The Experts below are selected from a list of 2309895 Experts worldwide ranked by ideXlab platform
Sengwee Toh - One of the best experts on this subject based on the ideXlab platform.
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building an active medical product safety surveillance system in taiwan adaptation of the u s sentinel system common data Model Structure to the national health insurance research database in taiwan
Pharmacoepidemiology and Drug Safety, 2021Co-Authors: Kelly Huang, Fangju Lin, Chien Ning Hsu, Ling Ya Huang, Chichuan Wang, Sengwee TohAbstract:PURPOSE Using real-world data to support regulatory decision has become a global movement. However, a robust platform for active surveillance of medical product safety has not been established in Taiwan. METHODS Following the common data Model Structure of the U.S. Food and Drug Administration's Sentinel System, we built the Taiwan Sentinel Data Model (TSDM) using the National Health Insurance Research Database with longitudinal claims data from 23 million individuals, linked death and cause of death data from a national registry, and linked electronic health record data from a delivery system. We examined the conversion of the TSDM using the Sentinel Data Quality Review and Characterization Programs in a sample of sex- and age-stratified cohort of 3 million individuals. RESULTS The TSDM fulfilled the requirements of data quality assurance. Only about 6% of sex and 0.0007% of birth year were missing, and <0.001% of date data had illogical values. CONCLUSIONS The TSDM-converted database could be a valuable data resource for domestic pharmacovigilance analysis in Taiwan and cross-country evaluation.
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building an active medical product safety surveillance system in taiwan adaptation of the u s sentinel system common data Model Structure to the national health insurance research database in taiwan
Pharmacoepidemiology and Drug Safety, 2020Co-Authors: Kelly Huang, Fangju Lin, Chien Ning Hsu, Ling Ya Huang, Chichuan Wang, Sengwee TohAbstract:PURPOSE Using real-world data to support regulatory decision has become a global movement. However, a robust platform for active surveillance of medical product safety has not been established in Taiwan. METHODS Following the common data Model Structure of the U.S. Food and Drug Administration's Sentinel System, we built the Taiwan Sentinel Data Model (TSDM) using the National Health Insurance Research Database with longitudinal claims data from 23 million individuals, linked death and cause of death data from a national registry, and linked electronic health record data from a delivery system. We examined the conversion of the TSDM using the Sentinel Data Quality Review and Characterization Programs in a sample of sex- and age-stratified cohort of three million individuals. RESULTS The TSDM fulfilled the requirements of data quality assurance. Only about six percent of sex and 0.0007% of birth year were missing, and <0.001% of date data had illogical values. CONCLUSIONS The TSDM-converted database could be a valuable data resource for domestic pharmacovigilance analysis in Taiwan and cross-country evaluation.
Chien Ning Hsu - One of the best experts on this subject based on the ideXlab platform.
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building an active medical product safety surveillance system in taiwan adaptation of the u s sentinel system common data Model Structure to the national health insurance research database in taiwan
Pharmacoepidemiology and Drug Safety, 2021Co-Authors: Kelly Huang, Fangju Lin, Chien Ning Hsu, Ling Ya Huang, Chichuan Wang, Sengwee TohAbstract:PURPOSE Using real-world data to support regulatory decision has become a global movement. However, a robust platform for active surveillance of medical product safety has not been established in Taiwan. METHODS Following the common data Model Structure of the U.S. Food and Drug Administration's Sentinel System, we built the Taiwan Sentinel Data Model (TSDM) using the National Health Insurance Research Database with longitudinal claims data from 23 million individuals, linked death and cause of death data from a national registry, and linked electronic health record data from a delivery system. We examined the conversion of the TSDM using the Sentinel Data Quality Review and Characterization Programs in a sample of sex- and age-stratified cohort of 3 million individuals. RESULTS The TSDM fulfilled the requirements of data quality assurance. Only about 6% of sex and 0.0007% of birth year were missing, and <0.001% of date data had illogical values. CONCLUSIONS The TSDM-converted database could be a valuable data resource for domestic pharmacovigilance analysis in Taiwan and cross-country evaluation.
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building an active medical product safety surveillance system in taiwan adaptation of the u s sentinel system common data Model Structure to the national health insurance research database in taiwan
Pharmacoepidemiology and Drug Safety, 2020Co-Authors: Kelly Huang, Fangju Lin, Chien Ning Hsu, Ling Ya Huang, Chichuan Wang, Sengwee TohAbstract:PURPOSE Using real-world data to support regulatory decision has become a global movement. However, a robust platform for active surveillance of medical product safety has not been established in Taiwan. METHODS Following the common data Model Structure of the U.S. Food and Drug Administration's Sentinel System, we built the Taiwan Sentinel Data Model (TSDM) using the National Health Insurance Research Database with longitudinal claims data from 23 million individuals, linked death and cause of death data from a national registry, and linked electronic health record data from a delivery system. We examined the conversion of the TSDM using the Sentinel Data Quality Review and Characterization Programs in a sample of sex- and age-stratified cohort of three million individuals. RESULTS The TSDM fulfilled the requirements of data quality assurance. Only about six percent of sex and 0.0007% of birth year were missing, and <0.001% of date data had illogical values. CONCLUSIONS The TSDM-converted database could be a valuable data resource for domestic pharmacovigilance analysis in Taiwan and cross-country evaluation.
Kelly Huang - One of the best experts on this subject based on the ideXlab platform.
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building an active medical product safety surveillance system in taiwan adaptation of the u s sentinel system common data Model Structure to the national health insurance research database in taiwan
Pharmacoepidemiology and Drug Safety, 2021Co-Authors: Kelly Huang, Fangju Lin, Chien Ning Hsu, Ling Ya Huang, Chichuan Wang, Sengwee TohAbstract:PURPOSE Using real-world data to support regulatory decision has become a global movement. However, a robust platform for active surveillance of medical product safety has not been established in Taiwan. METHODS Following the common data Model Structure of the U.S. Food and Drug Administration's Sentinel System, we built the Taiwan Sentinel Data Model (TSDM) using the National Health Insurance Research Database with longitudinal claims data from 23 million individuals, linked death and cause of death data from a national registry, and linked electronic health record data from a delivery system. We examined the conversion of the TSDM using the Sentinel Data Quality Review and Characterization Programs in a sample of sex- and age-stratified cohort of 3 million individuals. RESULTS The TSDM fulfilled the requirements of data quality assurance. Only about 6% of sex and 0.0007% of birth year were missing, and <0.001% of date data had illogical values. CONCLUSIONS The TSDM-converted database could be a valuable data resource for domestic pharmacovigilance analysis in Taiwan and cross-country evaluation.
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building an active medical product safety surveillance system in taiwan adaptation of the u s sentinel system common data Model Structure to the national health insurance research database in taiwan
Pharmacoepidemiology and Drug Safety, 2020Co-Authors: Kelly Huang, Fangju Lin, Chien Ning Hsu, Ling Ya Huang, Chichuan Wang, Sengwee TohAbstract:PURPOSE Using real-world data to support regulatory decision has become a global movement. However, a robust platform for active surveillance of medical product safety has not been established in Taiwan. METHODS Following the common data Model Structure of the U.S. Food and Drug Administration's Sentinel System, we built the Taiwan Sentinel Data Model (TSDM) using the National Health Insurance Research Database with longitudinal claims data from 23 million individuals, linked death and cause of death data from a national registry, and linked electronic health record data from a delivery system. We examined the conversion of the TSDM using the Sentinel Data Quality Review and Characterization Programs in a sample of sex- and age-stratified cohort of three million individuals. RESULTS The TSDM fulfilled the requirements of data quality assurance. Only about six percent of sex and 0.0007% of birth year were missing, and <0.001% of date data had illogical values. CONCLUSIONS The TSDM-converted database could be a valuable data resource for domestic pharmacovigilance analysis in Taiwan and cross-country evaluation.
Fangju Lin - One of the best experts on this subject based on the ideXlab platform.
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building an active medical product safety surveillance system in taiwan adaptation of the u s sentinel system common data Model Structure to the national health insurance research database in taiwan
Pharmacoepidemiology and Drug Safety, 2021Co-Authors: Kelly Huang, Fangju Lin, Chien Ning Hsu, Ling Ya Huang, Chichuan Wang, Sengwee TohAbstract:PURPOSE Using real-world data to support regulatory decision has become a global movement. However, a robust platform for active surveillance of medical product safety has not been established in Taiwan. METHODS Following the common data Model Structure of the U.S. Food and Drug Administration's Sentinel System, we built the Taiwan Sentinel Data Model (TSDM) using the National Health Insurance Research Database with longitudinal claims data from 23 million individuals, linked death and cause of death data from a national registry, and linked electronic health record data from a delivery system. We examined the conversion of the TSDM using the Sentinel Data Quality Review and Characterization Programs in a sample of sex- and age-stratified cohort of 3 million individuals. RESULTS The TSDM fulfilled the requirements of data quality assurance. Only about 6% of sex and 0.0007% of birth year were missing, and <0.001% of date data had illogical values. CONCLUSIONS The TSDM-converted database could be a valuable data resource for domestic pharmacovigilance analysis in Taiwan and cross-country evaluation.
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building an active medical product safety surveillance system in taiwan adaptation of the u s sentinel system common data Model Structure to the national health insurance research database in taiwan
Pharmacoepidemiology and Drug Safety, 2020Co-Authors: Kelly Huang, Fangju Lin, Chien Ning Hsu, Ling Ya Huang, Chichuan Wang, Sengwee TohAbstract:PURPOSE Using real-world data to support regulatory decision has become a global movement. However, a robust platform for active surveillance of medical product safety has not been established in Taiwan. METHODS Following the common data Model Structure of the U.S. Food and Drug Administration's Sentinel System, we built the Taiwan Sentinel Data Model (TSDM) using the National Health Insurance Research Database with longitudinal claims data from 23 million individuals, linked death and cause of death data from a national registry, and linked electronic health record data from a delivery system. We examined the conversion of the TSDM using the Sentinel Data Quality Review and Characterization Programs in a sample of sex- and age-stratified cohort of three million individuals. RESULTS The TSDM fulfilled the requirements of data quality assurance. Only about six percent of sex and 0.0007% of birth year were missing, and <0.001% of date data had illogical values. CONCLUSIONS The TSDM-converted database could be a valuable data resource for domestic pharmacovigilance analysis in Taiwan and cross-country evaluation.
Ling Ya Huang - One of the best experts on this subject based on the ideXlab platform.
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building an active medical product safety surveillance system in taiwan adaptation of the u s sentinel system common data Model Structure to the national health insurance research database in taiwan
Pharmacoepidemiology and Drug Safety, 2021Co-Authors: Kelly Huang, Fangju Lin, Chien Ning Hsu, Ling Ya Huang, Chichuan Wang, Sengwee TohAbstract:PURPOSE Using real-world data to support regulatory decision has become a global movement. However, a robust platform for active surveillance of medical product safety has not been established in Taiwan. METHODS Following the common data Model Structure of the U.S. Food and Drug Administration's Sentinel System, we built the Taiwan Sentinel Data Model (TSDM) using the National Health Insurance Research Database with longitudinal claims data from 23 million individuals, linked death and cause of death data from a national registry, and linked electronic health record data from a delivery system. We examined the conversion of the TSDM using the Sentinel Data Quality Review and Characterization Programs in a sample of sex- and age-stratified cohort of 3 million individuals. RESULTS The TSDM fulfilled the requirements of data quality assurance. Only about 6% of sex and 0.0007% of birth year were missing, and <0.001% of date data had illogical values. CONCLUSIONS The TSDM-converted database could be a valuable data resource for domestic pharmacovigilance analysis in Taiwan and cross-country evaluation.
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building an active medical product safety surveillance system in taiwan adaptation of the u s sentinel system common data Model Structure to the national health insurance research database in taiwan
Pharmacoepidemiology and Drug Safety, 2020Co-Authors: Kelly Huang, Fangju Lin, Chien Ning Hsu, Ling Ya Huang, Chichuan Wang, Sengwee TohAbstract:PURPOSE Using real-world data to support regulatory decision has become a global movement. However, a robust platform for active surveillance of medical product safety has not been established in Taiwan. METHODS Following the common data Model Structure of the U.S. Food and Drug Administration's Sentinel System, we built the Taiwan Sentinel Data Model (TSDM) using the National Health Insurance Research Database with longitudinal claims data from 23 million individuals, linked death and cause of death data from a national registry, and linked electronic health record data from a delivery system. We examined the conversion of the TSDM using the Sentinel Data Quality Review and Characterization Programs in a sample of sex- and age-stratified cohort of three million individuals. RESULTS The TSDM fulfilled the requirements of data quality assurance. Only about six percent of sex and 0.0007% of birth year were missing, and <0.001% of date data had illogical values. CONCLUSIONS The TSDM-converted database could be a valuable data resource for domestic pharmacovigilance analysis in Taiwan and cross-country evaluation.
