Semiautomated Surveillance of Deep Surgical Site Infections After Primary Total Hip or Knee Arthroplasty

2017 ◽  
Vol 38 (06) ◽  
pp. 732-735 ◽  
Author(s):  
Meander E. Sips ◽  
Marc J. M. Bonten ◽  
Maaike S. M. van Mourik
Keyword(s):  
Electronic Health Records ◽  
Knee Arthroplasty ◽  
Surgical Site Infections ◽  
Routine Care ◽  
Infect Control Hosp ◽  
Health Records ◽  
Total Hip ◽  
Electronic Health

Manual surveillance of surgical site infections (SSIs) after total hip or knee arthroplasty is time-consuming and prone to error. Semiautomated surveillance based on routine care data extracted from electronic health records can retrospectively identify deep SSIs and substantially reduce workload while maintaining 100% sensitivity.Infect Control Hosp Epidemiol2017;38:732–735

scholarly journals Validation of an algorithm for semiautomated surveillance to detect deep surgical site infections after primary total hip or knee arthroplasty—A multicenter study

2020 ◽  
Vol 42 (1) ◽  
pp. 69-74
Author(s):  
Janneke D. M. Verberk ◽  
Stephanie M. van Rooden ◽  
Mayke B. G. Koek ◽  
David J. Hetem ◽  
Annelies E. Smilde ◽  
...  
Keyword(s):  
Knee Arthroplasty ◽  
High Probability ◽  
Surgical Site Infections ◽  
Data Interpretation ◽  
Routine Care ◽  
Successful Implementation ◽  
Subjective Data ◽  
Essential Information ◽  
Total Hip ◽  
Healthcare Associated

AbstractObjective:Surveillance of healthcare-associated infections is often performed by manual chart review. Semiautomated surveillance may substantially reduce workload and subjective data interpretation. We assessed the validity of a previously published algorithm for semiautomated surveillance of deep surgical site infections (SSIs) after total hip arthroplasty (THA) or total knee arthroplasty (TKA) in Dutch hospitals. In addition, we explored the ability of a hospital to automatically select the patients under surveillance.Design:Multicenter retrospective cohort study.Methods:Hospitals identified patients who underwent THA or TKA either by procedure codes or by conventional surveillance. For these patients, routine care data regarding microbiology results, antibiotics, (re)admissions, and surgeries within 120 days following THA or TKA were extracted from electronic health records. Patient selection was compared with conventional surveillance and patients were retrospectively classified as low or high probability of having developed deep SSI by the algorithm. Sensitivity, positive predictive value (PPV), and workload reduction were calculated and compared to conventional surveillance.Results:Of 9,554 extracted THA and TKA surgeries, 1,175 (12.3%) were revisions, and 8,378 primary surgeries remained for algorithm validation (95 deep SSIs, 1.1%). Sensitivity ranged from 93.6% to 100% and PPV ranged from 55.8% to 72.2%. Workload was reduced by ≥98%. Also, 2 SSIs (2.1%) missed by the algorithm were explained by flaws in data selection.Conclusions:This algorithm reliably detects patients with a high probability of having developed deep SSI after THA or TKA in Dutch hospitals. Our results provide essential information for successful implementation of semiautomated surveillance for deep SSIs after THA or TKA.

Impact of an Automated Surveillance to Detect Surgical-Site Infections in Patients Undergoing Total Hip and Knee Arthroplasty in Brazil

2016 ◽  
Vol 37 (8) ◽  
pp. 991-993 ◽  
Author(s):  
Luciana B. Perdiz ◽  
Deborah S. Yokoe ◽  
Guilherme H. Furtado ◽  
Eduardo A. S. Medeiros
Keyword(s):  
Retrospective Study ◽  
Surgical Site Infection ◽  
Knee Arthroplasty ◽  
Surgical Site Infections ◽  
Infect Control Hosp ◽  
Site Infection ◽  
Total Hip ◽  
Routine Surveillance ◽  
Hip And Knee Arthroplasty ◽  
Automated Surveillance

In this retrospective study, we compared automated surveillance with conventional surveillance to detect surgical site infection after primary total hip or knee arthroplasty. Automated surveillance demonstrated better efficacy than routine surveillance in SSI diagnosis, sensitivity, and predictive negative value in hip and knee arthroplasty.Infect Control Hosp Epidemiol 2016;37:991–993

scholarly journals Patient Electronic Health Records Score for Preoperative Risk Assessment Before Total Knee Arthroplasty

2020 ◽  
Vol 5 (2) ◽  
pp. e0061 ◽  
Author(s):  
Thomas F. Osborne ◽  
Paola Suarez ◽  
Donna Edwards ◽  
Tina Hernandez-Boussard ◽  
Catherine Curtin
Keyword(s):  
Risk Assessment ◽  
Total Knee Arthroplasty ◽  
Electronic Health Records ◽  
Knee Arthroplasty ◽  
Preoperative Risk ◽  
Health Records ◽  
Preoperative Risk Assessment ◽  
Total Knee ◽  
Electronic Health

Electronic health records: Context matters!

2016 ◽  
Vol 34 (2) ◽  
pp. 163-165 ◽  
Author(s):  
William B. Ventres ◽  
Richard M. Frankel
Keyword(s):  
Electronic Health Records ◽  
Health Records ◽  
Electronic Health
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