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    <article-meta>
      <title-group>
        <article-title>Performance Evaluation Clinical Task Ontology(PECTO)</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Jose F Florez-Arango</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Santiago Patiño-Giraldo</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>M. Sriram Iyengar</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Jack W Smith</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>College of Medicine Texas A&amp;M University College Station</institution>
          ,
          <addr-line>TX</addr-line>
          ,
          <country country="US">USA</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Grupo INFORMED Facultad de Medicina Universidad de Antioquia Medellín</institution>
          ,
          <country country="CO">Colombia</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Línea e-salud, Centro Bioingeniería Escuela de Ciencias de la Salud Universidad Pontificia Bolivariana Medellín</institution>
          ,
          <country country="CO">Colombia</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>-This poster presents a proposed Clinical Tasks Ontology (PECTO) designed to evaluate effects of technologies on human performance under controlled conditions, such as clinical simulation scenarios (CSS), across multiple clinica l domains including prehospital care. In recent years there has been an explosion of technologies, including Information and Communications Technologies (ICTs) that are designed to assist health workers and improve their performance across a spectrum of clinical activities from pre-hospital care to post-surgical care. However, each new technology introduces its own requirements on the health worker and has the potential to either increase or decrease the perceived workload on the health -worker. Since perceived workload can have significant effects on health worke r performance [4], it is important to carefully measure work-loa d changes and relate these to health worker performance measures such as task errors, and procedure compliance. Clinical Simulatio n Scenarios are often used to perform controlled experiments in which health workers' performance on clinical conditions, simulated by various means, including Human Patient Simulators , is observed and measured with and without the technology being studied[5]. The Clinical Tasks Ontology (PECTO) was developed, among other applications, to help design such evaluation experiments. A major objective of such studies is to evaluate the performance of health workers as they perform specific clinica l tasks. In this context, the PECTO presents a novel approach for task classification and analysis since previous approaches [6]-[8] do not account for sources of workload, and measurement of human performance in terms of errors and protocol compliance . An ontological approach was selected to build the classification system enabling tasks to have multiple properties that can be related to dependent variables. Previous work in task analysis and task classification include an ontological approach to plans and processes[6], some modeling of event evaluation [7], and a clinica l</p>
      </abstract>
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  </front>
  <body>
    <sec id="sec-1">
      <title>4Hospital Pablo Tobón Uribe</title>
      <p>Medellín, Colombia
task model of care plans [8], as well as comprehensive approaches
to model human factors and workload.</p>
      <p>For the purpose of this research a Clinical Task (task ) is defined
as an action accomplished by a health care provider for the
purpose of solving a clinical case. A case is a clinical situation that
includes provider, patient’s conditions, clinical protocol or
guideline to de followed and resources available. A case is
expected to have a desirable outcome.</p>
      <p>Clinical Tasks can be determined by protocols. “Clinical
protocols are agreed statements about a specific issue, with
explicit steps based on clinical guidelines and/or organizational
consensus. A protocol is not specific to a named patient”[6].
The PECTO developed here was part of a broader study focused
on evaluating use on computerized clinical guidelines by
community health workers [10], [11].</p>
      <p>PECTO was constructed in Protégé by two clinical experts and is
informed by several previous research studies on task analysis and
clinical modeling. Each task in the PECTO has 9 possible
properties classes, 75 distinct classes and 14 object properties.
When applied to 30 pre-hospital cases for community health
workers, following 6 clinical protocols, PECTO resulted in 447
identifiable individual tasks. In a study of task performance by
Community Health Workers, application of PECTO enabled
differentiation between learning and technology effects. Another
application of PECTO is the development of a visual
representation of case similarity.</p>
      <p>There are 5 object properties in addition to 9 basic object
properties (relationships) between tasks and dimensions, as seen
in Figure 2. PECTO object properties . These object properties
allow for additional expressivity for particular inferred task, as a
critical task (a task that is indispensable or its not execution ends
in patient death). Or to establish complexity of tasks accordingly
with number of subtask/goal
For extrinsic evaluation a total of 982 tasks (individuals) were
derived from 30 clinical cases. Each task was assigned at least a
leaf class of each of 9 main domains. A total of 200 ontological
distinctive task were obtained after applying reasoner. The most
frequent task for the study particular data set was “Verify If Pulse
is Present”, is it a task present in 20 out of the 30 cases. An
ontological representation of such task is shown in Example 1.
is_a TaskAsAction
is_a TypeOfTask</p>
    </sec>
    <sec id="sec-2">
      <title>II. DISCUSSION AND CONCLUSION</title>
      <p>We developed a Clinical Task Ontology accounting with human
performance factors. One limitation is that this first version is
based on the clinical domain of pre-hospital care in which
Community Health Workers are the primary clinicians. While this
domain is very important in the global health context of
developing countries, the developmental methodology can be
extended to include other clinical domains .</p>
      <p>An important application, among others, of the PECTO is the
ability to create metrics to compare cases from a human
performance perspective.</p>
      <p>Future work include extending type of task model in order to have
a reasoner-based classification of task depending on additional
properties, instead of simply asserting the task type.
[1]
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[11]
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