iVOD / 163176

Field Value
IVOD_ID 163176
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/163176
日期 2025-07-17
會議資料.會議代碼 委員會-11-3-26-21
會議資料.會議代碼:str 第11屆第3會期社會福利及衛生環境委員會第21次全體委員會議
會議資料.屆 11
會議資料.會期 3
會議資料.會次 21
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3會期社會福利及衛生環境委員會第21次全體委員會議
影片種類 Clip
開始時間 2025-07-17T09:21:43+08:00
結束時間 2025-07-17T09:32:13+08:00
影片長度 00:10:30
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/1404c3f0fc5b9857c5625b3fe2f6ea217e529aa6299d4c225af1ef4f9e86959b3f69a6de72969f305ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 陳昭姿
委員發言時間 09:21:43 - 09:32:13
會議時間 2025-07-17T09:00:00+08:00
會議名稱 立法院第11屆第3會期社會福利及衛生環境委員會第21次全體委員會議(事由:邀請衛生福利部部長、勞動部部長、財政部部長、農業部針對「因應嚴重災情、緊急重大事件,醫療院所承擔救護量能困境及因應台美關稅談判對台灣食品安全相關影響」進行專題報告,並備質詢。)
transcript.pyannote[0].speaker SPEAKER_02
transcript.pyannote[0].start 4.30034375
transcript.pyannote[0].end 5.68409375
transcript.pyannote[1].speaker SPEAKER_01
transcript.pyannote[1].start 6.19034375
transcript.pyannote[1].end 6.79784375
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 6.79784375
transcript.pyannote[2].end 6.86534375
transcript.pyannote[3].speaker SPEAKER_04
transcript.pyannote[3].start 11.28659375
transcript.pyannote[3].end 11.43846875
transcript.pyannote[4].speaker SPEAKER_02
transcript.pyannote[4].start 11.43846875
transcript.pyannote[4].end 41.98221875
transcript.pyannote[5].speaker SPEAKER_04
transcript.pyannote[5].start 11.70846875
transcript.pyannote[5].end 11.72534375
transcript.pyannote[6].speaker SPEAKER_03
transcript.pyannote[6].start 13.41284375
transcript.pyannote[6].end 13.42971875
transcript.pyannote[7].speaker SPEAKER_04
transcript.pyannote[7].start 13.42971875
transcript.pyannote[7].end 14.07096875
transcript.pyannote[8].speaker SPEAKER_04
transcript.pyannote[8].start 16.02846875
transcript.pyannote[8].end 16.46721875
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 42.10034375
transcript.pyannote[9].end 42.87659375
transcript.pyannote[10].speaker SPEAKER_02
transcript.pyannote[10].start 43.78784375
transcript.pyannote[10].end 44.37846875
transcript.pyannote[11].speaker SPEAKER_02
transcript.pyannote[11].start 47.83784375
transcript.pyannote[11].end 48.31034375
transcript.pyannote[12].speaker SPEAKER_04
transcript.pyannote[12].start 48.34409375
transcript.pyannote[12].end 52.68096875
transcript.pyannote[13].speaker SPEAKER_02
transcript.pyannote[13].start 48.98534375
transcript.pyannote[13].end 51.51659375
transcript.pyannote[14].speaker SPEAKER_02
transcript.pyannote[14].start 52.68096875
transcript.pyannote[14].end 57.81096875
transcript.pyannote[15].speaker SPEAKER_02
transcript.pyannote[15].start 58.45221875
transcript.pyannote[15].end 58.67159375
transcript.pyannote[16].speaker SPEAKER_04
transcript.pyannote[16].start 58.58721875
transcript.pyannote[16].end 59.07659375
transcript.pyannote[17].speaker SPEAKER_02
transcript.pyannote[17].start 59.11034375
transcript.pyannote[17].end 61.08471875
transcript.pyannote[18].speaker SPEAKER_04
transcript.pyannote[18].start 59.73471875
transcript.pyannote[18].end 71.20971875
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 61.99596875
transcript.pyannote[19].end 62.40096875
transcript.pyannote[20].speaker SPEAKER_02
transcript.pyannote[20].start 66.19784375
transcript.pyannote[20].end 66.63659375
transcript.pyannote[21].speaker SPEAKER_02
transcript.pyannote[21].start 71.10846875
transcript.pyannote[21].end 94.07534375
transcript.pyannote[22].speaker SPEAKER_00
transcript.pyannote[22].start 81.40221875
transcript.pyannote[22].end 81.75659375
transcript.pyannote[23].speaker SPEAKER_04
transcript.pyannote[23].start 94.76721875
transcript.pyannote[23].end 103.81221875
transcript.pyannote[24].speaker SPEAKER_02
transcript.pyannote[24].start 94.98659375
transcript.pyannote[24].end 95.67846875
transcript.pyannote[25].speaker SPEAKER_02
transcript.pyannote[25].start 97.99034375
transcript.pyannote[25].end 99.55971875
transcript.pyannote[26].speaker SPEAKER_02
transcript.pyannote[26].start 103.47471875
transcript.pyannote[26].end 104.77409375
transcript.pyannote[27].speaker SPEAKER_04
transcript.pyannote[27].start 104.35221875
transcript.pyannote[27].end 110.54534375
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 109.68471875
transcript.pyannote[28].end 112.11471875
transcript.pyannote[29].speaker SPEAKER_04
transcript.pyannote[29].start 111.43971875
transcript.pyannote[29].end 122.17221875
transcript.pyannote[30].speaker SPEAKER_04
transcript.pyannote[30].start 122.52659375
transcript.pyannote[30].end 128.55096875
transcript.pyannote[31].speaker SPEAKER_02
transcript.pyannote[31].start 126.39096875
transcript.pyannote[31].end 131.77409375
transcript.pyannote[32].speaker SPEAKER_04
transcript.pyannote[32].start 129.10784375
transcript.pyannote[32].end 131.04846875
transcript.pyannote[33].speaker SPEAKER_04
transcript.pyannote[33].start 131.89221875
transcript.pyannote[33].end 133.63034375
transcript.pyannote[34].speaker SPEAKER_02
transcript.pyannote[34].start 134.28846875
transcript.pyannote[34].end 135.28409375
transcript.pyannote[35].speaker SPEAKER_04
transcript.pyannote[35].start 134.50784375
transcript.pyannote[35].end 141.76409375
transcript.pyannote[36].speaker SPEAKER_02
transcript.pyannote[36].start 136.53284375
transcript.pyannote[36].end 137.81534375
transcript.pyannote[37].speaker SPEAKER_03
transcript.pyannote[37].start 137.81534375
transcript.pyannote[37].end 137.83221875
transcript.pyannote[38].speaker SPEAKER_02
transcript.pyannote[38].start 140.07659375
transcript.pyannote[38].end 140.11034375
transcript.pyannote[39].speaker SPEAKER_03
transcript.pyannote[39].start 140.11034375
transcript.pyannote[39].end 140.12721875
transcript.pyannote[40].speaker SPEAKER_02
transcript.pyannote[40].start 140.12721875
transcript.pyannote[40].end 140.27909375
transcript.pyannote[41].speaker SPEAKER_03
transcript.pyannote[41].start 140.27909375
transcript.pyannote[41].end 140.29596875
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 140.29596875
transcript.pyannote[42].end 140.32971875
transcript.pyannote[43].speaker SPEAKER_03
transcript.pyannote[43].start 140.32971875
transcript.pyannote[43].end 140.46471875
transcript.pyannote[44].speaker SPEAKER_02
transcript.pyannote[44].start 140.46471875
transcript.pyannote[44].end 143.29971875
transcript.pyannote[45].speaker SPEAKER_04
transcript.pyannote[45].start 141.96659375
transcript.pyannote[45].end 148.59846875
transcript.pyannote[46].speaker SPEAKER_02
transcript.pyannote[46].start 145.78034375
transcript.pyannote[46].end 147.50159375
transcript.pyannote[47].speaker SPEAKER_02
transcript.pyannote[47].start 148.17659375
transcript.pyannote[47].end 161.08596875
transcript.pyannote[48].speaker SPEAKER_02
transcript.pyannote[48].start 161.55846875
transcript.pyannote[48].end 174.87284375
transcript.pyannote[49].speaker SPEAKER_04
transcript.pyannote[49].start 175.29471875
transcript.pyannote[49].end 179.68221875
transcript.pyannote[50].speaker SPEAKER_02
transcript.pyannote[50].start 177.57284375
transcript.pyannote[50].end 177.60659375
transcript.pyannote[51].speaker SPEAKER_02
transcript.pyannote[51].start 177.74159375
transcript.pyannote[51].end 205.07909375
transcript.pyannote[52].speaker SPEAKER_04
transcript.pyannote[52].start 180.32346875
transcript.pyannote[52].end 180.59346875
transcript.pyannote[53].speaker SPEAKER_02
transcript.pyannote[53].start 205.72034375
transcript.pyannote[53].end 207.35721875
transcript.pyannote[54].speaker SPEAKER_04
transcript.pyannote[54].start 208.52159375
transcript.pyannote[54].end 213.33096875
transcript.pyannote[55].speaker SPEAKER_02
transcript.pyannote[55].start 213.06096875
transcript.pyannote[55].end 217.11096875
transcript.pyannote[56].speaker SPEAKER_04
transcript.pyannote[56].start 214.49534375
transcript.pyannote[56].end 214.84971875
transcript.pyannote[57].speaker SPEAKER_04
transcript.pyannote[57].start 215.15346875
transcript.pyannote[57].end 221.95409375
transcript.pyannote[58].speaker SPEAKER_02
transcript.pyannote[58].start 220.09784375
transcript.pyannote[58].end 222.98346875
transcript.pyannote[59].speaker SPEAKER_02
transcript.pyannote[59].start 223.33784375
transcript.pyannote[59].end 226.66221875
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 226.66221875
transcript.pyannote[60].end 226.76346875
transcript.pyannote[61].speaker SPEAKER_02
transcript.pyannote[61].start 226.76346875
transcript.pyannote[61].end 226.78034375
transcript.pyannote[62].speaker SPEAKER_01
transcript.pyannote[62].start 226.78034375
transcript.pyannote[62].end 226.81409375
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 226.98284375
transcript.pyannote[63].end 272.96721875
transcript.pyannote[64].speaker SPEAKER_00
transcript.pyannote[64].start 246.01784375
transcript.pyannote[64].end 246.32159375
transcript.pyannote[65].speaker SPEAKER_00
transcript.pyannote[65].start 246.33846875
transcript.pyannote[65].end 246.54096875
transcript.pyannote[66].speaker SPEAKER_00
transcript.pyannote[66].start 247.53659375
transcript.pyannote[66].end 248.63346875
transcript.pyannote[67].speaker SPEAKER_00
transcript.pyannote[67].start 249.02159375
transcript.pyannote[67].end 249.46034375
transcript.pyannote[68].speaker SPEAKER_00
transcript.pyannote[68].start 257.15534375
transcript.pyannote[68].end 257.66159375
transcript.pyannote[69].speaker SPEAKER_02
transcript.pyannote[69].start 272.96721875
transcript.pyannote[69].end 284.69534375
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 284.69534375
transcript.pyannote[70].end 284.72909375
transcript.pyannote[71].speaker SPEAKER_02
transcript.pyannote[71].start 284.72909375
transcript.pyannote[71].end 284.74596875
transcript.pyannote[72].speaker SPEAKER_01
transcript.pyannote[72].start 285.20159375
transcript.pyannote[72].end 297.97596875
transcript.pyannote[73].speaker SPEAKER_02
transcript.pyannote[73].start 296.03534375
transcript.pyannote[73].end 297.48659375
transcript.pyannote[74].speaker SPEAKER_02
transcript.pyannote[74].start 297.97596875
transcript.pyannote[74].end 303.02159375
transcript.pyannote[75].speaker SPEAKER_02
transcript.pyannote[75].start 303.56159375
transcript.pyannote[75].end 313.78784375
transcript.pyannote[76].speaker SPEAKER_04
transcript.pyannote[76].start 313.61909375
transcript.pyannote[76].end 315.40784375
transcript.pyannote[77].speaker SPEAKER_02
transcript.pyannote[77].start 315.40784375
transcript.pyannote[77].end 319.35659375
transcript.pyannote[78].speaker SPEAKER_04
transcript.pyannote[78].start 319.66034375
transcript.pyannote[78].end 320.53784375
transcript.pyannote[79].speaker SPEAKER_02
transcript.pyannote[79].start 319.82909375
transcript.pyannote[79].end 323.44034375
transcript.pyannote[80].speaker SPEAKER_04
transcript.pyannote[80].start 323.44034375
transcript.pyannote[80].end 334.12221875
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 326.14034375
transcript.pyannote[81].end 327.23721875
transcript.pyannote[82].speaker SPEAKER_02
transcript.pyannote[82].start 330.59534375
transcript.pyannote[82].end 332.24909375
transcript.pyannote[83].speaker SPEAKER_02
transcript.pyannote[83].start 332.62034375
transcript.pyannote[83].end 333.61596875
transcript.pyannote[84].speaker SPEAKER_02
transcript.pyannote[84].start 334.00409375
transcript.pyannote[84].end 347.62221875
transcript.pyannote[85].speaker SPEAKER_04
transcript.pyannote[85].start 336.46784375
transcript.pyannote[85].end 336.80534375
transcript.pyannote[86].speaker SPEAKER_02
transcript.pyannote[86].start 348.06096875
transcript.pyannote[86].end 350.27159375
transcript.pyannote[87].speaker SPEAKER_04
transcript.pyannote[87].start 350.22096875
transcript.pyannote[87].end 357.08909375
transcript.pyannote[88].speaker SPEAKER_02
transcript.pyannote[88].start 351.48659375
transcript.pyannote[88].end 351.95909375
transcript.pyannote[89].speaker SPEAKER_02
transcript.pyannote[89].start 357.12284375
transcript.pyannote[89].end 360.54846875
transcript.pyannote[90].speaker SPEAKER_00
transcript.pyannote[90].start 360.54846875
transcript.pyannote[90].end 360.58221875
transcript.pyannote[91].speaker SPEAKER_00
transcript.pyannote[91].start 360.76784375
transcript.pyannote[91].end 360.78471875
transcript.pyannote[92].speaker SPEAKER_02
transcript.pyannote[92].start 360.78471875
transcript.pyannote[92].end 362.48909375
transcript.pyannote[93].speaker SPEAKER_04
transcript.pyannote[93].start 360.80159375
transcript.pyannote[93].end 364.24409375
transcript.pyannote[94].speaker SPEAKER_00
transcript.pyannote[94].start 362.48909375
transcript.pyannote[94].end 363.21471875
transcript.pyannote[95].speaker SPEAKER_02
transcript.pyannote[95].start 363.21471875
transcript.pyannote[95].end 363.23159375
transcript.pyannote[96].speaker SPEAKER_00
transcript.pyannote[96].start 364.42971875
transcript.pyannote[96].end 371.98971875
transcript.pyannote[97].speaker SPEAKER_04
transcript.pyannote[97].start 368.78346875
transcript.pyannote[97].end 368.98596875
transcript.pyannote[98].speaker SPEAKER_04
transcript.pyannote[98].start 369.55971875
transcript.pyannote[98].end 369.89721875
transcript.pyannote[99].speaker SPEAKER_04
transcript.pyannote[99].start 370.94346875
transcript.pyannote[99].end 371.02784375
transcript.pyannote[100].speaker SPEAKER_02
transcript.pyannote[100].start 371.02784375
transcript.pyannote[100].end 371.85471875
transcript.pyannote[101].speaker SPEAKER_00
transcript.pyannote[101].start 372.32721875
transcript.pyannote[101].end 379.83659375
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 379.33034375
transcript.pyannote[102].end 384.69659375
transcript.pyannote[103].speaker SPEAKER_00
transcript.pyannote[103].start 381.40596875
transcript.pyannote[103].end 386.50221875
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 386.50221875
transcript.pyannote[104].end 386.51909375
transcript.pyannote[105].speaker SPEAKER_00
transcript.pyannote[105].start 386.51909375
transcript.pyannote[105].end 386.53596875
transcript.pyannote[106].speaker SPEAKER_02
transcript.pyannote[106].start 386.53596875
transcript.pyannote[106].end 396.05346875
transcript.pyannote[107].speaker SPEAKER_00
transcript.pyannote[107].start 386.82284375
transcript.pyannote[107].end 389.59034375
transcript.pyannote[108].speaker SPEAKER_02
transcript.pyannote[108].start 396.23909375
transcript.pyannote[108].end 397.70721875
transcript.pyannote[109].speaker SPEAKER_04
transcript.pyannote[109].start 396.27284375
transcript.pyannote[109].end 396.86346875
transcript.pyannote[110].speaker SPEAKER_04
transcript.pyannote[110].start 397.74096875
transcript.pyannote[110].end 400.27221875
transcript.pyannote[111].speaker SPEAKER_02
transcript.pyannote[111].start 399.91784375
transcript.pyannote[111].end 405.14909375
transcript.pyannote[112].speaker SPEAKER_04
transcript.pyannote[112].start 405.04784375
transcript.pyannote[112].end 406.44846875
transcript.pyannote[113].speaker SPEAKER_04
transcript.pyannote[113].start 406.90409375
transcript.pyannote[113].end 409.03034375
transcript.pyannote[114].speaker SPEAKER_03
transcript.pyannote[114].start 409.03034375
transcript.pyannote[114].end 411.83159375
transcript.pyannote[115].speaker SPEAKER_02
transcript.pyannote[115].start 411.83159375
transcript.pyannote[115].end 430.19159375
transcript.pyannote[116].speaker SPEAKER_04
transcript.pyannote[116].start 430.19159375
transcript.pyannote[116].end 430.39409375
transcript.pyannote[117].speaker SPEAKER_02
transcript.pyannote[117].start 431.01846875
transcript.pyannote[117].end 445.85159375
transcript.pyannote[118].speaker SPEAKER_02
transcript.pyannote[118].start 446.05409375
transcript.pyannote[118].end 467.56971875
transcript.pyannote[119].speaker SPEAKER_00
transcript.pyannote[119].start 451.30221875
transcript.pyannote[119].end 451.42034375
transcript.pyannote[120].speaker SPEAKER_00
transcript.pyannote[120].start 451.79159375
transcript.pyannote[120].end 451.89284375
transcript.pyannote[121].speaker SPEAKER_00
transcript.pyannote[121].start 454.59284375
transcript.pyannote[121].end 455.45346875
transcript.pyannote[122].speaker SPEAKER_00
transcript.pyannote[122].start 455.48721875
transcript.pyannote[122].end 455.52096875
transcript.pyannote[123].speaker SPEAKER_00
transcript.pyannote[123].start 455.53784375
transcript.pyannote[123].end 455.63909375
transcript.pyannote[124].speaker SPEAKER_04
transcript.pyannote[124].start 467.56971875
transcript.pyannote[124].end 487.56659375
transcript.pyannote[125].speaker SPEAKER_02
transcript.pyannote[125].start 468.59909375
transcript.pyannote[125].end 469.79721875
transcript.pyannote[126].speaker SPEAKER_00
transcript.pyannote[126].start 477.22221875
transcript.pyannote[126].end 478.38659375
transcript.pyannote[127].speaker SPEAKER_02
transcript.pyannote[127].start 487.56659375
transcript.pyannote[127].end 489.13596875
transcript.pyannote[128].speaker SPEAKER_04
transcript.pyannote[128].start 488.39346875
transcript.pyannote[128].end 488.66346875
transcript.pyannote[129].speaker SPEAKER_04
transcript.pyannote[129].start 489.01784375
transcript.pyannote[129].end 501.91034375
transcript.pyannote[130].speaker SPEAKER_02
transcript.pyannote[130].start 501.64034375
transcript.pyannote[130].end 503.86784375
transcript.pyannote[131].speaker SPEAKER_04
transcript.pyannote[131].start 503.47971875
transcript.pyannote[131].end 510.04409375
transcript.pyannote[132].speaker SPEAKER_02
transcript.pyannote[132].start 509.53784375
transcript.pyannote[132].end 513.48659375
transcript.pyannote[133].speaker SPEAKER_04
transcript.pyannote[133].start 511.39409375
transcript.pyannote[133].end 517.95846875
transcript.pyannote[134].speaker SPEAKER_02
transcript.pyannote[134].start 516.77721875
transcript.pyannote[134].end 529.29846875
transcript.pyannote[135].speaker SPEAKER_04
transcript.pyannote[135].start 519.17346875
transcript.pyannote[135].end 519.54471875
transcript.pyannote[136].speaker SPEAKER_03
transcript.pyannote[136].start 527.86409375
transcript.pyannote[136].end 538.86659375
transcript.pyannote[137].speaker SPEAKER_02
transcript.pyannote[137].start 531.35721875
transcript.pyannote[137].end 532.18409375
transcript.pyannote[138].speaker SPEAKER_02
transcript.pyannote[138].start 533.55096875
transcript.pyannote[138].end 533.87159375
transcript.pyannote[139].speaker SPEAKER_02
transcript.pyannote[139].start 535.05284375
transcript.pyannote[139].end 535.37346875
transcript.pyannote[140].speaker SPEAKER_02
transcript.pyannote[140].start 537.04409375
transcript.pyannote[140].end 537.17909375
transcript.pyannote[141].speaker SPEAKER_02
transcript.pyannote[141].start 538.25909375
transcript.pyannote[141].end 602.40096875
transcript.pyannote[142].speaker SPEAKER_03
transcript.pyannote[142].start 541.29659375
transcript.pyannote[142].end 541.60034375
transcript.pyannote[143].speaker SPEAKER_04
transcript.pyannote[143].start 601.99596875
transcript.pyannote[143].end 605.99534375
transcript.pyannote[144].speaker SPEAKER_02
transcript.pyannote[144].start 604.96596875
transcript.pyannote[144].end 617.47034375
transcript.pyannote[145].speaker SPEAKER_04
transcript.pyannote[145].start 606.56909375
transcript.pyannote[145].end 608.12159375
transcript.pyannote[146].speaker SPEAKER_04
transcript.pyannote[146].start 615.58034375
transcript.pyannote[146].end 616.57596875
transcript.pyannote[147].speaker SPEAKER_04
transcript.pyannote[147].start 616.67721875
transcript.pyannote[147].end 618.38159375
transcript.pyannote[148].speaker SPEAKER_02
transcript.pyannote[148].start 618.28034375
transcript.pyannote[148].end 625.73909375
transcript.pyannote[149].speaker SPEAKER_04
transcript.pyannote[149].start 619.39409375
transcript.pyannote[149].end 620.69346875
transcript.pyannote[150].speaker SPEAKER_04
transcript.pyannote[150].start 622.21221875
transcript.pyannote[150].end 630.37971875
transcript.pyannote[151].speaker SPEAKER_00
transcript.pyannote[151].start 625.73909375
transcript.pyannote[151].end 627.17346875
transcript.pyannote[152].speaker SPEAKER_03
transcript.pyannote[152].start 627.17346875
transcript.pyannote[152].end 627.24096875
transcript.pyannote[153].speaker SPEAKER_02
transcript.pyannote[153].start 627.24096875
transcript.pyannote[153].end 627.30846875
transcript.pyannote[154].speaker SPEAKER_00
transcript.pyannote[154].start 627.30846875
transcript.pyannote[154].end 627.39284375
transcript.pyannote[155].speaker SPEAKER_00
transcript.pyannote[155].start 629.08034375
transcript.pyannote[155].end 629.51909375
transcript.whisperx[0].start 4.275
transcript.whisperx[0].end 6.736
transcript.whisperx[0].text 謝謝主席 麻煩邱部長今天有幾個議題跟您討論但是我還是要先跟您談討就是老師拿分數當武器逼迫學生交出血液這件事情那因為訊息一直進來昨天我看到有一位受害者學生姓簡他出來說他忍耐了四年
transcript.whisperx[1].start 28.446
transcript.whisperx[1].end 30.707
transcript.whisperx[1].text 那跟同一篇報導說市政政見行為已經進行了7年所以我認為是這個學校在包庇教育部在裝睡那衛福部讓你選一個是裝聾還是裝傻你講一下這麼久了
transcript.whisperx[2].start 47.861
transcript.whisperx[2].end 49.783
transcript.whisperx[2].text 這不只是倫理問題他涉及醫療法這個涉及醫療法還有不只倫理問題醫療法跟人體研究法
transcript.whisperx[3].start 59.239
transcript.whisperx[3].end 64.202
transcript.whisperx[3].text 是我們是法的主管機關然後這個部分從研究的一個督導考核以及調查其實是世衛主管機關但是有涉及醫療法部林次長他又對接受媒體採訪的時候他有說就是監察院在調查那教育部等等也是在跟學校在調查然後等這個之後
transcript.whisperx[4].start 83.313
transcript.whisperx[4].end 88.102
transcript.whisperx[4].text 衛福部再來做一次處理但是教育部已經完成了他有行政處罰都已經裁定了我就不再多談那請問衛福部現在要處理了嗎
transcript.whisperx[5].start 94.833
transcript.whisperx[5].end 112.044
transcript.whisperx[5].text 是的我想教育部以及像地檢署也做資料調查所以這個部分我們可以期盼能夠調查得更清楚那衛福部現在要做什麼我們還是要堅持學生的人權以及學生的受教權的傷害絕對不能受到傷害所以如果以這樣的事件來講我們當然整體都要來檢討整個機制是不是能夠更加的落實所以我們第一個我們會把
transcript.whisperx[6].start 123.012
transcript.whisperx[6].end 131.541
transcript.whisperx[6].text 針對受害的學生我們昨天也開過相關的會議準備要來保護他的身心健康你要積極在做這件事對 身心健康我們會提供對 我意思就是說先最急的是趕快照顧這些受害的家屬以及他們的受教權還有他們的家庭因為這樣的衝刺
transcript.whisperx[7].start 142.113
transcript.whisperx[7].end 144.594
transcript.whisperx[7].text 然後我們會去跟相關的機關來檢討整個是不是能夠在連結方面更加的落實因為那個市長在這裡但是那個16號之後醫師是副市長劉副市長他在回答受訪時而講他當時認為研究中的抽血不是醫療行為也不是醫療輔助行為
transcript.whisperx[8].start 161.644
transcript.whisperx[8].end 174.156
transcript.whisperx[8].text 但是因為他有提到說因為有關受試者的保護他覺得執行這個還是要醫護人員或學校的醫護人員或是醫檢室來執行部長我想問你同意嗎研究中的抽血不是醫療行為或不是醫療輔助行為您同意這個說法嗎
transcript.whisperx[9].start 175.576
transcript.whisperx[9].end 202.474
transcript.whisperx[9].text 我想我們一切都要按照醫師法規你同不同意這個說法他說出來了副司長說出來了所以我就從國衛院喔他有關這個倫理委員會的審查紀錄中找到了一個我隨機去找了一個需要抽血的試驗那國衛院的這個倫理委員會有講到說抽血就是屬於醫療行為醫療輔助行為必須由具有執照的醫護人員來執行而且需要在醫療場所那即便是研究案也不例外所以我想請問部長是醫事師副司長的說法錯了
transcript.whisperx[10].start 205.916
transcript.whisperx[10].end 217.042
transcript.whisperx[10].text 還是國務院說法有誤呢?我想在醫療醫療法這個部分當然是很清楚他抽選是不是醫療行為或醫療輔助行為?因為這個部分不是在醫療及格的執行所以我們要了解一下醫療行為還是醫療輔助行為?他說都不是
transcript.whisperx[11].start 227.108
transcript.whisperx[11].end 246.482
transcript.whisperx[11].text 我覺得這件事情要拆開兩個層面來講因為今天是研究案裡面他我覺得從頭到尾這件事情最大的問題會在IRB到底通過了什麼這個學校到底那個執行的PA到底做了什麼這問題的癥結在這邊這是第一件事第二件事情我們家副市長講的是最好的照顧會是什麼
transcript.whisperx[12].start 249.444
transcript.whisperx[12].end 272.135
transcript.whisperx[12].text 我覺得這兩塊是不一樣的最好的照顧在Pollocall裡面最好是醫事人員的這件事情可是研究案裡面在這個案子我們才會覺得剛剛委員垂詢說很像這邊我們衛福部要做什麼其實是每一個事業目的主管機關到底在他們所委託的兩位都是醫師
transcript.whisperx[13].start 273.255
transcript.whisperx[13].end 290.474
transcript.whisperx[13].text 因為這個抽血有一點雖然說不是傷害但是這個侵入性的一個做法啦所以我希望衛婦是不是以後對於相關的這個研究案要設有這個查核跟檢舉機制可以嗎這我們會督導各個事業目的主管機關去做把那個標準拉一致
transcript.whisperx[14].start 290.794
transcript.whisperx[14].end 319.136
transcript.whisperx[14].text 因為現在審查出去的東西每一個事業目的主管機關都有委託審查會照價值還嚴重喔好好就是說請你們繼續就是要有一些監察跟後來的集合制度好謝謝 部長那個衛福部推動三班互併筆啦我知道你最怕這幾位啦月底他首度撥付了獎勵金你知道他總共撥付了多少錢嗎到現在是5.96億已經到好我的好謝謝那既然放了獎勵金表示有改善喔
transcript.whisperx[15].start 319.936
transcript.whisperx[15].end 333.261
transcript.whisperx[15].text 是不是?部長這樣有改善嗎?你錢都搬下去了,有沒有改善?我們這個三半負分比的獎勵金花下去以後也要求他要按照KPI來做整個用在護理醫生的狀況我這幾天上網去查,結果發現不管是健保署的網站或是照護師的網站上都查不到今年上半年的三半負分比資料現在都77萬了,那為什麼資料還沒有上線呢?
transcript.whisperx[16].start 348.126
transcript.whisperx[16].end 361.175
transcript.whisperx[16].text 怕規避監督嗎 沒有資料耶沒有 我們廠長在這邊也跟大家報告過我們整個醫學中心已經到達三百戶病予合乎的已經六成了就是上網 你上網沒有資料 以前有 現在斷掉了市長報告一下
transcript.whisperx[17].start 364.777
transcript.whisperx[17].end 383.831
transcript.whisperx[17].text 我們目前的資料是由醫院做填寶我知道醫院 但是你們要催促現在目前健保署的BPM是公告到12月沒有錯但是一到近年啦 已經半年啦 你沒有資料就是沒有資料好嗎沒有資料就是沒有資料最近就漏出來
transcript.whisperx[18].start 386.593
transcript.whisperx[18].end 389.315
transcript.whisperx[18].text 那部長您本身是資歷豐厚的醫師我想請問部長如果現在要你去值班OK嗎?只要人民健康需要我上山下海都可以你可以值班喔那我請問昭偉昭偉您現在可以去值班嗎?職業班嗎?昭偉可能常常在值班
transcript.whisperx[19].start 407.943
transcript.whisperx[19].end 428.569
transcript.whisperx[19].text 還是有時候守第一線不過體力是有差但是你看這張圖因為明年8月要進來兒科這個是2月26日的報導對外招聘幾乎乏人問津某些中南部的醫學中心55到60歲的主治醫師甚至必須在醫院睡覺值班就很類似能力當然不是做醫師但是他的行為必須像住院醫師一樣的來處理
transcript.whisperx[20].start 432.23
transcript.whisperx[20].end 448.606
transcript.whisperx[20].text 那現在就很多組織醫師可能去招不到人嘛斷崖嘛就是說整個這個是人力斷崖那很多組織醫師去開業或是說林聽醫師覺得說少子化他覺得未來就是夕陽工業他就沒有投入這個領域嘛那健保我知道之前健保署也會編列預算想要調高這個極重難科別的支付
transcript.whisperx[21].start 451.909
transcript.whisperx[21].end 467.367
transcript.whisperx[21].text 那144也有在監測專科醫師的人數那我可不可以請報告一下就是健保署這邊我想知道這個策略有沒有成功呢你調高致富標準有沒有增加那144的監測指標是什麼有沒有如所欲起
transcript.whisperx[22].start 467.927
transcript.whisperx[22].end 486.81
transcript.whisperx[22].text 我先跟委員做報告 再請兩位署長跟市長報告一下第一個就是說我們從健保署當然加成他的給護不管是在兒科的診察會 譬如說我們加成3%那先增加一個他給醫院有一定的力量嘛 量能嘛那在醫事室方面也用兒童的一個照護的一個計畫
transcript.whisperx[23].start 487.691
transcript.whisperx[23].end 501.045
transcript.whisperx[23].text 你預期什麼時候會看到效果?其實讓這樣的我們會看到其實很多醫院都針對集中男患症真的有加薪啦那自己加薪以後是不是外界的環境這個牽涉到比較複雜我們當然有在督導因為沒有兒科醫師就不得了了嘛對當然我們今年的領證人數還到達123人是每年的榮爾是300人
transcript.whisperx[24].start 510.094
transcript.whisperx[24].end 518.021
transcript.whisperx[24].text 那沒有心血進來啊 人家都七歲都還要值班啊我們當然一定要督導整個進來的心血署長你有沒有資料 你這樣發有沒有你monitor你在監測 還是司長你在監測有沒有進步這幾個補助的科有沒有進步 有沒有進步就簡單回答一下跟委員報告 確實這個兒科的困境現在是開業的比較多 留在醫院的比較少
transcript.whisperx[25].start 535.257
transcript.whisperx[25].end 539.299
transcript.whisperx[25].text 所以我們現在努力的目標是如何讓兒科醫師留在醫院請你繼續往這個方向去走好嗎那部長我還在請教你醫師加班費一加班降低所得稅這很多人期待但是他們覺得有可能是因為看得到吃不到為什麼呢因為醫師大家都認為他是責任制所以對加班的這個定義是模糊的
transcript.whisperx[26].start 554.724
transcript.whisperx[26].end 558.026
transcript.whisperx[26].text 那譬如外科醫師手術隨時後他去寫報告那算不算在工作通訊軟體這麼發達那醫師在回覆這個護理站的訊息或家屬訊息算不算PGY算不算等等等等那財政部今天是來謝次長我有看到這個您一邊上來我一邊談我有看到
transcript.whisperx[27].start 572.835
transcript.whisperx[27].end 598.55
transcript.whisperx[27].text 複稅署在新聞上回應說相關法規需要由主管機關法定就是說法定來訂定延長工作時間及規定的標準也要為服務用函式的方式去通案處理或是憲保署要修法在全民健保法醫療服務機構及管理特別局管理辦法才能夠進行跨部會的討論我希望這個財政部是不是可以更積極努力就是兩個跨部門來處理是不是盡可能如果你們要做這件事盡可能讓明年報稅的時候這個時間讓醫師就可以去試用
transcript.whisperx[28].start 602.393
transcript.whisperx[28].end 623.331
transcript.whisperx[28].text 為了留住醫院的人力 真的我覺得這個是需要來努力的做這是你們提出來的方法 試試看嘛那另外就是說比較困難科別 譬如說你們可以借清楚比如小兒科 剛剛我提到小兒科可不可以適度的拉高那個上限就是這個免稅 加班免稅的上限我們都可以來研議好 謝謝啦 您還沒有站起來我只好先離開了因為今天有安安演習謝謝主席 謝謝兩位所長