Validation of semiautomated surgical site infection surveillance using electronic screening algorithms in 38 surgery categories

2018 ◽  
Vol 39 (8) ◽  
pp. 931-935 ◽  
Author(s):  
Sun Young Cho ◽  
Doo Ryeon Chung ◽  
Jong Rim Choi ◽  
Doo Mi Kim ◽  
Si-Ho Kim ◽  
...  
Keyword(s):  
Surgical Site Infection ◽  
Surveillance System ◽  
Chart Review ◽  
Medical Center ◽  
Tertiary Care ◽  
Microbial Culture ◽  
Site Infection ◽  
Electronic Screening ◽  
Sensitivity Specificity ◽  
Infection Preventionists

ObjectiveTo verify the validity of a semiautomated surgical site infection (SSI) surveillance system using electronic screening algorithms in 38 categories of surgery.DesignA cohort study for validation of semiautomated SSI surveillance system using screening algorithms.SettingA 1,989-bed tertiary-care referral center in Seoul, Republic of Korea.MethodsA dataset of 40,516 surgical procedures in 38 categories stored in the conventional SSI surveillance registry at the Samsung Medical Center between January 2013 and December 2014 was used as the reference standard. In the semiautomated surveillance system, electronic screening algorithms flagged cases meeting at least 1 of 3 criteria: antibiotic prescription, microbial culture, and infectious disease consultation. Flagged cases were audited by infection preventionists. Analyses of sensitivity, specificity, and positive predictive value (PPV) were conducted for the semiautomated surveillance system, and its effect on reducing the workload for chart review was evaluated.ResultsA total of 575 SSI events (1·42%) were identified by conventional SSI surveillance. The sensitivity of the semiautomated SSI surveillance was 96·7%, and the PPV of the screening algorithms alone was 4·1%. Semiautomated SSI surveillance reduced the chart review workload of the infection preventionists from 1,283 to 482 person hours per year (a 62·4% decrease).ConclusionsCompared to conventional surveillance, semiautomated surveillance using electronic screening algorithms followed by chart review of selected cases can provide high-validity surveillance results and can significantly reduce the workload of infection preventionists.

scholarly journals Independent risk factors for surgical site infection after cesarean delivery in a rural tertiary care medical center

2016 ◽  
Vol 31 (1) ◽  
pp. 120-126 ◽  
Author(s):  
Manuel C. Vallejo ◽  
Ahmed F. Attaallah ◽  
Robert E. Shapiro ◽  
Osama M. Elzamzamy ◽  
Michael G. Mueller ◽  
...  
Keyword(s):  
Risk Factors ◽  
Surgical Site Infection ◽  
Cesarean Delivery ◽  
Medical Center ◽  
Tertiary Care ◽  
Site Infection ◽  
Tertiary Care Medical Center ◽  
Independent Risk Factors

Building and Validating a Computerized Algorithm for Surveillance of Ventilator-Associated Events

2015 ◽  
Vol 36 (9) ◽  
pp. 999-1003 ◽  
Author(s):  
Tal Mann ◽  
Joseph Ellsworth ◽  
Najia Huda ◽  
Anupama Neelakanta ◽  
Thomas Chevalier ◽  
...  
Keyword(s):  
Infection Control ◽  
Predictive Value ◽  
Medical Center ◽  
Care Center ◽  
Tertiary Care ◽  
Tertiary Care Center ◽  
Mechanically Ventilated ◽  
Automated Method ◽  
Sensitivity Specificity ◽  
Infection Preventionists

OBJECTIVETo develop an automated method for ventilator-associated condition (VAC) surveillance and to compare its accuracy and efficiency with manual VAC surveillanceSETTINGThe intensive care units (ICUs) of 4 hospitalsMETHODSThis study was conducted at Detroit Medical Center, a tertiary care center in metropolitan Detroit. A total of 128 ICU beds in 4 acute care hospitals were included during the study period from August to October 2013. The automated VAC algorithm was implemented and utilized for 1 month by all study hospitals. Simultaneous manual VAC surveillance was conducted by 2 infection preventionists and 1 infection control fellow who were blinded to each another’s findings and to the automated VAC algorithm results. The VACs identified by the 2 surveillance processes were compared.RESULTSDuring the study period, 110 patients from all the included hospitals were mechanically ventilated and were evaluated for VAC for a total of 992 mechanical ventilation days. The automated VAC algorithm identified 39 VACs with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 100%. In comparison, the combined efforts of the IPs and the infection control fellow detected 58.9% of VACs, with 59% sensitivity, 99% specificity, 91% PPV, and 92% NPV. Moreover, the automated VAC algorithm was extremely efficient, requiring only 1 minute to detect VACs over a 1-month period, compared to 60.7 minutes using manual surveillance.CONCLUSIONSThe automated VAC algorithm is efficient and accurate and is ready to be used routinely for VAC surveillance. Furthermore, its implementation can optimize the sensitivity and specificity of VAC identification.Infect. Control Hosp. Epidemiol. 2015;36(9):999–1003

scholarly journals Variable Case Detection and Many Unreported Cases of Surgical-Site Infection Following Colon Surgery and Abdominal Hysterectomy in a Statewide Validation

2017 ◽  
Vol 38 (9) ◽  
pp. 1091-1097 ◽  
Author(s):  
Michael S. Calderwood ◽  
Susan S. Huang ◽  
Vicki Keller ◽  
Christina B. Bruce ◽  
N. Neely Kazerouni ◽  
...  
Keyword(s):  
Surgical Site Infection ◽  
Chart Review ◽  
External Validation ◽  
Colon Surgery ◽  
Abdominal Hysterectomy ◽  
Site Infection ◽  
California Department ◽  
Added Benefit ◽  
Infection Preventionists ◽  
Traditional Surveillance

OBJECTIVETo assess hospital surgical-site infection (SSI) identification and reporting following colon surgery and abdominal hysterectomy via a statewide external validationMETHODSInfection preventionists (IPs) from the California Department of Public Health (CDPH) performed on-site SSI validation for surgical procedures performed in hospitals that voluntarily participated. Validation involved chart review of SSI cases previously reported by hospitals plus review of patient records flagged for review by claims codes suggestive of SSI. We assessed the sensitivity of traditional surveillance and the added benefit of claims-based surveillance. We also evaluated the positive predictive value of claims-based surveillance (ie, workload efficiency).RESULTSUpon validation review, CDPH IPs identified 239 SSIs following colon surgery at 42 hospitals and 76 SSIs following abdominal hysterectomy at 34 hospitals. For colon surgery, traditional surveillance had a sensitivity of 50% (47% for deep incisional or organ/space [DI/OS] SSI), compared to 84% (88% for DI/OS SSI) for claims-based surveillance. For abdominal hysterectomy, traditional surveillance had a sensitivity of 68% (67% for DI/OS SSI) compared to 74% (78% for DI/OS SSI) for claims-based surveillance. Claims-based surveillance was also efficient, with 1 SSI identified for every 2 patients flagged for review who had undergone abdominal hysterectomy and for every 2.6 patients flagged for review who had undergone colon surgery. Overall, CDPH identified previously unreported SSIs in 74% of validation hospitals performing colon surgery and 35% of validation hospitals performing abdominal hysterectomy.CONCLUSIONSClaims-based surveillance is a standardized approach that hospitals can use to augment traditional surveillance methods and health departments can use for external validation.Infect Control Hosp Epidemiol 2017;38:1091–1097

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

2011 ◽  
Vol 32 (4) ◽  
pp. 351-359 ◽  
Author(s):  
Maria C. S. Inacio ◽  
Elizabeth W. Paxton ◽  
Yuexin Chen ◽  
Jessica Harris ◽  
Enid Eck ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Surgical Site Infection ◽  
Joint Replacement ◽  
Chart Review ◽  
Total Joint Replacement ◽  
Health Record ◽  
Site Infection ◽  
Predictive Values ◽  
Electronic Screening ◽  
Screening Algorithm

Objective.TO evaluate whether a hybrid electronic screening algorithm using a total joint replacement (TJR) registry, electronic surgical site infection (SSI) screening, and electronic health record (EHR) review of SSI is sensitive and specific for SSI detection and reduces chart review volume for SSI surveillance.Design.Validation study.Setting.A large health maintenance organization (HMO) with 8.6 million members.Methods.Using codes for infection, wound complications, cellullitis, procedures related to infections, and surgeon-reported complications from the International Classification of Diseases, Ninth Revision, Clinical Modification, we screened each TJR procedure performed in our HMO between January 2006 and December 2008 for possible infections. Flagged charts were reviewed by clinical-content experts to confirm SSIs. SSIs identified by the electronic screening algorithm were compared with SSIs identified by the traditional indirect surveillance methodology currently employed in our HMO. Positive predictive values (PPVs), negative predictive values (NPVs), and specificity and sensitivity values were calculated. Absolute reduction of chart review volume was evaluated.Results.The algorithm identified 4,001 possible SSIs (9.5%) for the 42,173 procedures performed for our TJR patient population. A total of 440 case patients (1.04%) had SSIs (PPV, 11.0%; NPV, 100.0%). The sensitivity and specificity of the overall algorithm were 97.8% and 91.5%, respectively.Conclusion.An electronic screening algorithm combined with an electronic health record review of flagged cases can be used as a valid source for TJR SSI surveillance. The algorithm successfully reduced the volume of chart review for surveillance by 90.5%.

256 Do Non-Beta-lactam antibiotics increase risk for surgical site infection after cesarean: a retrospective chart review

2021 ◽  
Vol 224 (2) ◽  
pp. S169-S170
Author(s):  
Ariana L. Lewis ◽  
Amanda M. Murray ◽  
Luke A. Newton ◽  
Shawna A. Mattathil ◽  
Diana A. Rascon
Keyword(s):  
Surgical Site Infection ◽  
Chart Review ◽  
Retrospective Chart Review ◽  
Site Infection ◽  
Beta Lactam ◽  
Beta Lactam Antibiotics ◽  
Increase Risk

Developing a Surgical Site Infection Surveillance System Based on Hospital Unstructured Clinical Notes and Text Mining

2020 ◽  
Vol 21 (8) ◽  
pp. 716-721 ◽  
Author(s):  
Marta Luisa Ciofi Degli Atti ◽  
Fabrizio Pecoraro ◽  
Simone Piga ◽  
Daniela Luzi ◽  
Massimiliano Raponi
Keyword(s):  
Text Mining ◽  
Surgical Site Infection ◽  
Surveillance System ◽  
Site Infection ◽  
Clinical Notes ◽  
Infection Surveillance

scholarly journals Communications and Screening for 2019 Novel Coronavirus at a Tertiary-Care Medical Center

2020 ◽  
Vol 41 (S1) ◽  
pp. s84-s84
Author(s):  
Lorinda Sheeler ◽  
Mary Kukla ◽  
Oluchi Abosi ◽  
Holly Meacham ◽  
Stephanie Holley ◽  
...  
Keyword(s):  
Screening Tool ◽  
Medical Center ◽  
Academic Medical Center ◽  
Tertiary Care ◽  
The United States ◽  
World Health ◽  
Communication Campaign ◽  
Electronic Screening ◽  
Novel Coronavirus ◽  
The Impact

Background: In December of 2019, the World Health Organization reported a novel coronavirus (severe acute respiratory coronavirus virus 2 [SARS-CoV-2)]) causing severe respiratory illness originating in Wuhan, China. Since then, an increasing number of cases and the confirmation of human-to-human transmission has led to the need to develop a communication campaign at our institution. We describe the impact of the communication campaign on the number of calls received and describe patterns of calls during the early stages of our response to this emerging infection. Methods: The University of Iowa Hospitals & Clinics is an 811-bed academic medical center with >200 outpatient clinics. In response to the coronavirus disease 2019 (COVID-19) outbreak, we launched a communications campaign on January 17, 2020. Initial communications included email updates to staff and a dedicated COVID-19 webpage with up-to-date information. Subsequently, we developed an electronic screening tool to guide a risk assessment during patient check in. The screening tool identifies travel to China in the past 14 days and the presence of symptoms defined as fever >37.7°C plus cough or difficulty breathing. The screening tool was activated on January 24, 2020. In addition, university staff contacted each student whose primary residence record included Hubei Province, China. Students were provided with medical contact information, signs and symptoms to monitor for, and a thermometer. Results: During the first 5 days of the campaign, 3 calls were related to COVID-19. The number of calls increased to 18 in the 5 days following the implementation of the electronic screening tool. Of the 21 calls received to date, 8 calls (38%) were generated due to the electronic travel screen, 4 calls (19%) were due to a positive coronavirus result in a multiplex respiratory panel, 4 calls (19%) were related to provider assessment only (without an electronic screening trigger), and 2 calls (10%) sought additional information following the viewing of the web-based communication campaign. Moreover, 3 calls (14%) were for people without travel history but with respiratory symptoms and contact with a person with recent travel to China. Among those reporting symptoms after travel to China, mean time since arrival to the United States was 2.7 days (range, 0–11 days). Conclusion: The COVID-19 outbreak is evolving, and providing up to date information is challenging. Implementing an electronic screening tool helped providers assess patients and direct questions to infection prevention professionals. Analyzing the types of calls received helped tailor messaging to frontline staff.Funding: NoneDisclosures: None

Surgical site infection in colorectal surgeries: Experience in tertiary care hospital

2015 ◽  
Vol 12 ◽  
pp. S11
Author(s):  
Afshan Anjum Wani ◽  
Nisar Ahmad Chowdri ◽  
Fazal Q. Parray ◽  
Rouf A. Wani
Keyword(s):  
Surgical Site Infection ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Care Hospital ◽  
Site Infection
Sign in / Sign up

Export Citation Format

Share Document