<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03837418</url>
  </required_header>
  <id_info>
    <org_study_id>SMB03092018</org_study_id>
    <nct_id>NCT03837418</nct_id>
  </id_info>
  <brief_title>DESIGNING A PROGRAMMING LANGUAGE FOR PATIENT-ORIENTED PRESCRIPTIONS (POP-PL)</brief_title>
  <official_title>DESIGNING A PROGRAMMING LANGUAGE FOR PATIENT-ORIENTED PRESCRIPTIONS (POP-PL)</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Northwestern University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Northwestern University</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      The purpose of this study is to create a human-readable and executable computer language to&#xD;
      implement medical prescriptions and to evaluate and refine this language, with the goal of&#xD;
      improving safety and efficacy of patient care&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Preventable errors in healthcare are a leading cause of patient injury and death. Despite&#xD;
      extensive effort and the expenditure of billions of dollars, computerization has failed to&#xD;
      solve this problem. Research has shown that software design and debugging of a paper&#xD;
      prescription markedly decreases the rate of injury and death associated with use of opioids&#xD;
      in hospitalized patients. To further the application of insights from software engineering to&#xD;
      the practice of medicine, the PIs will design and build a Patient-Oriented Prescription&#xD;
      Programming Language (POP-PL) and evaluate if this new platform can be used to improve&#xD;
      medical management of patients. The design of POP-PL will be based on building an&#xD;
      understanding of the process of medical treatment of patients. This project is a&#xD;
      collaboration between computer scientists and clinicians at Northwestern Medicine. The&#xD;
      collaborating clinicians are co-investigators on this research project and also are providing&#xD;
      healthcare to the patients that are being observed. The computer scientists and other&#xD;
      research staff have undergone human subjects research training and are co-investigators on&#xD;
      this research project as well. The clinician-investigators will oversee research project&#xD;
      staff during all observations of patients, clinical encounters between healthcare providers&#xD;
      and patients, and interactions between healthcare providers and healthcare information&#xD;
      systems. Researchers involved in this study will observe interactions between health care&#xD;
      providers and patients and will collate these observations with data from electronic data&#xD;
      sources. Since this research is based mainly upon observation and chart review and will not&#xD;
      involve any interventions or changes to patient care, the risk to study participants is&#xD;
      minimal, involving inadvertent disclosure of healthcare information. This risk will be&#xD;
      mitigated by anonymizing collected data.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Withdrawn</overall_status>
  <why_stopped>
    Investigator is no longer at Northwestern University.&#xD;
  </why_stopped>
  <start_date type="Actual">January 17, 2019</start_date>
  <completion_date type="Anticipated">June 2026</completion_date>
  <primary_completion_date type="Anticipated">June 2022</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Evaluation of Differences between Ideal and Actual Performance of Prescriptions by Number of Deviations between Sequences of Events</measure>
    <time_frame>2 years</time_frame>
    <description>Investigators will express the intent of prescriptions in prescription programming language. Investigators will then compare the actual performance of the prescription in a clinical environment to the performance of the prescription in a simulated environment based on the same inputs as occurred in the real clinical environment.</description>
  </primary_outcome>
  <enrollment type="Actual">0</enrollment>
  <condition>Programming Languages</condition>
  <condition>Patients</condition>
  <eligibility>
    <study_pop>
      <textblock>
        Patients seen at Northwestern Memorial Hospital, Northwestern Medicine Clinics, Lurie&#xD;
        Children's Clinics, and Lurie Children's Hospital between the ages of 0-79.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Patients seen at Northwestern Memorial Hospital, Northwestern Medicine Clinics, Lurie&#xD;
             Children's Clinics, and Lurie Children's Hospital between the ages of 0-79.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Patients without data within the NMEDW medical record database or LCH CDW or BIS&#xD;
             medical record database.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>0 Years</minimum_age>
    <maximum_age>79 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Steven M Belknap, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Northwestern University</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Northwestern University</name>
      <address>
        <city>Chicago</city>
        <state>Illinois</state>
        <zip>60611</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>October 2020</verification_date>
  <study_first_submitted>February 8, 2019</study_first_submitted>
  <study_first_submitted_qc>February 8, 2019</study_first_submitted_qc>
  <study_first_posted type="Actual">February 12, 2019</study_first_posted>
  <last_update_submitted>October 7, 2020</last_update_submitted>
  <last_update_submitted_qc>October 7, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">October 9, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Northwestern University</investigator_affiliation>
    <investigator_full_name>Stephanie Rangel</investigator_full_name>
    <investigator_title>Research Assistant Professor of Dermatology</investigator_title>
  </responsible_party>
  <keyword>Patient-Oriented</keyword>
  <keyword>Designing</keyword>
  <keyword>Prescriptions</keyword>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03837418
org study id: SMB03092018
nct id: NCT03837418
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
The purpose of this study is to create a human-readable and executable computer language to
      implement medical prescriptions and to evaluate and refine this language, with the goal of
      improving safety and efficacy of patient care
Preventable errors in healthcare are a leading cause of patient injury and death. Despite
      extensive effort and the expenditure of billions of dollars, computerization has failed to
      solve this problem. Research has shown that software design and debugging of a paper
      prescription markedly decreases the rate of injury and death associated with use of opioids
      in hospitalized patients. To further the application of insights from software engineering to
      the practice of medicine, the PIs will design and build a Patient-Oriented Prescription
      Programming Language (POP-PL) and evaluate if this new platform can be used to improve
      medical management of patients. The design of POP-PL will be based on building an
      understanding of the process of medical treatment of patients. This project is a
      collaboration between computer scientists and clinicians at Northwestern Medicine. The
      collaborating clinicians are co-investigators on this research project and also are providing
      healthcare to the patients that are being observed. The computer scientists and other
      research staff have undergone human subjects research training and are co-investigators on
      this research project as well. The clinician-investigators will oversee research project
      staff during all observations of patients, clinical encounters between healthcare providers
      and patients, and interactions between healthcare providers and healthcare information
      systems. Researchers involved in this study will observe interactions between health care
      providers and patients and will collate these observations with data from electronic data
      sources. Since this research is based mainly upon observation and chart review and will not
      involve any interventions or changes to patient care, the risk to study participants is
      minimal, involving inadvertent disclosure of healthcare information. This risk will be
      mitigated by anonymizing collected data.
observational model: Cohort
time perspective: Prospective
measure: Evaluation of Differences between Ideal and Actual Performance of Prescriptions by Number of Deviations between Sequences of Events
time frame: 2 years
description: Investigators will express the intent of prescriptions in prescription programming language. Investigators will then compare the actual performance of the prescription in a clinical environment to the performance of the prescription in a simulated environment based on the same inputs as occurred in the real clinical environment.
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 0 Years
maximum age: 79 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Steven M Belknap, MD
role: Principal Investigator
affiliation: Northwestern University
facility: 
country: United States
responsible party type: Principal Investigator
investigator affiliation: Northwestern University
investigator full name: Stephanie Rangel
investigator title: Research Assistant Professor of Dermatology
sharing ipd: No