DEVELOPMENT OF A SCREENING ALGORITHM FOR TIMELY IDENTIFICATION OF PATIENTS WITH MILD COGNITIVE IMPAIRMENT A…

Assistance award details

Assistance award identifier

ASST_NON_R00AG076808_075

FAIN

R00AG076808

Recipient

THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK

Awarding agency

Department of Health and Human Services

Funding agency

Department of Health and Human Services

Assistance listing (CFDA)

93.866

Total obligated

$741,962

Period

Dec 15, 2022 – Jun 30, 2027

Fiscal year

2024

Place of performance state

NY

Source file

FY2024_All_Assistance_Full_20261006.zip

Description

DEVELOPMENT OF A SCREENING ALGORITHM FOR TIMELY IDENTIFICATION OF PATIENTS WITH MILD COGNITIVE IMPAIRMENT AND EARLY DEMENTIA IN HOME HEALTHCARE - MILD COGNITIVE IMPAIRMENT (MCI) AND EARLY-STAGE DEMENTIA (ED) HAVE A SIGNIFICANT IMPACT ON ELDERLY PATIENTS’ QUALITY OF LIFE, HEALTHCARE UTILIZATION, AND COST. DESPITE NATIONWIDE EFFORTS FOR TIMELY DIAGNOSIS OF MCI AND ED (MCI-ED), MORE THAN 50% OF PATIENTS REMAINED UNDERDIAGNOSED AND UNDERTREATED. THIS IS MOSTLY DUE TO PATIENTS’ INABILITY TO RECOGNIZE EARLY SYMPTOMS, LIMITED AVAILABILITY OF BIOMARKERS, AND CLINICIANS’ INSUFFICIENT TIME TO ASSESS PATIENTS FOR MCI-ED, PARTICULARLY FOR PATIENTS ADMITTED TO THE HOME HEALTHCARE (HHC) SETTING. THIS K99/R00 WILL ADDRESS BARRIERS TO EARLY IDENTIFICATION OF MCI-ED VIA THE DEVELOPMENT OF AN INNOVATIVE ALGORITHM BUILT ON A COMBINATION OF MULTIPLE DATA STREAMS, INCLUDING DATA EXTRACTED FROM ELECTRONIC HEALTH RECORDS (EHRS) AND AUDIO-RECORDED PATIENT-CLINICIAN VERBAL COMMUNICATION DURING ROUTINE ENCOUNTERS. OUR PRIMARY GOAL IS TO UTILIZE THE ROUTINELY GENERATED DATA IN THE HHC SETTING, INCLUDING OASIS (OUTCOME AND ASSESSMENT INFORMATION SET - A FEDERALLY REQUIRED ASSESSMENT OF PATIENTS ADMITTED TO HHC), HHC NURSES’ NOTES, AND HHC PATIENT-NURSE VERBAL COMMUNICATION TO DEVELOP AN MCI-ED SCREENING ALGORITHM. THE LONG-TERM TRAINING GOAL IS FOR DR. ZOLNOORI TO BECOME AN INDEPENDENT INVESTIGATOR CONDUCTING A PROGRAM OF RESEARCH DEDICATED TO MITIGATING THE BURDEN OF DELAYED CARE FOR PATIENTS WITH MCI-ED BY DEVELOPING LOW-COST, EFFECTIVE INFORMATICS SOLUTIONS. THE SOLUTIONS WILL TAKE ADVANTAGE OF EASILY ACCESSIBLE DATA GENERATED IN CLINICAL ENCOUNTERS AND WILL BE BUILT ON NOVEL DATA SCIENCE METHODS, PARTICULARLY SPEECH ANALYSIS, THE FOCUS OF HER POSTDOCTORAL WORK. USING EXCEPTIONAL RESOURCES AVAILABLE FROM COLUMBIA UNIVERSITY AND THE VISITING NURSE SERVICE OF NEW YORK, THE K99 PHASE OF THIS PROJECT WILL FOCUS ON GAINING ESSENTIAL COMPETENCIES AND SKILLS IN THEORY AND PRACTICE OF SPEEC