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Improving Patient Prioritization During Hospital-homecare Transition (PREVENT)

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ClinicalTrials.gov Identifier: NCT04136951
Recruitment Status : Not yet recruiting
First Posted : October 23, 2019
Last Update Posted : June 16, 2021
Sponsor:
Collaborators:
Visiting Nurse Service of New York
National Institute of Nursing Research (NINR)
Information provided by (Responsible Party):
Maxim Topaz, Columbia University

Brief Summary:
This research work is focused on building and evaluating one of the first evidence-based clinical decision support tools for homecare in the United States. The results of this study have the potential to standardize and individualize nursing decision making using cutting-edge technology and to improve patient outcomes in the homecare setting.

Condition or disease Intervention/treatment Phase
Diabetes Mellitus, Type 2 Congestive Heart Failure Obstructive Pulmonary Disease Dyspnea Renal Failure Other: PREVENT clinical decision support Not Applicable

Detailed Description:

Each year, more than 5 million patients are admitted to the approximately 12,000 homecare agencies across the United States. About 20% of homecare patients are rehospitalized during the homecare episode, with as many as 68% of these rehospitalizations occurring within the first two weeks of services. A significant portion of these rehospitalizations may be prevented by timely and appropriately targeted allocation of homecare services. The first homecare nursing visit is one of the most critical steps of the homecare episode. This visit includes an examination of the home environment, a discussion regarding whether a caregiver is present, an assessment of the patient's capacity for self-care, and medication reconciliation. A unique care plan is created based on this evaluation of the patient's needs. Hence, appropriate timing of the first visit is crucial, especially for patients with urgent healthcare needs. However, nurses often have very limited and inaccurate information about incoming patients and patient priority decisions vary significantly between nurses.

The investigators developed an innovative decision support tool called "Priority for the First Nursing Visit Tool" (PREVENT) to assist nurses in prioritizing patients in need of immediate first homecare nursing visits. In a recent efficacy pilot study of PREVENT, high-risk patients received their first homecare nursing visit a half day sooner as compared to the control group, and 60-day rehospitalizations decreased by almost half as compared to the control group. The proposed study assembles a strong interdisciplinary team of experts in health informatics, nursing, homecare, and sociotechnical disciplines to evaluate PREVENT in a pre-post intervention effectiveness study. Specifically, the study aims are: Aim 1) Evaluate the effectiveness of the PREVENT tool on process and patient outcomes. Using survival analysis and logistic regression with propensity score matching the researchers will test the following hypotheses: Compared to not using the tool in the pre-intervention phase, when homecare clinicians use the PREVENT tool, high risk patients in the intervention phase will: a) receive more timely first homecare visits and b) have decreased incidence of rehospitalization and have decreased emergency department (ED) use within 60 days. Aim 2) Explore PREVENT's reach and adoption by the homecare admission staff and describe the tool's implementation during homecare admission. Aim 2 will be assessed using mixed methods including homecare admission staff interviews, think-aloud simulations, and analysis of staffing and other relevant data.

This innovative study addresses several National Institute of Nursing Research strategic priorities, such as promoting innovation and using technology to improve health. Mixed methods will enable us to gain in-depth understanding of the complex socio-technological aspects of hospital-homecare transition.

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Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 2094 participants
Allocation: N/A
Intervention Model: Single Group Assignment
Intervention Model Description: To examine the study aims, the researchers are using an embedded mixed methods study design. The researchers will conduct pre- and post intervention trial of clinical decision support tool PREVENT's integration into clinical practice using homecare admissions from two New York City urban hospitals serving diverse racial and ethnic population. Quantitative methods, including logistic regression and survival analysis with propensity score matching, will be used to evaluate the effects of the tool on process and patient outcomes. Qualitative methods will be used to match the quantitative questions and provide an in depth insight into homecare admission processes using think-aloud simulations and interviews with homecare admission staff.
Masking: None (Open Label)
Primary Purpose: Screening
Official Title: Improving Patient Prioritization During Hospital-homecare Transition: A Mixed Methods Study of a Clinical Decision Support Tool
Estimated Study Start Date : September 1, 2021
Estimated Primary Completion Date : September 1, 2022
Estimated Study Completion Date : September 1, 2022

Resource links provided by the National Library of Medicine


Arm Intervention/treatment
Experimental: Experimental phase
The PREVENT recommendation about patient homecare priority will be shared in homecare referral communication with the homecare intake coordinators. Homecare intake coordinators will be instructed to prioritize high risk patients for care.
Other: PREVENT clinical decision support
PREVENT clinical decision support tool consideres five patient risk factors as significant predictors of patient's priority for the first homecare nursing visit: (a) Presence of wounds (either surgical or pressure ulcers); (b) a documented comorbid condition of depression; (c) need for assistive equipment, assistive person, or both for toileting; (d) number of medications; and (e) number of comorbid conditions. Each risk factor was assigned a specific score based on the logistic regression weights. For instance, for a wound (e.g., pressure ulcer, vascular ulcer), the patient received a score of 15 points. For each additional co-morbid condition, one point was added to the final score. Summing the scores for the factors generated a cumulative score. The optimal cut-off point was established based on the regression model performance statistics, indicating that patients with a score greater than 26 points are a high priority for the first nursing visit.




Primary Outcome Measures :
  1. To learn if using PREVENT tool results in decreased incidence of rehospitalization [defined as recurrent hospital admission within 60 days from hospital discharge] [ Time Frame: within 60 days after hospital discharge ]
    Patient outcomes include rehospitalization measure within 60 days after hospital discharge. The hypothesis is that using the PREVENT tool will result in decreased incidence of rehospitalization. Rehospitalization information will be extracted from the New York Regional Health Information Exchange (RHIO) database.

  2. To learn if using PREVENT tool results in high nurses' system usability perception measured by the System Usability Scale (SUS). [ Time Frame: 30-60 days after clinical decision support tool (PREVENT) implementation ]
    Nurses' usability perception of the clinical decision support tool (PREVENT) will be assessed by using he System Usability Scale (SUS).



Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

Aim 1:

Inclusion criteria:

  1. being a patient of either NewYork-Presbyterian (NYP)/Columbia University Irving Medical Center or NewYork-Presbyterian Allen Hospital;
  2. being referred to Visiting Nurse Services of New York (VNSNY) homecare services
  3. 18 years old or older.

Exclusion criteria:

All other patients are going to be excluded.

Aim 2 :

Inclusion criteria:

  1. working as an admission staff for VNSNY
  2. 18 years old or older.

Exclusion criteria:

All other staff members are going to be excluded.

For both study aims, there will be no exclusion based on sex, race, or ethnic group.


Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04136951


Contacts
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Contact: Maxim Topaz, PhD 16462760460 mt3315@cumc.columbia.edu

Locations
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United States, New York
Columbia University School of Nursing
New York, New York, United States, 10032
Contact: Maxim Topaz    646-276-0460    mt3315@cumc.columbia.edu   
Principal Investigator: Maxim Topaz, PhD         
Sub-Investigator: Kenrick Cato, PhD         
Visiting Nurse Service of New York
New York, New York, United States, 10033
Contact: Maxim Topaz    646-276-0460    mt3315@cumc.columbia.edu   
Principal Investigator: Margaret McDonald, PhD         
Sub-Investigator: Yolanda Barron-Vaya, PhD         
Sponsors and Collaborators
Columbia University
Visiting Nurse Service of New York
National Institute of Nursing Research (NINR)
Investigators
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Principal Investigator: Maxim Topaz, PhD Associate Professor of Nursing at CUMC
Publications:
Publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):
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Responsible Party: Maxim Topaz, Associate Professor, Columbia University
ClinicalTrials.gov Identifier: NCT04136951    
Other Study ID Numbers: AAAS7265
1R01NR018831-01 ( U.S. NIH Grant/Contract )
First Posted: October 23, 2019    Key Record Dates
Last Update Posted: June 16, 2021
Last Verified: June 2021
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No
Plan Description: No sharing planned

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Maxim Topaz, Columbia University:
home health
clinical decisions support
care transitions
patient prioritization
health informatics
home care
Additional relevant MeSH terms:
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Lung Diseases, Obstructive
Dyspnea
Heart Failure
Diabetes Mellitus, Type 2
Heart Diseases
Cardiovascular Diseases
Lung Diseases
Respiratory Tract Diseases
Diabetes Mellitus
Glucose Metabolism Disorders
Metabolic Diseases
Endocrine System Diseases
Respiration Disorders
Signs and Symptoms, Respiratory