<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/NCT03791541</url>
  </required_header>
  <id_info>
    <org_study_id>2016-0748</org_study_id>
    <nct_id>NCT03791541</nct_id>
  </id_info>
  <brief_title>A Study Evaluating the Use of Potential Predictors of Readmission in Hospitalized Medicine Patients</brief_title>
  <official_title>A Study Evaluating the Use of Potential Predictors of Readmission in Hospitalized Medicine Patients</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Illinois at Chicago</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>University of Illinois at Chicago</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 primary objective of this study is the development and implementation of a survey&#xD;
      administered to hospitalized patients on Internal Medicine that can be used in conjunction&#xD;
      with previously validated predictive indices to identify patients at risk for readmission.&#xD;
      The survey consists of previously validated as well as investigator developed survey&#xD;
      instruments that will assess the following: health literacy, numeracy, medication adherence,&#xD;
      self-efficacy, and tolerance. The predictive indices are the LACE, Charlson Comorbidity Index&#xD;
      (included in LACE), and the Comorbidity Polypharmacy Score (CPS) which have been previously&#xD;
      validated for risk of readmissions. The survey consists of both closed and open ended&#xD;
      questions. A part of the survey will be administered by the study personnel while the rest is&#xD;
      a questionnaire-based survey that will be completed by the subjects. Study personnel will be&#xD;
      with the subjects in an open dialogue while subjects are completing the survey to answer any&#xD;
      questions and identify questions that may be confusing or bias subjects. Approximately 30&#xD;
      days after hospital discharge, patients will be contacted via telephone to ask how many&#xD;
      admissions and/or Emergency Department (ED) visits they have had since discharge. A&#xD;
      correlation analysis will be done of the different aspects of the survey to determine whether&#xD;
      there are redundancies. A regression analysis will be done to determine the predictive&#xD;
      ability of the survey combined with predictive indices for readmission.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Many patients are readmitted to the hospital shortly after discharge. Twenty percent of&#xD;
      Medicare beneficiaries discharged were re-hospitalized within 30 days at a cost to Medicare&#xD;
      estimated at $17.4 billion. This problem does not only affect the elderly. Medicaid enrollees&#xD;
      aged 21-64 had 10.7% 30-day readmission rate. Identifying which patients are at highest risk&#xD;
      is important for allocating resources to those high risk individuals.&#xD;
&#xD;
      Several studies have attempted to retrospectively identify medical conditions, medications,&#xD;
      labs, and vitals associated with increased risk of readmission with different levels of&#xD;
      success. Examples of these include the Charlson Comorbidity Index, LACE, and the Comorbidity&#xD;
      Polypharmacy Score. Although not always developed for use in predicting readmissions, they&#xD;
      have been subsequently associated with this.&#xD;
&#xD;
      While these indices examine objective data, it is thought that health beliefs, abilities, and&#xD;
      behaviors can also affect the risk of readmissions. Health literacy in particular has been&#xD;
      shown to be associated with 30 day readmissions after an acute myocardial infarction and in&#xD;
      general medical patients. Low numeracy has been associated with increased risk of 30 day&#xD;
      readmission in patients with acute heart failure.&#xD;
&#xD;
      Inpatient questionnaires are able to identify patients who are more likely than others to be&#xD;
      readmitted. Additionally, objective qualities such as insurance status, comorbidities, and&#xD;
      admissions within the past year are predictors of readmission. Due to the unique patient&#xD;
      populations at different health systems, an institution-specific approach is necessary to&#xD;
      analyze the specific factors contributing to readmission. Therefore, a survey will be used to&#xD;
      gauge the most predictive factors of readmissions and ED visits, including objective and&#xD;
      subjective sections. After further research and modification, the survey will potentially&#xD;
      serve as a tool for clinicians to select the best approach to post-discharge care and&#xD;
      follow-up.&#xD;
&#xD;
      This pilot will attempt to test a survey for predicting readmission through measurements of&#xD;
      health literacy, numeracy, medication adherence, self-efficacy, and tolerance, and in&#xD;
      conjunction with co-morbidity indices.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Withdrawn</overall_status>
  <why_stopped>
    Pilot study results not meaningful. Students researchers graduated.&#xD;
  </why_stopped>
  <start_date type="Actual">February 1, 2017</start_date>
  <completion_date type="Actual">February 27, 2018</completion_date>
  <primary_completion_date type="Actual">December 1, 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>
    <intervention_model_description>targeted, cost-effective interventions based on results of surveys and other factors studied will be applied to study arm to see if re-admissions can be prevented</intervention_model_description>
    <primary_purpose>Prevention</primary_purpose>
    <masking>Single (Participant)</masking>
    <masking_description>Survey will be given to all participants</masking_description>
  </study_design_info>
  <primary_outcome>
    <measure>Number of readmissions after 1 month</measure>
    <time_frame>30 days post-discharge</time_frame>
    <description>Number of readmissions after 30 days post-discharge</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Number of readmissions after 2 months</measure>
    <time_frame>60 days post-discharge</time_frame>
    <description>Number of readmissions after 60 days post-discharge</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">0</enrollment>
  <condition>The Focus is to Test a Survey Predicting Readmissions</condition>
  <condition>Inpatient Internal Medicine Patients</condition>
  <arm_group>
    <arm_group_label>No Intervention</arm_group_label>
    <arm_group_type>No Intervention</arm_group_type>
    <description>Only surveys will be done and re admissions tracked. No additional interventions based on survey results will be done.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Intervention</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Pharmacist Services&#xD;
Surveys plus increased outpatient pharmacist/pharmacy student services including but not limited to pre and post clinic visit phone calls, prescription counseling, and helping with adherence and compliance with medications. Increased services will be given based on survey results.</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Pharmacist services</intervention_name>
    <description>Additional pharmacist/pharmacy student follow-ups, counseling, and other services</description>
    <arm_group_label>Intervention</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Inpatient on Internal Medicine service at UIH (University at Illinois Health Hospital)&#xD;
&#xD;
          -  Adults &gt; 18 years of age, fluency in English&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Prisoners&#xD;
&#xD;
          -  Active illicit substance abuse per admitting History &amp; Physical note in EMR&#xD;
             (Electronic Medical Record)&#xD;
&#xD;
          -  Admitted for alcohol withdrawal or abuse&#xD;
&#xD;
          -  Nursing home resident likely to be discharged back to a nursing home&#xD;
&#xD;
          -  Unable to provide informed consent&#xD;
&#xD;
          -  Unable to complete survey (e.g., dementia)&#xD;
&#xD;
          -  Unable to communicate verbally (aphasia)&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Mat Thambi, PharmD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Illinois at Chicago</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>University of Illinois at Chicago</name>
      <address>
        <city>Chicago</city>
        <state>Illinois</state>
        <zip>60612</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>September 2020</verification_date>
  <study_first_submitted>December 20, 2018</study_first_submitted>
  <study_first_submitted_qc>December 31, 2018</study_first_submitted_qc>
  <study_first_posted type="Actual">January 2, 2019</study_first_posted>
  <last_update_submitted>September 22, 2020</last_update_submitted>
  <last_update_submitted_qc>September 22, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">September 24, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University of Illinois at Chicago</investigator_affiliation>
    <investigator_full_name>Mathew Thambi</investigator_full_name>
    <investigator_title>Clinical Assistant Professor</investigator_title>
  </responsible_party>
  <keyword>Readmissions</keyword>
  <keyword>Survey</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/NCT03791541
org study id: 2016-0748
nct id: NCT03791541
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
The primary objective of this study is the development and implementation of a survey
      administered to hospitalized patients on Internal Medicine that can be used in conjunction
      with previously validated predictive indices to identify patients at risk for readmission.
      The survey consists of previously validated as well as investigator developed survey
      instruments that will assess the following: health literacy, numeracy, medication adherence,
      self-efficacy, and tolerance. The predictive indices are the LACE, Charlson Comorbidity Index
      (included in LACE), and the Comorbidity Polypharmacy Score (CPS) which have been previously
      validated for risk of readmissions. The survey consists of both closed and open ended
      questions. A part of the survey will be administered by the study personnel while the rest is
      a questionnaire-based survey that will be completed by the subjects. Study personnel will be
      with the subjects in an open dialogue while subjects are completing the survey to answer any
      questions and identify questions that may be confusing or bias subjects. Approximately 30
      days after hospital discharge, patients will be contacted via telephone to ask how many
      admissions and/or Emergency Department (ED) visits they have had since discharge. A
      correlation analysis will be done of the different aspects of the survey to determine whether
      there are redundancies. A regression analysis will be done to determine the predictive
      ability of the survey combined with predictive indices for readmission.
Many patients are readmitted to the hospital shortly after discharge. Twenty percent of
      Medicare beneficiaries discharged were re-hospitalized within 30 days at a cost to Medicare
      estimated at $17.4 billion. This problem does not only affect the elderly. Medicaid enrollees
      aged 21-64 had 10.7% 30-day readmission rate. Identifying which patients are at highest risk
      is important for allocating resources to those high risk individuals.

      Several studies have attempted to retrospectively identify medical conditions, medications,
      labs, and vitals associated with increased risk of readmission with different levels of
      success. Examples of these include the Charlson Comorbidity Index, LACE, and the Comorbidity
      Polypharmacy Score. Although not always developed for use in predicting readmissions, they
      have been subsequently associated with this.

      While these indices examine objective data, it is thought that health beliefs, abilities, and
      behaviors can also affect the risk of readmissions. Health literacy in particular has been
      shown to be associated with 30 day readmissions after an acute myocardial infarction and in
      general medical patients. Low numeracy has been associated with increased risk of 30 day
      readmission in patients with acute heart failure.

      Inpatient questionnaires are able to identify patients who are more likely than others to be
      readmitted. Additionally, objective qualities such as insurance status, comorbidities, and
      admissions within the past year are predictors of readmission. Due to the unique patient
      populations at different health systems, an institution-specific approach is necessary to
      analyze the specific factors contributing to readmission. Therefore, a survey will be used to
      gauge the most predictive factors of readmissions and ED visits, including objective and
      subjective sections. After further research and modification, the survey will potentially
      serve as a tool for clinicians to select the best approach to post-discharge care and
      follow-up.

      This pilot will attempt to test a survey for predicting readmission through measurements of
      health literacy, numeracy, medication adherence, self-efficacy, and tolerance, and in
      conjunction with co-morbidity indices.
allocation: Randomized
intervention model: Parallel Assignment
intervention model description: targeted, cost-effective interventions based on results of surveys and other factors studied will be applied to study arm to see if re-admissions can be prevented
primary purpose: Prevention
masking: Single (Participant)
masking description: Survey will be given to all participants
measure: Number of readmissions after 1 month
time frame: 30 days post-discharge
description: Number of readmissions after 30 days post-discharge
measure: Number of readmissions after 2 months
time frame: 60 days post-discharge
description: Number of readmissions after 60 days post-discharge
arm group label: No Intervention
arm group type: No Intervention
description: Only surveys will be done and re admissions tracked. No additional interventions based on survey results will be done.
arm group label: Intervention
arm group type: Experimental
description: Pharmacist Services
Surveys plus increased outpatient pharmacist/pharmacy student services including but not limited to pre and post clinic visit phone calls, prescription counseling, and helping with adherence and compliance with medications. Increased services will be given based on survey results.
intervention type: Behavioral
intervention name: Pharmacist services
description: Additional pharmacist/pharmacy student follow-ups, counseling, and other services
arm group label: Intervention
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: Mat Thambi, PharmD
role: Principal Investigator
affiliation: University of Illinois at Chicago
facility: 
country: United States
responsible party type: Principal Investigator
investigator affiliation: University of Illinois at Chicago
investigator full name: Mathew Thambi
investigator title: Clinical Assistant Professor
sharing ipd: No