CN103313650A - 急诊处理系统信息面板 - Google Patents
急诊处理系统信息面板 Download PDFInfo
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- CN103313650A CN103313650A CN2011800648165A CN201180064816A CN103313650A CN 103313650 A CN103313650 A CN 103313650A CN 2011800648165 A CN2011800648165 A CN 2011800648165A CN 201180064816 A CN201180064816 A CN 201180064816A CN 103313650 A CN103313650 A CN 103313650A
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Abstract
根据本发明实施例的医疗系统包括:配置为监视病人生理状态和根据生理状态生成传感器数据的至少一个传感器;用户接口设备;可通信地耦合至用户接口设备的处理器,该处理器配置为:通过用户接口设备显示两个或更多可能的输入单元的阵列,每个输入单元包括一类病人或诊断和治疗途径;根据用户在两个或更多可能的输入单元之中的选择接收选定的输入单元;获取传感器数据和处理该传感器数据以生成生理数据;和根据为该选定的输入单元定制的模板,通过用户接口单元显示该生理数据。
Description
相关申请的交叉引用
本申请要求于2010年11月11日提交的序列号为61/412,679的美国临时专利申请、于2010年11月12日提交的序列号为61/413,266的美国临时专利申请和于2011年1月27日提交的序列号为61/436,943的美国临时专利申请的优先权,在此将其全文引用作为参考。
技术领域
本发明的实施例总体上涉及用于辅助急诊处理的工具,更具体地涉及用于临床决策支持和鉴别诊断的系统和方法。
背景技术
在院前和急诊处理的情景中,医疗救护人员通常面临准确地确诊特定病人的困难。即使训练有素的医生在需要依靠有限信息进行瞬间判断的紧急情况下通常也有困难。研发了计算机自动诊断来改进现场和医院病人治疗的准确性、有效性和可靠性。
自动鉴别诊断使用计算机推断算法,例如贝叶斯算法、神经网络或遗传算法。根据维基百科记录:
贝叶斯网络是基于知识的图形表示,其图示了一组变量和它们在疾病和症状之间的概率关系。它们基于条件概率,在出现另一事件的情况下一个事件的概率,例如诊断测试的解释。贝叶斯法则帮助我们借助于一些更现成的信息来计算事件的概率,且它在出现新证据时一致地处理选项。在CDSS【(clinical decision support system,门诊决策支持系统)】的情况下,可以使用贝叶斯网络在给定其症状的情况下计算可能的疾病存在的概率。贝叶斯网络的一些优点包括概率形式的专家知识和结论,当新信息可用和基于可应用于多种模型的无偏概率时进行协助决策。贝叶斯网络的一些缺点包括难以获取用于可能诊断的概率知识和对于给定多种症状的大型复杂系统不实用。针对多种同时症状的贝叶斯计算可能使用户不知所措。在CDSS情景中贝叶斯网络的例子是伊利亚特(Iliad)系统,其使用贝叶斯推理根据给定症状计算可能诊断的后验概率。该系统目前涵盖基于数以千计的检查所见的大约1500种诊断。另一种例子是使用改进形式的贝叶斯逻辑的DXplain系统。该CDSS生成与症状关联的分级诊断列表。
人工神经网络(ANN,Artificial Neural Network)是非基于知识的自适应CDSS,其使用一种形式的人工智能,也称作机器学习,允许该系统从先前经验/实例中进行学习和识别临床信息中的模式。它由称作神经元的节点和以单向方式在神经元之间传送信号的加权连接组成。ANN由三个主要的层组成:输入(数据接收器或检查所见)、输出(传送结果或可能的疾病)和隐藏(处理数据)。使用针对大量数据的已知结果,该系统变得更加有效。ANN的优点包括不再需要给系统编程和提供来自专家的输入。通过对缺失数据进行有据猜测,ANNCDSS可以处理不完整的数据,并且由于其自适应系统学习而在每次使用后得以改进。此外,ANN系统并不需要大型数据库存储具有其相关概率的结果数据。一些缺点是训练处理可能耗费时间,导致用户不能有效地使用系统。ANN系统基于在时间上的统计识别模式推导它们自己的用于加权和组合数据的公式,这可能难以解释并质疑该系统的可靠性。例子包括阑尾炎、背痛、心肌梗塞、精神病急症和皮肤失调的诊断。在一些情况下,ANN对肺栓塞的诊断预测甚至好于医生的预测。此外,基于ANN的应用在ECG(也称作EKG)波形的分析中也已经是有用的。
遗传算法(GA)是于上世纪四十年代在麻省理工学院开发的非基于知识的方法,其基于达尔文的适者生存的进化理论。该算法重新排列以形成优于先前解决方案的不同的重新组合。类似于神经网络,遗传算法根据病人数据推导它们的信息。遗传算法的优点在于这些系统通过迭代处理生成最佳解决方案。适应度函数确定好的解决方案和可以被淘汰的解决方案。缺点在于在决策支持系统涉及的推断中缺乏透明度,使其不受医生的欢迎。使用遗传算法的主要挑战在于定义适应度标准。为了使用遗传算法,必须有很多组成部分,例如多种药物、症状、治疗方法等以便可用于解决问题。已经证明遗传算法在妇科尿失禁的诊断中是有用的。
尽管事实上已经研发了自动鉴别诊断系统和现在已经尝试实施超过35年,这样的系统在用于急诊处理(ACT,acute care treatment)的紧急医疗场景中尚未被接受。这一失败的主要原因是因为实施急诊治疗所处的条件。在那些情况下,例如创伤、心搏停止或呼吸停止的治疗,决策速度是关键的,救护人员必须在病人、生理监视器以及去纤颤器之间分配时间。在这种情况下,自动鉴别诊断(ADD,automated differential diagnosis)工具通常被视为干扰救护处理且是对病人治疗的延迟。假定每分钟可能导致生存率降低10%,例如在心搏停止的情况下,ADD工具被其设计协助的对象所忽略并不奇怪。
已经发现在急诊情况下救护人员不能查看大部分的病人病史,因为通常在院前环境下治疗病人,其中家庭成员通常在受伤时不在现场。
发明内容
本发明的实施例包括一种为救护人员提供以更有效和准确地执行鉴别诊断的工具的系统,其被集成至在急诊情况下救护人员的现有工作流程中。本发明的实施例还可以向救护人员以自动方式提供来自病人的生理数据以及治疗、病历和检查所见的集成观看。
根据本发明实施例的医疗系统包括:配置为监视病人的生理状态和根据该生理状态生成传感器数据的至少一个传感器;用户接口设备;可通信地耦合至用户接口设备的处理器,该处理器配置为:通过用户接口设备显示两个或更多可能的输入单元的阵列,每个输入单元包括一类病人或诊断和处理途径;根据用户在两个或更多可能的输入单元之中的选择接收选定的输入单元;获取传感器数据和处理该传感器数据以生成生理数据;和根据为选定的输入单元定制的模板通过用户接口设备显示该生理数据。
段落【0008】的医疗系统,其中根据一个或多个开关的激活选择选定的输入单元。
段落【0008】至【0009】中任一段落的医疗系统,其中根据对触摸激活屏幕的触摸来选择选定的输入单元。
段落【0008】至【0010】中任一段落的医疗系统,其中该触摸激活屏幕是用户接口屏幕。
段落【0008】至【0011】中任一段落的医疗系统,其中该至少一个传感器是ECG传感器、SpO2传感器、NIR组织灌注传感器、NIR pH传感器、超声波传感器、通气流量传感器、EtCO2传感器、侵入式血压传感器和非侵入式血压传感器中的一个或多个。
段落【0008】至【0012】中任一段落的医疗系统,其中该处理器被进一步配置为接收通过在触摸激活屏幕上使用同一只手同时触摸两点生成的卡尺手势信号,和一旦接收到卡尺手势信号则将测量数据重叠至生理数据上。
段落【0008】至【0013】中任一段落的医疗系统,其中两个或更多可能的输入单元的阵列包括下述的至少之一:呼吸窘迫或呼吸困难诊断和处理途径;精神状态改变的诊断和处理途径;心区不适的诊断和处理途径;创伤的诊断和处理途径;和疼痛或异常神经感知的诊断和处理途径。
段落【0008】至【0014】中任一段落的医疗系统,其中两个或更多可能的输入单元的阵列包括:呼吸窘迫或呼吸困难的诊断和处理途径;精神状态改变的诊断和处理途径;心区不适的诊断和处理途径;创伤的诊断和处理途径;和疼痛或异常神经感知的诊断和处理途径。
段落【0008】至【0015】中任一段落的医疗系统,进一步包括平板计算机。
段落【0008】至【0016】中任一段落的医疗系统,其中该处理器是平板计算机的一部分。
段落【0008】至【0018】中任一段落的医疗系统,其中该用户接口屏幕是平板计算机的一部分。
段落【0008】至【0019】中任一段落的医疗系统,进一步包括去纤颤器。
段落【0008】至【0020】中任一段落的医疗系统,其中用户接口屏幕是去纤颤器的一部分。
段落【0008】至【0021】中任一段落的医疗系统,其中平板计算机包括保护外壳,其中该保护外壳包括第一安装特征,该医疗系统进一步包括第二安装特征,配置为与第一安装特征相互配合。
段落【0008】至【0022】中任一段落的医疗系统,其中该两个或更多可能的输入单元的阵列包括呼吸窘迫或呼吸困难的诊断和处理途径。
段落【0008】至【0023】中任一段落的医疗系统,其中该至少一个传感器配置为监视病人的心音。
段落【0008】至【0024】中任一段落的医疗系统,其中该至少一个传感器配置为监视病人的呼吸音。
段落【0008】至【0025】中任一段落的医疗系统,其中该处理器进一步配置为鉴别哮鸣、爆裂音、罗音和喘鸣呼吸音。
段落【0008】至【0026】中任一段落的医疗系统,其中该至少一个传感器是基于近红外线的传感器。
段落【0008】至【0027】中任一段落的医疗系统,其中该至少一个传感器配置为测量病人组织或血液的pH。
段落【0008】至【0028】中任一段落的医疗系统,其中该至少一个传感器是ECG传感器,和其中该生理数据反映心率变异性。
虽然公开了多个实施例,根据图示和描述本发明说明性实施例的下述详细描述,本发明的其它实施例对于本领域的技术人员来说将变得明晰可见。因此,附图和详细描述将被视为本质上说明性而非限制性的。
附图说明
图1图示根据本发明实施例的门诊决策支持系统。
图2图示根据本发明实施例的用于医疗设备的用户接口。
图3图示根据本发明实施例的选择急诊模式时的图2的用户接口。
图4图示根据本发明实施例的选择呼吸窘迫模式时的图2和图3的用户接口。
图5是描述成人急性呼吸困难的鉴别诊断概况的表格。
图6是描述呼吸困难诊断线索的表格。
图7是列出急性呼吸困难诊断中身体检查所见的表格。
图8A是用于成人呼吸短促的常见治疗规程和鉴别诊断流程图的上部。
图8B是图8A的常见治疗规程和鉴别诊断流程图的继续。
图9图示根据本发明实施例的当由用户选择时可以在用户接口上显示的二氧化碳快照波形。
图10图示根据本发明实施例的带有所显示的测量值的图9的二氧化碳快照波形。
图11图示根据本发明实施例的在去纤颤器设备上入坞的平板计算设备。
图12图示在心搏停止病人中使用的规程。
图13图示示例性的创伤评估规程。
图14图示示例性的快速创伤评估规程。
图15图示示例性的重点身体检查规程。
图16图示示例性的截肢损伤规程。
图17图示示例性的出血控制规程。
图18图示示例性的烧伤规程。
图19图示示例性的触电规程。
图20图示示例性的脊柱固定规程。
图21图示在图20的脊柱固定规程中的附加步骤。
图22图示示例性的多系统创伤规程。
图23图示示例性的近溺水规程。
图24图示示例性的怀孕创伤规程。
图25图示示例性的创伤性心搏停止规程。
虽然本发明可以被修改为各种变型和替代形式,在附图中已经通过例子图示和在下文中详细描述了具体实施例。然而,目的并不是将本发明限制于所描述的具体实施例。相反地,本发明将涵盖落入由权利要求书定义的本发明保护范围之内的全部变型、等同物和替代物。
具体实施方式
图1图示根据本发明实施例的系统的框图。在一种实施例中,组合式去纤颤器/监视器设备,例如由马萨诸塞州切姆斯福德市的卓尔医学产品公司制造的E系列,具有由屏幕显示文本提供其标签的按键。因此,根据用户输入或由去纤颤器或在去纤颤器使用时该去纤颤器与之通信的其它设备进行的分析和决策结果,该文本是实时可配置的,该其它设备例如是计算机平板设备214或者与该计算机平板通信的医疗派遣人员或医疗监督人员维护的远程基站。该计算机平板可以采用iPad(苹果公司,加利福尼亚州库珀蒂诺市)的形式。这种屏幕标签按键可以被称作“软按键”。根据本发明的实施例,如图2所示,在设备打开时将专用软按键初始化标签为“急诊诊断”。一旦检测到急诊诊断按键的按键按压,该去纤颤器将按键的功能和标签改变为图3所示的形式。这五个标签-“呼吸窘迫”或替代地“呼吸困难”、“精神状态改变”、“心区不适”、“创伤”和“疼痛/异常神经感知”-与鉴别诊断相关的传统症状的不同之处在于它们标识病人分类、潜在工作流程以及诊断和处理途径(DTP,diagnosis and treatment pathway),并以救护人员和其他急诊人员在实践中遇到符合这些标准的病人的相对频率列出。
通过按下用于每个DTP的软按键,该去纤颤器随后被配置为潜在地激活某些生理传感器并显示该传感器数据,从而给救护人员提供最优信息,以最优方式显示从而最准确地和有效地诊断和处理该病人。每个DTP可以包括模板,根据其以对于特定DTP的最有用和/或有效的方式显示自其推导的传感器数据、生理和/或测量数据。例如,如果按下“呼吸窘迫”软按键,则在屏幕上的波形和数字生理数据改变成如图4所示。通过CO2快照软按键可以激活所存储的单个CO2呼吸波形的快照。这些快照保持在显示器上以供临床医生参考,用于诊断的自动测量以及用于评估特定治疗的有效性。
心音测量和检测可以被合并在用于S3和S4心音检测的监视设备中,并用于自动地缩小鉴别范围,或者建议救护人员确认与心力衰竭或肺水肿的软件诊断一致。在图8A和8B中图示用于评估心音的流程图。脉搏测氧法和二氧化碳图是非常有用的测量并可以被自动地并入该算法以进行更准确的诊断。用于检测心音的同一传感器也可以用于检测呼吸音和分析它们的品质。可以使用特定的算法来检测哮鸣、爆裂音、罗音或喘鸣,它们分别可能指示特定疾病。
将诸如流量传感器和氧气传感器等传感器包括在相同的实施例中,以便附加的生理测量值,诸如体积Co2、体积O2和肺量测定,其与呼吸困难的诊断和处理相关,可以被包括和显示在呼吸窘迫DTP屏幕上。氧气传感器可以被定位在病人的气道内,其可以协助计算病人的新陈代谢需要。
根据本发明的一些实施例,在去纤颤器212上的显示器是触摸屏。救护人员可以容易地初始化测量,例如通过诸如双击等触摸屏手势在CO2快照波形或肺量快照波形之上。缩放图标可以存在于每个波形框的上部角落,例如CO2快照,以便当触摸缩放按钮时,该特定波形填充去纤颤器的显示。根据本发明的实施例,提供另一测量按钮,当触摸该按钮时显示用于特定波形的全部相关测量值。作为触摸屏的一部分提供手势接口。使用两个手指或者手指和拇指触摸波形中的两点(也可以将其称作“卡尺”测量或手势)将导致测量值被显示和/或重叠至生理数据上,如图10所示。例如,在CO2波形测量激活之后可以在屏幕上列出死腔量、指示COPD的阶段II和III斜率和动脉pCO2的估计值。
根据本发明的实施例,可以配置与决策支持系统的触摸屏部分可通信地耦合的处理器以识别所显示的波信号的波形,和/或识别所显示的图像的边沿,从而提高卡尺触摸手势的准确度。例如,如果用户使用卡尺手势在ECG波显示内的ST正视图上测量或“放大”,则可以配置该决策支持系统以识别用户的手指之一是否刚好点击在该ECG波顶部之下,用户可能希望将ECG波顶部包括在放大或选定视图内。此外,可以配置该决策支持系统以允许分别地使用触摸屏进行放大(缩放)和调整测量点的能力。可以使用轻击/单击和拖拽的方法设置卡尺手势;例如,为了放大所显示波形的特定部分,用户可以按在一点上和拖拽到另一点以指示该卡尺手势的端点。
可以用红色显示或者通过其它机制,例如粗体和/或闪烁,突出显示特定的超出范围的读数。根据本发明的实施例,触摸该突出显示的数值将导致显示器显示与该测量值一致的可能诊断。可以使用计算机平板的图形图像标明该屏幕的特定图形区域。通过将波形、测量值或在显示器上显示的任何其它数据对象拖拽到计算机平板图标上,它可在链接到该去纤颤器的计算机平板上自动地显示。
二氧化碳图有助于哮喘的评估,其中呼气平台中的递增斜率提供支气管痉挛的测量。平台阶段(阶段III)的斜率提供气道阻塞的测量。通过阶段III斜率改变的观察可以监视哮喘加重的b-激动剂支气管扩张疗法的充分性。
如在于2011年7月14日公开的美国专利申请公开文本2011/0172550号中提到的,在此将其全文引用作为参考用于所有目的,可以通过监视器与病人生理测量值一起通过计算机平板输入病历数据。因为鉴别诊断通常涉及病历、病人检查所见以及通过诸如ECG、二氧化碳图和脉搏测氧法等监视的病人生理状态的测量值,将这些数据单元集成到用户接口内,其自动地或半自动地将各种数据单元集成在计算机平板上应用内的单个鉴别诊断屏幕上。该接口可以开始于要求救护人员从常见症状或病人陈述的列表之中选择,例如呼吸困难或呼吸窘迫。例如在图5、6和7的屏幕上的信息(来自《美国家庭医生》(Am Fam Physician)2003;68:1803-10)为救护人员提供了获取信息的一种可能的结构化方法。当在计算机平板上输入病历和身体检查所见时,鉴别诊断页面将逐渐地缩小可能的诊断范围。
在另一实施例中,去纤颤器包含入坞特征,用于通过集成到去纤颤器上的安装特征在固定位置上在去纤颤器的顶部上支撑计算机平板,例如苹果如图11所示。可以使用其它移动计算设备,包括平板计算机,例如和其它触摸屏监视器。可替代地,可以使用低功率、电池供电的触摸屏监视器,例如通过有线或无线USB连接在其与计算设备之间相互传输信息的那些监视器。可以在两个设备(例如医疗设备和移动计算设备)之间无线地提供通信。可以在两个设备之间实现其它可通信的耦合,例如有线的。iPAD可以包括保护外壳和/或防水外壳以保护它免于在院前环境中将可能遇到的典型物理损伤。与这样一个iPad外壳构成整体的安装特征允许将其容易地现场安装在去纤颤器的顶部。在去纤颤器上的安装特征能够铰链接合以允许在不使用时向下铰接至去纤颤器上的保护袋内。该还可以出坞,并在去纤颤器附近使用,而不需要物理连接。还可以设置物理插槽,优选地在该单元的侧面、顶部或背面,允许该利用去纤颤器给它的电池充电。根据本发明的实施例,在保护外壳框架的内部是标准连接器,而在保护外壳框架的外部上是牢固得多的机械和电连接,其可以承受在院前紧急场景中医疗设备经历的各种随意使用。
随后可以在去纤颤器上显示生理数据、病历和检查所见的集成分析结果,这可能以询问进行附加生理测量的形式做出。可以替代地或附加地在平板计算机上显示生理数据、病历和检查所见的集成分析结果。根据本发明的一些实施例,该平板计算机或其它移动计算设备可以与去纤颤器或其它生理评估设备可通信地耦合,例如通过无线连接。如在此使用的,以其最广泛的含义使用术语“可通信地耦合”来指经其可以传送信息的任意耦合。因而,例如可通信地耦合包括通过例如电线的电耦合;通过例如光缆的光耦合;和/或例如通过射频或其它传输介质的无线耦合。“可通信地耦合”还包括例如诸如通过网络的间接耦合或直接耦合。
根据本发明的实施例,用户接口设备被可通信地耦合至处理器,配置该处理器以接收通过用户接口设备输入的数据,以及自一个或多个传感器接收的数据,从而根据这两个数据源执行临床决策支持。该用户接口设备可以包括一个或多个设备,例如触摸屏计算机、平板计算机、移动计算设备、智能手机、音频接收机、音频收发器、视频接收机、视频收发器、摄像机和在用户的眼睛或面罩上投影的“头戴式”显示器。可以将小型监视器安装在眼镜、面罩上,和/或与其它可佩戴通信设备集成,例如耳塞或蓝牙免持手机适配器。用户接口设备可以包括用于传送选项和接收输入的设备组合;例如,音频扬声器可以用于传送可能的DTP,音频接收器可以用于接收指示选择DTP之一的口头命令。可以不使用音频接收机,而是使用视频摄像机来接收手势命令,其将由处理器解释为对可能的DTP之一或输入单元的选择。将免持设备用于用户接口设备可以释放救护人员的双手以执行临床任务,同时依然允许救护人员的非侵入式决策支持和/或鉴别诊断。
图8A和8B图示根据本发明实施例的使用该用户接口设备的鉴别诊断和/或临床支持处理,计算机处理器通过其协助救护人员。例如,如果救护人员从在图3的屏幕上显示的五个DTP之中选择“呼吸窘迫”,则用户接口设备将向救护人员提示输入与图8流程图中的步骤802相关的信息,其自上至下。在步骤802,如果12引线表明S3心音,或者如果呼吸困难符合度分数大于3,则该决策支持系统将协助用户通过急性失代偿性心力衰竭(CHF)决策/诊断处理。
该决策支持系统可以同时考虑自传感器接收的生理数据和自救护人员(例如通过诸如等移动计算设备)接收的信息数据,以协助救护人员自流程图中的一个决策点移动到下一个,同时更新沿路径提供的任何显示或信息。例如,决策支持系统可以向用户指示,根据ECG数据的处理,看起来并不存在S3心音,并询问救护人员确认该评估。该决策支持系统还可以或者替代地请求救护人员输入呼吸困难符合度分数,或者建议一个以便救护人员确认。在步骤802,如果12引线表明没有S3心音,或者如果呼吸困难符合度分数低于3,则该决策支持系统将识别出该救护人员并非在处理CHF情况,因而前进至步骤804,其中该决策支持系统改变其显示和/或输入提示以帮助救护人员确定是否输入哮喘处理途径或COPD处理途径。
再次,该决策支持系统可以包括来自传感器的各种生理数据以及所接收的关于特定病人的各种信息数据,以帮助支持救护人员的决策。例如,如图6所示,如果病人信息(由救护人员输入或者自另一个来源获得的)指示病人是重度烟民,则该决策支持系统将在步骤804识别出COPD诊断更为可能,而如果救护人员向决策支持系统指示病人在经历咳嗽,或者具有哮喘病史,则决策支持系统可以在804识别出哮喘诊断更为可能。除了图6所示的信息决策支持之外或者可替代地,该决策支持系统可以使用生理数据收集检查所见以帮助救护人员确定适当的处理途径。例如,如果呼吸或呼吸音传感器生成数据,当予以处理时指示杵状指、桶状胸或者减量呼吸音,该决策支持系统可以在步骤804识别出COPD处理途径更为合适,而如果呼吸音传感器生成指示奇脉的数据,或者如果肌肉活动传感器指示使用副肌,则决策支持系统可以在步骤804识别出哮喘途径更为适当。
根据本发明的实施例,该决策支持系统可以推荐或建议诊断或处理途径,例如通过指示统计概率(基于例如图6和图7的图形和数据)或相对可能性,并请求救护人员的确认或最终选择。例如,如果在步骤804该决策支持系统接收到哮喘诊断的确认,则该用户接口设备可以改变向救护人员显示的信息,例如通过启动进入哮喘诊断专用的处理规程。在步骤806,该决策支持系统可以建议救护人员将增湿器添加给病人氧气供应设备,和给予2.5毫克沙丁胺醇混合由连接至6-9公升每分钟源的雾化器给予的0.5毫克爱喘乐(溴化异丙阿托品),并指示该剂量可以持续给予,只要心率不高于140。该决策支持系统可以监视心率,在这个例子中,当如果心率达到或接近140时,则给出可视和/或音频指示。
在步骤808,该决策支持系统可以例如通过显示与血氧含量、呼吸率或呼吸量相关的数据或测量值,来帮助救护人员确定该病人是否支气管极度收缩。一旦在步骤808由救护人员确认该病人支气管极度收缩,则决策支持系统可以向救护人员建议以慢速(例如2分钟)静脉注射给予125毫克剂量的甲强龙。在步骤810,该决策支持系统可以帮助救护人员确定病人症状是否已经改善(例如病人的呼吸短促通过如此处理是否已经改善)。例如,该决策支持系统可以显示和/或分析病人的潮气末波形,并表明病人看起来并不对处理产生响应,并请求救护人员确认。如果救护人员确定该决策,则该决策支持系统可以继续通过附加处理选项,例如在图8中所示的那些选项,指导救护人员。这样,在门诊过程中,使用自病人收集或由救护人员输入的生理数据和信息数据,以如果没有该决策支持系统则救护人员将非常不方便或耗费时间的方式,该决策支持系统通过复杂的决策处理指导救护人员。
根据本发明实施例的决策支持可以是也可以不是完全自动化的。可以使用利用贝叶斯网络、神经网络、遗传算法或更简单的基于规则的系统的推断引擎。
在另一实施例中,利用如在美国专利6,055,447中描述的方法,其描述了舌下组织CO2传感器,或者在美国专利5,813,403、6,564,088和6,766,188中描述的方法,其描述了用于通过近红外光谱法(NIRS)测量组织pH的方法和设备,在此将上述专利全文引入作为参考用于所有目的,来测量组织CO2或pH。NIRS技术允许组织PO2、PCO2和pH的同时测量。用于组织pH测量的先前方法的一个缺点是测量值在复苏过程中在一系列测量中执行的给定基线测量上提供极好的相对准确度,但是绝对准确度并不如此好,原因是特定于病人的偏移,例如皮肤色素。由本发明的一些实施例实现的优点之一是不再需要这些测量的绝对准确度,而仅依赖于在复苏过程中偏移和增益稳定。组织CO2和pH在监视创伤DTP中特别有用。在显示器上用于创伤DTP的生理参数可以是下述一个或多个:侵入和非侵入血压、组织CO2和pH、ECG、SpO2趋势和心率变异性风险指数。可以分析ECG以确定在QRS复合体的相邻R波之间的间隔,并使用该间隔计算作为相邻R-R间隔之间运行差值的心率变异性。本领域的技术人员公知,在变异性的突然降低之前通常将先出现几分钟病人血压的急剧下降(创伤性心搏停止)。通过监视心率变异性的趋势,可以预期和防止创伤性心搏停止。
根据本发明的实施例,用于创伤DTP的另一传感器是超声波传感器。根据C.Hernandez et al.,C.A.U.S.E.:心搏停止超声波检查-管理初级非心律失常性心搏停止病人的更好方法,Cardiac arrest ultra-sound exam--A betterapproach to managing patients in primarynon-arrhythmogenic cardiac arrest,《复苏》(Resuscitation)(2007),doi:10.1016/j.resuscitation.2007.06.033,在此将其全文引入作为参考:
C.A.U.S.E.是由作者研发的新方法。该C.A.U.S.E规程解决心搏停止的四个主要原因,且通过使用胸腔的两个超声波检查透视图实现该目的;心脏和心包膜的四腔图和在第二肋间水平上在锁骨中线上两侧对称的肺和胸膜的前内图。使用肋下、胸骨旁或顶胸的窗口实现心脏和心包膜的四腔图。这允许分别地执行检查以根据病人解剖学选择最适当的视图。该作者建议首先开始于肋下视图,因为该视图使医生可以在不中断胸外按压的情况下评估心脏。如果该视图不可能,则可以在复苏团队领导者领导的配合脉搏检查过程中使用顶点或肋骨旁方法。在该规程中使用四腔图,因为它允许在心脏内不同腔室之间容易的比较,便于血容量减少、大量PE和心脏压塞的诊断(图6)。通过查看在锁骨中线(图7)的第二肋间空间上的矢状平面时识别滑动符号和慧尾人工效应的缺少,诊断气胸。对于心脏和肺视图,建议使用2.5-5.0的相位阵列传感器探针。这允许检查者将同一探针用于肺和心脏,如果需要,腹部检查。这种类型的探针由Knudtson在他的研究中使用,除了FAST检查之外,涉及用于识别气胸的超声波,它在检测气胸中产生非常高的准确度,在识别心脏和腹部器官时依然保持有用。该规程以图形格式被最佳地描述。【参见图12】。
救护人员选择该流程图中的单元导致超声波传感器被激活和图像被显示在计算机平板上。可以自计算机平板和/或去纤颤器上的接口请求附加指令。根据本发明的实施例,基于该选择和指令,可以调整超声波设置以提供最优图像。
尽管参考图3讨论了五种诊断和处理途径,可以配置该鉴别诊断/决策支持系统以支持针对其它DTP的决策确定和诊断,并可以配置其显示和支持自图3所示的五种和其它诊断中选择的一个或多个DTP的各种组合。根据本发明的其它实施例,每个用户可以配置该决策支持系统以将定制的DTP用于每个DTP选项;例如用户可以用基于救护人员专用、病人专用、地理专用和/或法规专用的处理规程的一系列新的问题/步骤/读数来改变问题/步骤/读数的缺省序列。这样,根据本发明实施例的决策支持系统操作以涵盖各种DTP的方式指导救护人员的决策和诊断。
例如,如果用户自图3的屏幕中选择创伤DTP选项,则该决策支持系统可以被配置为指导用户以通过类似于图13至25所示的决策和处理途径。随后,将向用户提供一系列的进一步选项,例如“截肢损伤”、“出血控制”、“烧伤”、等等。选择这些进一步选项之一随后将导致该决策支持系统进入和显示与选定选项相关的一条或多条特定途径。根据本发明的实施例,该决策支持系统包括用户接口设备,其独立于医疗设备或一个或多个传感器,其中根据预先建立的流程图简单地指导救护人员通过一系列的决策。基本地,医疗设备,例如去纤颤器,可以包括一个或多个决策支持流程图和/或处理规程,其在有或没有传感器数据或其它数据输入的情况下指导救护人员通过各种决策。图形DTP可以被包括在去纤颤器设备内作为电子可导航的参考文件。
根据其它实施例,该决策支持系统通过救护人员观察、病人信息和/或传感器数据的组合得到信息。通过接收来自救护人员的数据,或者接收来自传感器的数据,或两者,可以执行评估和/或评分。例如,对于创伤DTP,该决策支持系统可以考虑脉搏率、呼吸数据、定性呼吸数据、脉搏次数、血液流失、血压、断肢的存在和/或复合骨折。或者,在心区不适DTP中,该决策支持系统可以被配置为显示在某时刻上的心搏停止概率,其可以由该决策支持系统根据选定标准计算和/或预测。该决策支持系统还可以被配置为跟踪某些标准,从而建议处理结果概率,例如建议具有最高或较高预期成功概率的处理途径。
根据本发明的一些实施例,可以配置监视器、去纤颤器/监视器组合或其它类似设备,以提供图形工具用于配置该监视器遵循所识别的抢救规程,例如在此描述和/或图示的一个或多个规程。根据本发明的实施例,这样的工具可以被包括在监视器或去纤颤器设备上、在平板或手持或其它计算设备上和/或两者上。这样的工具可以具有图形界面,例如流程图。该工具允许用户配置病人监视器遵循特定的抢救规程,例如通过可视地显示用于规程的流程图和允许用户定制该规程。例如,可以由用户配置CPR周期的长度以定制处理规程。根据本发明的实施例,这样的工具还允许相对监视设备下载和上载定制处理规程,这还可以允许在移动设备上执行同一定制规程设置和/或在不同位置和/或不同时间上传输或上载至多个其它设备。
在不脱离本发明保护范围的情况下,可以对所讨论的示例实施例进行各种修改和添加。例如,虽然上述实施例提及特定特征,本发明的保护范围还包括具有不同特征组合的实施例和并不包括全部所述特征的实施例。因此,本发明的保护范围将涵盖落入权利要求书保护范围之内的全部此类替代、修改和变型以及其全部等同物。
Claims (24)
1.一种医疗系统,包括:
至少一个传感器,其配置为监视病人生理状态和根据生理状态生成传感器数据;
用户接口设备;
可通信地耦合至用户接口设备的处理器,该处理器配置为:
使用户接口设备显示两个或更多可能的输入单元的阵列,每个输入单元包括一类病人或诊断和治疗途径;
根据用户在两个或更多可能的输入单元之中的选择接收选定的输入单元;
获取传感器数据并处理该传感器数据以生成生理数据;和
根据为选定的输入单元定制的模板,在用户接口单元显示该生理数据。
2.权利要求1的医疗系统,其特征在于,该用户接口设备是用户接口屏幕,其中该处理器被进一步配置为在用户接口屏幕上显示两个或更多可能的输入单元的阵列,和其中该处理器被进一步配置为根据该模板在用户接口屏幕上显示该生理数据。
3.权利要求1的医疗系统,其特征在于,根据一个或多个开关的激活选择选定的输入单元。
4.权利要求1的医疗系统,其特征在于,用户接口设备是触摸激活屏幕,和其中根据对该触摸激活屏幕的触摸来选择选定的输入单元。
5.权利要求1的医疗系统,其特征在于,该至少一个传感器是ECG传感器、SpO2传感器、NIR组织灌注传感器、NIR pH传感器、超声波传感器、通气流量传感器、EtCO2传感器、侵入式血压传感器、非侵入式血压传感器、血糖监视器和气道氧气传感器中的一个或多个。
6.权利要求4的医疗系统,其特征在于,该处理器被进一步配置为接收通过在触摸激活屏幕上使用同一只手同时触摸两点生成的卡尺手势信号,和一旦接收到卡尺手势信号则将测量数据重叠至生理数据上。
7.权利要求1的医疗系统,其特征在于,该用户接口设备包括可视输入设备,和其中该处理器被进一步配置为将通过可视输入设备接收的手势识别为指示选定的输入单元。
8.权利要求1的医疗系统,其特征在于,两个或更多可能的输入单元的阵列包括下述的至少之一:
呼吸窘迫或呼吸困难的诊断和治疗途径;
精神状态改变的诊断和治疗途径;
心区不适的诊断和治疗途径;
创伤的诊断和治疗途径;和
疼痛或异常神经感知的诊断和治疗途径。
9.权利要求1的医疗系统,其特征在于,两个或更多可能的输入单元的阵列包括:
呼吸窘迫或呼吸困难的诊断和治疗途径;
精神状态改变的诊断和治疗途径;
心区不适的诊断和治疗途径;
创伤的诊断和治疗途径;和
疼痛或异常神经感知的诊断和治疗途径。
10.权利要求1的医疗系统,进一步包括移动计算设备。
11.权利要求10的医疗系统,其特征在于,该处理器是移动计算设备的一部分。
13.权利要求10的医疗系统,其特征在于,该用户接口设备是移动计算设备的一部分。
14.权利要求1的医疗系统,进一步包括去纤颤器。
15.权利要求14的医疗系统,其特征在于,用户接口设备是去纤颤器的一部分。
16.权利要求10的医疗系统,其特征在于,该移动计算设备包括保护外壳,其中该保护外壳包括第一安装特征,该医疗系统进一步包括第二安装特征,该第二安装特征配置为与第一安装特征相互配合。
17.权利要求1的医疗系统,其特征在于,该两个或更多可能的输入单元的阵列包括呼吸窘迫或呼吸困难的诊断和治疗途径。
18.权利要求17的医疗系统,其特征在于,该至少一个传感器配置为监视病人的心音。
19.权利要求17的医疗系统,其特征在于,该至少一个传感器配置为监视病人的呼吸音。
20.权利要求19的医疗系统,其特征在于,该处理器进一步配置为鉴别哮鸣、爆裂音、罗音和喘鸣呼吸音。
21.权利要求1的医疗系统,其特征在于,该至少一个传感器是基于近红外线的传感器。
22.权利要求1的医疗系统,其特征在于,该至少一个传感器配置为测量病人组织或血液的pH。
23.权利要求1的医疗系统,其特征在于,该至少一个传感器是ECG传感器,和其中该生理数据反映心率变异性。
24.权利要求1的医疗系统,其特征在于,该至少一个传感器是血糖传感器,和其中该生理数据反映当前血糖水平。
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US11826181B2 (en) | 2023-11-28 |
CN103313650B (zh) | 2016-09-14 |
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US20190254615A1 (en) | 2019-08-22 |
US10485490B2 (en) | 2019-11-26 |
US20240090856A1 (en) | 2024-03-21 |
WO2012065131A1 (en) | 2012-05-18 |
JP6441441B2 (ja) | 2018-12-19 |
JP2019022830A (ja) | 2019-02-14 |
JP2016187562A (ja) | 2016-11-04 |
JP6722413B2 (ja) | 2020-07-15 |
JP2018060559A (ja) | 2018-04-12 |
US20200214651A1 (en) | 2020-07-09 |
EP2638511A4 (en) | 2014-09-03 |
JP7014500B2 (ja) | 2022-02-01 |
EP4020344A1 (en) | 2022-06-29 |
JP2020168397A (ja) | 2020-10-15 |
JP6250096B2 (ja) | 2017-12-20 |
US10959683B2 (en) | 2021-03-30 |
US11759152B2 (en) | 2023-09-19 |
US20200359972A1 (en) | 2020-11-19 |
CN107007253B (zh) | 2020-09-01 |
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