노인을위한 환자 중심 정밀 의학 실험실 결과 커뮤니케이션
Hemoglobin A1C가 높아진 노인을위한 환자 중심 실험실 결과 커뮤니케이션 도구 (A1C) 또는 만성 신장 질환 (CKD)
연구 개요
상세 설명
Prediabetes thresholds based on hemoglobin A1c were originally developed using younger, healthier populations and may not reflect the slower and more variable glycemic changes observed in older adults. Evidence from large community-based cohorts suggests that adults aged 65 years and older with A1c values in the prediabetes range are often more likely to return to normal glycemia than to progress to diabetes, creating uncertainty for patients and providers when interpreting lab results.
Machine learning models developed using de-identified UCLA Health EHR data from multiple annual cohorts between 2020 and 2024 demonstrated strong performance in predicting progression to diabetes. The final model uses a CatBoost architecture and incorporates approximately 94 routinely collected clinical variables to generate patient-specific risk scores. Model performance was evaluated across yearly cohorts, and the selected model is locked for the duration of the study without updating or adapting to new data.
The study follows a real-world, randomized deployment design in which eligible individuals in the lowest 15% of model-predicted risk within the eligible study population are identified automatically at the time lab results are processed and assigned to either modified or standard lab result messaging. De-identified EHR data and free-text provider comments are used to examine healthcare utilization, disease progression, and provider response patterns over time.
All participants who are randomized are invited to complete two surveys. The first survey is administered shortly after receipt of the laboratory result and is designed to assess immediate patient understanding of the result and emotional responses such as anxiety or reassurance. A second survey is administered approximately one month later and uses validated instruments to measure health-related quality of life, food-related quality of life and eating behavior, and perceived burden of healthcare. Both study arms receive the same surveys, allowing comparison of patient-reported outcomes between standard and modified laboratory result messaging. Surveys are distributed only to participants who have been randomized to either modified or standard laboratory result messaging. Therefore, no additional eligibility criteria apply for survey participation beyond randomization.
By embedding model-generated risk information directly into routine EHR workflows, this study aims to generate evidence on whether precision-based communication can support more individualized, patient-centered care and inform future implementation across broader patient populations and clinical use cases.
연구 유형
등록 (추정된)
단계
- 해당 없음
연락처 및 위치
연구 연락처
- 이름: Katelyn Nguyen Assistant Clinical Research Coordinator
- 전화번호: 310-267-5250
- 이메일: katenguyen@mednet.ucla.edu
연구 장소
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California
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Los Angeles, California, 미국, 90049
- 모병
- UCLA Health System
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연락하다:
- Katelyn Assistant Clinical Research Coordinator
- 전화번호: 310-267-5250
- 이메일: csarkisian@mednet.ucla.edu
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연락하다:
- Catherine Sarkisian, MD
- 전화번호: 3102068272
- 이메일: csarkisian@mednet.ucla.edu
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수석 연구원:
- Catherine Sarkisian, MD
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참여기준
자격 기준
공부할 수 있는 나이
- 고령자
건강한 자원 봉사자를 받아들입니다
설명
포함 기준 :
환자 포함 기준 : UCLA 1 차 진료 제공자가있는 노인 (65 세).
- 환자 포털에 등록;
- 영어를 사용하는 (도구의 언어는 현재 영어로만 가능하며, 도구 모형의 모든 잠재적 변형과 파생물에 대해 검증 된 번역을 작성하는 것이 비현실적입니다); 그리고
- 치매 또는 다른 신경인지 질환없이.
제공자 포함 기준 :
-외래 환자 환경에서 많은 노인들을 돌보는 핵무기 의료 제공자.
제외 기준 :
환자 제외 기준 :
- 정의 된 포함 범위 외부에 실험실 결과가 있습니다.
- UCLA PCP가 없습니다.
- 65 세 미만입니다.
- 영어 말하기가 아닙니다 (도구 프로토 타입은 최종 언어가 결정될 때까지 영어로만 사용됩니다).
- UCLA Mychart 환자 포털에 등록되지 않습니다. 또는
- 치매로 진단됩니다
제공자 제외 기준 :
-외래 환자 환경에서 많은 노인을 신경 쓰지 마십시오.
공부 계획
연구는 어떻게 설계됩니까?
디자인 세부사항
- 주 목적: 건강 서비스 연구
- 할당: 무작위
- 중재 모델: 병렬 할당
- 마스킹: 없음(오픈 라벨)
무기와 개입
참가자 그룹 / 팔 |
개입 / 치료 |
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실험적: Personalized Lab Result Messaging
Participants receive modified electronic health record (EHR) lab result communications in the patient portal (MyChart) and provider-facing EHR interface that include a qualitative "very low risk" label generated by a machine learning-based tool, along with brief explanatory text providing context about their current results and indicating a low level of concern at this time.
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A behavioral intervention delivered through a personalized Electronic Health Record (EHR)-integrated lab result communication tool designed to improve emotional and cognitive responses to lab results among adults aged 65+.
The tool applies behavioral science principles such as risk personalization, simplified messaging, and visual framing to reduce patient anxiety, enhance understanding, and support informed decision-making.
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간섭 없음: Standard Lab Result Messaging
Participants receive standard electronic health record (EHR) lab result communications without any machine learning-generated risk labeling or explanatory text providing additional context about level of concern.
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연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
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Prediabetes- Related Healthcare Utilization
기간: 365 days after result
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Total count of prediabetes-related healthcare utilization defined as the sum of outpatient visits to endocrinology, repeat hemoglobin A1c tests, and new prescriptions for diabetes-related medications following the index A1c result.
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365 days after result
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2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Number of Repeat Hemoglobin A1c Tests
기간: 365 days after result
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Total number of repeat hemoglobin A1c laboratory tests performed after the index test.
This measure reflects follow-up glycemic testing and serves as an indicator of diabetes-related monitoring and healthcare utilization.
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365 days after result
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Number of Prescriptions for Diabetes-Related Medications
기간: 180 days after result
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Total number of prescriptions issued for medications commonly used for glycemic management (e.g., metformin) following the index hemoglobin A1c result.
This outcome captures initiation of pharmacologic treatment related to diabetes risk.
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180 days after result
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Total Number of Outpatient Healthcare
기간: 180 days after result
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Total count of outpatient visits across all specialties following the index A1c result
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180 days after result
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Numbers of Referrals to Endocrinology
기간: 14 days after initial result
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Total number of outpatient referrals to an endocrinologist occurring after the index hemoglobin A1c laboratory result.
This measure is used to quantify diabetes-related specialty care utilization potentially associated with interpretation of the laboratory result communication.
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14 days after initial result
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Number of Referrals to Nutrition Services
기간: 14 days after initial result
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Number of participants with an electronic referral order placed to clinical nutrition services documented in the electronic health record after release of the hemoglobin A1c result.
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14 days after initial result
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Number of Referrals to Diabetes Education
기간: 14 days after initial result
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Number of participants with an electronic referral order placed to diabetes education services documented in the electronic health record after release of the hemoglobin A1c result.
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14 days after initial result
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Number of Completed Endocrinology Visit
기간: 180 days after result
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Number of participants who complete an outpatient endocrinology encounter documented in the electronic health record after laboratory result notification.
Visit completion will be identified using encounter records associated with endocrinology clinic services.
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180 days after result
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Completed Nutrition Services Visit
기간: 180 days after result
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Number of participants who complete an outpatient visit with clinical nutrition services documented in the electronic health record following laboratory result notification.
Completion will be determined using encounter data associated with nutrition services.
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180 days after result
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Completed Appointments to Diabetes Education
기간: 180 days after result
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Number of participants who complete an outpatient visit with diabetes education services documented in the electronic health record following laboratory result notification.
Completion will be determined using encounter data associated with diabetes education.
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180 days after result
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Number of Patient MyChart Messages
기간: 7 days after viewing lab result
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Count of MyChart Test Result Messages
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7 days after viewing lab result
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Numbers of Phone Calls Received after A1c Results
기간: 7 days after viewing lab result
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Count of telephone encounters to ordering provider
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7 days after viewing lab result
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기타 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Self-Reported Quality of Life
기간: 30 days after initial survey invitation
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Patient-reported quality of life assessed using survey responses evaluating overall physical, mental, and health-related well-being following receipt of lab result communication.
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30 days after initial survey invitation
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Self-Reported Physical Function Following Lab Result
기간: 30 days after initial survey invitation
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Self-reported physical function asking about ability to perform activities such as household chores, stair climbing, walking, and running errands following receipt of lab result communication.
This measure uses structured survey items to evaluate whether receipt of A1c lab result communication is associated with changes in exercise.
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30 days after initial survey invitation
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Self-Reported Dietary Behaviors Following Lab Result
기간: 30 days after initial survey invitation
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Patient-reported dietary behaviors following receipt of lab result, including eating patterns, appetite, satiety, and food-related changes or restrictions due to concerns about lab results.
These behaviors are assessed to understand potential impacts on health and weight-related decision-making.
This measure uses structured survey items to evaluates whether receipt of A1c lab result communication is associated with changes dietary behaviors.
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30 days after initial survey invitation
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Patient Understanding and Anxiety Related to Lab Result Communication
기간: 7 days after results
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Patient-reported understanding of lab report and emotional response to result communication, including perceived clarity, reassurance, and level of concern, assessed using structured survey items designed to measure comprehension and anxiety following receipt of laboratory result messaging.
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7 days after results
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Number of Incidence of Diabetes
기간: 3 years
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Proportion of participants who progress from prediabetes to diabetes based on electronic health record data, defined by meeting diagnostic criteria for diabetes during follow-up.
This outcome is included to monitor long-term clinical safety and progression.
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3 years
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공동 작업자 및 조사자
연구 기록 날짜
연구 주요 날짜
연구 시작 (실제)
기본 완료 (추정된)
연구 완료 (추정된)
연구 등록 날짜
최초 제출
QC 기준을 충족하는 최초 제출
처음 게시됨 (실제)
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
QC 기준을 충족하는 마지막 업데이트 제출
마지막으로 확인됨
추가 정보
이 연구와 관련된 용어
기타 연구 ID 번호
- IRB-24-6052
- P30AG073104 (미국 NIH 보조금/계약)
개별 참가자 데이터(IPD) 계획
개별 참가자 데이터(IPD)를 공유할 계획입니까?
약물 및 장치 정보, 연구 문서
미국 FDA 규제 의약품 연구
미국 FDA 규제 기기 제품 연구
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