External and internal validation of healthcare-associated infection data collected by the Korean National healthcare-associated Infections Surveillance System (KONIS)

被引:1
|
作者
Song, Je Eun [1 ,2 ]
Kwak, Yee Gyung [1 ,2 ,10 ]
Oh, Gang-Bok [2 ]
Choi, Young Hwa [3 ]
Kim, Sung Ran [4 ]
Ha Han, Su [5 ]
Yoo, So-Yeon [6 ]
Yoo, Hyeon Mi [7 ]
Choi, Ji-youn [8 ]
Shin, Myoung Jin [9 ]
机构
[1] Inje Univ, Ilsan Paik Hosp, Dept Internal Med, Goyang, South Korea
[2] Inje Univ, Ilsan Paik Hosp, Infect Control Off, Goyang, South Korea
[3] Ajou Univ, Sch Med, Dept Infect Dis, Suwon, South Korea
[4] Korea Univ, Guro Hosp, Infect Control Off, Seoul, South Korea
[5] Soonchunhyang Univ Med, Dept Nursing, Cheonan, South Korea
[6] Catholic Univ Korea, Coll Nursing, Dept Nursing, Seoul, South Korea
[7] Inje Univ, Sanggye Paik Hosp, Infect Control Off, Seoul, South Korea
[8] Chungang Univ Hosp, Infect Control Team, Seoul, South Korea
[9] Seoul Natl Univ, Infect Control Off, Bundang Hosp, Seongnam, South Korea
[10] Inje Univ, Ilsan Paik Hosp, Dept Internal Med, Div Infect Dis, 170 Juhwaro, Goyang Si, Gyeonggi Do, South Korea
关键词
Urinary tract infection; Pneumonia; Bloodstream infection; Surveillance; Nosocomial infection;
D O I
10.1016/j.ajic.2023.06.020
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: This study analyzed the validity of healthcare -associated infection (HAI) data of the Korean National healthcare -associated Infections Surveillance System. Methods: The validation process consisted of external (EV) and internal (IV) validation phases. Of the 193 hospitals that participated from July 2016 through June 2017, EV was performed for 10 hospitals that were selected based on the HAI rate percentile. The EV team reviewed 295 medical records for 60 HAIs and 235 non-HAI control patients. IV was performed for both the 10 EV hospitals and 11 other participating hospitals that did not report any HAIs. Results: In the EV, the diagnosis of urinary tract infections had a sensitivity of 72.0% and a specificity of 99.3%. The respective sensitivities of bloodstream infection and pneumonia were 63.2% and 70.6%; the respective specificities were 98.8% and 99.6%. The agreement (kappa) between the EV and IV for 10 hospitals was 0.754 for urinary tract infections and 0.674 for bloodstream infections (P < .001, respectively). Additionally, IV found additional cases among 11 zero -report hospitals. Discussion: This study demonstrates the need for ongoing validation and continuous training to maintain the accuracy of nationwide surveillance data. Conclusions: IV should be considered a validation method to supplement EV. (c) 2023 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
引用
收藏
页码:214 / 219
页数:6
相关论文
共 50 条
  • [21] Surveillance of healthcare-associated infections in a Tunisian university hospital
    Hannachi, H.
    Ben Cheikh, A.
    Bhiri, S.
    Ghali, H.
    Khefacha, S.
    Dhidah, L.
    Ben Rejeb, M.
    Latiri, H. Said
    EUROPEAN JOURNAL OF PUBLIC HEALTH, 2019, 29
  • [22] Getting it right: automated surveillance of healthcare-associated infections
    van Mourik, Maaike S. M.
    CLINICAL MICROBIOLOGY AND INFECTION, 2021, 27 : S1 - S2
  • [23] Automated Surveillance for Healthcare-Associated Infections: Opportunities for Improvement
    van Mourik, Maaike S. M.
    Troelstra, Annet
    van Solinge, Wouter W.
    Moons, Karel G. M.
    Bonten, Marc J. M.
    CLINICAL INFECTIOUS DISEASES, 2013, 57 (01) : 85 - 93
  • [24] Accuracy of administrative data for surveillance of healthcare-associated infections: a systematic review
    van Mourik, Maaike S. M.
    van Duijn, Pleun Joppe
    Moons, Karel G. M.
    Bonten, Marc J. M.
    Lee, Grace M.
    BMJ OPEN, 2015, 5 (08):
  • [25] Potential Uses of a National Healthcare-Associated Infection Reporting System
    Snyder, Graham M.
    Morgan, Daniel J.
    INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY, 2016, 37 (09): : 1109 - 1110
  • [26] Healthcare-associated central nervous system infections
    Ippolito, Mariachiara
    Giarratano, Antonino
    Cortegiani, Andrea
    CURRENT OPINION IN ANESTHESIOLOGY, 2022, 35 (05) : 549 - 554
  • [27] Validation of a novel method to identify healthcare-associated infections
    Lee, J.
    Imanaka, Y.
    Sekimoto, M.
    Nishikawa, H.
    Ikai, H.
    Motohashi, T.
    JOURNAL OF HOSPITAL INFECTION, 2011, 77 (04) : 316 - 320
  • [28] Flowers and healthcare-associated infection
    Kerr, K. G.
    JOURNAL OF HOSPITAL INFECTION, 2006, 64 (03) : 301 - 302
  • [29] Comparison of Data Collection for Healthcare-Associated Infection Surveillance in Nursing Homes
    Epstein, Lauren
    Stone, Nimalie D.
    LaPlace, Lisa
    Harper, Jane
    Lynfield, Ruth
    Warnke, Linn
    Whitten, Tory
    Maloney, Meghan
    Melchreit, Richard
    Rodriguez, Richard
    Quinlan, Gail
    Concannon, Cathleen
    Dumyati, Ghinwa
    Thompson, Deborah L.
    Thompson, Nicola
    INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY, 2016, 37 (12): : 1440 - 1445
  • [30] Evaluation of Healthcare-Associated Infection Surveillance in Pennsylvania Hospitals
    Palumbo, Aimee J.
    Loveless, P. Ann
    Moll, Maria E.
    Ostroff, Stephen
    INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY, 2012, 33 (02): : 105 - 111