繼續教育課程

2019學術討論會

$7,000
課程分享
學習人數
19
收藏人數
1
章節數目
42
課程時長
17h 16m 18s
下架日:無
購課觀看期限與下架日相同
$7,000
課程公告

本課程為台灣急診醫學會2019年學術討論會之錄製內容,購買並完成觀看7個以上單元課程且觀看實數大於10小時,可得甲類35學分,已於活動當日參與課程者可輸入折扣碼後以優惠價購買不可取得學分

課程簡介
Plenary lecture I

Effective Implementation of CBME in Residency Training - Challenges and Strategies 
主講人:Eric S. Holmboe, MD, MACP FRCP FAoME(Accreditation Council for Graduate Medical Education)
簡介:CONTEXT Competency-based medical education (CBME) has emerged as a core strategy to educate and assess the next generation of physicians. Advantages of CBME include a focus on outcomes and learner achievement; requirements for multifaceted assessment that embraces formative and summative approaches; support of flexible, time-independent trajectory through the curriculum; and increased accountability to stakeholders with a shared set of expectations; and a common language for education, assessment and regulation. Despite the advantages of CBME, numerous concerns and challenges to implementation of CBME frameworks have been described, including; increased administrative requirements, need for more faculty development, lack of models for flexible curricula, and inconsistencies in terms and definitions.  Additionally, concerns have been raised about reductionist approaches to assessment in CBME, lack of good assessments for some competencies, and whether CBME frameworks include domains of current importance. 
METHODS Expressed concerns and challenges are divided into two primary categories: 1) those related to practical, administrative and logistical challenges in implementing CBME frameworks, and 2) those that have more conceptual and/or theoretical bases. This presentation will review the early experience with CBME implementation globally and provide suggestions from implementation science to facilitate the adoption of a CBME approach.
OBJECTIVES
●    Discuss current gaps between healthcare system needs and medical education.
●    Review early research on CBME implementation efforts, using a core components framework.
●    Discuss strategies from implementation science to facilitate adoption of CBME approaches.

Emergency Toxicology- Optimizing the Chain of Collaboration and Care 
主講人:Bruno Mégarbane, MD, PhD(Department of Medical and Toxicological Critical Care, Lariboisière Hospital, Paris-Diderot University)
簡介:Poisonings represent one of the first causes of admission to the emergency department. Due to the significant morbidities and mortality resulting from poisonings, patient transfer to the ICU may become mandatory. Poisoning should be considered as severe and require ICU admission for: i- onset of life-threatening symptoms including loss in consciousness, respiratory, and circulatory failure; ii- close monitoring in relation to marked drug exposure; iii- enhanced individual vulnerability. Toxicity could result either from the direct effects of the drug or from non-specific complications. Absence of severe symptoms on admission does not necessarily mean that the poisoning is not severe. The risk assessment should take into account the dose, the formulation, the co-ingestions, the delay in management since exposure, patient vulnerability and potential delayed toxicity. The poison control centers contribute to inform and guide the specific management of drug exposures. For decision at the bedside, readily available prognosticators are mandatory. Prognosticators including clinical, biological, ECG, and analytical parameters are drug-specific. During the last thirty years, they have been determined for antidepressants, acetaminophen, aspirin, chloroquine, colchicine, paraquat, corrosives organophosphates and recently for cardiotoxicants. In contrast, general (such as SAPSII and SOFA) and specific poisoning scores (such as Poisoning Severity Score) are interesting for retrospective stratification but of limited usefulness for decision at the bedside. This lecture will present the history of collaboration between the partners involved in the management of poisonings in France including the poison control centre, the pre-hospital medical services, the emergency department, the toxicological ICU and the toxicology laboratory.

From Mission to Action- Improving Cardiac Arrest Survival Rates
主講人:Michael R Sayre, MD(University of Washington)
簡介:Emergency physicians share the mission to save lives from sudden, unexpected declines in health. A sudden cardiac arrest presents a major challenge as the patient may survive if the appropriate treatment is provided quickly and effectively. 
You can lead a high performing resuscitation team. A high performing team practices their individual skills until they achieve mastery. The team then practices together to ensure that performance is optimal. 
Measuring individual and team performance during practice and then during actual resuscitations is essential. The Resuscitation Academy has a mantra: Measure and Improve. Your teams can Measure and Improve. 
Survival from sudden cardiac arrest is possible and is more likely to happen with great teamwork.

Plenary lecture Ⅱ

Smart EMS; Health Information and AI
主講人:Kang Hyun Lee(Yonsei University Wonju College of Medicine, Wonju, South Korea)
簡介:
The use of information and communication technologies (ICT) are important practice in daily practice of Emergency Medical Service (EMS) system. It is generally assumed that the use of new technologies improves the quality of EMS. With development of ICT, methods of the telecommunication have been invented for checking patients' vital signs and ECG during their transport to the hospital, via EMS system. EMTs are accustomed to On-line medical direction (OLMD) during transport with enhanced IT. We developed the real time telemetry system (RTS) by which the patient’s data is transmitted from ambulance to a hospital in real-time in Korea. I would like to present the experience of building the RTS system and the application of the new technology to the emergency medical system. We expected to enhance a use of medical direction and quality of emergency treatment at scene with the new system to RTS monitoring. 
Also, thanks to artificial intelligence (AI) and machine learning, diagnostic tools can be trained to read radiologic scans. AI algorithms and machine learning have recently made huge advances in automatically diagnosing diseases and predicting the disease, making diagnostics cheaper and more accessible. AI can assess the risk of sudden cardiac death or other heart diseases based on electrocardiograms and cardiac images. More advanced AI diagnostics are coming soon. 
I will review what trends and technologies will have an impact on the future of emergency medical services system. The use of new technologies in ICT and AI are improving the quality of EMS system.

Using Artificial Intelligence to Understand and Improve Doctors' Decisions
主講人:Ziad Obermeyer, MD(UC Berkeley)
簡介:Low-value health care—care that provides little health benefit relative to its cost—is a central concern for policymakers.Identifying exactly which care is likely to be of low-value ex ante, however, has proven challenging. Here we apply machine learning tools to study an iconic decision, widely thought to epitomize low-value care: advanced testing for heart attack (acute coronary syndromes) in the emergency setting. By comparing doctors' decisions to individualized, prospective risk estimates, we show that mis-prediction of risk is a major driver of low-value care, in two ways. First, we find substantial over-testing: patients with very low model-predicted risk, whom doctors nonetheless decide to test. These tests are low yield, in that few patients go on to benefit from interventions to treat heart attack in their wake. Second, we also find evidence of a second kind of low-value care, under-testing: large numbers of patients at high model-predicted risk, whom doctors choose not to test. We find serious complications (or death), consistent with untreated heart attack, at remarkably high rates in highrisk patients. These results suggest that both under- and over-testing are prevalent, and that targeting misprediction is an important but understudied policy priority.

Using Clinical Information to Improve Emergency Department Care: Successes, Constraints and Opportunities
主講人:Sally McCarthy MBBS FACEM MBA(University of New South Wales Sydney)
簡介:In theory, rapid improvements in technology, information availability and computational power should enable us to provide efficient, safer and more tailored emergency care around the clock. In practice, the digital transformation of EDs and the capacity to use real time data to improve the quality of ED care and staff and patient experience has been slow.  Constraints and opportunities for the use of health information and communication technology in enhancing emergency care will be presented.

第 3 章:台灣災難醫療20年:過去現在與未來

921震災20周年回顧
主講人:石富元(台大醫院)

資訊系統於災難醫療隊應變管理中的演進與未來發展
主講人:林鍵皓(台大醫院)
簡介:隨著科技的進步,利用資訊系統來管理醫療機構並增進其運作效能,已經是現今醫療體系中習以為常的一項方法。然而災難事件的現場,過往受限於有限的資源,包含通訊、電力等,資訊系統在現場醫療應變的應用,發展得相當緩慢;不可否認的,隨著手持式裝置的普及,網路系統的微型化,利用資訊系統來進行現場醫療應變管理,如災難醫療隊的運作,是個必要且無法抗拒的方向。國家級災難醫療隊北區執行中心,自西元2008年開始,開始發展災難醫療隊資訊系統(MEDical Assistance and Information Dashboard, MED-AID),利用流程分析,演習驗證,使用者回饋的機制,將資訊系統逐步擴充、滲透入災難醫療隊的應變管理中,建構出一套災難醫療隊資訊系統的核心運作架構,未來可以做為不同應變單位開發災難醫療隊資訊系統的重要參考。


第 4 章:改變行醫模式的急診醫學新知III

人工智慧 vs. 真實智慧,急診醫師如何面對?
主講人:蔡居霖(台大醫院)
簡介:The aim of this talk is to provide an introduction to various aspects of artificial intelligence (AI) in emergency medicine. The first part of this talk will review the history of AI, including how AI was developed and what sort of work has been done in the past to assist clinical practice in general. A brief introduction to AI analytics, including machine learning, artificial neural network will be included. Part two will include discussions on how AI reemerges in the era of big data with the proliferation of electronic health record. This part will also showcase the different applications of AI that has been done recently, particularly in emergency medicine, including mortality prediction in sepsis, and emergency department operations. Finally, the pros and cons of AI vs. human intelligence will be discussed.

酸了啦,補個幾支Jusomine吧!
主講人:哈多吉(輔大附醫)
簡介:Lactic acidosis causes a decrease in serum bicarbonate concentration. Lactate is a metabolizable organic anion. That, when oxidized, will generate bicarbonate. The role of exogenous bicarbonate therapy in patients with lactic acidosis is controversial. Most of the experts believe that it is appropriate to use bicarbonate in acutely ill patients in profound lactic acidosis and acidemia (arterial pH less than 7.1). Such severe acidemia may produce hemodynamic instability as a result of reduced left ventricular contractility, and impaired responsiveness to catecholamine. In my opinion, bicarbonate therapy should be initiated when acidosis has generated severe acidemia (ie, pH<7.2). In the BICARICU study, patients with less severe acidemia (eg, pH 7.1 to 7.2) and severe acute kidney injury, bicarbonate therapy can potentially prevent the need for dialysis and may improve survival. And, the goal is to raise the pH above 7.3. Rapid infusions of sodium bicarbonate may increase the partial pressure of carbon dioxide (PCO2), accelerate the production of lactate, lower the ionized calcium, expand the extracellular space, and raise the serum sodium concentration. My talk will start from a case with HHS and sepsis from liver abscess. He also take Metformin for the sugar control. On the way to the CT scan with the enhancement, we will discuss more about the safety and indications for using sodium bicarbonate in ER.

最適合做輸液反應預測的方式?
主講人:鄭凱文(大林慈濟醫院)
簡介:Fluid resuscitation is a cornerstone for treatment of hemodynamically unstable patient. The rationale of fluid resuscitation are augmentation of cardiac output and improvement of tissue perfusion ultimately. However, merely 50% hemodynamically unstable patient would be fluid responsiveness, and over-resuscitation could be harmful or evening killing the patient softly.
There are several ways to predict fluid responsiveness in a hemodynamically unstable patient, and these methods would be discussed In this session. It’s time to change our ways to monitoring fluid responsiveness in the critically ill, from static to dynamic methods.

Af + PSVT有什麼新的治療?
主講人:吳彥鴻(高醫附醫)
簡介:根據文獻介紹關於新發生的心房顫動及陣發性上心室頻脈的過往治療準則流程及是否有新的療法以及在急診室應用的討論。


第 5 章:面對醫療爭議或醫療暴力事件,如何和媒體打交道?

面對醫療爭議或醫療暴力事件,如何和媒體打交道?
主講人:何啟聖副總經理(前TVBS新聞主播、現任1111人力銀行副總經理)
簡介:身為急診醫師,你知道醫療爭議或暴力事件披露後,媒體有興趣的問題包括哪些?醫院和醫師的回應該如何準備?面對媒體的詢問,發言人選、眼神、手勢、語調、穿著、內容長短等,有哪些建議?有哪些是絕不能碰的陷阱?電子媒體和平面媒體有沒有差別?進入訴訟中的案件有沒有不同?新聞稿該如何撰寫?有沒有教戰手冊?有哪些地雷?專業主播心目中,有哪些超成功、和超失敗的案例分享。
對於上述林林種種的問題,你有沒有很好的腹案?甚至你可能徹底排斥和媒體打交道!請你今年的年會一定要來參與這個課程,讓資深媒體人來和大家分享最專業的「急診公關學」!


第 6 章:智慧醫療促進病人安全

急診辨識電子床頭卡
主講人:簡定國(淡水馬偕醫院)
簡介:智慧醫療科技的進步,對病人安全的維護和促進,有許多的成效。
急診辨識電子床頭卡,可以即時更新病患的資料,避免因病患轉床或是做檢查移動後,造成病人床位改變及辨識的錯誤。智慧醫療之敗血症處置,可以提醒醫師對病人的處置是否完善和注意時效,給予病人即時的醫療。智慧排檢與ACLS即時記錄,可以減少病人等待檢查的排程,減少醫護花在聯絡的時間精力;在ACLS部分可以達到即時記錄和提醒,促進標準化ACLS的執行。這些都是讓智慧醫療可以為醫護所用,除了減輕醫護的負擔,避免出錯,同時也可讓病人安全得到多方面的保障。

智慧醫療之敗血症處置
主講人:鍾睿元(國泰醫院)
簡介:敗血症為急診常見的急症,且致死率高。根據世界衛生組織(WHO)統計,全世界每年有約3000萬人得到敗血症,而其中應有將近600萬人死於敗血症,死亡率約20%。而根據我國資料統計顯示,敗血症的發生率為317~560人/十萬人,估計死亡率則高達18~33%。
面對日新月異,複雜繁瑣的敗血症定義及治療方式,加上急診無時無刻人山人海,病人壅塞的情況,我們希望能藉由資訊系統的輔助,幫助醫護人員在敗血症的治療達到以下三點:一、在繁忙的急診尖峰時刻,提醒醫師護理人員病人敗血症的嚴重情況。二、標準化敗血症的治療處理方式,讓大家在忙碌中不會遺漏任何能夠幫助病人的治療項目。三、改善敗血症病人的治療品質,希望能進一步降低敗血症病人的死亡率、住院天數以及、醫療花費。

應用即時記錄輔助系統於ACLS教學
主講人:徐毓嶸(中國附醫)
簡介:高級心臟救命術(Advanced Cardiovascular Life Support,ACLS)是醫護人員執行急救復甦時最重要的指引,急救團隊能否適當的運用課程所學的知識與技能是復甦成功與否的重要關鍵。醫院定期辦理ACLS課程以確保醫護人員急救知識與技術的更新,然而目前的訓練模式存在三大問題:(1)即時性:無法即時記錄學員的急救程序、(2)精確性:容易遺漏學員錯誤或細微步驟,以致教師無法針對個人提供完整回饋、(3)成效性:學員個別總結式考評無法統合分析常犯錯誤並進行課程優化。此急救輔助系統的即時記錄功能,可以記錄受訓學員在綜合演練時的處置,由系統的品管功能分析學員對ACLS 指引的遵從性,並藉由分析得知易犯缺失於課程中強調其重要性並確認學員的理解。透過持續改善與再教育的循環,不斷增加學員急救時ACLS指引之遵從性。


第 7 章:偏遠地區與離島之轉送安全

轉診安全之過去、現在與未來展望
主講人:蔡昌宏(部立苗栗醫院)

偏遠地區與離島之院際間轉送歷史演進
主講人:鄭宏熙(台東馬偕醫院)

黑客松視訊醫療導入之美麗與哀愁
主講人:王仲毅(
台東馬偕醫院)

澎湖之院際間轉送實務經驗分享
主講人:蔡文祥(部立澎湖醫院)

蘭嶼之院際間轉送實務經驗分享
主講人:鄭麗妹主任(台東縣蘭嶼鄉衛生所)

綠島之院際間轉送實務經驗分享
主講人:陳姷頵(台東縣綠島鄉衛生所)

簡介:偏遠地區與離島之病人轉送,常常受到轉送距離、轉送人員、轉送交通工具、以及天候等因素影響,讓院際間的急重症病人轉送充滿了不確定的風險。2018年2月蘭嶼衛生所啟動了空中轉診,卻發生了黑鷹直升機墜海的意外事件,喪失6條人命的悲痛引起舉國矚目,更迫切敦促主管機關重新檢視偏遠地區及離島之醫療需求及轉送安全議題。藉由了解偏遠地區及離島之轉送歷史,以及現行醫療需求及轉送困境,我們嘗試從臨床實務來切入議題,並探討遠距視訊醫療的導入可行性及實用性,期望醫療資源缺乏地區之急重症病人轉送安全能獲得保障。

第 8 章:二代公共場所早期電擊政策論壇PAD 2.0

我國公共場所AED政策的歷史與成果
主講人:馬惠明(台大醫院雲林分院)

AED佈建策略探討
主講人:林皓陽(台大醫院雲林分院)

教育面議題與探討
主講人:謝明儒(台大醫院)

系統建置議題探討
主講人:方品惠(成大醫院)

簡介:為了完備我國的緊急醫療救護體系,台灣急診醫學會在衛生福利部的指導下,2011年時跨領域研究小組進行「民眾CPR與早期電擊推動之評估計劃」,分別依照法規面、教育面及系統建置面打造出我國的公共場所民眾心肺復甦與早期電擊的政策,  將社區生命之鏈進一步向前推進。如何提升民眾AED啟動率是下一階段公眾電及計畫優化的重要目標。未來計畫目標應朝向優化現有系統、加入空間及時間因素達到智慧佈署、簡化民眾教育並提升公眾電擊使用率,另結合行動裝置及現有資料庫達成群眾派遣之社區急救。本論壇整合專家學者之建議,針對下一代公眾電擊之場所更新、登錄管理以及教育三個面向做出政策建議。

第 9 章:台灣急診電子病歷使用之現況、困難及展望

台大醫院急診資訊系統的現況與展望
主講人:呂宗謙(台大醫院)
簡介:台大醫院自從2004年啟動新醫院資訊系統的轉型評估,2006年依序啟動門診系統、住院系統,至2008年啟動急診資訊系統,至今已經走過了15年。本演講將介紹本院資訊系統架構的過去與現況,特別著重在急診資訊系統的功能性介紹與呈現,以及目前所面臨的挑戰與未來的發展。

中國醫藥大學附設醫院急診資訊系統的現況與展望
主講人:鄭凱文(中國附醫)
簡介:敗血症為急診常見的急症,且致死率高。根據世界衛生組織(WHO)統計,全世界每年有約3000萬人得到敗血症,而其中應有將近600萬人死於敗血症,死亡率約20%。而根據我國資料統計顯示,敗血症的發生率為317~560人/十萬人,估計死亡率則高達18~33%。
面對日新月異,複雜繁瑣的敗血症定義及治療方式,加上急診無時無刻人山人海,病人壅塞的情況,我們希望能藉由資訊系統的輔助,幫助醫護人員在敗血症的治療達到以下三點:一、在繁忙的急診尖峰時刻,提醒醫師護理人員病人敗血症的嚴重情況。二、標準化敗血症的治療處理方式,讓大家在忙碌中不會遺漏任何能夠幫助病人的治療項目。三、改善敗血症病人的治療品質,希望能進一步降低敗血症病人的死亡率、住院天數以及、醫療花費。

以雲端藥歷及醫院電子病歷進行高齡病人用藥整合
主講人:黃建程(奇美醫院)
簡介:多重用藥及潛在不適當用藥是常見造成老年人藥物不良反應的原因。然而,要整合老年人用藥必須要有完整用藥清單。奇美醫學中心建立一套智慧資訊平台,自動整合雲端藥歷及醫院用藥,篩選出有嚴重多重用藥及潛在不適當用藥的高齡病人給藥師,藥師再以資訊平台回饋給臨床醫師,成功的減少嚴重多重用藥及潛在不適當用藥。

長庚醫院急診資訊系統的現況與展望
主講人:
王豐林(林口長庚醫院)
簡介:長庚急診的定位是成為E化的急診,透由資訊化作業,簡化病患就診流程,整合治療所需之相關資訊,提昇臨床處置效率,改善病患服務及照護品質,同時並以無紙化作業達到綠色環保的目的。
目前已全面資訊化的急診作業,內容涵蓋病患基本資料、檢傷掛號、疾病診斷、病患動態、會診作業、病歷紀錄、護理作業、檢驗及檢查報告及轉診等管理系統。本院同時建置診斷別之標準醫囑及流程照護指引,護理人員線上執行醫囑處置並進行條碼化病人辨識作業,搭配電子簽章制度,病歷及醫囑全部電子輸入,達成零手寫及「病歷無紙化」目的。

第 10 章:急診醫師如何因應病人自主權利法

簡介病主法及對急診之衝擊
主講人:賴昭智(北市聯醫-仁愛院區)
簡介:簡介病主法重要內容與安寧緩和醫療條例之簡單比較,並說明民眾簽屬預立醫療決定的期待與現行法律規定之落差。以病例說明病情告知,啟動預立醫療決定的相關事宜與急診醫師應該注意的情形與因應之道。

第 11 章:普悠瑪火車事件分享

面對大量傷患事件,地區醫院能肩負更多的責任
主講人:彭鈐澤(蘇澳榮總)
簡介:地區醫院因人力、設備規模限制,許多急重症患者需再轉診至後線醫院。然而正因醫療資源不足又承擔緊急醫療網的第一線責任,相較於都市區域,更凸顯急診醫學科醫師之重要性。
台北榮總蘇澳分院為宜蘭縣溪南地區唯一之公立醫院,位處國道5號終點暨蘇花公路改善計畫起點。針對以往曾經發生過的相關災難事件類型,院內訂立有事件處置指揮系統與應變計畫。然而107年10月21日發生於宜蘭縣蘇澳鎮新馬車站之「台鐵6432次普悠瑪自強號出軌事故」即為一完全超出原應變計劃想定之災難事件;醫院與相關地區緊急醫療應變系統將面臨更加嚴峻之挑戰。期待藉由本院的經驗分享,能為地區醫院於大量傷患事件中所肩負的責任帶來更多省思。

普悠瑪事件經驗分享-羅東聖母醫院
主講人:徐守謙(羅東聖母醫院)

2018年普悠瑪火車大量傷患事件-羅東博愛醫院經驗分享
主講人:許智翔(羅東博愛醫院)
簡介:2018年10月21日下午4時50分普悠瑪火車在冬山新馬車站翻覆,造成嚴重人員傷亡,第一時間大量傷患送到宜蘭區各急救責任醫院,位居宜蘭區唯一重度急救責任醫院的羅東博愛醫院,立即動員急診大量傷患機制,在超出急診負荷量的傷患人數情況下,結合現場急診醫療人員—後續支援醫療人力及相關部門協助中,共同搶救受傷病患,藉由分享本次羅東博愛醫院急診大量傷患實戰經驗,讓急診同仁在未來遇到大量傷患事故中,處理治療更有所精益。

第 12 章:智慧急診室

Smart algorithms for the emergency department
主講人:
Ziad Obermeyer, MD(UC Berkeley)
簡介:Much of emergency medicine relies on human judgment: which patients to test, how to interpret complex data like radiology or ECG waveforms, etc. Machine learning methods provide new ways of helping humans make complex decisions in high-stakes clinical scenarios. I will present a few empirical examples that illustrate the ways this can work in practice in emergency departments.

Smart ER
主講人:
Kang Hyun Lee(Yonsei University Wonju College of Medicine, Wonju, South Korea)
簡介:At this time information and communication technologies (ICT) are very fast and well developed. in the era of the 4th industrial revolution, ICT will be necessary in the field of emergency department. So, mobile technologies and their adoption in the healthcare is a rapidly growing trend. ICT-based technologies are increasingly being used in the ER. It will enable the doctors and nurses to perform the patient related procedures more quickly and smoothly in the emergency departments. The ED using various advanced ICT-based technologies is called Smart ER. Smart ER is not just software, it is planned as a system that includes a monitor screen to be mounted on the wall, a barcode bracelet for the patients, mobile devices to be used by doctors and nurses. 
The system is designed with web technologies which will run effective on the mobile devices.
Since then, artificial intelligence (AI) has made rapid progress. AI is transforming the world of medicine. Emergency medicine has witnessed increasing interest in the use of AI and machine learning algorithms for numerous applications. AI can help doctors make faster, more accurate diagnoses. It can predict the risk of a disease in time to prevent it. Smart ER is a system that accelerates, regulates and disciplines the diagnosis and treatment process in ED services. In this presentation we are going to get a discussion of the future ED services.

急診病人智慧化資訊系統經驗分享
主講人:
蔡維德(台北馬偕醫院)
簡介:急診室的傳統醫病溝通模式,以面對面直接溝通為主要的方式。所有病人相關資訊的傳遞,都必須透過急診團隊中的一份子來跟病人家屬轉達告知。相對的,病人或家屬有任何就醫相關問題需要諮詢時,也必須要找到的急診團隊同仁直接提問。在急診臨床要進行順暢而且有效的醫病溝通並不是那麼容易。常見的幾種醫病溝通問題狀況包含錯誤的諮詢對象,溝通的時機點不佳,無系統性的通知病人機制。從病人家屬的觀點來看,他們所提出的諮詢需求,都希望能即刻獲得解決回覆,即時的回應能降低病人在急診的無助感與焦慮,是有助於提升急診的就醫經驗與服務品質。從醫護團隊的觀點來看,即時解決病人家屬的諮詢,是重要的,但是需要一個更好的方法來進行,否則上述三個急診常見的溝通狀況,會花費很多人力資源與時間在效果不加的溝通。
急診病人智慧化資訊系統專案計劃的思維是「用科技解決問題」,務實的運用現有的科技,不追求高深的尖端的科技,透過本專案自行開發的急診病人資訊看板,以及全國首創的急診病人行動資訊站 App,從臨床面串聯資訊,提供急診病人資訊流通問題的解決方法。

區塊鍊在緊急醫療的應用
主講人:
李亞鑫執行長(薩摩亞商數金科技有限公司)
簡介:台大醫院自從2004年啟動新醫院資訊系統的轉型評估,2006年依序啟動門診系統、住院系統,至2008年啟動急診資訊系統,至今已經走過了15年。本演講將介紹本院資訊系統架構的過去與現況,特別著重在急診資訊系統的功能性介紹與呈現,以及目前所面臨的挑戰與未來的發展。

第 13 章:緊急醫療資訊共享與人工智慧

從AI立方談急重症醫療-高雄榮總經驗分享
主講人:楊宗龍(台大醫院)
簡介:台大醫院自從2004年啟動新醫院資訊系統的轉型評估,2006年依序啟動門診系統、住院系統,至2008年啟動急診資訊系統,至今已經走過了15年。本演講將介紹本院資訊系統架構的過去與現況,特別著重在急診資訊系統的功能性介紹與呈現,以及目前所面臨的挑戰與未來的發展。

運用醫療資訊人工智慧,協助急救ACLS執行
主講人:賴佩芳(台大醫院)
簡介:台大醫院自從2004年啟動新醫院資訊系統的轉型評估,2006年依序啟動門診系統、住院系統,至2008年啟動急診資訊系統,至今已經走過了15年。本演講將介紹本院資訊系統架構的過去與現況,特別著重在急診資訊系統的功能性介紹與呈現,以及目前所面臨的挑戰與未來的發展。

第 14 章:精準醫學與感染急症

性愛與藥
主講人:顏慕庸(北市聯醫-昆明防治中心)

即時性診斷工具對感染急症與社區防疫的應用與效用
主講人:陳世英(台大醫院)

簡介:雖然感染症自古以來即嚴重的威脅著人類的健康,雖然醫療藥物的進步與公衛環境的改善,某種程度的減輕了以往致命性的感染症對人類的衝擊,然而新的時代中,隨著人類行為與自然環境的改變,卻給這些古老的疾病帶來新的面貌與對病人健康的影響,這包括傳染途徑與臨床表現的改變,在在地增加了第一線醫師診斷與治療上的困難。而面對新時代新面貌的感染症,如何提供精準、即時、個人化的診斷工具,進而提供疫病偵測、疾病診斷、病人照護、住院資源分配、乃至緩解急診壅塞的決策參考,是現代醫學上嶄新的領域,特別在面對可能由諸多不同的致病原所引起的感染症上。
急診醫學會鑒於第一線醫護人員為防治重要感染性疾病與疫情的重要把關者,為加強第一線急診同仁對於疾病新型態與各種即時性診斷工具的認識,進而體現現代醫學對精準醫療的要求,本論壇特別規劃兩場演講「性愛與藥」與「即時性診斷工具對感染急症與社區防疫的應用與效用」,分別讓急診同仁可以認知感染症型態演變對急診醫師所帶來的挑戰,以及如何應用新的科技來因應前述的挑戰。

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