Objectives: In this study, we examined the validity of Clostridium difficile culture results as a proxy measure of Clostridium difficile infection, and inferred the epidemiologic characteristics of Clostridium difficile infection by tracking the trends of Clostridium difficile culture results. Methods: We reviewed the medical records to figure out the actual possibilities of Clostridium difficile infection of those with positive or negative results of Clostridium difficile culture during the time span from January 2012 to March 2012. We calculated the positive and negative predictive value of Clostridium difficile culture results for Clostridium difficile infection. Furthermore, epidemiologic characteristics of Clostridium difficile infection in a tertiary general hospital in 2012 were analyzed. Result: The estimated positive predictive value of Clostridium difficile culture tests for Clostridium difficile infection was 100%, and the estimated negative predictive value was around 94.4~99.3% depending on the cutoff value of possibility of Clostridium difficile infection. A total of 622 cases were identified as Clostridium difficile infection in a tertiary general hospital in 2012 and there were 4.9 patients with Clostridium difficile infection per 1,000 inpatients. Conclusion: In conclusion, we identified that Clostridium difficile culture results can be used as a proxy measure of Clostridium difficile infection.

Purpose: Globally, falls are a major public health problem. The study aimed to evaluate the predictive validity of the Timed Up and Go test (TUGT) as a screening tool for fall risk. Methods: An electronic search was performed Medline, EMBASE, CINAHL, Cochran Library, KoreaMed and the National Digital Science Library and other databases, using the following keywords: 'fall', 'fall risk assessment', 'fall screening', 'mobility scale', and 'risk assessment tool'. The QUADAS-II was applied to assess the internal validity of the diagnostic studies. Thirteen studies were analyzed using meta-analysis with MetaDisc 1.4. Results: The selected 13 studies reporting predictive validity of TUGT of fall risks were meta-analyzed with a sample size of 1004 with high methodological quality. Overall predictive validity of TGUT was as follows. The pooled sensitivity 0.72 (95% confidence interval [CI]: 0.67-0.77), pooled specificity 0.58 (95% CI: 0.54-0.63) and sROC AUC was 0.75 respectively. Heterogeneity among studies was a moderate level in sensitivity. Conclusion: The TGUT's predictive validity for fall risk is at a moderate level. Although there is a limit to interpret the results for heterogeneity between the literature, TGUT is an appropriate tool to apply to all patients at a potential risk of accidental fall in a hospital or long-term care facility.

Purpose: The aims of this study were to assess the presence of core patient safety practices in Korean hospitals and assess the differences in reporting and learning systems of patient safety, infrastructure, and safe practices by hospital characteristics. Methods: The authors developed a questionnaire including 39 items of patient safety staffing, health information system, reporting system, and event-specific prevention practices. The survey was conducted online or e-mail with 407 tertiary, general and specialty hospitals. Results: About 90% of hospitals answered the self-reporting system of patient safety related events is established. More than 90% of hospitals applied incidence monitoring or root cause analysis on healthcare-associated infection, in-facility pressure ulcers and falls, but only 60% did on surgery/procedure related events. More than 50% of the hospitals did not adopted present on admission (POA) indicators. One hundred (80.0%) hospitals had a department of patient safety and/or quality and only 52.8% of hospitals had a patient safety officer (PSO). While 82.4% of hospitals used electronic medical records (EMRs), only 53% of these hospitals adopted clinical decision support function. Infrastructure for patient safety except EMRs was well established in training, high-level and large hospitals. Most hospitals implemented prevention practices of adverse drug events, in-facility pressure ulcers and falls (94.4-100.0%). But prevention practices of surgery/procedure related events had relatively low adoption rate (59.2-92.8%). Majority of prevention practices for patient safety events were also implemented with a relatively modest increase in resources allocated. Conclusion: The hospital-based reporting and learning system, EMRs, and core evidence-based prevention practices were implemented well in high-level and large hospitals. But POA indicator and PSO were not adopted in more than half of surveyed hospitals and implementation of prevention practices for specific event had low. To support and monitor progress in hospital's patient safety effort, national-level safety practices set is needed.

Objectives: This study measures the level of cognition of employee's patient safety culture and evaluates the current level through comparing the results to external levels. Ultimately it is performed to construct a strategic improvement plan through the basic database for patient's safety culture. Methods: A questionnaire survey of self reporting type was carried out using structured questionnaire of the patient's safety culture for employees currently employed in a hospital. Total responders was 1,129 and a response rate was 54.6%. The survey results were calculated with a percent positive response, and the current level was evaluated by comparing with the survey results of a hospital (2009 and 2014) and the survey result of The Agency for Healthcare Research and Quality(2014). Results: Sub-dimension of high percent positive response for each area were 'teamwork within hospital units' (80%), 'feedback & communication about error' (73%) and 'supervisor/manager expectations & actions promoting safety' (67%). Meanwhile, 'teamwork across hospital units' (31%), 'hospital management support for patient safety' (29%), 'staffing' (27%) and 'non-punitive response to error' (17%) were relatively low percent positive response. Compared to the survey results of AHRQ (2014) for each area, 'teamwork within hospital units' (80%), 'feedback & communication about error' (73%), 'frequency of event reporting' (66%) were at the top 50% percentile level and the remaining sub-dimensions showed a very low level in the lower 10% percentile area. Conclusion: In order to establish a system for patient safety culture within the hospital and evaluate the effect on this, it is necessary to periodically evaluate the patient's safety culture and establish regulations on hospital safety culture to comply with this.

Purpose: Ancillary tests such as immunohistochemistry or molecular testing for pathologic diagnosis are performed using ready-made tissue blocks for a histological examination. Various methods and processes during ancillary testing cause some of issues, particularly in the time required and the results reporting scheme. Methods: To solve these issues, we constructed real-time management software. When a pathologist or a clinician had ancillary tests examined using this software by selecting the codes of the needed ancillary tests on site and the system assigned the tests to each laboratory. Then, pathology technologists checked the referred tests and performed the examination. In clinical departments, serial number of each ancillary test can be matched the original pathologic ID. In the department of pathology, numbers of tissue blocks that needed additional tests could be indicated and detected using one-click detection system when a clinician referred the test. Results: Using this system resulted in simplifying the referral procedures from nine-steps to three-steps in each clinical department and from seven-steps to two-steps in department of pathology. Errors that happened on the paper-based request system were also reduced. Furthermore, the time required was saved by seven hours in pathologic laboratory on average. Mean durations from requesting to reporting of the ancillary test was reduced by three days for specimens of health promotion center. Conclusion: Construction of an effective information transfer system may be helpful for shortening the time required, reducing errors, and checking processing information of the tests in real time.