Table 2 AS SSI systems presented by this work
AS SSI system | Danish Healthcare-associated infections database (HAIBA) | Dutch AS SSI system for hip and knee replacement (PREZIES–PAS ORTHO) | Spanish local hospital AS SSI system (No name determined) | French surveillance and Prevention of Infection in Surgery and Interventional Medicine (SPICMI) |
|---|---|---|---|---|
Institution hosting the AS SSI system, country | Danish National Institute for Public Health, Statens Serum Institut, Denmark | Dutch National Institute for Public Health and the Environment (RIVM), the Netherlands | Bellvitge Hospital, Spain | Centre for Prevention of Healthcare-Associated Infections (CPias) and Santé Publique France (SpF), Paris, France |
Aim of surveillance/surveillance purpose | National trend monitoring, internal quality control, research | National trend monitoring, risk factor monitoring, benchmarking | Hospital trend monitoring, internal quality control and improvement | SSI identification for targeted specialties, benchmarking, internal quality control, research |
Aim of automation | Offer national, continuous surveillance of HAIs and provide a standardized data basis for infection control efforts and research | Reduction of workload and improvement of data quality by means of increased standardization of surveillance | Reduce the workload of surveillance | Reduce workload of surveillance |
Stakeholders involved | Department of Data Integration and Analysis at Statens Serum Institut, clinical societies, RKKP, surgeons, hospital management, IPC teams, researchers | Medical microbiologists, IPC specialists, orthopedic surgeons, IT and legal specialists, scientific associations, umbrella organizations for hospitals | Frontline stakeholders (IPC teams, surgeons, nurses), hospital management, IT teams, pharmacists, microbiologists, healthcare coding department | AS SSI teams at CPias, IPC teams, surgeons, IT teams, nurses, hospital management, healthcare coding department |
Setting, e.g. hospital, hospital network | National level, all hospitals in Denmark | Voluntarily participating hospitals | A single hospital | All voluntary public and private French hospitals practicing surgery, each participating HCF selects at least one surgical specialty and at least one associated procedure for inclusion during the first 6 months every year |
Level of automation | Fully automated | Semi-automated | Semi-automated | Semi-automated |
Implementation approach | Centrally implemented | Locally implemented | Locally implemented | Locally implemented |
Target / Surveillance population with inclusion criteria | All Danish residents undergoing primary hip or knee arthroplasty procedures | Patients in participating hospitals undergoing primary hip or knee arthroplasty procedures | Adult patients undergoing cardiac surgery and prosthetic knee and hip replacements | Patients undergoing digestive surgery, gyneco-obstetrics surgery, neurosurgery, coronary surgery, orthopedic surgery and/or urologic surgery |
Selection of patient population under surveillance | Fully automated, using procedure codes based on the Nordic Medico-Statistical Committee (NOMESCO) Classification of Surgical Procedures [31] | Fully automated, patient selection based on procedure codes in EHR data | Currently partially automated, population under surveillance (denominator data) selected by specific ICD-10 codes, completeness and reliability currently manually verified | Partially automated, HDD for procedures and diagnosis (ICD-10 codification), some variables extracted from the HDD required post-hoc recoding or manual editing |
SSI types/definition targeted | Deep/incisional SSI | Deep/incisional SSI | Deep and organ/space SSI | Superficial, deep and organ/space SSI |
Follow-up period | 2–90 days after the index operation and up to 365 days | 90 days, while the algorithm performs monitoring until 120 days post-surgery | 90 days, while the algorithm performs monitoring until 120 days post-surgery | 30 days according to usual definition, extended to 90 days for prosthetic surgery (orthopaedic, cardiac and breast) |
Data sources for patient selection and algorithms | MiBa, NPR (diagnosis and procedure codes, operation dates), SOR (geographical data) | EHR (Demographic/administrative data, procedures, antibiotic prescriptions) and Laboratory information system (LIMS; culture orders and results) | Hospital data warehouse (microbiological data; radiological data; pharmacy data) and the minimum basic set of discharge data (CMBD, National Health System) with sociodemographic and administrative data; | HDD with demographic/administrative data, comorbidities, etc.), microbiological data base, local IT systems (i.a. NNIS risk scores, Altmeier wound classification) |
Phase of the automated surveillance system | In current use | In current use/ upscaling phase | Development phase / in current use | In current use |
Quality management / maintenance | Quarterly meetings between surgeons, hospital management, IPC teams | Manual, user group meetings, individual guidance and training, evaluation of the strategy in 5 frontrunner hospitals for strategy improvement | Regular audits of the process, annual monitoring of accuracy of data extraction and algorithm performance, comprehensive version control and documentation summarizing design decisions, algorithms and methodologies | Electronic platform for hospital data recording, quarterly steering committee meetings, all guidelines available on SPICMI website, monthly webinars, research projects for improvement of surveillance performance (e.g. choice of risk factors, algorithm effectiveness) |
Year of implementation | 2015 | 2022 | 2024 | 2021 |