Description and classification of field-defined and natural language processing systems for automated detection of harm*
| Automated method | Data source used | Events identified | Comments |
| Complications Screening Program (CSP)8–10 46 | ICD-9 CM codes | Adverse drug events, adverse surgical outcomes, infections, and miscellaneous complications such as falls | A computerised method for identifying potentially preventable complications of hospital care. |
| Health Evaluation through Logical Processing (HELP)11–14 | Electronic Medical Record: specifically including pharmacy, laboratory, radiology and surgery records | Adverse drug events, adverse medical device events, infection | Integrated electronic medical record of the LDS Hospital in Salt Lake City, Utah, which contains an interactive modular knowledge base that continually analyses information |
| Patient Safety Indicators (PSI)15–17 46 | Administrative data: billing information, ICD-9 CM diagnosis codes and procedure codes | Adverse events | A fully automated method developed by the Agency for Healthcare Research and Quality |
| Computer algorithms18–21 | Electronic Medical Record: components specific to the particular program: see online appendix 1 | Adverse events, adverse drug events, infection | Specific, named computer programs |
| Lab signal detection tools22–26 | Laboratory Database | Adverse drug events | Automated tools search for key words or word combinations that signal potential or actual harm—for example, detection of elevated potassium levels |
| ICD-9 CM or billing code detection tools27–30 | Administrative data: ICD-9 CM or billing codes | Adverse drug events, infections, surgical complications | Automated tools scan for diagnosis, discharge, or billing codes that signal potential or actual harm—for example, evidence of antibiotic exposure following a postoperative infection |
| Tools using computerised triggers31–45 50 | Electronic Medical Record: multiple sources such as pharmacy, laboratory, and microbiology databases | Adverse events, adverse drug events infection | Automated tools using multiple triggers to signal actual or potential harm—for example, detection of elevated potassium levels (laboratory database) combined with certain medication administration (pharmacy database). Among the various tools included in this category, there are four named systems: Dynamic Pharmaco-Monitoring System, Nosocomial Infection Marker, Event Detector, New York Antimicrobial Resistance Project. |
| Natural language processing systems 33 34 47–49 | Free text in the Electronic Medical Record: discharge summaries, radiology reports, chart notes | Adverse events, infection | Sophisticated programs that ‘read’ free text via the application of computer logic |
↵* Multiple detection strategies were used in several studies, including those that combined two or more field-defined systems,46 two natural language-processing systems,47 and both a field-defined and natural language-processing system.33 ,34