Identifying Adverse Events Using International Classification of Diseases, Tenth Revision Y Codes in Korea: A Cross-sectional Study / 예방의학회지

OBJECTIVES: The use of administrative data is an affordable alternative to conducting a difficult large-scale medical-record review to estimate the scale of adverse events. We identified adverse events from 2002 to 2013 on the national level in Korea, using International Classification of Diseases, tenth revision (ICD-10) Y codes. METHODS: We used data from the National Health Insurance Service-National Sample Cohort (NHIS-NSC). We relied on medical treatment databases to extract information on ICD-10 Y codes from each participant in the NHIS-NSC. We classified adverse events in the ICD-10 Y codes into 6 types: those related to drugs, transfusions, and fluids; those related to vaccines and immunoglobulin; those related to surgery and procedures; those related to infections; those related to devices; and others. RESULTS: Over 12 years, a total of 20 817 adverse events were identified using ICD-10 Y codes, and the estimated total adverse event rate was 0.20%. Between 2002 and 2013, the total number of such events increased by 131.3%, from 1366 in 2002 to 3159 in 2013. The total rate increased by 103.9%, from 0.17% in 2002 to 0.35% in 2013. Events related to drugs, transfusions, and fluids were the most common (19 446, 93.4%), followed by those related to surgery and procedures (1209, 5.8%) and those related to vaccines and immunoglobulin (72, 0.3%). CONCLUSIONS: Based on a comparison with the results of other studies, the total adverse event rate in this study was significantly underestimated. Improving coding practices for ICD-10 Y codes is necessary to precisely monitor the scale of adverse events in Korea.

Identifying Adverse Events Using International Classification of Diseases, Tenth Revision Y Codes in Korea: A Cross-sectional Study / 예방의학회지

OBJECTIVES@#The use of administrative data is an affordable alternative to conducting a difficult large-scale medical-record review to estimate the scale of adverse events. We identified adverse events from 2002 to 2013 on the national level in Korea, using International Classification of Diseases, tenth revision (ICD-10) Y codes.@*METHODS@#We used data from the National Health Insurance Service-National Sample Cohort (NHIS-NSC). We relied on medical treatment databases to extract information on ICD-10 Y codes from each participant in the NHIS-NSC. We classified adverse events in the ICD-10 Y codes into 6 types: those related to drugs, transfusions, and fluids; those related to vaccines and immunoglobulin; those related to surgery and procedures; those related to infections; those related to devices; and others.@*RESULTS@#Over 12 years, a total of 20 817 adverse events were identified using ICD-10 Y codes, and the estimated total adverse event rate was 0.20%. Between 2002 and 2013, the total number of such events increased by 131.3%, from 1366 in 2002 to 3159 in 2013. The total rate increased by 103.9%, from 0.17% in 2002 to 0.35% in 2013. Events related to drugs, transfusions, and fluids were the most common (19 446, 93.4%), followed by those related to surgery and procedures (1209, 5.8%) and those related to vaccines and immunoglobulin (72, 0.3%).@*CONCLUSIONS@#Based on a comparison with the results of other studies, the total adverse event rate in this study was significantly underestimated. Improving coding practices for ICD-10 Y codes is necessary to precisely monitor the scale of adverse events in Korea.

Feasibility of using the RAPAEL Smart Glove in upper limb physical therapy for patients after stroke: A randomized controlled trial.

We aim to assess the feasibility of using the RAPAEL Smart Glove as an assistive tool for therapists in clinical rehabilitation therapy settings and to investigate if it can be used to improve the motor recovery rate of stroke survivors. Our randomized controlled study involved 13 post-stroke inpatients. An experimental treatment consisted of one 30-minute game-assisted therapy and one 30-minute conventional therapy per day while the control treatment consisted of two 30-minute conventional therapies. Each therapy block consisted of 15 days over a period of 3 weeks. The measured outcomes were the scores on the Wolf Motor Function Test and the active range of motion for the forearm and the wrist. The mean Wolf Motor Function Test score for the group that received game therapies as well as conventional therapies was significantly higher than that for the group who received only conventional therapies. The results suggest that the motor recovery rate of the clinical rehabilitation therapies can be improved when wearable sensors and therapeutic games are used by therapists in their routine therapy practice.