iVOD / 165443

Field Value
IVOD_ID 165443
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/165443
日期 2025-11-13
會議資料.會議代碼 委員會-11-4-26-10
會議資料.會議代碼:str 第11屆第4會期社會福利及衛生環境委員會第10次全體委員會議
會議資料.屆 11
會議資料.會期 4
會議資料.會次 10
會議資料.種類 委員會
會議資料.委員會代碼[0] 26
會議資料.委員會代碼:str[0] 社會福利及衛生環境委員會
會議資料.標題 第11屆第4會期社會福利及衛生環境委員會第10次全體委員會議
影片種類 Clip
開始時間 2025-11-13T12:35:48+08:00
結束時間 2025-11-13T12:48:25+08:00
影片長度 00:12:37
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/fffa2c65c610face5ee316818fb2316e8ff38efa2589ba0871572932e1d9cfea11b57a280f0214d75ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 涂權吉
委員發言時間 12:35:48 - 12:48:25
會議時間 2025-11-13T09:00:00+08:00
會議名稱 立法院第11屆第4會期社會福利及衛生環境委員會第10次全體委員會議(事由:邀請衛生福利部部長及行政院主計總處就「癌症新藥暫時性支付及罕見疾病藥物專款預算運用成效及政策檢討」進行專題報告,並備質詢。 (討論事項) 審查 一、委員羅廷瑋等16人擬具「癌症防治法第十三條及第十六條條文修正草案」案。 二、委員陳菁徽等16人擬具「癌症防治法第十六條條文修正草案」案。 三、委員邱鎮軍等19人擬具「癌症防治法第五條及第十六條條文修正草案」案。 四、委員劉建國等17人擬具「癌症防治法第十六條條文修正草案」案。 五、委員王正旭等17人擬具「癌症防治法第十六條條文修正草案」案。 六、委員顏寬恒等21人擬具「癌症防治法第十三條條文修正草案」案。 七、委員林淑芬等20人擬具「癌症防治法第十六條條文修正草案」案。 八、委員盧縣一等17人擬具「癌症防治法第八條及第十六條條文修正草案」案。 九、委員顏寬恒等24人擬具「癌症防治法第十六條條文修正草案」案。 十、委員蘇巧慧等30人擬具「癌症防治法修正草案」案。 十一、委員林月琴等16人擬具「癌症防治法第十六條條文修正草案」案。 十二、委員邱議瑩等16人擬具「癌症防治法第十六條條文修正草案」案。 十三、委員羅智強等18人擬具「癌症防治法第十六條條文修正草案」案。 十四、台灣民眾黨黨團擬具「癌症防治法第一條、第十三條及第十六條條文修正草案」案。 十五、委員陳亭妃等17人擬具「癌症防治法第十六條條文修正草案」案。 十六、委員黃秀芳等21人擬具「癌症防治法第十六條條文修正草案」案。 十七、委員馬文君等16人擬具「癌症防治法第十六條條文修正草案」案。 【專題報告及討論事項綜合詢答;討論事項僅詢答】)
transcript.pyannote[0].speaker SPEAKER_02
transcript.pyannote[0].start 2.47784375
transcript.pyannote[0].end 6.64596875
transcript.pyannote[1].speaker SPEAKER_01
transcript.pyannote[1].start 6.66284375
transcript.pyannote[1].end 8.08034375
transcript.pyannote[2].speaker SPEAKER_01
transcript.pyannote[2].start 9.00846875
transcript.pyannote[2].end 10.13909375
transcript.pyannote[3].speaker SPEAKER_02
transcript.pyannote[3].start 9.83534375
transcript.pyannote[3].end 10.59471875
transcript.pyannote[4].speaker SPEAKER_02
transcript.pyannote[4].start 12.13034375
transcript.pyannote[4].end 14.13846875
transcript.pyannote[5].speaker SPEAKER_02
transcript.pyannote[5].start 14.62784375
transcript.pyannote[5].end 20.29784375
transcript.pyannote[6].speaker SPEAKER_02
transcript.pyannote[6].start 20.60159375
transcript.pyannote[6].end 21.81659375
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 22.13721875
transcript.pyannote[7].end 24.60096875
transcript.pyannote[8].speaker SPEAKER_02
transcript.pyannote[8].start 25.36034375
transcript.pyannote[8].end 57.97971875
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 58.18221875
transcript.pyannote[9].end 63.81846875
transcript.pyannote[10].speaker SPEAKER_02
transcript.pyannote[10].start 63.97034375
transcript.pyannote[10].end 64.02096875
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 64.02096875
transcript.pyannote[11].end 64.03784375
transcript.pyannote[12].speaker SPEAKER_02
transcript.pyannote[12].start 64.03784375
transcript.pyannote[12].end 73.48784375
transcript.pyannote[13].speaker SPEAKER_02
transcript.pyannote[13].start 74.04471875
transcript.pyannote[13].end 78.38159375
transcript.pyannote[14].speaker SPEAKER_01
transcript.pyannote[14].start 78.38159375
transcript.pyannote[14].end 112.06409375
transcript.pyannote[15].speaker SPEAKER_02
transcript.pyannote[15].start 107.35596875
transcript.pyannote[15].end 107.96346875
transcript.pyannote[16].speaker SPEAKER_02
transcript.pyannote[16].start 111.16971875
transcript.pyannote[16].end 118.15596875
transcript.pyannote[17].speaker SPEAKER_01
transcript.pyannote[17].start 118.15596875
transcript.pyannote[17].end 131.50409375
transcript.pyannote[18].speaker SPEAKER_02
transcript.pyannote[18].start 118.17284375
transcript.pyannote[18].end 118.61159375
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 119.94471875
transcript.pyannote[19].end 120.40034375
transcript.pyannote[20].speaker SPEAKER_02
transcript.pyannote[20].start 131.50409375
transcript.pyannote[20].end 138.40596875
transcript.pyannote[21].speaker SPEAKER_01
transcript.pyannote[21].start 134.67659375
transcript.pyannote[21].end 135.26721875
transcript.pyannote[22].speaker SPEAKER_01
transcript.pyannote[22].start 136.21221875
transcript.pyannote[22].end 144.98721875
transcript.pyannote[23].speaker SPEAKER_02
transcript.pyannote[23].start 144.43034375
transcript.pyannote[23].end 152.53034375
transcript.pyannote[24].speaker SPEAKER_01
transcript.pyannote[24].start 149.59409375
transcript.pyannote[24].end 149.96534375
transcript.pyannote[25].speaker SPEAKER_01
transcript.pyannote[25].start 151.23096875
transcript.pyannote[25].end 152.31096875
transcript.pyannote[26].speaker SPEAKER_01
transcript.pyannote[26].start 152.53034375
transcript.pyannote[26].end 152.56409375
transcript.pyannote[27].speaker SPEAKER_02
transcript.pyannote[27].start 152.56409375
transcript.pyannote[27].end 152.58096875
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 153.13784375
transcript.pyannote[28].end 153.55971875
transcript.pyannote[29].speaker SPEAKER_02
transcript.pyannote[29].start 153.86346875
transcript.pyannote[29].end 161.55846875
transcript.pyannote[30].speaker SPEAKER_02
transcript.pyannote[30].start 161.72721875
transcript.pyannote[30].end 163.61721875
transcript.pyannote[31].speaker SPEAKER_02
transcript.pyannote[31].start 164.05596875
transcript.pyannote[31].end 178.88909375
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 178.92284375
transcript.pyannote[32].end 188.37284375
transcript.pyannote[33].speaker SPEAKER_00
transcript.pyannote[33].start 179.91846875
transcript.pyannote[33].end 180.27284375
transcript.pyannote[34].speaker SPEAKER_00
transcript.pyannote[34].start 181.87596875
transcript.pyannote[34].end 182.51721875
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 185.77409375
transcript.pyannote[35].end 185.84159375
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 186.06096875
transcript.pyannote[36].end 186.16221875
transcript.pyannote[37].speaker SPEAKER_02
transcript.pyannote[37].start 188.84534375
transcript.pyannote[37].end 196.48971875
transcript.pyannote[38].speaker SPEAKER_00
transcript.pyannote[38].start 196.27034375
transcript.pyannote[38].end 196.45596875
transcript.pyannote[39].speaker SPEAKER_00
transcript.pyannote[39].start 196.48971875
transcript.pyannote[39].end 196.69221875
transcript.pyannote[40].speaker SPEAKER_02
transcript.pyannote[40].start 196.69221875
transcript.pyannote[40].end 202.66596875
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 196.70909375
transcript.pyannote[41].end 196.77659375
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 203.03721875
transcript.pyannote[42].end 210.17534375
transcript.pyannote[43].speaker SPEAKER_00
transcript.pyannote[43].start 210.17534375
transcript.pyannote[43].end 210.27659375
transcript.pyannote[44].speaker SPEAKER_02
transcript.pyannote[44].start 210.27659375
transcript.pyannote[44].end 214.32659375
transcript.pyannote[45].speaker SPEAKER_02
transcript.pyannote[45].start 215.15346875
transcript.pyannote[45].end 231.08346875
transcript.pyannote[46].speaker SPEAKER_01
transcript.pyannote[46].start 231.08346875
transcript.pyannote[46].end 231.48846875
transcript.pyannote[47].speaker SPEAKER_02
transcript.pyannote[47].start 231.48846875
transcript.pyannote[47].end 231.53909375
transcript.pyannote[48].speaker SPEAKER_02
transcript.pyannote[48].start 231.64034375
transcript.pyannote[48].end 236.68596875
transcript.pyannote[49].speaker SPEAKER_02
transcript.pyannote[49].start 238.01909375
transcript.pyannote[49].end 240.02721875
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 240.02721875
transcript.pyannote[50].end 246.52409375
transcript.pyannote[51].speaker SPEAKER_01
transcript.pyannote[51].start 246.92909375
transcript.pyannote[51].end 247.90784375
transcript.pyannote[52].speaker SPEAKER_01
transcript.pyannote[52].start 248.49846875
transcript.pyannote[52].end 278.35034375
transcript.pyannote[53].speaker SPEAKER_00
transcript.pyannote[53].start 271.49909375
transcript.pyannote[53].end 271.93784375
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 278.63721875
transcript.pyannote[54].end 281.69159375
transcript.pyannote[55].speaker SPEAKER_01
transcript.pyannote[55].start 282.21471875
transcript.pyannote[55].end 284.22284375
transcript.pyannote[56].speaker SPEAKER_02
transcript.pyannote[56].start 284.12159375
transcript.pyannote[56].end 293.03159375
transcript.pyannote[57].speaker SPEAKER_01
transcript.pyannote[57].start 287.90159375
transcript.pyannote[57].end 288.01971875
transcript.pyannote[58].speaker SPEAKER_01
transcript.pyannote[58].start 293.03159375
transcript.pyannote[58].end 294.07784375
transcript.pyannote[59].speaker SPEAKER_02
transcript.pyannote[59].start 294.07784375
transcript.pyannote[59].end 294.76971875
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 294.76971875
transcript.pyannote[60].end 296.91284375
transcript.pyannote[61].speaker SPEAKER_02
transcript.pyannote[61].start 294.87096875
transcript.pyannote[61].end 297.57096875
transcript.pyannote[62].speaker SPEAKER_01
transcript.pyannote[62].start 297.57096875
transcript.pyannote[62].end 303.42659375
transcript.pyannote[63].speaker SPEAKER_02
transcript.pyannote[63].start 298.88721875
transcript.pyannote[63].end 300.72659375
transcript.pyannote[64].speaker SPEAKER_02
transcript.pyannote[64].start 303.02159375
transcript.pyannote[64].end 304.72596875
transcript.pyannote[65].speaker SPEAKER_01
transcript.pyannote[65].start 303.47721875
transcript.pyannote[65].end 303.51096875
transcript.pyannote[66].speaker SPEAKER_01
transcript.pyannote[66].start 303.54471875
transcript.pyannote[66].end 305.97471875
transcript.pyannote[67].speaker SPEAKER_02
transcript.pyannote[67].start 305.97471875
transcript.pyannote[67].end 340.02846875
transcript.pyannote[68].speaker SPEAKER_00
transcript.pyannote[68].start 326.52846875
transcript.pyannote[68].end 326.78159375
transcript.pyannote[69].speaker SPEAKER_00
transcript.pyannote[69].start 331.10159375
transcript.pyannote[69].end 331.48971875
transcript.pyannote[70].speaker SPEAKER_00
transcript.pyannote[70].start 334.59471875
transcript.pyannote[70].end 334.93221875
transcript.pyannote[71].speaker SPEAKER_01
transcript.pyannote[71].start 334.93221875
transcript.pyannote[71].end 334.94909375
transcript.pyannote[72].speaker SPEAKER_01
transcript.pyannote[72].start 340.02846875
transcript.pyannote[72].end 340.04534375
transcript.pyannote[73].speaker SPEAKER_02
transcript.pyannote[73].start 340.04534375
transcript.pyannote[73].end 345.12471875
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 340.12971875
transcript.pyannote[74].end 341.39534375
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 344.28096875
transcript.pyannote[75].end 344.78721875
transcript.pyannote[76].speaker SPEAKER_01
transcript.pyannote[76].start 345.12471875
transcript.pyannote[76].end 345.46221875
transcript.pyannote[77].speaker SPEAKER_02
transcript.pyannote[77].start 346.05284375
transcript.pyannote[77].end 351.65534375
transcript.pyannote[78].speaker SPEAKER_02
transcript.pyannote[78].start 351.94221875
transcript.pyannote[78].end 359.72159375
transcript.pyannote[79].speaker SPEAKER_00
transcript.pyannote[79].start 358.20284375
transcript.pyannote[79].end 358.25346875
transcript.pyannote[80].speaker SPEAKER_00
transcript.pyannote[80].start 358.40534375
transcript.pyannote[80].end 358.69221875
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 360.04221875
transcript.pyannote[81].end 363.45096875
transcript.pyannote[82].speaker SPEAKER_02
transcript.pyannote[82].start 363.85596875
transcript.pyannote[82].end 365.03721875
transcript.pyannote[83].speaker SPEAKER_01
transcript.pyannote[83].start 365.03721875
transcript.pyannote[83].end 386.11409375
transcript.pyannote[84].speaker SPEAKER_01
transcript.pyannote[84].start 386.75534375
transcript.pyannote[84].end 391.96971875
transcript.pyannote[85].speaker SPEAKER_00
transcript.pyannote[85].start 388.02096875
transcript.pyannote[85].end 388.03784375
transcript.pyannote[86].speaker SPEAKER_02
transcript.pyannote[86].start 388.03784375
transcript.pyannote[86].end 389.69159375
transcript.pyannote[87].speaker SPEAKER_02
transcript.pyannote[87].start 391.96971875
transcript.pyannote[87].end 393.55596875
transcript.pyannote[88].speaker SPEAKER_02
transcript.pyannote[88].start 393.94409375
transcript.pyannote[88].end 399.88409375
transcript.pyannote[89].speaker SPEAKER_02
transcript.pyannote[89].start 400.54221875
transcript.pyannote[89].end 403.63034375
transcript.pyannote[90].speaker SPEAKER_02
transcript.pyannote[90].start 403.88346875
transcript.pyannote[90].end 405.36846875
transcript.pyannote[91].speaker SPEAKER_02
transcript.pyannote[91].start 405.65534375
transcript.pyannote[91].end 409.78971875
transcript.pyannote[92].speaker SPEAKER_00
transcript.pyannote[92].start 410.05971875
transcript.pyannote[92].end 410.31284375
transcript.pyannote[93].speaker SPEAKER_02
transcript.pyannote[93].start 410.31284375
transcript.pyannote[93].end 412.55721875
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 412.65846875
transcript.pyannote[94].end 413.24909375
transcript.pyannote[95].speaker SPEAKER_02
transcript.pyannote[95].start 413.60346875
transcript.pyannote[95].end 416.77596875
transcript.pyannote[96].speaker SPEAKER_01
transcript.pyannote[96].start 416.77596875
transcript.pyannote[96].end 417.06284375
transcript.pyannote[97].speaker SPEAKER_02
transcript.pyannote[97].start 417.06284375
transcript.pyannote[97].end 417.13034375
transcript.pyannote[98].speaker SPEAKER_02
transcript.pyannote[98].start 417.14721875
transcript.pyannote[98].end 417.16409375
transcript.pyannote[99].speaker SPEAKER_02
transcript.pyannote[99].start 417.19784375
transcript.pyannote[99].end 420.11721875
transcript.pyannote[100].speaker SPEAKER_02
transcript.pyannote[100].start 420.47159375
transcript.pyannote[100].end 435.91221875
transcript.pyannote[101].speaker SPEAKER_01
transcript.pyannote[101].start 424.20096875
transcript.pyannote[101].end 424.30221875
transcript.pyannote[102].speaker SPEAKER_01
transcript.pyannote[102].start 424.38659375
transcript.pyannote[102].end 424.58909375
transcript.pyannote[103].speaker SPEAKER_00
transcript.pyannote[103].start 424.58909375
transcript.pyannote[103].end 424.67346875
transcript.pyannote[104].speaker SPEAKER_00
transcript.pyannote[104].start 430.98471875
transcript.pyannote[104].end 431.03534375
transcript.pyannote[105].speaker SPEAKER_01
transcript.pyannote[105].start 431.03534375
transcript.pyannote[105].end 431.38971875
transcript.pyannote[106].speaker SPEAKER_00
transcript.pyannote[106].start 432.92534375
transcript.pyannote[106].end 432.94221875
transcript.pyannote[107].speaker SPEAKER_01
transcript.pyannote[107].start 432.94221875
transcript.pyannote[107].end 433.00971875
transcript.pyannote[108].speaker SPEAKER_02
transcript.pyannote[108].start 436.31721875
transcript.pyannote[108].end 437.36346875
transcript.pyannote[109].speaker SPEAKER_02
transcript.pyannote[109].start 437.46471875
transcript.pyannote[109].end 441.24471875
transcript.pyannote[110].speaker SPEAKER_01
transcript.pyannote[110].start 441.24471875
transcript.pyannote[110].end 441.26159375
transcript.pyannote[111].speaker SPEAKER_02
transcript.pyannote[111].start 441.68346875
transcript.pyannote[111].end 442.03784375
transcript.pyannote[112].speaker SPEAKER_01
transcript.pyannote[112].start 442.03784375
transcript.pyannote[112].end 444.82221875
transcript.pyannote[113].speaker SPEAKER_01
transcript.pyannote[113].start 445.19346875
transcript.pyannote[113].end 459.08159375
transcript.pyannote[114].speaker SPEAKER_01
transcript.pyannote[114].start 459.36846875
transcript.pyannote[114].end 465.24096875
transcript.pyannote[115].speaker SPEAKER_02
transcript.pyannote[115].start 465.24096875
transcript.pyannote[115].end 466.92846875
transcript.pyannote[116].speaker SPEAKER_01
transcript.pyannote[116].start 465.64596875
transcript.pyannote[116].end 469.20659375
transcript.pyannote[117].speaker SPEAKER_02
transcript.pyannote[117].start 468.88596875
transcript.pyannote[117].end 478.97721875
transcript.pyannote[118].speaker SPEAKER_01
transcript.pyannote[118].start 474.82596875
transcript.pyannote[118].end 478.96034375
transcript.pyannote[119].speaker SPEAKER_01
transcript.pyannote[119].start 478.97721875
transcript.pyannote[119].end 479.82096875
transcript.pyannote[120].speaker SPEAKER_02
transcript.pyannote[120].start 479.38221875
transcript.pyannote[120].end 498.45096875
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 486.55409375
transcript.pyannote[121].end 487.97159375
transcript.pyannote[122].speaker SPEAKER_00
transcript.pyannote[122].start 490.63784375
transcript.pyannote[122].end 491.02596875
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 491.02596875
transcript.pyannote[123].end 491.48159375
transcript.pyannote[124].speaker SPEAKER_00
transcript.pyannote[124].start 491.48159375
transcript.pyannote[124].end 491.51534375
transcript.pyannote[125].speaker SPEAKER_01
transcript.pyannote[125].start 493.75971875
transcript.pyannote[125].end 494.35034375
transcript.pyannote[126].speaker SPEAKER_01
transcript.pyannote[126].start 494.45159375
transcript.pyannote[126].end 495.12659375
transcript.pyannote[127].speaker SPEAKER_01
transcript.pyannote[127].start 498.14721875
transcript.pyannote[127].end 506.92221875
transcript.pyannote[128].speaker SPEAKER_02
transcript.pyannote[128].start 506.77034375
transcript.pyannote[128].end 510.46596875
transcript.pyannote[129].speaker SPEAKER_01
transcript.pyannote[129].start 508.37346875
transcript.pyannote[129].end 509.77409375
transcript.pyannote[130].speaker SPEAKER_02
transcript.pyannote[130].start 510.60096875
transcript.pyannote[130].end 512.38971875
transcript.pyannote[131].speaker SPEAKER_02
transcript.pyannote[131].start 512.82846875
transcript.pyannote[131].end 523.83096875
transcript.pyannote[132].speaker SPEAKER_02
transcript.pyannote[132].start 524.40471875
transcript.pyannote[132].end 534.78284375
transcript.pyannote[133].speaker SPEAKER_01
transcript.pyannote[133].start 534.78284375
transcript.pyannote[133].end 547.18596875
transcript.pyannote[134].speaker SPEAKER_01
transcript.pyannote[134].start 547.54034375
transcript.pyannote[134].end 560.97284375
transcript.pyannote[135].speaker SPEAKER_00
transcript.pyannote[135].start 550.34159375
transcript.pyannote[135].end 551.74221875
transcript.pyannote[136].speaker SPEAKER_01
transcript.pyannote[136].start 561.17534375
transcript.pyannote[136].end 564.19596875
transcript.pyannote[137].speaker SPEAKER_02
transcript.pyannote[137].start 563.72346875
transcript.pyannote[137].end 567.03096875
transcript.pyannote[138].speaker SPEAKER_01
transcript.pyannote[138].start 567.03096875
transcript.pyannote[138].end 569.02221875
transcript.pyannote[139].speaker SPEAKER_02
transcript.pyannote[139].start 568.58346875
transcript.pyannote[139].end 570.77721875
transcript.pyannote[140].speaker SPEAKER_01
transcript.pyannote[140].start 570.77721875
transcript.pyannote[140].end 572.02596875
transcript.pyannote[141].speaker SPEAKER_02
transcript.pyannote[141].start 572.02596875
transcript.pyannote[141].end 582.03284375
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 582.03284375
transcript.pyannote[142].end 589.22159375
transcript.pyannote[143].speaker SPEAKER_01
transcript.pyannote[143].start 589.40721875
transcript.pyannote[143].end 607.19346875
transcript.pyannote[144].speaker SPEAKER_02
transcript.pyannote[144].start 605.94471875
transcript.pyannote[144].end 607.14284375
transcript.pyannote[145].speaker SPEAKER_02
transcript.pyannote[145].start 607.19346875
transcript.pyannote[145].end 611.02409375
transcript.pyannote[146].speaker SPEAKER_01
transcript.pyannote[146].start 611.02409375
transcript.pyannote[146].end 626.76846875
transcript.pyannote[147].speaker SPEAKER_02
transcript.pyannote[147].start 623.51159375
transcript.pyannote[147].end 624.00096875
transcript.pyannote[148].speaker SPEAKER_02
transcript.pyannote[148].start 624.82784375
transcript.pyannote[148].end 635.08784375
transcript.pyannote[149].speaker SPEAKER_01
transcript.pyannote[149].start 628.40534375
transcript.pyannote[149].end 628.99596875
transcript.pyannote[150].speaker SPEAKER_01
transcript.pyannote[150].start 630.63284375
transcript.pyannote[150].end 631.27409375
transcript.pyannote[151].speaker SPEAKER_00
transcript.pyannote[151].start 633.38346875
transcript.pyannote[151].end 671.72346875
transcript.pyannote[152].speaker SPEAKER_02
transcript.pyannote[152].start 666.15471875
transcript.pyannote[152].end 666.52596875
transcript.pyannote[153].speaker SPEAKER_02
transcript.pyannote[153].start 667.40346875
transcript.pyannote[153].end 668.73659375
transcript.pyannote[154].speaker SPEAKER_00
transcript.pyannote[154].start 671.85846875
transcript.pyannote[154].end 673.54596875
transcript.pyannote[155].speaker SPEAKER_00
transcript.pyannote[155].start 673.83284375
transcript.pyannote[155].end 702.52034375
transcript.pyannote[156].speaker SPEAKER_02
transcript.pyannote[156].start 701.11971875
transcript.pyannote[156].end 705.22034375
transcript.pyannote[157].speaker SPEAKER_02
transcript.pyannote[157].start 705.69284375
transcript.pyannote[157].end 708.39284375
transcript.pyannote[158].speaker SPEAKER_02
transcript.pyannote[158].start 708.44346875
transcript.pyannote[158].end 709.35471875
transcript.pyannote[159].speaker SPEAKER_00
transcript.pyannote[159].start 708.96659375
transcript.pyannote[159].end 725.41971875
transcript.pyannote[160].speaker SPEAKER_00
transcript.pyannote[160].start 725.74034375
transcript.pyannote[160].end 740.20221875
transcript.pyannote[161].speaker SPEAKER_02
transcript.pyannote[161].start 735.78096875
transcript.pyannote[161].end 736.21971875
transcript.pyannote[162].speaker SPEAKER_02
transcript.pyannote[162].start 738.10971875
transcript.pyannote[162].end 738.66659375
transcript.pyannote[163].speaker SPEAKER_02
transcript.pyannote[163].start 739.03784375
transcript.pyannote[163].end 747.50909375
transcript.pyannote[164].speaker SPEAKER_01
transcript.pyannote[164].start 745.55159375
transcript.pyannote[164].end 749.80409375
transcript.pyannote[165].speaker SPEAKER_02
transcript.pyannote[165].start 748.90971875
transcript.pyannote[165].end 754.00596875
transcript.pyannote[166].speaker SPEAKER_00
transcript.pyannote[166].start 750.52971875
transcript.pyannote[166].end 756.16596875
transcript.pyannote[167].speaker SPEAKER_00
transcript.pyannote[167].start 756.92534375
transcript.pyannote[167].end 757.11096875
transcript.whisperx[0].start 2.543
transcript.whisperx[0].end 24.108
transcript.whisperx[0].text 好 謝謝主席 請我們石部長還有國建署省署長部長 署長 國建署 圖遠好部長 那我們罕病也知道及早篩檢是很重要的早期發現 早期治療那我們目前台灣少子的話每年大概超過
transcript.whisperx[1].start 25.884
transcript.whisperx[1].end 52.96
transcript.whisperx[1].text 600位的婴儿死亡那也就是说每15个小时就超过一个婴儿失去生命那后来我们来探究他死亡的原因超过100位的婴儿大部分都是因为先天性畸形变形或者染色体异常等先天疾病那部长我请问一下像我们脊髓性的肌肉萎缩症SMA也是婴儿死亡
transcript.whisperx[2].start 53.9
transcript.whisperx[2].end 74.591
transcript.whisperx[2].text 死亡機率低高的遺傳疾病那龐佩氏症如果在兩歲以前沒有治療他的死亡率幾乎高達百分之百那目前我們國健署補助公費針對新生兒先天性代謝異常的疾病篩檢裡面有21項那我請問一下這21項有包含我剛剛說的那兩項嗎
transcript.whisperx[3].start 78.693
transcript.whisperx[3].end 98.368
transcript.whisperx[3].text 跟委員說明這兩個罕病目前都有健保給付的藥品治療那至於說篩檢新生兒篩檢的部分這個SMA經過了大概一年的討論那麼現在大概有了定案會納入公費的新生兒篩檢的項目以前是建議啦
transcript.whisperx[4].start 99.088
transcript.whisperx[4].end 119.142
transcript.whisperx[4].text 是自費的項目啦那明年會把它納入那這個是已經經過HTA的評估是OK那另外龐氏症的部分現在還在評估當中所以因為我看國健署今年9月就說研議要納入所以現在已經確定會納入了SMA確定會納入
transcript.whisperx[5].start 120.003
transcript.whisperx[5].end 140.682
transcript.whisperx[5].text 那什麼時候可以開始實施應該是在明年的下半年因為要配合地方政府編列的有六都的預算他們要配合去編列其他縣市我們都補助好 所以SMA明年下半年度就可以實施對那龐貝市政也希望龐貝市政是現在還在進行HTA當中就是科技評估當中
transcript.whisperx[6].start 141.403
transcript.whisperx[6].end 163.281
transcript.whisperx[6].text 那一有結果的話就會送到專家會議來討論來決定那這部分就請部長來幫我們進行所以SMS確定啦那龐貝市政現在也在評估中好那我再請問一下像我們今天主要是針對我們癌症新藥基金嘛那賴總統健康台灣政策他有講
transcript.whisperx[7].start 164.122
transcript.whisperx[7].end 193.212
transcript.whisperx[7].text 百億癌症新藥基金那我看一下我們2025年是編列50億那50億我剛剛有聽部長講所以預計到明年應該是有七八十億因為今年大概會留下20幾億然後再加上明年50億所以大概會有76億多我們大概有算了一下可是這76億多我們要包含2025年已經收窄的藥品
transcript.whisperx[8].start 193.972
transcript.whisperx[8].end 214.111
transcript.whisperx[8].text 分期可能会支付掉39亿多所以76亿多里面支付掉39亿多其实它也只剩下30几亿那30几亿如果说以我们今年2025年你看你下半年度就大概20亿20几亿那如果全年度30几亿势必是会不够用的
transcript.whisperx[9].start 215.262
transcript.whisperx[9].end 236.692
transcript.whisperx[9].text 如果以这样子来推算4BH不够用而且你到2027年还要支付2025年收窄的分期的费用还有到2026也要付他分期的费用算下来就要70几亿所以你到2027年如果没有到百亿绝对是破产了
transcript.whisperx[10].start 238.089
transcript.whisperx[10].end 253.899
transcript.whisperx[10].text 那部長針對這部分你們有沒有了解過我們推估啦大概也是差不多2027是要百億啦因為我們是這樣這個要不是大家一起在同一個時間收窄進來他會有時間嘛一月幾個二月這樣陸陸續續進來
transcript.whisperx[11].start 255.8
transcript.whisperx[11].end 278.002
transcript.whisperx[11].text 然後進來我們審查通過發布要幾副的時候醫院還要去採購 溢價等等的程序所以都稍微會delay所以明年大概我們認為大概七八十一是夠用但後年會到百億沒有錯接下來我們前面的這些藥會因為經過三年他有的就評估完就會回到健保
transcript.whisperx[12].start 279.083
transcript.whisperx[12].end 293.676
transcript.whisperx[12].text 所以他就會有進進出出啦就是一個這個活水的概念這樣對 所以因為他本身沒有公務預算嘛那目前也沒有辦法編列正式編列這個基金進來嘛現在是用公務預算
transcript.whisperx[13].start 294.876
transcript.whisperx[13].end 306.062
transcript.whisperx[13].text 來撥補在這個你是撥補的嘛對對對是挪用嘛從公務預算去編列進來去挪用嘛它不是正式編列嘛正式編列專款專用專款專用對專款專用那可是照現在50億看起來是勢必到2027是絕對不夠對2027就會到100億就會再我們會再去爭取100億進來
transcript.whisperx[14].start 313.806
transcript.whisperx[14].end 332.395
transcript.whisperx[14].text 好 我們希望一定要逐年增加因為如果說以現在這樣子的算法2025、51、2026、51勢必到2027年錢就絕對不夠用最少要到百億那不然到2028年很多這些癌症的患者
transcript.whisperx[15].start 332.935
transcript.whisperx[15].end 345.256
transcript.whisperx[15].text 它就会变成药品的孤儿甚至自己要自费负担这高额的费用我们会去做好预估跟预算的编列希望这个赶快在逐年最慢在2027年一定要达到百年会会会
transcript.whisperx[16].start 346.648
transcript.whisperx[16].end 363.25
transcript.whisperx[16].text 那還有針對部長你在六月受訪的時候你有說失智症百萬新藥今年年底有機會完成評估研疫納保那這個阿茲海默症的新藥納入健保給付
transcript.whisperx[17].start 364.391
transcript.whisperx[17].end 385.086
transcript.whisperx[17].text 請問現在的審議制度進行到哪裡這個已經經過那個專家會議已經討論過了那根據這個HTA的報告那麼還有其他國家的HTA的報告是目前認為這一個阿茲海默症的新藥它的這個療效 長期療效不明所以還需要再繼續的
transcript.whisperx[18].start 386.847
transcript.whisperx[18].end 409.073
transcript.whisperx[18].text 更多的數據 所以暫時不納入健保的給付好 那今天主要要討論一下審議進度的問題因為我們看一下國健署他在針對藥品健康風險評估審查的情形他不管是申請的業者 流程 還有他的進度
transcript.whisperx[19].start 410.413
transcript.whisperx[19].end 437.125
transcript.whisperx[19].text 都很明確一目了然然後國健署在這一方面我們感覺他做得還算非常的完善那部長你一月份我記得一月份那時候還擔任健保署署長那時候你在詢答的時候你也答應說針對這個審議制度盡量炒透明公開藥品的審查案件那你現在也做部長了不知道這一個部分
transcript.whisperx[20].start 437.725
transcript.whisperx[20].end 458.805
transcript.whisperx[20].text 什麼時候可以讓藥品審查的審議進度能夠公開透明跟委員說明我們那個有醫材跟藥品那醫材的部分現在進度就像這樣都可以查了那個醫材的這個審查的進度已經做好了那個資訊公開透明了那現在正在進行
transcript.whisperx[21].start 459.806
transcript.whisperx[21].end 478.715
transcript.whisperx[21].text 藥品的部分仿造這個醫材這樣一併把它公開應該是那大概什麼時候可以做到大概年底前會完成年底前可以完成所以一般來講如果照部長這樣講明年我們就有機會把這些對 這不論是醫材或者是藥品的審議的進度公開透明對 因為
transcript.whisperx[22].start 480.516
transcript.whisperx[22].end 508.513
transcript.whisperx[22].text 我們當然我們立法委員他可以透過詢答去了解你這個制度可是很多民眾他不知道他不知道他什麼時候他這個用藥到底什麼時候才可以用造成他很不明確不知道到底什麼時候才可以使用所以我覺得公開透明對民眾一定有很大的幫助就是審查的進度到哪裡然後最後的審查結果如何是怎麼樣的給付方式都會在未來都可以查詢的到所以部長說明年就應該就沒問題了
transcript.whisperx[23].start 510.014
transcript.whisperx[23].end 535.934
transcript.whisperx[23].text 好 那還有我們最近食安連環報一下黑心豬大腸那現在又有毒雞蛋一下豬大腸用工業級的雙氧水那毒雞蛋分埔泥又超標那針對這一部分我們這食安武漢看起來又破功了那這一部分看起來是不是源頭控管的問題跟委員報告 其實這一次這個
transcript.whisperx[24].start 538.435
transcript.whisperx[24].end 565.547
transcript.whisperx[24].text 問題蛋是我們的例行性查核查出來的就是從在2017年之後我們就開始做這個後市場的例行性的抽驗所以這個是例行性抽驗我們過去七年其實都是零檢出啦抽驗的都是正常這一次才有發現有一個不合格品所以這個食安五環其實是有發揮它的作用所以目前抽驗到只有彰化這個畜牧場是嗎
transcript.whisperx[25].start 567.588
transcript.whisperx[25].end 588.862
transcript.whisperx[25].text 這個畜牧場出來的蛋所以抽驗其他都沒有問題對 目前的都是這樣那我們之前抽驗出來現在聽說好像我們復驗又針對蛋機它的羽毛還有它的代謝物都是超標而且超標很多對 就是為了要找源頭因為我們是在後市場所以後市場是查到蛋有
transcript.whisperx[26].start 589.642
transcript.whisperx[26].end 617.385
transcript.whisperx[26].text 但是為什麼蛋裡面會有分譜你就要找原因啦所以才有農政單位去介入從這個環境包含它的飲用水它的飼料包含它的羽毛啦其他的其他的雞的蛋都去大更過大抽菸所以針對你們抽菸的結果看出來應該是不是注射在雞的身上不是現在抽菸的結果因為它的飲用水飼料都沒有檢出啦
transcript.whisperx[27].start 617.965
transcript.whisperx[27].end 641.184
transcript.whisperx[27].text 剪出的是它的羽毛而且羽毛跟蛋跟它的排泄物來比是比較高的所以它的飼料跟土囊沒有問題啊但是它蛋積本身的羽毛還有它的代謝物是驗出來超標啊而且超標很高嘛 跟委員這邊進一步說明那目前因為剛好這次是剪掉跨部會其實進去協助的
transcript.whisperx[28].start 641.764
transcript.whisperx[28].end 670.323
transcript.whisperx[28].text 在這個抽煉的過程中羽毛上面有其實不是常態所以的確在推論上面是高度懷疑是直接有在噴灑在羽毛身上在農政單位的就我了解我剛才跟畜牧師去做溝通這個是嚴格禁止他們也是積極過去從107以後積極輔導從來都沒有查到有這樣的情形所以他們現在也是積極的那現在到底知道原因是對 原因就是應該是
transcript.whisperx[29].start 672.345
transcript.whisperx[29].end 691.577
transcript.whisperx[29].text 業主個人的行為對於這個施藥的行為其實本來不能施藥的他做了一個錯誤的施藥那過去的管理也相對我聽起來是很嚴格那個人行為這個他們去積極矯正在後市場端4382次的抽驗裡面我們目前
transcript.whisperx[30].start 692.458
transcript.whisperx[30].end 709.019
transcript.whisperx[30].text 都沒有所以整個看起來台灣對於芬普尼這個管制其實有效那這一次失靈我相信在農場端所以署長的意思說這個目前看起來是個案對不對那我們其他的都有去抽菸嗎都有去抽菸嗎
transcript.whisperx[31].start 709.54
transcript.whisperx[31].end 724.778
transcript.whisperx[31].text 我們其實今年度到現在461件11 12月持續一個月都還有五六十件所以這個是不會停止的那過去的數據是在隨機抽驗下來在一些科學的基礎上面我們看起來的確
transcript.whisperx[32].start 726.059
transcript.whisperx[32].end 744.398
transcript.whisperx[32].text 農政單位往前的部分還持續的我們後市長也會持續的監測那部長也跟我們提到只要有任何新的任何事件一直查到哪裡我們就公佈到哪裡一定再會有大家委員其實很多的期許我們會努力的那希望部長跟署長我們這食安五環尤其這源頭控管的部分還是要幫我們加強會
transcript.whisperx[33].start 746.44
transcript.whisperx[33].end 751.905
transcript.whisperx[33].text 好 謝謝 原則把關讓大家都時的安心好 謝謝委員 時的安心好 謝謝啦 時的安心那接下來請廖翔 張偉來做詢問