ABSTRACT
BACKGROUND: Conventional systems of drug surveillance lack a seamless workflow, which makes it crucial to have an active drug surveillance system that proactively assesses adverse drug events. OBJECTIVE: The aim of this study was to develop a seamless, Web-based workflow for comparing the safety and effectiveness of drugs in a database of electronic medical records. METHODS: We proposed a comprehensive integration process for cohort surveillance using the National Taiwan University Hospital Clinical Surveillance System (NCSS). We studied a practical application of the NCSS that evaluates the drug safety and effectiveness of novel oral anticoagulants (NOACs) and warfarin by cohort tree analysis in an efficient and interoperable platform. RESULTS: We demonstrated a practical example of investigating the differences in effectiveness and safety between NOACs and warfarin in patients with nonvalvular atrial fibrillation (AF) using the NCSS. We efficiently identified 2357 patients with nonvalvular AF with newly prescribed oral anticoagulants between 2010 and 2015 and further developed 1 main cohort and 2 subcohorts for separately measuring ischemic stroke as the clinical effectiveness outcome and intracranial hemorrhage (ICH) as the safety outcome. In the subcohort of ischemic stroke, NOAC users exhibited a significantly lower risk of ischemic stroke than warfarin users after adjusting for age, sex, comorbidity, and comedication in an intention-to-treat (ITT) analysis (P=.01) but did not exhibit a significantly distinct risk in an as-treated (AT) analysis (P=.12) after the 2-year follow-up. In the subcohort of ICH, NOAC users did not exhibit a different risk of ICH both in ITT (P=.68) and AT analyses (P=.15). CONCLUSIONS: With a seamless and Web-based workflow, the NCSS can serve the critical role of forming associations between evidence and the real world at a medical center in Taiwan.
ABSTRACT
BACKGROUND: Traditional clinical surveillance relied on the results from clinical trials and observational studies of administrative databases. However, these studies not only required many valuable resources but also faced a very long time lag. OBJECTIVE: This study aimed to illustrate a practical application of the National Taiwan University Hospital Clinical Surveillance System (NCSS) in the identification of patients with an osteoporotic fracture and to provide a high reusability infrastructure for longitudinal clinical data. METHODS: The NCSS integrates electronic medical records in the National Taiwan University Hospital (NTUH) with a data warehouse and is equipped with a user-friendly interface. The NCSS was developed using professional insight from multidisciplinary experts, including clinical practitioners, epidemiologists, and biomedical engineers. The practical example identifying the unmet treatment needs for patients encountering major osteoporotic fractures described herein was mainly achieved by adopting the computerized workflow in the NCSS. RESULTS: We developed the infrastructure of the NCSS, including an integrated data warehouse and an automatic surveillance workflow. By applying the NCSS, we efficiently identified 2193 patients who were newly diagnosed with a hip or vertebral fracture between 2010 and 2014 at NTUH. By adopting the filter function, we identified 1808 (1808/2193, 82.44%) patients who continued their follow-up at NTUH, and 464 (464/2193, 21.16%) patients who were prescribed anti-osteoporosis medications, within 3 and 12 months post the index date of their fracture, respectively. CONCLUSIONS: The NCSS systems can integrate the workflow of cohort identification to accelerate the survey process of clinically relevant problems and provide decision support in the daily practice of clinical physicians, thereby making the benefit of evidence-based medicine a reality.
Subject(s)
Osteoporosis/complications , Osteoporotic Fractures/therapy , Public Health Surveillance/methods , Aged , Cohort Studies , Databases, Factual , Feasibility Studies , Female , Humans , Middle Aged , Osteoporotic Fractures/pathology , Surveys and QuestionnairesABSTRACT
BACKGROUND: Surveillance of health care-associated infections is an essential component of infection prevention programs, but conventional systems are labor intensive and performance dependent. OBJECTIVE: To develop an automatic surveillance and classification system for health care-associated bloodstream infection (HABSI), and to evaluate its performance by comparing it with a conventional infection control personnel (ICP)-based surveillance system. METHODS: We developed a Web-based system that was integrated into the medical information system of a 2200-bed teaching hospital in Taiwan. The system automatically detects and classifies HABSIs. RESULTS: In this study, the number of computer-detected HABSIs correlated closely with the number of HABSIs detected by ICP by department (n=20; r=.999 P<.001) and by time (n=14; r=.941; P<.001). Compared with reference standards, this system performed excellently with regard to sensitivity (98.16%), specificity (99.96%), positive predictive value (95.81%), and negative predictive value (99.98%). The system enabled decreasing the delay in confirmation of HABSI cases, on average, by 29 days. CONCLUSIONS: This system provides reliable and objective HABSI data for quality indicators, improving the delay caused by a conventional surveillance system.
ABSTRACT
Observing the pattern changes of inpatient fall and validating the Fall Prevention Tool Kit (FPTK) are essential for developing fall prevention strategies. However, the work requires the collection, calculation, and comparison of large amount of data. The information is often scattered in diverse information systems and lack of integration, which makes the work difficult and often neglected. This study demonstrates the development of an Interactive Data Repository System (IDRS) and uses it in the analysis of the pattern changes of inpatient fall within the institute, and validates efficiency of the FPTK across time. This study collected the incident data of year 2011 and compared it with the previous analysis in 2001. The result shows that reasons for patient fall had turned from physical disability to impaired conscious or cognition. The scoring result may be too sensitive in identifying patient falls. Patients with high scores needed to reinforce in functional strength.
Subject(s)
Accidental Falls/prevention & control , Accidental Falls/statistics & numerical data , Electronic Health Records/statistics & numerical data , Information Storage and Retrieval/methods , Medical Record Linkage/methods , Pattern Recognition, Automated/methods , Population Surveillance/methods , User-Computer Interface , Hospitalization/statistics & numerical data , Humans , Incidence , Inpatients/statistics & numerical data , Risk Assessment/methods , Software , TaiwanABSTRACT
Healthcare-associated infections (HAIs) are a major patient safety issue. These adverse events add to the burden of resource use, promote resistance to antibiotics, and contribute to patient deaths and disability. A rule-based HAI classification and surveillance system was developed for automatic integration, analysis, and interpretation of HAIs and related pathogens. Rule-based classification system was design and implement to facilitate healthcare-associated bloodstream infection (HABSI) surveillance. Electronic medical records from a 2200-bed teaching hospital in Taiwan were classified according to predefined criteria of HABSI. The detailed information in each HABSI was presented systematically to support infection control personnel decision. The accuracy of HABSI classification was 0.94, and the square of the sample correlation coefficient was 0.99.
Subject(s)
Algorithms , Bacteremia/diagnosis , Bacteremia/epidemiology , Cross Infection/diagnosis , Decision Support Systems, Clinical , Population Surveillance/methods , Cross Infection/epidemiology , Female , Humans , Male , Prevalence , Risk Assessment/methods , Taiwan/epidemiologyABSTRACT
BACKGROUND: The emergence and spread of multidrug-resistant organisms (MDROs) are causing a global crisis. Combating antimicrobial resistance requires prevention of transmission of resistant organisms and improved use of antimicrobials. OBJECTIVES: To develop a Web-based information system for automatic integration, analysis, and interpretation of the antimicrobial susceptibility of all clinical isolates that incorporates rule-based classification and cluster analysis of MDROs and implements control chart analysis to facilitate outbreak detection. METHODS: Electronic microbiological data from a 2200-bed teaching hospital in Taiwan were classified according to predefined criteria of MDROs. The numbers of organisms, patients, and incident patients in each MDRO pattern were presented graphically to describe spatial and time information in a Web-based user interface. Hierarchical clustering with 7 upper control limits (UCL) was used to detect suspicious outbreaks. The system's performance in outbreak detection was evaluated based on vancomycin-resistant enterococcal outbreaks determined by a hospital-wide prospective active surveillance database compiled by infection control personnel. RESULTS: The optimal UCL for MDRO outbreak detection was the upper 90% confidence interval (CI) using germ criterion with clustering (area under ROC curve (AUC) 0.93, 95% CI 0.91 to 0.95), upper 85% CI using patient criterion (AUC 0.87, 95% CI 0.80 to 0.93), and one standard deviation using incident patient criterion (AUC 0.84, 95% CI 0.75 to 0.92). The performance indicators of each UCL were statistically significantly higher with clustering than those without clustering in germ criterion (P < .001), patient criterion (P = .04), and incident patient criterion (P < .001). CONCLUSION: This system automatically identifies MDROs and accurately detects suspicious outbreaks of MDROs based on the antimicrobial susceptibility of all clinical isolates.
Subject(s)
Disease Outbreaks/classification , Drug Resistance, Multiple , Epidemiological Monitoring , Internet , Cluster Analysis , Databases, Factual , Disease Outbreaks/prevention & control , Disease Outbreaks/statistics & numerical data , Hospitals, Teaching , Humans , Infection Control , Infections/drug therapy , Infections/epidemiology , Infections/microbiology , Molecular Epidemiology , Prospective Studies , Software , Taiwan/epidemiologyABSTRACT
OBJECTIVE: Telehealthcare has been used to provide healthcare service, and information technology infrastructure appears to be essential while providing telehealthcare service. Insufficiencies have been identified, such as lack of integration, need of accommodation of diverse biometric sensors, and accessing diverse networks as different houses have varying facilities, which challenge the promotion of telehealthcare. This study designs an information technology framework to strengthen telehealthcare delivery. MATERIALS AND METHODS: The proposed framework consists of a system architecture design and a network transmission design. The aim of the framework is to integrate data from existing information systems, to adopt medical informatics standards, to integrate diverse biometric sensors, and to provide different data transmission networks to support a patient's house network despite the facilities. The proposed framework has been evaluated with a case study of two telehealthcare programs, with and without the adoption of the framework. RESULTS: The proposed framework facilitates the functionality of the program and enables steady patient enrollments. The overall patient participations are increased, and the patient outcomes appear positive. The attitudes toward the service and self-improvement also are positive. CONCLUSIONS: The findings of this study add up to the construction of a telehealthcare system. Implementing the proposed framework further assists the functionality of the service and enhances the availability of the service and patient acceptances.