<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/NCT01710293</url>
  </required_header>
  <id_info>
    <org_study_id>CRE 12-033</org_study_id>
    <secondary_id>CIRB 15-07</secondary_id>
    <nct_id>NCT01710293</nct_id>
  </id_info>
  <brief_title>Intervention Protocol for Automated Point-of-Care Surveillance of Outpatient Delays in Cancer Diagnosis</brief_title>
  <acronym>PACT CREATE 3</acronym>
  <official_title>Automated Point-of-Care Surveillance of Outpatient Delays in Cancer Diagnosis</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>VA Office of Research and Development</agency>
      <agency_class>U.S. Fed</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>VA Office of Research and Development</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
    <is_us_export>No</is_us_export>
  </oversight_info>
  <brief_summary>
    <textblock>
      Many missed and delayed cancer diagnoses result from breakdowns in communication and&#xD;
      coordination of abnormal findings suspicious for cancer, which often first emerge in the&#xD;
      primary care setting. Delays in the follow-up of abnormal test results persist despite the&#xD;
      reliable delivery of test results through the electronic health record.&#xD;
&#xD;
      This intervention is the final study in a three-phase project that will develop and test an&#xD;
      innovative automated surveillance intervention to improve timely diagnosis and follow-up of&#xD;
      five common cancers in primary care practice.&#xD;
&#xD;
      The investigators hypothesize that the median time in days from diagnostic clue to follow-up&#xD;
      action (e.g. time to colonoscopy examination after am abnormal colon-related test) will be&#xD;
      significantly less in the intervention arm than in usual care. The investigators also&#xD;
      hypothesize that the proportion of patients receiving appropriate and timely follow-up care&#xD;
      will be significantly higher in the intervention arm than in usual care.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The CREATE Project encompasses three phases, the first and second of which do not contain&#xD;
      interventions. The first phase of the project determines the effectiveness of computerized&#xD;
      queries the investigators develop to accurately identify which patients are at risk for&#xD;
      delays in cancer diagnosis. Patients the investigators identify will have abnormal test&#xD;
      results or symptoms that have not been followed up by their providers. In Phase 2 of the&#xD;
      study, the research team will use interviewing and other participatory techniques to&#xD;
      determine the best way to convey information about such at-risk patients to providers in an&#xD;
      automated fashion. In Phase 3 of the project, the investigators will evaluate the effects of&#xD;
      an automated surveillance intervention on the timeliness of the diagnostic process of five&#xD;
      cancers.&#xD;
&#xD;
      This project will improve communication and coordination of cancer-related diagnostic&#xD;
      information to improve quality and safety.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Withdrawn</overall_status>
  <why_stopped>
    Unable to obtain data needed to run the RCT; project never began recruitment&#xD;
  </why_stopped>
  <start_date type="Actual">January 27, 2017</start_date>
  <completion_date type="Actual">January 27, 2017</completion_date>
  <primary_completion_date type="Actual">January 27, 2017</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <primary_purpose>Health Services Research</primary_purpose>
    <masking>Single (Care Provider)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Median Time from Initial Follow-up Delay to Follow-up Action</measure>
    <time_frame>1 year</time_frame>
    <description>The investigators will conduct chart reviews of patients shown by our automated surveillance system to have not received appropriate follow-up care in both intervention and control groups at least 6 months after the first documentation of a diagnostic clue (e.g., initial abnormal chest X-ray). Chart review will be used to quantify time in days from documentation of the clinical clue to the time when follow-up action on that clue was initiated.</description>
  </primary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">0</enrollment>
  <condition>Lung Cancer</condition>
  <condition>Bladder Cancer</condition>
  <condition>Colorectal Cancer</condition>
  <condition>Hepatocellular Carcinoma</condition>
  <condition>Breast Cancer</condition>
  <arm_group>
    <arm_group_label>Communication of Patients Lost to Follow-up to Providers</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>This intervention will consist of two related, continuous steps over at least a 12-month period. In the first step, the investigators will query the VA's Corporate Data Warehouse (CDW, a repository of near real-time patient data from all VA medical centers) weekly to identify possible lost to follow-up events in a pre-specified time period and for a random sample of about half of the providers at the investigators' study sites. These identified patient charts will be reviewed by Facility Recipients/Cancer Trackers at each site who will then communicate patients truly found to be lost to follow-up to the appropriate provider/care team.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Usual Care</arm_group_label>
    <arm_group_type>No Intervention</arm_group_type>
    <description>In the usual care group, providers will continue to use the existing notification system to receive abnormal test results in accordance with institutional norms, policies, and procedures. There are no formal patient-tracking programs currently at our study sites for all abnormal test results. The investigators will apply our computerized surveillance tools in the usual care arm only when the investigators are ready to conduct the final chart reviews on intervention patients and identify these patients in similar time periods as in the intervention arm. If persistent delays are found, the investigators will inform the patients' primary care providers.</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Communication of Patients Lost to Follow-up to Providers</intervention_name>
    <description>The investigators will query the VA's database weekly to identify possible lost to follow-up events for a random sample of about half of the providers at our study sites. The queries will use the trigger criteria developed in our previous work for colorectal cancer, lung cancer, hepatocellular carcinoma, breast cancer, and bladder cancer. The list of trigger positive patients will be transmitted to a facility-level recipient who will either disseminate the information to existing facility individual cancer care coordinators/trackers or will review the charts of the &quot;triggered&quot; patients in order to determine whether these patients have been truly lost to follow-up or not. If patients are found to be lost to follow-up, the Facility Recipient or cancer care coordinator/tracker will communicate the need for follow-up to the PACT or primary care provider, using secure emails, phone calls, or in person, depending on which method of communication they deem most appropriate and effective.</description>
    <arm_group_label>Communication of Patients Lost to Follow-up to Providers</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Patient charts: Medical charts of Veteran patients who receive care from participating&#xD;
             VA facility (Madison VAH, Jesse Brown VAMC, Hines VAH, Michael E. DeBakey VAMC, and&#xD;
             Minneapolis VAMC) providers during the one year study period (tentatively October&#xD;
             2016-October 2017) and who have potential delays in diagnostic evaluation for lung,&#xD;
             colorectal, liver, bladder, or breast cancer will be reviewed as part of the study.&#xD;
&#xD;
          -  Providers: Providers who have seen primary care outpatients in any of the&#xD;
             participating facilities or their outpatient clinics within the year-long study&#xD;
             period.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Patient Charts: Medical charts of patients who are not receiving care from&#xD;
             participating facility providers or charts of patients who do not have potential&#xD;
             follow-up delays for lung, colorectal, liver, bladder, or breast cancer in the time&#xD;
             period of interest.&#xD;
&#xD;
          -  Providers: Providers who have not seen primary care outpatients in any of the&#xD;
             participating facilities or their outpatient clinics within the time period of&#xD;
             interest.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>21 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Hardeep Singh, MD MPH BS</last_name>
    <role>Principal Investigator</role>
    <affiliation>Michael E. DeBakey VA Medical Center, Houston, TX</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Jesse Brown VA Medical Center, Chicago, IL</name>
      <address>
        <city>Chicago</city>
        <state>Illinois</state>
        <zip>60612</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Edward Hines Jr. VA Hospital, Hines, IL</name>
      <address>
        <city>Hines</city>
        <state>Illinois</state>
        <zip>60141-5000</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Minneapolis VA Health Care System, Minneapolis, MN</name>
      <address>
        <city>Minneapolis</city>
        <state>Minnesota</state>
        <zip>55417</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Michael E. DeBakey VA Medical Center, Houston, TX</name>
      <address>
        <city>Houston</city>
        <state>Texas</state>
        <zip>77030</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>William S. Middleton Memorial Veterans Hospital, Madison, WI</name>
      <address>
        <city>Madison</city>
        <state>Wisconsin</state>
        <zip>53705</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <reference>
    <citation>Murphy DR, Meyer AN, Russo E, Sittig DF, Wei L, Singh H. The Burden of Inbox Notifications in Commercial Electronic Health Records. JAMA Intern Med. 2016 Apr;176(4):559-60. doi: 10.1001/jamainternmed.2016.0209. No abstract available.</citation>
    <PMID>26974737</PMID>
  </reference>
  <results_reference>
    <citation>Bhise V, Meyer AND, Singh H, Wei L, Russo E, Al-Mutairi A, Murphy DR. Errors in Diagnosis of Spinal Epidural Abscesses in the Era of Electronic Health Records. Am J Med. 2017 Aug;130(8):975-981. doi: 10.1016/j.amjmed.2017.03.009. Epub 2017 Mar 31.</citation>
    <PMID>28366427</PMID>
  </results_reference>
  <results_reference>
    <citation>Murphy DR, Meyer AN, Vaghani V, Russo E, Sittig DF, Richards KA, Wei L, Wu L, Singh H. Application of Electronic Algorithms to Improve Diagnostic Evaluation for Bladder Cancer. Appl Clin Inform. 2017 Mar 22;8(1):279-290. doi: 10.4338/ACI-2016-10-RA-0176.</citation>
    <PMID>28326433</PMID>
  </results_reference>
  <results_reference>
    <citation>Meyer AND, Murphy DR, Al-Mutairi A, Sittig DF, Wei L, Russo E, Singh H. Electronic Detection of Delayed Test Result Follow-Up in Patients with Hypothyroidism. J Gen Intern Med. 2017 Jul;32(7):753-759. doi: 10.1007/s11606-017-3988-z. Epub 2017 Jan 30.</citation>
    <PMID>28138875</PMID>
  </results_reference>
  <results_reference>
    <citation>Menon S, Singh H, Giardina TD, Rayburn WL, Davis BP, Russo EM, Sittig DF. Safety huddles to proactively identify and address electronic health record safety. J Am Med Inform Assoc. 2017 Mar 1;24(2):261-267. doi: 10.1093/jamia/ocw153.</citation>
    <PMID>28031286</PMID>
  </results_reference>
  <results_reference>
    <citation>Baldwin JL, Singh H, Sittig DF, Giardina TD. Patient portals and health apps: Pitfalls, promises, and what one might learn from the other. Healthc (Amst). 2017 Sep;5(3):81-85. doi: 10.1016/j.hjdsi.2016.08.004. Epub 2016 Oct 3.</citation>
    <PMID>27720139</PMID>
  </results_reference>
  <results_reference>
    <citation>Singh H, Graber ML, Hofer TP. Measures to Improve Diagnostic Safety in Clinical Practice. J Patient Saf. 2019 Dec;15(4):311-316. doi: 10.1097/PTS.0000000000000338.</citation>
    <PMID>27768655</PMID>
  </results_reference>
  <results_reference>
    <citation>Singh H. Improving Diagnostic Safety in Primary Care by Unlocking Digital Data. Jt Comm J Qual Patient Saf. 2017 Jan;43(1):29-31. doi: 10.1016/j.jcjq.2016.10.007. Epub 2016 Oct 14. No abstract available.</citation>
    <PMID>28334582</PMID>
  </results_reference>
  <results_reference>
    <citation>Giardina TD, Sarkar U, Gourley G, Modi V, Meyer AN, Singh H. Online public reactions to frequency of diagnostic errors in US outpatient care. Diagnosis (Berl). 2016 Mar;3(1):17-22. doi: 10.1515/dx-2015-0022. Epub 2016 Feb 19.</citation>
    <PMID>27347474</PMID>
  </results_reference>
  <results_reference>
    <citation>Singh H, Schiff GD, Graber ML, Onakpoya I, Thompson MJ. The global burden of diagnostic errors in primary care. BMJ Qual Saf. 2017 Jun;26(6):484-494. doi: 10.1136/bmjqs-2016-005401. Epub 2016 Aug 16.</citation>
    <PMID>27530239</PMID>
  </results_reference>
  <results_reference>
    <citation>Sittig DF, Wright A, Ash J, Singh H. New Unintended Adverse Consequences of Electronic Health Records. Yearb Med Inform. 2016 Nov 10;(1):7-12. doi: 10.15265/IY-2016-023.</citation>
    <PMID>27830226</PMID>
  </results_reference>
  <results_reference>
    <citation>Pfoh ER, Engineer L, Singh H, Hall LL, Fried ED, Berger Z, Wu AW. Informing the Design of a New Pragmatic Registry to Stimulate Near Miss Reporting in Ambulatory Care. J Patient Saf. 2021 Apr 1;17(3):e121-e127. doi: 10.1097/PTS.0000000000000317.</citation>
    <PMID>28248748</PMID>
  </results_reference>
  <verification_date>February 2018</verification_date>
  <study_first_submitted>October 16, 2012</study_first_submitted>
  <study_first_submitted_qc>October 18, 2012</study_first_submitted_qc>
  <study_first_posted type="Estimate">October 19, 2012</study_first_posted>
  <last_update_submitted>February 22, 2018</last_update_submitted>
  <last_update_submitted_qc>February 22, 2018</last_update_submitted_qc>
  <last_update_posted type="Actual">February 26, 2018</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Electronic Health Records</keyword>
  <keyword>Diagnostic Delay</keyword>
  <keyword>Triggers</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Carcinoma, Hepatocellular</mesh_term>
  </condition_browse>
  <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/NCT01710293
org study id: CRE 12-033
secondary id: CIRB 15-07
nct id: NCT01710293
lead sponsor: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
is us export: No
Many missed and delayed cancer diagnoses result from breakdowns in communication and
      coordination of abnormal findings suspicious for cancer, which often first emerge in the
      primary care setting. Delays in the follow-up of abnormal test results persist despite the
      reliable delivery of test results through the electronic health record.

      This intervention is the final study in a three-phase project that will develop and test an
      innovative automated surveillance intervention to improve timely diagnosis and follow-up of
      five common cancers in primary care practice.

      The investigators hypothesize that the median time in days from diagnostic clue to follow-up
      action (e.g. time to colonoscopy examination after am abnormal colon-related test) will be
      significantly less in the intervention arm than in usual care. The investigators also
      hypothesize that the proportion of patients receiving appropriate and timely follow-up care
      will be significantly higher in the intervention arm than in usual care.
The CREATE Project encompasses three phases, the first and second of which do not contain
      interventions. The first phase of the project determines the effectiveness of computerized
      queries the investigators develop to accurately identify which patients are at risk for
      delays in cancer diagnosis. Patients the investigators identify will have abnormal test
      results or symptoms that have not been followed up by their providers. In Phase 2 of the
      study, the research team will use interviewing and other participatory techniques to
      determine the best way to convey information about such at-risk patients to providers in an
      automated fashion. In Phase 3 of the project, the investigators will evaluate the effects of
      an automated surveillance intervention on the timeliness of the diagnostic process of five
      cancers.

      This project will improve communication and coordination of cancer-related diagnostic
      information to improve quality and safety.
allocation: Randomized
intervention model: Parallel Assignment
primary purpose: Health Services Research
masking: Single (Care Provider)
measure: Median Time from Initial Follow-up Delay to Follow-up Action
time frame: 1 year
description: The investigators will conduct chart reviews of patients shown by our automated surveillance system to have not received appropriate follow-up care in both intervention and control groups at least 6 months after the first documentation of a diagnostic clue (e.g., initial abnormal chest X-ray). Chart review will be used to quantify time in days from documentation of the clinical clue to the time when follow-up action on that clue was initiated.
arm group label: Communication of Patients Lost to Follow-up to Providers
arm group type: Experimental
description: This intervention will consist of two related, continuous steps over at least a 12-month period. In the first step, the investigators will query the VA's Corporate Data Warehouse (CDW, a repository of near real-time patient data from all VA medical centers) weekly to identify possible lost to follow-up events in a pre-specified time period and for a random sample of about half of the providers at the investigators' study sites. These identified patient charts will be reviewed by Facility Recipients/Cancer Trackers at each site who will then communicate patients truly found to be lost to follow-up to the appropriate provider/care team.
arm group label: Usual Care
arm group type: No Intervention
description: In the usual care group, providers will continue to use the existing notification system to receive abnormal test results in accordance with institutional norms, policies, and procedures. There are no formal patient-tracking programs currently at our study sites for all abnormal test results. The investigators will apply our computerized surveillance tools in the usual care arm only when the investigators are ready to conduct the final chart reviews on intervention patients and identify these patients in similar time periods as in the intervention arm. If persistent delays are found, the investigators will inform the patients' primary care providers.
intervention type: Behavioral
intervention name: Communication of Patients Lost to Follow-up to Providers
description: The investigators will query the VA's database weekly to identify possible lost to follow-up events for a random sample of about half of the providers at our study sites. The queries will use the trigger criteria developed in our previous work for colorectal cancer, lung cancer, hepatocellular carcinoma, breast cancer, and bladder cancer. The list of trigger positive patients will be transmitted to a facility-level recipient who will either disseminate the information to existing facility individual cancer care coordinators/trackers or will review the charts of the "triggered" patients in order to determine whether these patients have been truly lost to follow-up or not. If patients are found to be lost to follow-up, the Facility Recipient or cancer care coordinator/tracker will communicate the need for follow-up to the PACT or primary care provider, using secure emails, phone calls, or in person, depending on which method of communication they deem most appropriate and effective.
arm group label: Communication of Patients Lost to Follow-up to Providers
criteria: 
gender: All
minimum age: 21 Years
maximum age: N/A
healthy volunteers: No
last name: Hardeep Singh, MD MPH BS
role: Principal Investigator
affiliation: Michael E. DeBakey VA Medical Center, Houston, TX
facility: 
facility: 
facility: 
facility: 
facility: 
country: United States
citation: Murphy DR, Meyer AN, Russo E, Sittig DF, Wei L, Singh H. The Burden of Inbox Notifications in Commercial Electronic Health Records. JAMA Intern Med. 2016 Apr;176(4):559-60. doi: 10.1001/jamainternmed.2016.0209. No abstract available.
PMID: 26974737
citation: Bhise V, Meyer AND, Singh H, Wei L, Russo E, Al-Mutairi A, Murphy DR. Errors in Diagnosis of Spinal Epidural Abscesses in the Era of Electronic Health Records. Am J Med. 2017 Aug;130(8):975-981. doi: 10.1016/j.amjmed.2017.03.009. Epub 2017 Mar 31.
PMID: 28366427
citation: Murphy DR, Meyer AN, Vaghani V, Russo E, Sittig DF, Richards KA, Wei L, Wu L, Singh H. Application of Electronic Algorithms to Improve Diagnostic Evaluation for Bladder Cancer. Appl Clin Inform. 2017 Mar 22;8(1):279-290. doi: 10.4338/ACI-2016-10-RA-0176.
PMID: 28326433
citation: Meyer AND, Murphy DR, Al-Mutairi A, Sittig DF, Wei L, Russo E, Singh H. Electronic Detection of Delayed Test Result Follow-Up in Patients with Hypothyroidism. J Gen Intern Med. 2017 Jul;32(7):753-759. doi: 10.1007/s11606-017-3988-z. Epub 2017 Jan 30.
PMID: 28138875
citation: Menon S, Singh H, Giardina TD, Rayburn WL, Davis BP, Russo EM, Sittig DF. Safety huddles to proactively identify and address electronic health record safety. J Am Med Inform Assoc. 2017 Mar 1;24(2):261-267. doi: 10.1093/jamia/ocw153.
PMID: 28031286
citation: Baldwin JL, Singh H, Sittig DF, Giardina TD. Patient portals and health apps: Pitfalls, promises, and what one might learn from the other. Healthc (Amst). 2017 Sep;5(3):81-85. doi: 10.1016/j.hjdsi.2016.08.004. Epub 2016 Oct 3.
PMID: 27720139
citation: Singh H, Graber ML, Hofer TP. Measures to Improve Diagnostic Safety in Clinical Practice. J Patient Saf. 2019 Dec;15(4):311-316. doi: 10.1097/PTS.0000000000000338.
PMID: 27768655
citation: Singh H. Improving Diagnostic Safety in Primary Care by Unlocking Digital Data. Jt Comm J Qual Patient Saf. 2017 Jan;43(1):29-31. doi: 10.1016/j.jcjq.2016.10.007. Epub 2016 Oct 14. No abstract available.
PMID: 28334582
citation: Giardina TD, Sarkar U, Gourley G, Modi V, Meyer AN, Singh H. Online public reactions to frequency of diagnostic errors in US outpatient care. Diagnosis (Berl). 2016 Mar;3(1):17-22. doi: 10.1515/dx-2015-0022. Epub 2016 Feb 19.
PMID: 27347474
citation: Singh H, Schiff GD, Graber ML, Onakpoya I, Thompson MJ. The global burden of diagnostic errors in primary care. BMJ Qual Saf. 2017 Jun;26(6):484-494. doi: 10.1136/bmjqs-2016-005401. Epub 2016 Aug 16.
PMID: 27530239
citation: Sittig DF, Wright A, Ash J, Singh H. New Unintended Adverse Consequences of Electronic Health Records. Yearb Med Inform. 2016 Nov 10;(1):7-12. doi: 10.15265/IY-2016-023.
PMID: 27830226
citation: Pfoh ER, Engineer L, Singh H, Hall LL, Fried ED, Berger Z, Wu AW. Informing the Design of a New Pragmatic Registry to Stimulate Near Miss Reporting in Ambulatory Care. J Patient Saf. 2021 Apr 1;17(3):e121-e127. doi: 10.1097/PTS.0000000000000317.
PMID: 28248748
responsible party type: Sponsor
mesh term: Carcinoma, Hepatocellular
sharing ipd: No