences from real-life utilization. J Hosp Infect 2022; 122:35-43. [PMID: 35031393 DOI: 10.1016/j.jhin.2021.12.021] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/04/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND As most automated surveillance (AS) methods to detect healthcare-associated infections (HAIs) have been developed and implemented in research settings, information about the feasibility of large-scale implementation is scarce. AIM We aimed to describe key aspects of the design of AS systems and implementation in European institutions and hospitals. METHODS An online survey was distributed via email in February/March 2019 among 1) PRAISE (Providing a Roadmap for Automated Infection Surveillance in Europe) network members; 2) corresponding authors of peer-reviewed European publications on existing AS systems; and 3) the mailing list of national infection prevention and control focal points of the European Centre for Disease Prevention and Control. Three AS systems from the survey were selected, based on quintessential features, for in-depth review focusing on implementation in practice. FINDINGS Through the survey and the review of three selected AS systems, notable differences regarding the methods, algorithms, data sources and targeted HAIs were identified. The majority of AS systems used a classification algorithm for semi-automated surveillance and targeted HAIs were mostly surgical site infections, urinary tract infections, sepsis or other bloodstream infections. AS systems yielded a reduction of workload for hospital staff. Principal barriers of implementation were strict data security regulations as well as creating and maintaining an information technology infrastructure. CONCLUSION AS in Europe is characterized by heterogeneity in methods and surveillance targets. To allow for comparisons and encourage homogenization, future publications on AS systems should provide detailed information on source data, methods and the state of implementation.
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Affiliation(s)
- Janneke D M Verberk
- Department of Medical Microbiology and Infection Prevention, University Medical Centre Utrecht, Utrecht, the Netherlands; Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, the Netherlands; Department of Epidemiology and Surveillance, Centre for Infectious Diseases Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
| | - Seven J S Aghdassi
- Institute of Hygiene and Environmental Medicine, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digital Clinician Scientist Program, Anna-Louisa-Karsch-Straße 2, 10178 Berlin, Germany
| | - Mohamed Abbas
- Infection Control Programme, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland
| | - Pontus Nauclér
- Department of Medicine Solna, Division of Infectious Disease, Karolinska Institutet, Stockholm, Sweden; Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Sophie Gubbels
- Department of Infectious Disease Preparedness, Statens Serum Institut, Copenhagen, Denmark
| | - Natalia Maldonado
- Unit of Infectious Diseases, Clinical Microbiology and Preventive Medicine, Hospital Universitario Virgen Macarena, Institute of Biomedicine of Seville (IBIS), Sevilla, Spain
| | - Zaira R Palacios-Baena
- Unit of Infectious Diseases, Clinical Microbiology and Preventive Medicine, Hospital Universitario Virgen Macarena, Institute of Biomedicine of Seville (IBIS), Sevilla, Spain
| | - Anders F Johansson
- Department of Clinical microbiology and the Laboratory for Molecular Infection Medicine (MIMS), Umeå University, Umeå, Sweden
| | - Petra Gastmeier
- Institute of Hygiene and Environmental Medicine, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Michael Behnke
- Institute of Hygiene and Environmental Medicine, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Stephanie M van Rooden
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, the Netherlands; Department of Epidemiology and Surveillance, Centre for Infectious Diseases Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Maaike S M van Mourik
- Department of Medical Microbiology and Infection Prevention, University Medical Centre Utrecht, Utrecht, the Netherlands
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Ratnesh K, Kumar P, Arya A. Incidence of Surgical Site Infections and Surgical Antimicrobial Prophylaxis in JNMC, Bhagalpur, India. JOURNAL OF PHARMACY AND BIOALLIED SCIENCES 2022; 14:S868-S871. [PMID: 36110734 PMCID: PMC9469243 DOI: 10.4103/jpbs.jpbs_30_22] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 02/26/2022] [Indexed: 11/04/2022] Open
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Streefkerk HRA, Verkooijen RP, Bramer WM, Verbrugh HA. Electronically assisted surveillance systems of healthcare-associated infections: a systematic review. ACTA ACUST UNITED AC 2020; 25. [PMID: 31964462 PMCID: PMC6976884 DOI: 10.2807/1560-7917.es.2020.25.2.1900321] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Background Surveillance of healthcare-associated infections (HAI) is the basis of each infection control programme and, in case of acute care hospitals, should ideally include all hospital wards, medical specialties as well as all types of HAI. Traditional surveillance is labour intensive and electronically assisted surveillance systems (EASS) hold the promise to increase efficiency. Objectives To give insight in the performance characteristics of different approaches to EASS and the quality of the studies designed to evaluate them. Methods In this systematic review, online databases were searched and studies that compared an EASS with a traditional surveillance method were included. Two different indicators were extracted from each study, one regarding the quality of design (including reporting efficiency) and one based on the performance (e.g. specificity and sensitivity) of the EASS presented. Results A total of 78 studies were included. The majority of EASS (n = 72) consisted of an algorithm-based selection step followed by confirmatory assessment. The algorithms used different sets of variables. Only a minority (n = 7) of EASS were hospital-wide and designed to detect all types of HAI. Sensitivity of EASS was generally high (> 0.8), but specificity varied (0.37–1). Less than 20% (n = 14) of the studies presented data on the efficiency gains achieved. Conclusions Electronically assisted surveillance of HAI has yet to reach a mature stage and to be used routinely in healthcare settings. We recommend that future studies on the development and implementation of EASS of HAI focus on thorough validation, reproducibility, standardised datasets and detailed information on efficiency.
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Affiliation(s)
- H Roel A Streefkerk
- Albert Schweitzer Hospital/Rivas group Beatrix hospital/Regionaal Laboratorium medische Microbiologie, Dordrecht/Gorinchem, the Netherlands.,Erasmus University Medical Center (Erasmus MC), Rotterdam, the Netherlands
| | - Roel Paj Verkooijen
- Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Wichor M Bramer
- Medical Library, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Henri A Verbrugh
- Erasmus University Medical Center (Erasmus MC), Rotterdam, the Netherlands
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Alamrew K, Tadesse TA, Abiye AA, Shibeshi W. Surgical Antimicrobial Prophylaxis and Incidence of Surgical Site Infections at Ethiopian Tertiary-Care Teaching Hospital. Infect Dis (Lond) 2019; 12:1178633719892267. [PMID: 31819472 PMCID: PMC6882032 DOI: 10.1177/1178633719892267] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 11/09/2019] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Surgical site infections (SSIs) are infections that develop within 30 days after an operation or surveillance of surgical wound infection implementation within 90 days after surgery when an implant is placed. The objective of this study was to assess preoperative and postoperative antimicrobial use in St. Paul's Hospital Millennium Medical College (SPHMMC), Addis Ababa, Ethiopia. METHODS A hospital-based cross-sectional study was undertaken in surgery wards of SPHMMC for 4 months by reviewing 413 patients' charts. All patients 13 years and older who were admitted and underwent different types of surgical procedures were included in the study. Epi info 7 was used for data entry, and then data were exported to Statistical Package for Social Sciences (SPSS) version 20.0 software for analysis. Descriptive analyses were computed and rate of SSI was calculated in this study. Moreover, bivariate analysis was done to examine the relationship between the outcome variable and predictor variables with a value of P < .2 retained for subsequent multivariate analyses using multiple logistic regressions. P value of <.05 was considered as statistically significant. RESULTS Out of 413 patients, 152 (36.8%) were operated for general surgery, and the remaining were for other types of surgeries. Most of the patients, 196 (79.7%), were managed by a single surgical antibiotic agent, followed by 2 agents (20.3%) for surgical prophylaxis indication. Surgical site infections occurred in 46 (11.1%) patients before discharge from the hospital. In those patients who need treatment for SSIs, almost half of them (49.5%) received combination therapy of ceftriaxone and metronidazole. Emergency surgical cases were 2.647 times more likely to develop SSIs than the elective surgical cases (adjusted odds ratio [AOR] = 2.647; 95% confidence interval [CI] = 1.406-4.983; P = .003). Patients who did not receive antibiotic prophylaxis were 2.572 times more likely to develop SSIs compared to those who received antibiotic prophylaxis (AOR = 2.572; 95% CI = 1.02-6.485; P = .045). Clean-contaminated and contaminated types of wound were a protective factor against SSI in our study. CONCLUSIONS This study indicated that most of the patients (72.1%) received surgical antimicrobial prophylaxis. The overall incidence rate of SSIs was 11.1% in the studied hospital. Ceftriaxone was the most commonly used drug. Being not receiving prophylaxis, wound class, and surgery types were significantly associated with the development of SSI.
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Affiliation(s)
- Kerebih Alamrew
- School of Pharmacy, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Tamrat Assefa Tadesse
- School of Pharmacy, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Alfoalem Araba Abiye
- School of Pharmacy, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Workineh Shibeshi
- School of Pharmacy, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
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Aid Mellouk K, Soulaymani A, Gao F, Astagneau P, Misset B. Infectious complications of endoarterial interventional radiology: protocol for an observational study of a longitudinal national cohort of patients assessed in the French hospital discharge database (MOEVA study). BMJ Open 2019; 9:e024181. [PMID: 31164361 PMCID: PMC6561437 DOI: 10.1136/bmjopen-2018-024181] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Revised: 01/02/2019] [Accepted: 01/16/2019] [Indexed: 11/04/2022] Open
Abstract
Around seven million patients undergo endoarterial interventional radiology procedures (EAIRP) annually worldwide. These procedures have become part of the standard repertoire of vascular surgery. However, the healthcare-associated infections related to these procedures are relatively unknown. Prevalence and adverse outcome of infectious complication (IC) post-EAIRP may be underestimated. We aim to provide national trend estimation of EAIRP incidence and outcome in France. METHODS AND ANALYSIS: From the French Common Classification of Medical Acts, we will define four categories of EAIRP. We will collect procedures via the French nationwide hospital discharge database, called Programme de Médicalisation des Systèmes d'Information (PMSI) and derived from the Diagnosis Related Group system. Various combinations to identify the numerator will be employed according to a pre-established algorithm. Technical data wrangling tools facilitating the use of PMSI will be developed to obtain a clean and well-structured database ready for statistical analysis. This protocol will require competences in medicine, epidemiology, statistics, data processing and techniques through various stages of the study. The cohort will contain the denominator (the first act of the first stay of each patient) and the corresponding numerator (the IC which will occur during the first stay). ETHICS AND DISSEMINATION: No nominative, sensitive or personal data on patients have been collected. The study of the MOrtality and infectious complications of therapeutic EndoVAscular interventional radiology (MOEVA) study does not involve humans, and falls within the scope of the French Reference Methodology MR-004 according to 2016-41 law dated 26 January 2016 on the modernisation of the French health system. Our study involves the reuse of already recorded data, which require neither information or non-opposition of the included individuals. Access to linked ANOnymous (ANO) file in the PMSI databases was approved by the French National Commission for Data Protection and Liberties (CNIL number 1564135). The results will be disseminated through a peer-reviewed publication.
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Affiliation(s)
- Kaoutar Aid Mellouk
- Center of Doctoral Studies, Universite Ibn Tofail Kenitra Faculte des Sciences, Kenitra, Morocco
| | - Abdelmajid Soulaymani
- Center of Doctoral Studies, Universite Ibn Tofail Kenitra Faculte des Sciences, Kenitra, Morocco
| | - Fei Gao
- Public Health, French School for Advanced Studies in Public Health (EHESP), Rennes, France
| | - Pascal Astagneau
- CPias, Center of Support for the Prevention of the Infections Associated with Care Paris 14, Paris 14, Île-de-France, France
- Public Health, Pierre & Marie Curie faculty of medicine, Sorbonne universities, Paris, Île-de-France, France
| | - Benoit Misset
- Department of Intensive Care, Rouen University Hospital, Rouen, France
- Rouen University, Faculty of medecine and Pharmacy, Rouen, France
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Aliyu S, Furuya Y, Larson E. Risk of subsequent health care-associated infection among patients with a bloodstream infection present on hospital admission. Am J Infect Control 2019; 47:196-200. [PMID: 30709483 DOI: 10.1016/j.ajic.2018.11.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Revised: 11/19/2018] [Accepted: 11/28/2018] [Indexed: 10/27/2022]
Abstract
BACKGROUND The risks and outcomes of acquiring a health care-associated infection (HAI) among patients with a bloodstream infection present on hospital admission (BSI-POA) have not been well described. The objective of this study was to examine the incidence of and risk factors for developing a subsequent HAI and to compare length of stay and mortality between patients with a BSI-POA who develop an HAI and those who do not. METHODS This was a retrospective cohort study of patients aged ≥18 years discharged with a BSI-POA from 3 hospitals in New York City between 2006 and 2014. RESULTS There were 761 HAIs among the 11,436 patients with a BSI-POA. Incidence rates were: catheter-associated urinary tract infections, 5.03 infections per 1,000 catheter days; pneumonia, 2.7% among BSI-POA patients; surgical site infections, 9.2% among BSI-POA patients. Length of stay was longer among patients who developed an HAI (mean ± SD, 35.0 ± 29.8 vs 12.4 ± 11.9, P < .001). Mortality was higher in patients who developed an HAI (23.9% vs 11.6%, P < .001). CONCLUSIONS Risk factors for those who developed an HAI differed by infection type. Overall, HAI was associated with longer hospitalization, and pneumonia was associated with increased mortality.
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COHEN B, LIU J, LARSON E. Changes in the incidence and antimicrobial susceptibility of healthcare-associated infections in a New York hospital system, 2006-2012. JOURNAL OF PREVENTIVE MEDICINE AND HYGIENE 2017; 58:E294-E301. [PMID: 29707660 PMCID: PMC5912789 DOI: 10.15167/2421-4248/jpmh2017.58.4.774] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 10/28/2017] [Indexed: 11/16/2022]
Abstract
Introduction National efforts to curtail healthcare-associated infections (HAI) proliferated recently, though data detailing progress over time are limited. This retrospective cohort study aims to describe changes in incidence and antimicrobial susceptibility of HAI in four New York City hospitals over seven years. Methods Electronic data were collected retrospectively for all patients discharged from 2006 through 2012. Previously validated computerized algorithms based on National Healthcare Safety Network criteria detected bloodstream infections, pneumonia, surgical site infections, and urinary tract infections with Enterococcus spp., Staphylococcus aureus, Streptococcus pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Klebsiella pneumoniae. Antimicrobial susceptibilities were obtained from electronic laboratory records. Logistic regression was used to assess changes in odds of acquiring an HAI and odds of antimicrobial resistance over time, controlling for age, gender, severity of illness, previous hospitalizations, and admission source. Results In total, 19,052 HAI were identified among 761,426 discharges. HAI rates fell for all organisms, all infection types, and within all hospitals. Odds of acquiring an HAI decreased significantly over time for all organisms. Resistance levels were stable for Enterococcus spp., S. aureus, A. baumannii, and S. pneumoniae. Multidrug resistance increased for P. aeruginosa and decreased for K. pneumoniae, though imipenem resistance among K. pneumoniae climbed sharply in 2011. Conclusions This study suggests that HAI incidence rates are falling, possibly due to increased federal, state and local attention to healthcare quality and patient safety. Though we found no substantial reductions in resistance, recent national attention towards antimicrobial stewardship may precipitate a change in coming years.
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Affiliation(s)
- B. COHEN
- Columbia University School of Nursing, New York, NY, USA
- Department of Epidemiology, Mailman School of Public Health, New York, NY, USA
- * Correspondence: Bevin Cohen, Columbia University School of Nursing, 630 West 168 Street, New York, NY 10032 USA - Tel. 212-342-4111 - 212-305-0722 - E-mail:
| | - J. LIU
- Columbia University School of Nursing, New York, NY, USA
| | - E. LARSON
- Columbia University School of Nursing, New York, NY, USA
- Department of Epidemiology, Mailman School of Public Health, New York, NY, USA
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Cato KD, Liu J, Cohen B, Larson E. Electronic Surveillance of Surgical Site Infections. Surg Infect (Larchmt) 2017; 18:498-502. [PMID: 28402721 DOI: 10.1089/sur.2016.262] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Electronic health and administrative data are increasingly being used for identifying surgical site infections (SSI). We found an unexpectedly high number of patients who could not be classified definitively as having an infection or not. To further explore this, we present an electronic classification algorithm for conservative case finding and identify alterations that would adapt the method for other purposes. METHODS Two computer algorithms were created to identify SSI. One model used a strict National Healthcare Safety Network (NHSN) based SSI algorithm, which was applied to all discharges from 443,284 all discharges from four hospitals in Manhattan, NY, 2009 through 2012. The second model used discharges that only had NHSN-defined SSI procedures during the same period. RESULTS The strict SSI algorithm was able to classify SSI status for 27.3% of discharges; there was a high number of indeterminate cases. In contrast, the modified, less strict model, classified 97.2% of discharges with NHSN-approved SSI procedures. CONCLUSION Electronic records provide several options for aiding with the identification of infections in healthcare settings and can be tailored to suit specific uses. While algorithms for SSI classification should reflect the NHSN definition, our research emphasizes how variations of model building can affect the number of indeterminate cases that may necessitate manual review.
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Affiliation(s)
- Kenrick D Cato
- 1 School of Nursing, Columbia University , New York, New York.,3 New York Presbyterian Hospital , New York, New York
| | - Jianfang Liu
- 1 School of Nursing, Columbia University , New York, New York
| | - Bevin Cohen
- 1 School of Nursing, Columbia University , New York, New York.,2 Department of Epidemiology, Mailman School of Public Health, Columbia University , New York, New York
| | - Elaine Larson
- 1 School of Nursing, Columbia University , New York, New York.,2 Department of Epidemiology, Mailman School of Public Health, Columbia University , New York, New York
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Woelber E, Schrick EJ, Gessner BD, Evans HL. Proportion of Surgical Site Infections Occurring after Hospital Discharge: A Systematic Review. Surg Infect (Larchmt) 2016; 17:510-9. [DOI: 10.1089/sur.2015.241] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Affiliation(s)
- Erik Woelber
- University of Washington School of Medicine, Seattle, Washington
| | - Emily J. Schrick
- University of Washington College of Arts and Sciences, Seattle, Washington
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Glied S, Cohen B, Liu J, Neidell M, Larson E. Trends in mortality, length of stay, and hospital charges associated with health care-associated infections, 2006-2012. Am J Infect Control 2016; 44:983-9. [PMID: 27207157 DOI: 10.1016/j.ajic.2016.03.010] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2015] [Revised: 02/23/2016] [Accepted: 03/02/2016] [Indexed: 11/25/2022]
Abstract
BACKGROUND Many factors associated with hospital-acquired infections (HAIs), including reimbursement policies, drug prices, practice patterns, and the distribution of organisms causing infections, change over time. We examined whether outcomes, including mortality, length of stay (LOS), daily charges, and total charges associated with HAIs, changed during 2006-2012. METHODS Electronic data on adults discharged from 2 tertiary-quaternary hospitals and 1 community hospital during 2006-2012 were collected retrospectively. Computerized algorithms identified infections using laboratory and administrative codes. Propensity scores were used to match cases with uninfected controls. Differences in mortality, LOS, daily charges, and total charges were modeled against infection status and time period (2006-2008 vs 2009-2012), including interaction for infection status by time period. RESULTS Among 352,077 discharges, 24,466 HAIs were detected. There was no significant change in mortality. LOS declined only for bloodstream infections (3-day reduction; P < 0.01). Daily charges rose 4% for urinary tract infections but did not change significantly for other HAIs. Total charges declined by 11% for bloodstream infections and 13% for pneumonia. CONCLUSIONS We found no appreciable or consistent improvement in HAI mortality or LOS during 2006-2012. Costs of bloodstream infections and pneumonia have declined, with most of the change occurring before 2008.
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Tseng YJ, Wu JH, Lin HC, Chen MY, Ping XO, Sun CC, Shang RJ, Sheng WH, Chen YC, Lai F, Chang SC. A Web-Based, Hospital-Wide Health Care-Associated Bloodstream Infection Surveillance and Classification System: Development and Evaluation. JMIR Med Inform 2015; 3:e31. [PMID: 26392229 PMCID: PMC4705006 DOI: 10.2196/medinform.4171] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2014] [Revised: 06/07/2015] [Accepted: 07/24/2015] [Indexed: 11/16/2022] Open
Abstract
Background Surveillance of health care-associated infections is an essential component of infection prevention programs, but conventional systems are labor intensive and performance dependent. Objective To develop an automatic surveillance and classification system for health care-associated bloodstream infection (HABSI), and to evaluate its performance by comparing it with a conventional infection control personnel (ICP)-based surveillance system. Methods We developed a Web-based system that was integrated into the medical information system of a 2200-bed teaching hospital in Taiwan. The system automatically detects and classifies HABSIs. Results In this study, the number of computer-detected HABSIs correlated closely with the number of HABSIs detected by ICP by department (n=20; r=.999 P<.001) and by time (n=14; r=.941; P<.001). Compared with reference standards, this system performed excellently with regard to sensitivity (98.16%), specificity (99.96%), positive predictive value (95.81%), and negative predictive value (99.98%). The system enabled decreasing the delay in confirmation of HABSI cases, on average, by 29 days. Conclusions This system provides reliable and objective HABSI data for quality indicators, improving the delay caused by a conventional surveillance system.
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Affiliation(s)
- Yi-Ju Tseng
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
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Cohen B, Vawdrey DK, Liu J, Caplan D, Furuya EY, Mis FW, Larson E. Challenges Associated With Using Large Data Sets for Quality Assessment and Research in Clinical Settings. Policy Polit Nurs Pract 2015; 16:117-24. [PMID: 26351216 DOI: 10.1177/1527154415603358] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
The rapidly expanding use of electronic records in health-care settings is generating unprecedented quantities of data available for clinical, epidemiological, and cost-effectiveness research. Several challenges are associated with using these data for clinical research, including issues surrounding access and information security, poor data quality, inconsistency of data within and across institutions, and a paucity of staff with expertise to manage and manipulate large clinical data sets. In this article, we describe our experience with assembling a data-mart and conducting clinical research using electronic data from four facilities within a single hospital network in New York City. We culled data from several electronic sources, including the institution's admission-discharge-transfer system, cost accounting system, electronic health record, clinical data warehouse, and departmental records. The final data-mart contained information for more than 760,000 discharges occurring from 2006 through 2012. Using categories identified by the National Institutes of Health Big Data to Knowledge initiative as a framework, we outlined challenges encountered during the development and use of a domain-specific data-mart and recommend approaches to overcome these challenges.
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Affiliation(s)
- Bevin Cohen
- Columbia University School of Nursing, New York, NY, USA
| | - David K Vawdrey
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Jianfang Liu
- Columbia University School of Nursing, New York, NY, USA
| | - David Caplan
- Department of Information Services, New York-Presbyterian Hospital, New York, NY, USA
| | - E Yoko Furuya
- Department of Medicine, Columbia University, New York, NY, USA
| | - Frederick W Mis
- Department of Information Services, New York-Presbyterian Hospital, New York, NY, USA
| | - Elaine Larson
- Columbia University School of Nursing, New York, NY, USA
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van Mourik MSM, van Duijn PJ, Moons KGM, Bonten MJM, Lee GM. Accuracy of administrative data for surveillance of healthcare-associated infections: a systematic review. BMJ Open 2015; 5:e008424. [PMID: 26316651 PMCID: PMC4554897 DOI: 10.1136/bmjopen-2015-008424] [Citation(s) in RCA: 91] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2015] [Accepted: 08/07/2015] [Indexed: 11/10/2022] Open
Abstract
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.
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Affiliation(s)
- Maaike S M van Mourik
- Department of Medical Microbiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Pleun Joppe van Duijn
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Karel G M Moons
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Marc J M Bonten
- Department of Medical Microbiology, University Medical Center Utrecht, Utrecht, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Grace M Lee
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, Massachusetts, USA
- Division of Infectious Diseases, Boston Children's Hospital, Boston, Massachusetts, USA
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Data elements and validation methods used for electronic surveillance of health care-associated infections: a systematic review. Am J Infect Control 2015; 43:600-5. [PMID: 26042848 DOI: 10.1016/j.ajic.2015.02.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2015] [Accepted: 02/04/2015] [Indexed: 11/22/2022]
Abstract
BACKGROUND We describe the primary data sources, data elements, and validation methods currently used in electronic surveillance systems (ESS) for identification and surveillance of health care-associated infections (HAIs), and compares these data elements and validation methods with recommended standards. METHODS Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a PubMed and manual search was conducted to identify research articles describing ESS for identification and surveillance of HAIs published January 1, 2009-August 31, 2014. Selected articles were evaluated to determine what data elements and validation methods were included. RESULTS Among the 509 articles identified in the original literature search, 30 met the inclusion criteria. Whereas the majority of studies (83%) used recommended data sources and validated the numerator (80%), only 10% of studies performed external and internal validation. In addition, there was variation in the ESS data formats used. CONCLUSIONS Our findings suggest that the majority of ESS for HAI surveillance use standard definitions, but the lack of widespread internal data, denominator, and external validation in these systems reduces the reliability of their findings. Additionally, advanced programming skills are required to create, implement, and maintain these systems and to reduce the variability in data formats.
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Shang J, Stone P, Larson E. Studies on nurse staffing and health care-associated infection: methodologic challenges and potential solutions. Am J Infect Control 2015; 43:581-8. [PMID: 26042847 DOI: 10.1016/j.ajic.2015.03.029] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2014] [Revised: 03/18/2015] [Accepted: 03/26/2015] [Indexed: 10/23/2022]
Abstract
BACKGROUND Researchers have been studying hospital nurse staffing in relation to health care-associated infections (HAIs) for >2 decades, and the results have been mixed. We summarized published research examining these issues, critically analyzed the commonly used approaches, identified methodologic challenges, proposed potential solutions, and suggested the possible benefits of applying an electronic health record (EHR) system. METHODS A scoping review was conducted using MEDLINE and CINAHL from 1990 onward. Original research studies examining relationships between nurse staffing and HAIs in the hospital setting and published in peer-reviewed English-language journals were selected. RESULTS A total of 125 articles and abstracts were identified, and 45 met inclusion criteria. Findings from these studies were mixed. The methodologic challenges identified included database selection, variable measurement, methods to link the nurse staffing and HAI data, and temporality. Administrative staffing data were often not precise or specific. The most common method to link staffing and HAI data did not assess the temporal relationship. We proposed using daily staffing information 2-4 days prior to HAI onset linked to individual patient HAI data. CONCLUSION To assess the relationships between nurse staffing and HAIs, methodologic decisions are necessary based on what data are available and feasible to obtain. National efforts to promote an EHR may offer solutions for future studies by providing more comprehensive data on HAIs and nurse staffing.
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Leclère B, Lasserre C, Bourigault C, Juvin ME, Chaillet MP, Mauduit N, Caillon J, Hanf M, Lepelletier D. Matching bacteriological and medico-administrative databases is efficient for a computer-enhanced surveillance of surgical site infections: retrospective analysis of 4,400 surgical procedures in a French university hospital. Infect Control Hosp Epidemiol 2014; 35:1330-5. [PMID: 25333426 DOI: 10.1086/678422] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
OBJECTIVE Our goal was to estimate the performance statistics of an electronic surveillance system for surgical site infections (SSIs), generally applicable in French hospitals. METHODS Three detection algorithms using 2 different data sources were tested retrospectively on 9 types of surgical procedures performed between January 2010 and December 2011 in the University Hospital of Nantes. The first algorithm was based on administrative codes, the second was based on bacteriological data, and the third used both data sources. For each algorithm, sensitivity, specificity, and positive and negative predictive values (PPV and NPV) were calculated. The reference method was the hospital's routine surveillance: a comprehensive review of the computerized medical charts of the patients who underwent one of the targeted procedures during the study period. SETTING A 3,000-bed teaching hospital in western France. POPULATION We analyzed 4,400 targeted surgical procedures. RESULTS Sensitivity results varied significantly between the three algorithms, from 25% (95% confidence interval, 17-33) when using only administrative codes to 87% (80%-93%) with the bacteriological data and 90% (85%-96%) with the combined algorithm. Fewer variations were observed for specificity (91%-98%), PPV (21%-25%), and NPV (98% to nearly 100%). Overall, performance statistics were higher for deep SSIs than for superficial infections. CONCLUSIONS A reliable computer-enhanced SSI surveillance can easily be implemented in French hospitals using common data sources. This should allow infection control professionals to spend more time on prevention and education duties. However, a multicenter study should be conducted to assess the generalizability of this method.
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Affiliation(s)
- Brice Leclère
- Department of Bacteriology and Infection Control, Nantes University Hospital, Nantes, France
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Ippolito P, Larson EL, Furuya EY, Liu J, Seres DS. Utility of Electronic Medical Records to Assess the Relationship Between Parenteral Nutrition and Central Line-Associated Bloodstream Infections in Adult Hospitalized Patients. JPEN J Parenter Enteral Nutr 2014; 39:929-34. [PMID: 24898208 DOI: 10.1177/0148607114536580] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2014] [Accepted: 04/29/2014] [Indexed: 11/16/2022]
Abstract
BACKGROUND Parenteral nutrition is associated with increased central line-associated bloodstream infections (CLABSIs). Electronic databases are important for identifying independent risk factors for prevention strategies. Our aims were to evaluate the utility of using electronic data sources to identify risk factors for CLABSIs, including parenteral nutrition (PN), and to assess the association between CLABSI and PN administration. METHODS Data were obtained for all discharges of adult patients in whom a central line was inserted between September 1, 2007, and December 31, 2008, in a large, academically affiliated hospital in New York City. CLABSI was defined electronically using a modified definition from the Centers for Disease Control and Prevention. A manual chart review was also undertaken to assess validity/reliability of the electronic database and gather additional information. Risk factors for CLABSI were examined using logistic regression. RESULTS Among 4840 patients, there were 220 CLABSIs, an incidence of 5.4 CLABSIs per 1000 central line days. Risk factors included PN (odds ratio [OR], 4.33; 95% confidence interval [CI], 2.50-7.48), intensive care unit stay (OR, 2.26; 95% CI, 1.58-3.23), renal disease (OR, 2.79; 95% CI, 2.00-3.88), and immunodeficiency (OR, 2.26; 95% CI, 1.70-3.00). Diabetes mellitus was associated with reduced CLABSI rates (OR, 0.63; 95% CI, 0.45-0.88). CONCLUSIONS The utility of electronic medical records for determining risk factors is limited by such things as free-text data entry. Using a hybrid between fully electronic and manual chart review, reliable data were obtained. PN is associated with a high risk for CLABSI in a population highly selected for indications for PN.
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Affiliation(s)
- Paul Ippolito
- Division of Preventive Medicine & Nutrition, Department of Medicine, Columbia University Medical Center, New York, New York
| | - Elaine L Larson
- Center for Interdisciplinary Research to Prevent Infections, Columbia University, New York, New York Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York Columbia University School of Nursing, New York, New York
| | - E Yoko Furuya
- Division of Infectious Diseases, Department of Medicine, Columbia University Medical Center, New York, New York
| | - Jianfang Liu
- Columbia University School of Nursing, New York, New York
| | - David S Seres
- Division of Preventive Medicine & Nutrition, Department of Medicine, Columbia University Medical Center, New York, New York Institute of Human Nutrition, Columbia University Medical Center, New York, New York
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Hogle NJ, Cohen B, Hyman S, Larson E, Fowler DL. Incidence and risk factors for and the effect of a program to reduce the incidence of surgical site infection after cardiac surgery. Surg Infect (Larchmt) 2014; 15:299-304. [PMID: 24800982 PMCID: PMC4063380 DOI: 10.1089/sur.2013.048] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Surgical site infection (SSI) after cardiac surgery (CS) is a serious complication that increases hospital length of stay (LOS), has a substantial financial impact, and increases mortality. The study described here was done to evaluate the effect of a program to reduce SSI after CS. METHODS In January 2007, a multi-disciplinary CS infection-prevention team developed guidelines and implemented bundled tactics for reducing SSI. Data for all patients who underwent CS from 2006-2008 were used to determine whether there was: 1) A difference in the incidence of SSI in white patients and those belonging to minority groups; 2) a reduction in SSI after intervention; and 3) a statistically significant difference in the incidence of SSI in the third quarter of each year as compared with the other quarters of the year. RESULTS Of 3,418 patients who underwent CS; 1,125 (32.9%) were members of minority groups and 2,293 (67.1%) were white. Eighty (2.3%) patients developed SSI. There was no significant difference in the incidence of SSI in non-Hispanic white patients and all others (2.1% vs. 2.8%, p=0. 42). The incidence of SSI decreased significantly from 2006 (3.0%) to 2007 (2.5%) and 2008 (1.4%), (p=0.03). Surgical site infection occurred more often in the third quarter of each of the years of the study than in other quarters of each year (3.3 vs. 2.0%, p=0.038). CONCLUSIONS Implementation of a program to reduce SSI after CS was associated with a lower incidence of SSI across all racial and ethnic groups and over time, but was not associated with a lower incidence of SSI in the third quarter of each year than in the other quarters.
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Affiliation(s)
- Nancy J. Hogle
- Department of Surgery, Columbia University College of Physicians and Surgeons, New York, New York
| | - Bevin Cohen
- Center for Interdisciplinary Research to Prevent Infections, School of Nursing, Columbia University, New York, New York
| | - Sandra Hyman
- Department of Perioperative Services, New York-Presbyterian Hospital, New York, New York
| | - Elaine Larson
- Center for Interdisciplinary Research to Prevent Infections, School of Nursing, Columbia University, New York, New York
| | - Dennis L. Fowler
- Department of Surgery, Columbia University College of Physicians and Surgeons, New York, New York
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Wolfe CM, Cohen B, Larson E. Prevalence and risk factors for antibiotic-resistant community-associated bloodstream infections. J Infect Public Health 2014; 7:224-32. [PMID: 24631369 DOI: 10.1016/j.jiph.2014.01.001] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2013] [Revised: 01/08/2014] [Accepted: 01/10/2014] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Antibiotic resistance is increasing in many community settings. The purpose of this study was to determine the proportion of antibiotic resistant community-associated bloodstream infections (CA-BSIs) present on hospital admissions to identify risk factors for acquiring resistant versus susceptible CA-BSIs and to describe the incidence of concurrent infections with CA-BSIs. METHODS We conducted a retrospective cohort study of patients discharged from one community, one pediatric, and two tertiary/quaternary care hospitals within an academically affiliated network in the borough of Manhattan in New York, NY, from 2006 to 2008. The CA-BSIs present at hospital admission were defined as BSIs occurring within the first 48h of hospitalization. Infections and patient characteristics were identified using data available from patients' electronic medical records and discharge records. RESULTS In total, 1677 CA-BSIs were identified. Staphylococcus aureus had the largest proportion of resistance (41.2%), followed by enterococcal species (24.3%), Pseudomonas aeruginosa (20.2%), Streptococcus pneumoniae (16.6%), Acinetobacter baumannii (10.0%), and Klebsiella pneumoniae (9.9%). Significant predictors of resistance were prior residence in a skilled nursing facility (OR, 2.55; 95% CI, 1.39-4.70), advanced age (1.01; 1.002-1.02), presence of malignancy (0.58; 0.37-0.91), prior hospitalization (1.62; 1.17-2.23), a weighted Charlson score (1.09; 1.02-1.17) for S. aureus, presence of malignancy (1.82; 1.004-3.30), prior hospitalizations (2.03; 1.12-3.38) for enterococcal species, and younger age for S. pneumoniae (p=0.02). Urinary tract infections were the most common concurrent infection (n=45/87, 51.7%). CONCLUSION Over 27% of the CA-BSIs present on admission were antibiotic resistant. Understanding the prevalence and risk factors for CA-BSIs may help improve empiric antibiotic therapy and outcomes for patients with community-onset infections.
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Affiliation(s)
- Caitlin M Wolfe
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, NY 10032, USA.
| | - Bevin Cohen
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, NY 10032, USA; Columbia University School of Nursing, 630 West 168th Street, New York, NY 10032, USA.
| | - Elaine Larson
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 West 168th Street, New York, NY 10032, USA; Columbia University School of Nursing, 630 West 168th Street, New York, NY 10032, USA.
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Gender differences in risk of bloodstream and surgical site infections. J Gen Intern Med 2013; 28:1318-25. [PMID: 23605308 PMCID: PMC3785652 DOI: 10.1007/s11606-013-2421-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2012] [Revised: 12/17/2012] [Accepted: 03/13/2013] [Indexed: 01/02/2023]
Abstract
BACKGROUND Identifying patients most at risk for hospital- and community-associated infections is one essential strategy for preventing infections. OBJECTIVE To investigate whether rates of community- and healthcare-associated bloodstream and surgical site infections varied by patient gender in a large cohort after controlling for a wide variety of possible confounders. DESIGN Retrospective cohort study. PARTICIPANTS All patients discharged from January 1, 2006 through December 31, 2008 (133,756 adult discharges and 66,592 pediatric discharges) from a 650-bed tertiary care hospital, a 220-bed community hospital, and a 280-bed pediatric acute care hospital within a large, academic medical center in New York, NY. MAIN MEASURES Data were collected retrospectively from various electronic sources shared by the hospitals and linked using patients' unique medical record numbers. Infections were identified using previously validated computerized algorithms. KEY RESULTS Odds of community-associated bloodstream infections, healthcare-associated bloodstream infections, and surgical site infections were significantly lower for women than for men after controlling for present-on-admission patient characteristics and events during the hospital stay [odds ratios (95 % confidence intervals) were 0.85 (0.77-0.93), 0.82 (0.74-0.91), and 0.78 (0.68-0.91), respectively]. Gender differences were greatest for older adolescents (12-17 years) and adults 18-49 years and least for young children (<12 years) and older adults (≥ 70 years). CONCLUSIONS In this cohort, men were at higher risk for bloodstream and surgical site infections, possibly due to differences in propensity for skin colonization or other anatomical differences.
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Knepper BC, Young H, Jenkins TC, Price CS. Time-saving impact of an algorithm to identify potential surgical site infections. Infect Control Hosp Epidemiol 2013; 34:1094-8. [PMID: 24018927 DOI: 10.1086/673154] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
OBJECTIVE To develop and validate a partially automated algorithm to identify surgical site infections (SSIs) using commonly available electronic data to reduce manual chart review. DESIGN Retrospective cohort study of patients undergoing specific surgical procedures over a 4-year period from 2007 through 2010 (algorithm development cohort) or over a 3-month period from January 2011 through March 2011 (algorithm validation cohort). SETTING A single academic safety-net hospital in a major metropolitan area. PATIENTS Patients undergoing at least 1 included surgical procedure during the study period. METHODS Procedures were identified in the National Healthcare Safety Network; SSIs were identified by manual chart review. Commonly available electronic data, including microbiologic, laboratory, and administrative data, were identified via a clinical data warehouse. Algorithms using combinations of these electronic variables were constructed and assessed for their ability to identify SSIs and reduce chart review. RESULTS The most efficient algorithm identified in the development cohort combined microbiologic data with postoperative procedure and diagnosis codes. This algorithm resulted in 100% sensitivity and 85% specificity. Time savings from the algorithm was almost 600 person-hours of chart review. The algorithm demonstrated similar sensitivity on application to the validation cohort. CONCLUSIONS A partially automated algorithm to identify potential SSIs was highly sensitive and dramatically reduced the amount of manual chart review required of infection control personnel during SSI surveillance.
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Affiliation(s)
- B C Knepper
- Department of Patient Safety and Quality, Denver Health Medical Center, Denver, Colorado
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King C, Aylin P, Chukwuemeka A, Anderson J, Holmes A. Assessing data sources for sustainable and continuous surveillance: surgical site infections following coronary artery bypass grafts in England. J Hosp Infect 2013; 84:305-10. [DOI: 10.1016/j.jhin.2013.05.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2013] [Accepted: 05/16/2013] [Indexed: 10/26/2022]
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Advances in electronic surveillance for healthcare-associated infections in the 21st Century: a systematic review. J Hosp Infect 2013; 84:106-19. [PMID: 23648216 DOI: 10.1016/j.jhin.2012.11.031] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2012] [Accepted: 11/30/2012] [Indexed: 11/23/2022]
Abstract
BACKGROUND Traditional methodologies for healthcare-associated infection (HCAI) surveillance can be resource intensive and time consuming. As a consequence, surveillance is often limited to specific organisms or conditions. Various electronic databases exist within the healthcare setting and may be utilized to perform HCAI surveillance. AIM To assess the utility of electronic surveillance systems for monitoring and detecting HCAI. METHODS A systematic review of published literature on surveillance of HCAI was performed. Databases were searched for studies published between January 2000 and December 2011. Search terms were divided into infection, surveillance and data management terms, and combined using Boolean operators. Studies were included for review if they demonstrated or proposed the use of electronic systems for HCAI surveillance. FINDINGS In total, 44 studies met the inclusion criteria. For the majority of studies, emphasis was on the linkage of electronic databases to provide automated methods for monitoring infections in specific clinical settings. Twenty-one studies assessed the performance of their method with traditional surveillance methodologies or a manual reference method. Where sensitivity and specificity were calculated, these varied depending on the organism or condition being surveyed and the data sources employed. CONCLUSIONS The implementation of electronic surveillance was found to be feasible in many settings, with several systems fully integrated into hospital information systems and routine surveillance practices. The results of this review suggest that electronic surveillance systems should be developed to maximize the efficacy of abundant electronic data sources existing within hospitals.
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Jeon CY, Furuya EY, Berman MF, Larson EL. The role of pre-operative and post-operative glucose control in surgical-site infections and mortality. PLoS One 2012; 7:e45616. [PMID: 23029136 PMCID: PMC3446927 DOI: 10.1371/journal.pone.0045616] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2012] [Accepted: 08/23/2012] [Indexed: 11/20/2022] Open
Abstract
Background and Objective The impact of glucose control on surgical-site infection (SSI) and death remains unclear. We examined how pre- and post-operative glucose levels and their variability are associated with the risk of SSI or in-hospital death. Methods This retrospective cohort study employed data on 13,800 hospitalized patients who underwent a surgical procedure at a large referral hospital in New York between 2006 and 2008. Over 20 different sources of electronic data were used to analyze how thirty-day risk of SSI and in-hospital death varies by glucose levels and variability. Maximum pre- and post-operative glucose levels were determined for 72 hours before and after the operation and glucose variability was defined as the coefficient of variation of the glucose measurements. We employed logistic regression to model the risk of SSI or death against glucose variables and the following potential confounders: age, sex, body mass index, duration of operation, diabetes status, procedure classification, physical status, emergency status, and blood transfusion. Results While association of pre- and post-operative hyperglycemia with SSI were apparent in the crude analysis, multivariate results showed that SSI risk did not vary significantly with glucose levels. On the other hand, in-hospital deaths were associated with pre-operative hypoglycemia (OR = 5.09, 95% CI (1.80, 14.4)) and glucose variability (OR = 1.14, 95% CI (1.03, 1.27) for 10% increase in coefficient of variation). Conclusion In-hospital deaths occurred more often among those with pre-operative hypoglycemia and higher glucose variability. These findings warrant further investigation to determine whether stabilization of glucose and prevention of hypoglycemia could reduce post-operative deaths.
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Affiliation(s)
- Christie Y Jeon
- School of Nursing, Columbia University School of Nursing, New York, NY, USA.
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