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Purpose: Shared decision making promotes patient participation in medical decisions. This study aims to explore the decision-making situation and influencing factors in patients with cancer. Patients and methods: A cross-sectional descriptive study was conducted for patient with cancers in regional teaching hospitals in northern Taiwan using short-form Mandarin Health Literacy Scale (s-MHLS) and Shared Decision Making Questionnaire (SDM-Q-9), with total 120 cases collected from January 15 to April 30, 2018. Results: Overall health literacy in patients with cancer is 86.52%, and degree of shared decision making is 89.63%; higher education level indicated better health literacy (p<0.001); health literacy is significantly correlated with Shared decision making (r=0.258, p=0.004). Increasing education level by one grade elevated health literacy by 0.623. Expanding health knowledge by one source increased health literacy by 0.307 points, one point increase in health literacy enhanced shared decision making by 0.128 points. Using path analysis, we found education level affects health literacy, which in turn influences shared decision making. Conclusion: Improving health literacy is indispensable to promote patient participation in shared decision making in the highly professional medical field. Education level directly affects health literacy; therefore, in the future, providing disease-matching health education is crucial for patients with lower education levels to enhance their health literacy. Health literacy directly affects shared decision making; therefore, more active assistance in achieving patient health literacy is crucial to implement shared decision making. [ABSTRACT FROM AUTHOR]

Background: Most nursing records in Taiwan have been computerized, resulting in a large amount of unstructured text data. The quality of these records has rarely been discussed. Purpose: This study used a text mining method to analyze the quality of a nursing record system to establish an auditing model and associated tools for nursing records, with the ultimate objective of improving the quality of electronic nursing records. Methods: This study utilized a retrospective method to collect the electronic nursing records of 6,277 patients who had been discharged from the internal medicine departments of a medical center in northern Taiwan from January to June 2014. SAS Enterprise Guide Version 6.1 and SAS Text Miner Version 13.2 software were used to perform text mining. Nursing experts were invited to examine the electronic nursing records. The text mining results were compared against a benchmark that was developed by the experts, and the efficiency of SAS Text Miner was examined using the criteria of specificity, sensitivity, and accuracy. Results: In this study, 27,356 nurse-formulated events were used in the analysis. The results of the nurse-formulated events showed an 8.08% similar error with system-formulated events, 29.72% were identified as necessary and appropriate names, 17.53% were retained, 10.15% involved error event names, and 34.52% were not classified. In this study, the sensitivity of SAS text mining in the training (testing) data set was 96% (95%), and the specificity and accuracy were both 99% (99%). Conclusions: The results of this study show that text mining is an effective approach to auditing the quality of electronic nursing records. SAS Text Miner software was shown to identify inappropriate nursing record content quickly and efficiently. Furthermore, the results of this study may be included in in-service education teaching materials to promote the writing of better nursing records to improve the quality of electronic nursing records. [ABSTRACT FROM AUTHOR]